United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
January 1993
Air
& EPA
A STUDY OF HIGHWAY
VEHICLE EMISSION
INVENTORY PROCEDURES
FOR SELECTED URBAN AREAS
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A STUDY OF HIGHWAY
VEHICLE EMISSION INVENTORY
PROCEDURES FOR
SELECTED URBAN AREAS
OFFICE OF AIR QUALTTTY PLANNING
AND STANDARDS
RESEARCH TRIANGLE PARK, NC 27711
U.S. ENVIRONMENTAL AGENCY
JANUARY 1993
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Notice
This material has been funded by the United States Environmental
Protection Agency (EPA) under contract 68D90073 to Cambridge
Systematics, Inc. This document has been approved for publication
as an EPA document. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
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Highway Vehicle Emission Inventories
Table of Contents
1.0 Introduction 1
Background 1
Objective 4
Approach 4
2.0 Urban Area Findings 6
Questions Investigated 6
Available VMT and Speed Methodologies 7
Synthesis of Key Issues 13
3.0 Existing Guidance Materials "... 19
Post-1987 Available EPA Guidance 19
Vehicle Speed Estimation 20
Vehicle Miles of Travel 21
Potential Areas of Additional Information 22
4.0 Recommendations 24
Appendix — Urban Area Case Studies.; A-l
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1.0 Introduction
Background
Passage of the Clean Air Act Amendments of 1990 has occasioned a significant resurgence
of interest in the analytical methodologies required to support transportation-air quality
related analyses. This report explores issues associated with the preparation of base and
future year mobile source emissions inventories, particularly the estimation of highway
vehicle miles of travel and speed.
An important component of the Clean Air Act is the set of planning and analysis activities
required by the states and designated non-attainment areas. State Implementation Plans,
commonly referred to as SIPs, are comprehensive documents that detail current emissions
and air quality conditions, and demonstrate commitments to implement measures that are
sufficient to achieve the national ambient air quality standards by a designated date.
As part of a State Implementation Plan, emissions inventories are developed for all sig-
nificant mobile, stationary, and area sources of pollutants. Such inventories are developed
for both a base year and a projected future year and provide the baseline condition against
which the effectiveness of alternative control policies can be measured. Mobile source
inventories include all transportation sources of emissions: highway vehicles, off-highway
vehicles, aircraft, railroads, and marine. The highway portion of a mobile source emissions
inventory classifies vehicles by type (e.g. auto, light truck, heavy truck, diesel) and esti-
mates both vehicle miles of travel and speed by vehicle and roadway classification.
At the state and urban area level, numerous practical problems can be encountered in
preparing mobile source emission inventories. For example, it has been customary in past
inventory analyses to assume that vehicle travel speeds are the same in future years as they
are in the current or base analysis year. This generally has been justified on the basis that
highway capacity will expand proportionally with the growth in vehicular travel. Real-
istically, it is often also based on the lack of information on which to base any other
assumption.
Increasingly, however, the assumption of constant vehicular speed over time is being called
into question. This is resulting from an acknowledged limitation on highway expenditures,
a recognition that congestion is increasing in many urban areas, and results from urban
transportation planning analyses. For example, the Southern California Association of
Governments has projected that the average daytime freeway speed in the Los Angeles area
will decline from 35 mph to 20 mph over the next 20 years in the absence of full imple-
mentation of an ambitious transportation management and improvement program.
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Analyses of the Federal Highway Administration's Highway Performance Monitoring
System (HPMS) traffic database indicate similar findings. For urban areas, vehicle speeds
generally are projected to decrease over time (Figure 1). Speeds decline the most for non-
interstate freeways and expressways, and next most severely for other principal arterials.
As expected, the magnitude of the projected speed decrease becomes larger with lower
levels of highway funding.
Accurate estimates of speed are particularly important given the non-linearity with which
emissions increase with decreasing vehicle speeds below 20 miles per hour.
EPA prepared a July, 1989 guidance document for the preparation of mobile source
emission inventories.1 This document covers all transportation modes: off highway
vehicles, highway vehicles, aircraft, railroads, and marine vessels. For highways, it
provides a comprehensive discussion of factors affecting highway vehicle emissions, the
use of MOBILE4, vehicle inspection/maintenance and anti-tampering programs, and the
urban transportation planning process and associated computerized modeling systems.
Particular questions with respect to the preparation of mobile source emission inventories
which have been addressed in this study include the following:
• What is the ability of states and urban areas to comply with EPA's July, 1989 emission
inventory guidance with respect to the use of urban transportation data and model
systems?
• What procedures are available for allocating mobile source emissions to hourly
emissions?
• How can the interface between transportation models and mobile source emission
models be improved?
Particular concern has been expressed with the procedures available for estimating vehicle
miles of travel (VMT) and vehicle speed. With respect to VMT, urban transportation
modeling systems may not cover the same geographic area as the non-attainment air
quality planning area, may not include all roadways (e.g. local roads), and may utilize
different analysis years than are required for EPA air quality analyses. Many smaller, as
well as some medium and large, urban areas may lack up-to-date transportation planning
data, and thus be forced to rely on entirely different data sources.
The problems associated with vehicle speed data generally are considered to be more
serious than those associated with VMT projections. The primary objective of an urban
transportation analysis is to predict vehicular volumes on one or more network links,
usually major radial or circumferential highways. Calculated vehicle speeds are used
I/ "Procedures For Emission Inventory Preparation - Volume IV: Mobile Sources", prepared by
the Technical Support Division of the Office of Air Quality Planning and Standards and the
Emission Control Technology Division of the Office of Mobile Sources, July 1989.
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Figure 1. Projected Change in Automobile
Time
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tn X
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2 20-
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Operating Speeds Over
• •
I-L ~*
° a
2000 2005
-E — •
— a
Urban Freeway and Xway
•
•
985 1990 1995
••
Urban Principal Arteries
1 " P|" u -
•
IB
>85 1990 1995
• Current Funding Levels Plus 10%
D Current Funding Levels Minus 20%
2000 2005
==0 J
2000 2005
Source: Highway Performance Monitoring System, US. Federal Highway Administration
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internally in these model systems to help calibrate the traffic volumes being estimated in a
base case analysis condition.
There also are a set of important temporal considerations regarding the use of urban
transportation planning data in air quality analyses. These include the analysis period
(average day, peak day, summer, winter) and the use of hourly vs. peak period vs. daily
emissions. The particular time periods of interest in an air quality analysis may not
coincide with the time periods for which urban transportation planning data are being
developed.
Objective
The objective of the work performed has been to identify potential areas where additional
information could be developed that would assist states and urban areas in the preparation
of mobile source emissions inventories. The work program was structured around a
review of current mobile source emissions inventory practices in fifteen urban areas.
Existing guidance-related materials were assessed in light of the results of this review, and
recommendations for improved emissions inventory information or procedures were
developed.
This report describes the findings from the review of existing mobile source inventory
practices. The problems and solutions uncovered from the state and local area inves-
tigations provide a base of comparison, or "reality check", for assessing both current and
proposed EPA mobile source inventory preparation procedures.
Approach
Representatives from state and local agencies involved in the preparation of mobile source
emissions were contacted by telephone to determine:
• problems being encountered in preparing the traffic related portion of their mobile
source emission inventory; and
• the availability of state and local data sources for estimating both baseline and future
year inventories.
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These contacts represent the following urban areas:
Detroit Portland (Oregon)
Phoenix Boston
San Francisco Denver
Los Angeles Chicago
Atlanta Nashville
Tampa Fresno
Houston Hartford (Connecticut)
Pittsburgh
Based on the list of non-attainment areas for ozone and carbon monoxide, these cities
represent different sizes levels of sophistication, and technical capability. The objective was
to sample the problems and solutions from different types of urban areas that could be
encountered in preparing mobile source inventories.
The reported results are limited to the information obtained during the telephone
conversations and a subsequent review of an interim report. Given the diversity of urban
areas, it was not possible to contact the full range of potentially involved individuals,
conduct detailed follow-up interviews, or review detailed documentation that is available
from these urban areas. The overall objective was to provide a reasonably quick assess-
ment of the mobile source emission inventory procedures currently being used.
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-2.0 Urban Area Findings
Questions Investigated
The approach centered on open ended telephone conversations with representatives of
state and local area agencies involved in preparing the mobile source inventory for their
respective non-attainment area.
The conversations were structured around the following questions:
1. Who/.what agency is responsible for development of local traffic data used for
MOBILE4 inputs and operation of the area-wide transportation network model? How
is the modeling process financed?
2. What network modeling procedure/software is used?
3. How are speed data gathered and calibrated for the transportation model? How are
VMT data gathered and calibrated for the transportation model?
- What are the sources of these data?
- When were the data collected?
- How are data disaggregated to geographic sub-areas?
- How are data temporarily distributed on a daily and seasonal basis?
- For what time periods?
4. How well does the transportation planning network geographically correspond to the
designated air quality planning area? What information is available for travel for
those areas outside the transportation planning coverage area?
5. How much of the existing local road system is not included in the coded trans-
portation network? How is travel on local roads accounted for in the network analysis
results?
6. What roadway classifications are accounted for in the network? How is VMT dis-
tributed to individual roadway types within the model?
7. Over a given geographic sub-area, for a given roadway type, how are speeds cal-
culated and how are variations in travel conditions due to congestion accounted for?
8. How confident are you with the accuracy of the speed and VMT estimates produced
by the transportation model? What procedures, if any, are applied to improve the
accuracy of these data?
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9. What is the process of factoring base year travel speeds and VMT from the trans-
portation model to future year speeds and VMT for input to MOBILE4?
Available VMT and Speed Methodologies
A diverse range of methodologies are being utilized to estimate vehicle miles of travel and
vehicle speeds for both current and future years, as illustrated in Figure 2. The important
messages from this table are: 1) the diversity of methodologies being employed, and 2) the
associated wide range of accuracy. The following is an overview of the VMT and speed
methodologies defined in Figure 2. In general, the techniques which have the ability to
analyze temporally and spatially disaggregate results offer better precision. Urban areas
which rely on more coarse methodologies are less precise.
VMT Estimation Methodologies
Network
Network based VMT methodologies rely on volumes generated as output from an urban
area transportation network model. In the past, those models generally were either
FHWA's UTPS or PLANPAC. The trend in recent years has been to the use of proprietary
microcomputer versions of UTPS. Volumes are calculated by the four-stage network
modeling process used by many Metropolitan Planning Organizations and validated
against cordon traffic count data. VMT is calculated by multiplying the volumes by link
distances. Depending on the specific urban area, links coded into a network model
generally correspond to the following facility types: Freeway, Expressway, Major Arterial,
Minor Arterial, and Major Collector. The number of links coded into a network and the
facility classification depends on the sophistication of the model. VMT can be calculated
only for the facility types (links) that are coded.
There are some significant problems associated with network based techniques. VMT
generated by facilities not included in the coded network, such as minor collectors or
residential streets, are not accounted for in a transportation network model. Ten to fifteen
percent of low speed VMT could be generated by non-network coded facilities. If the
emission inventory area is larger than that covered by the transportation network, VMT
generated outside the network also will not be accounted for.
Another important problem is the fact that VMT generated by a network model cor-
responds to a "typical" weekday, with no recognition of seasonal variation in volumes.
Most urban network models represent a 24-hour day, although they have the capability to
also simulate peak (congested) or off-peak travel as well if these special trip tables are
available.
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_ Figure 2. Speed/VMT Methodology Matrix
SPEED:
VMT:
Network
Network/Hybrid
HPMS
Manual
Fuel Apportionment
Network:
V/C
Phoenix
Detroit
Hartford
Distance
Matrix
Portland
Traffic
Assignment
San Francisco
Nashville
Houston
Los Angeles
Tampa
Atlanta
Denver
-
Tampa1
Speed
Runs
Pittsburgh
Boston
MOBILE4
Defaults
Fresno
Chicago
'Under consideration as an alternative to a network based approach
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Presently, "stand alone" urban area transportation network demand models are reasonably
accurate at simulating regional transportation demand. However, network models under
certain conditions may not accurately simulate the variations in link level traffic operations
during peak conditions. An important advantage of the network model approach is the
fact that urban area network models represent a repository of important link level data and
information that with refinement could lead to a process that simulates link level traffic
operations, an important requisite for an accurate emissions inventory. Other advantages
of network models are that they can be easily used to forecast future year conditions and
they can be used to support grid-based urban airshed modeling.
Network Hybrid
The Network Hybrid approach is a generic term that identifies urban areas that are
attempting to deal with problems of coordinating their inventory over many jurisdictions,
or the lack of non-network coded facility data inside or outside the urban network
boundary.
For instance, the inventory area in Portland, Oregon encompasses non-modeled rural areas
and modeled urban areas of two states, with three agencies involved in traffic modeling.
Because the models of these agencies are not fully coordinated and rely on different data
bases and networks, facility types must be aggregated in order to reach some level of
consistency. Data from these different sources are of different levels of accuracy, cor-
respond to different time periods, have been developed using different methodological
approaches, and generally are not readily consistent. This process of aggregating to the
MSA level significantly complicates the process of a link by link network based analysis
VMT estimation method.
HPMS
Some urban areas that were contacted are coordinating their emission inventory with the
data collected for the Highway Performance Monitoring System (HPMS), a highway
database developed and maintained by the U.S. Federal Highway Administration. State
transportation departments are responsible for collecting a sample of roadway travel data
for various facility types and reporting it to FHWA. FHWA compiles the information and
expands it for analysis.
HPMS is a highway inventory procedure that collects existing data through samples and
uses these data in an Analytical Process to estimate current and future road, traffic, and
vehicle operating characteristics. HPMS is based on empirical data sampled and submitted
in a consistent format by all 50 states. Unlike network systems which mathematically
simulate travel over a network, HPMS expands the empirical data to derive a statistically
valid representation of the functional system of highways and arterials.
An important advantage of HPMS is that, for each of the reported functional classes, HPMS
disaggregates VMT into 12 discrete daily units based on levels of congestion. Technically,
however, congestion levels are not measured in uniform hourly increments. Speeds are •
calculated for each congestion level based on V/C, pavement conditions, curves, grades,
speed changes and stop cycles, and idling time. This disaggregation of VMT and speeds is
critical for a precise emissions inventory because of the temporal components of speed and
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volume correspond to the amount of emissions generated. Other advantages include
flexible analysis periods for base and target years and the general low cost of retrieving
data.
HPMS can provide valid urban area emissions estimates but is not geographically based,
and does not directly support grid-based dispersion modeling. Other problems with
HPMS data are as follows: 1) HPMS data represent a statistical sample of varying accuracy
at the national, state, and larger metropolitan areas only; road segment and traffic count
samples may be too small to be representative for smaller rural and urban areas; 2) VMT is
generated at a regional level and not disaggregated by location; 3) only higher classification
roadways are included in samples i.e., highways, arterials and collectors; urban and rural
local VMT data may be very limited or non-existent; 4) vehicle speed information is
estimated rather than directly collected and may be of questionable accuracy in certain
areas; and 5) forecasts of future year traffic are input values rather than being estimated in
any way internally within HPMS.
Even though local roads are not sampled on a section by section basis in HPMS, states are
required to submit aggregate summary arearwide tables for each individual urbanized area
for mileage and daily vehicle miles traveled (DVMT) for each functional class including
local roads.
Finally, modifications may be necessary in some states for HPMS to be used as an emissions
inventory tool. Specifically, urbanized areas would have to be sampled at the desired level
of statistical accuracy.
Manual
The manual method is used to characterize the most aggregate or coarse method of
developing VMT input data for a mobile source emission inventory. Chicago is the only
example of this method in the urban areas reviewed. VMT is provided by 11 facility types
by county ranging from highway to local roads based on the Illinois Department of
Transportation's traffic counting program. No attempt was made to assign VMT to
facilities within the county or account for the effect of congestion. Future estimates of VMT
are extrapolated based on past trends.
While this method represents consistent usage of a single data source, it lacks the ability to
document link level operational characteristics. Data cannot be readily disaggregated and
realistic estimates of vehicle speed under congested conditions are difficult. Other
disadvantages of the manual method include the inability to systematically forecast future
year conditions in a manner that takes network conditions into account and the difficulty of
interfacing with an area-wide model system of any kind.
Fuel Apportionment
This method utilizes fuel sales as a factor in determining VMT. Daily average fuel con-
sumption multiplied by miles per gallon represents total VMT. Tampa, Florida is
considering a variation of this method to determine VMT where total VMT minus network
derived VMT equals non-network VMT.
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__ — Speed Estimation Methodologies
An underlying premise in performing this work has been that estimates of link level traffic
volumes are both reasonably reliable and more accurate than link level speeds produced by
urban transportation model systems; such as UTPS or microcomputer based systems.
Ideally, both volume and speed information would be equally accurate. In practice,
however, preference is given to developing accurate estimates of vehicle traffic volumes.
Speeds developed through the modeling process serve as a means of allocating trips to
balance the network. As such, they really are more of an input rather than an output of the
model. On the other hand, the vehicle speed data in the Transportation Research Board's
1985 Special Report 209 "Highway Capacity Manual" (HCM) are considered to be more
reliable than network model based estimates. In free flow (uncongested) conditions,
network and HCM speed estimates appear to be similar. However, under congested
conditions where vehicle speeds may drop below 20 miles per hour, these estimates begin
to differ significantly. Estimating speeds under congested conditions is crucial in air
quality analyses because important shares of VMT occur during.peak conditions and
because a non-linear relationship exists between speed and emissions below 20 MPH.
In many future year inventories, speeds generally are assumed to remain unchanged which
is contrary to recent national evidence. If sample size is small, an "average" speed by
facility class is used which may neglect temporal variations in travel.
Network: Volume to Capacity
This technique utilizes the link level volume output from the transportation network model
and establishes a volume to capacity (v/c) ratio for each link that is then used to estimate a
speed value for that link. The primary advantages of this method include: 1) the rela-
tionship between v/c and speed is based on data from actual operating conditions com-
piled for the Highway Capacity Manual, and 2) it closely simulates actual traffic operations
at the link level.
This method appears to offer a higher level of precision because it documents the daily
variations in travel speeds due to congestion which significantly influences the quantity of
mobile emissions produced. The primary disadvantage to this method is the cost and
coordination necessary to customize an existing network model to replicate link level
operational characteristics.
Distance Matrix
Portland, Oregon uses a variation of the link-specific volume/capacity method to estimate
speed. The calculated speed is based on the time it takes a vehicle to travel between the
various zone centroids. Speeds from the traffic assignment process in the network model
are not directly used. This method had been selected due to criticism of network derived
travel speeds.
A problem with this method is that speed data for urban and rural non-network coded
facilities are limited. For the Portland SIP, factors to disaggregate statewide local road
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VMT were used to assign VMT on facilities not coded on the network. This method also
does not account for variations in link level operational characteristics which may have an
impact on emissions.
Traffic Assignment
This refers to use of the vehicle speed data output directly from a traffic assignment model.
The capacity restraint method is a common type of traffic assignment algorithm which
attempts to model congested speeds during peak conditions for all facility types. The
capacity restraint methodology is used as a "default" formula in many urban areas' traffic
assignment model. The capacity constraint function is based on the inverse relationship
between speed and congestion. As congestion increases, vehicle operating speeds will
decrease.
However, the unique manner in which the traffic assignment algorithm manipulates speed
for a particular link does not necessarily represent an accurate estimate of speed for that
link but rather a value that optimizes traffic assignment over the entire "congested"
network.
A potential problem with the use of any single function is that it may not document well
the variations in traffic operating conditions across all types of links, especially on very
congested links. It may be unreasonable to assume that any single formula is able to
accurately estimate speed for facility types having very different operating characteristics.
A more appropriate procedure would include separate methods for estimating speed for
each facility class for each condition, i.e, peak versus off-peak conditions. A primary
advantage of the capacity restraint method is that it is institutionalized at many MFC's.
Speed Runs
Some urban areas, such as Boston, utilize manually collected speed runs for various facility
types as input to the mobile source emission inventory. This method is based on samples
of representative facility types. Speed runs, however, can be both costly and labor inten-
sive.
MOBILE4 Defaults
The Chicago component of the Illinois SIP is utilizing the MOBILE4 internal default speed
of 19.6 MPH for all facility types, corresponding to the average speed of the Federal Test
Procedure (FTP). Using 19.6 MPH as a default value may either over- or under-estimate
vehicle speeds on congested freeway and arterial links that are characteristic of larger
urban areas during peak period operations. Congested freeway speeds may be higher than
19.6 MPH, while travel speeds on congested local arterials may be below this default
average. If vehicle speeds are over-estimated, this, in turn, may underestimate the amount
of mobile emissions generated.
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Synthesis of Key Issues
The following is a list of key issues synthesized from the urban area interviews. In
conducting these interviews it was found that institutional arrangements (or lack of) as well
as the technical methodology may have an important impact on the quality of a mobile
source emissions inventory. Therefore, the list includes problems of institutional and
administrative arrangements as well as more technical considerations. In undertaking a
mobile source emissions inventory, it is essential that all problems are overcome so -that the
data of the necessary level of quality are provided to EPA. Summary write-ups for each of
the individual urban areas are provided as an appendix to this report.
1. Adequacy of Transportation Network Model for Air Quality Emissions Inventories.
Transportation network models were developed to establish the analytical basis for
assessing future transportation needs and evaluating projects that will satisfy those
needs. Emphasis generally is on planning for major corridor-level projects, and on
projecting traffic volumes on major radial and circumferential roadways. Con-
siderably less importance is given to.travel speed and to minor or local streets! A
stand alone transportation network model consequently may need "customization" to
be an effective tool for the emission inventory process.
Phoenix, Detroit and Los Angeles are three examples where customized procedures
have been developed to analyze variations in link level VMT and travel speed which
are important requisites for an accurate inventory. In Phoenix, peak period spreading
of traffic volumes is explicitly considered. Forecast link volumes are men converted to
volume-to-capacity ratios for use in a special speed estimation procedure. The Los
Angeles DTIM program calculates link level emissions, accounting for VMT and speed
on each link rather than aggregated by facility type.
2. Validity of Network Based Speed Estimates. Significant concern was expressed in a
number of urban areas with respect to the validity of the speed estimates produced by
network-based traffic assignment procedures. In response, a number of urban areas
have developed special speed estimation routines which calculate volume-capacity
ratios, and then use either Highway Capacity Manual or locally derived relationships
to convert V/C into speed estimates. A direct network derived speed estimate may
overestimate link speeds because of the capacity restraint algorithm used is based on
the equilibrium adjustment necessary to obtain a reasonable region-wide trip
allocation rather than on "observed" speeds of the roadway link.
San Francisco, Nashville, Atlanta, and Denver are urban areas identified as using
network based speed estimates. The problem is especially crucial during congested
conditions. Network based methodologies are fairly reasonable at simulating free-
flow or uncongested conditions. During congested periods, however, speeds
associated with links with heavy volumes may be incorrect. In terms of the emission
inventory, this condition would underestimate emissions produced by that link if the
speed is over-estimated.
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3. Coverage of Local Roads. Transportation network models typically do not include
minor and local roads, yet an emissions inventory requires that all travel be covered.
Available data on non-network modeled local road characteristics may be non-existent
or limited. Procedures used to estimate local road VMT may be based on judgement
and of questionable accuracy.
To replicate local street travel, a variety of techniques currently are being used. For
example, the Hartford inventory assumes the distance of all traffic generated by
centroid connectors, a point where all traffic is loaded on the network, to be .96 miles
long and operating at uncongested level of service "C" for peak and off-peak con-
ditions. Denver doubles its covered local network VMT to approximate total local
road conditions. A consistent and accurate procedure needs to be developed because
lower classification roadways, especially in urban areas, generally operate at low
speeds and may be susceptible in certain conditions to congestion during peak
periods.
4. Inconsistency in Accounting for Peak and Off-Peak Travel. There is a lack of a con-
sistent methodology being used to disaggregate VMT and speed data by time of day.
The failure to reasonably account for congested (high volume/low speed) conditions
may underestimate emissions. Using default speeds may not be appropriate
considering that most urban area speeds are lowest on facilities which have the highest
volume of traffic.
At the lower end of the precision spectrum in terms of accounting for the variation in
peak and off-peak travel are urban areas such as Boston, Fresno and Chicago that use
highly aggregate methods for estimating VMT and speed. The use of facility type
VMT by county and the use of an "average" daily speed value for that class of facility
does not adequately take into account peak period congestion.
The methods utilized by urban areas using a transportation network based technique,
such as San Francisco, are able to disaggregate volumes and speeds by AM/PM peak
periods and for off-peak conditions, as well as for individual corridors. These
methods fall within the middle of the precision spectrum because the methodology to
estimate volumes appears to be more reliable than the methodology to estimate
speeds.
Of the urban areas interviewed, the Phoenix and Detroit methods represent the
highest level of precision. Their methodologies relate speed to volumes on a link by
link basis, closely simulating real traffic operating conditions for peak as well as off-
peak periods.
5. Lack of Current Transportation Data. The validity of a transportation network model
is directly related to how frequently travel behavior data are collected and integrated
into the modeling process. Most larger Metropolitan Planning Organizations
conducted large scale household travel surveys in the 1960's and 1970's. Because these
efforts require extensive resources, most urban areas can not now replicate these early
survey efforts given the current lack of funding. To make up for this deficiency,
network models increasingly are being validated incrementally with the use of census
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data and smaller scale surveys. For example, it is estimated that about 30 urban areas
have conducted some form of limited origin-destination survey since 1980 for use in
re-validating their models.
The Los Angeles area is a typical example in which their current model was developed
using surveys and roadside interviews in 1967, and which subsequently has been
updated using information from a 1976 survey and the 1980 census. A new survey
may be conducted within the next few years. Representative and up-to-date travel
surveys are a critical component to a regional emissions inventory because they
provide the base line travel assumptions against which an area wide transportation
model can be calibrated.
6. Problems of County-wide Reporting. For areas that are not using network model
traffic outputs or areas in which the air quality planning area is larger than the
transportation network, traffic volume data may be limited. Facility classifications
may be inconsistent with the network model. Care must be taken in mixing empirical
data with model results. The cost of obtaining detailed information from non-modeled
areas, however, may not be worth the expense because of the small fraction of total
emissions these areas produce.
If consistent methodologies are desired, there may be a tendency to aggregate and
report VMT and speed data to the "least common denominator." HPMS statistics may
be used, and inventory results may be reported only at the county level. This
approximation will not document the nuances of different urbanized and rural area
traffic behavior for specific facility types.
In the cases of Illinois and Massachusetts, for example, VMT is inventoried at the
county or regional level by facility type with an area-wide "average" travel speed
assigned to that class of facility.
7. Lack of Alternative Approaches. With appropriate adjustment and post-processing,
transportation network-based models may be an appropriate tool for predicting traffic
inputs to the mobile source emission inventory process. However, for areas without
transportation model systems, alternative acceptable approaches need to be agreed
upon to assess VMT and speeds. Alternative methodologies can be defined that are
consistent with the magnitude of the problem. If congestion is a major component of
the transportation system, a detailed link assessment could be required. For those
portions of a region having relatively little travel, simpler methodologies could be
employed.
Portland, Oregon is an example of an inventory area in which a mixture of approaches
is necessary. Their inventory area encompasses both non-modeled rural areas and
modeled urban areas of two states. Three separate agencies are involved with
network modeling, but with none of the models being consistent and in a transferable
format for a regional link level emissions inventory.
8. Requirements of a Mobile Source Inventory are not Consistent with the Baseline of
the Metropolitan Area Transportation Planning Process. The urban transportation
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planning process, and its associated set of computerized (UTPS) travel demand
models, are not entirely consistent with the need to develop mobile source emissions
inventories. For example, the "typical" day in terms of average traffic used for
transportation planning purposes will not correspond to the same time period that
should be used for either a CO or VOC emissions inventory.
The urban transportation planning process utilized by larger MPO's often results in a
regional transportation plan with a single planning horizon in the range of 20-30 years.
This plan may then be updated every three to five years. The regional transportation
planning process compares and evaluates future alternative transportation plans that
will satisfy projected demand, with each alternative plan typically being projected
20-30 years into the future from a calibrated base-year. In contrast, the forecast
emission inventory for a SIP is required at 5 year increments or even annually, and
requires a high degree of precision over an entire region. There is no easy mechanism
to accurately interpolate transportation data at an internal of a small number of years.
Accurate intermediate year forecasts require a separately coded transportation
network, something which has almost never been done in the past.
A related issue is what transportation alternative to utilize as the basis for the future
year base emissions condition. The "preferred alternative" may satisfy demand, but is
it realistic considering funding restraints?
The base year for transportation planning purposes usually will not be the same as the
air quality base year desired by EPA. This means that VMT and other travel
projections can not be directly translated into EPA terms. Ideally, an entirely new set
of transportation analyses should be produced, but this is a time-consuming and
expensive task. Thus, transportation and emission inventory analyses are frequently
out of sync in terms of other base and horizon analysis years.
The Tampa inventory process is currently confronted with this issue of what network
model to use. The choice is an out-of-date model that would probably underestimate
VMT or wait for a calibrated model that will be available only after the EPA deadline.
The transportation planning and the mobile source emission inventory processes
ideally should be developed in tandem with each other. Currently in many urban
areas, they are running out of "sync" creating problems of consistency.
9. Requirements for Emissions Inventory Updates May Be Too Frequent. The urban
areas contacted indicated that the time interval between preparation of the base year
inventory and subsequent updates may not be long enough to make significant
difference in terms of regional emissions. Reasonable Further Progress (RFP)
reporting on an annual basis is felt by representatives of some urban areas to require
nearly the same level of effort as the inventory reporting procedure. The mobile
source emissions inventory process is resource and labor intensive at a time when
agencies are being requested to do more work with lower levels of funding. If
inventory updates are required frequently, there may be a tendency to use easier,
more approximate procedures. The use of detailed methodologies is easier to justify if
the need for their use is less frequent, and thus the need for the associated resource
expenditure also is less frequent.
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10. Available Expertise. The preparation of the highway vehicle portion of a mobile
source emissions inventory may require greater sophistication and capability than is
available in many areas. The urban transportation planning process requires
significant expertise in computer programming and transportations systems analysis.
Typically, only the large urban areas have these resources. The computer interface
between urban network models and MOBILE4 may require a "customization" which is
beyond the resources of smaller MFC's.
In many urban areas that do have a developed transportation network model, the
availability of transportation expertise may still be a problem. Many less advanced
urban areas are just trying to financially cope with the mechanics of the transportation
modeling process, i.e., data collection, network coding, calibration, etc., and do not
have resources to adapt their transportation model for air quality purposes. Tampa,
FL is an example of an urban area that is developing a new model to meet EPA
criteria. It is estimated, however, that it will take at least 18 months for this work to be
completed.
11. Staff Turnover. Lower level staff are usually responsible for running MOBILE4, and
may have only a limited understanding of transportation data and complex urban area
travel forecasting models. Typically once they have been trained and experienced,
they move on to higher positions. Internal expertise is not institutionalized over the
long term.
Problems of staff turnover and inexperience were identified in both the Detroit and
Boston interviews. It is assumed that most urban areas are confronted with these
issues because of the large amount of time since the last emissions inventory. A
related issue is the fact that air quality planning staff may not be trained to appreciate
that temporal variations in VMT and speed inputs in the MOBILE4 model can have
significant influence on the amount of emissions that are produced.
12. Funding Limitations. In light of reductions in Federal funding, including the EPA
Section 175 program that interfaced metropolitan transportation planning and air
quality planning, state transportation and air quality agencies are required to assume
more responsibility in completing a more detailed mobile source inventory for a larger
geographic area, and to do this for less money. While some DOT funding may become
available to support mobile source emission inventory work, these funds generally
have not yet made up for the loss of Section 175 monies.
Atlanta and Houston are examples of urban areas which are confronted with the
situation of producing a more detailed emissions inventory for a larger geographic
area with lower levels of available funding. During the early 80's, the Atlanta area
produced an emissions inventory for 7 counties, which approximated the area covered
by the local MPO transportation network model. The current emissions inventory
covers a total of 12 counties, of which 4 are not included in the network model.
13. Institutional Fragmentation. Relationships between air quality agencies and the
designated transportation Metropolitan Planning Organizations (MPO) are now too
often restricted to informal contact. Development of a mobile source inventory
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requires a large number of agencies in either a direct or review role. Input from other
agencies is frequently accepted on faith, with little understanding of how it was
developed and only minimal concern with the consistency or accuracy of underlying
assumptions. In some cases, transportation agencies which were responsible for
producing mobile source emissions estimates in the 1970's and early 1980's are
currently not involved.
According to representatives from the Chicago Area Transportation Study (CATS), the
formal institutional relationship that existed in the 1970's and early 1980's between the
environmental agency responsible for running the emission models and CATS has
ended. Currently only informal and infrequent data exchange occurs. Consequently,
the current Illinois SIP may have only limited urban area expertise to complete their
inventory. Primary reliance instead is being placed on state level data developed by
the Illinois Department of Transportation.
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3.0 Existing Guidance Materials
Post-1987 Available EPA Guidance
Four EPA documents have provided the primary guidance and background information
for the preparation of the mobile sources emissions inventories reviewed for this analysis.
These are:
• Emission Inventory Requirements for Post-1987 Ozone State Implementation Plans,
EPA-450/ 4-88-019, U.S. Environmental Protection Agency, Research Triangle Park, NC,
December 1988.
• Emission Inventory Requirements for Post-1987 Carbon Monoxide State Imple-
mentation Plans, EPA-450/4-88-020, U.S. Environmental Protection Agency, Research
Triangle Park, NC, December 1988.
• User's Guide to MOBILE4 (Mobile Source Emission Factor Model), EPA-AA-TEB-89-01,
U.S. Environmental Protection Agency, Ann Arbor, MI, February 1989.
• Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources, EPA-
450/4-81-026d (Revised), U.S. Environmental Protection Agency, Research Triangle
Park, NC, December 1988.
The first two documents identify the basic requirements which must be met for the
preparation and submittal of the Ozone and CO State Implementation Plans (SIPs).
Specifications are provided for base years, geographic coverage, and temporal and
atmospheric conditions which must be assumed. Also identified are data requirements, the
format in which data are to be provided, documentation requirements, and submission
schedules.
Of primary significance with respect to mobile source VMT and speed analysis is the
specification of the required geographic coverage for the inventories. Although exceptions
may be allowed in certain circumstances for the CO inventory, Ozone and CO SIP
inventories must be prepared for the entire metropolitan statistical area or consolidated
metropolitan statistical area (MSA/CMSA) in which nonattainment of NAAQS was
determined. This requirement may result in problems related to the availability of accurate
traffic data in portions of MSAs/CMSAs, depending upon the compatibility of trans-
portation and air quality planning areas.
Total highway vehicle emissions are to be determined by multiplying vehicle-miles
traveled (VMT) by MOBILE4 unit grams/mile emission factors for specific conditions and
roadway classifications. MOBILE4 calculates emission factors for individual vehicle types,
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dependent upon various conditions such as ambient temperature, speed, and mileage
accrual rates. The MOBILE4 User's Guide provides a handbook for inputting various area-
specific data to develop emission factors appropriate for a given analysis area.
Vehicle Speed Estimation
The speed at which vehicles travel has a critical bearing on the amount of emissions which
are produced. As stated in the User's Guide:
"Emission factors vary considerably with the average speed assumed. The value(s)
input for speed in MOBILE4 will have a significant impact on the resulting emission
factors."
MOBILE4's default average speed, based on Jhe Federal Test Procedure (FTP) driving cycle,
is 19.6 MPH, which is intended to be representative of driving conditions typical of a
standard trip in an urban area. Independent studies of urban area traffic conditions have
generally shown increasing highway congestion nationwide, resulting in lower average
travel speeds and a lengthening of the peak travel period. The net result is a trend toward
higher volumes of traffic travelling at slower speeds for a longer peak period. These
conditions are not only apparent in relation to suburb to CBD travel but also increasingly to
intra-suburban travel in response to higher densities of employment and commercial
development in suburban areas. The User's Guide stresses that "the prediction of average
speeds in the future is difficult, and may be a critical factor in some areas' ability to project
compliance with SIP commitments and air quality standards."
The user is referred to local, regional, or state transportation agencies as data sources as
well as to Volume IV for procedures in estimating area specific speeds. A specific issue
discussed in the Volume IV guidance is the accuracy of speed data produced by UTPS. As
stated in the guidance:
"Speed is not predicted by transportation planning models, instead it is used as a
measure of impedance to allocate travel across the network. Thus, the speed values
produced in the outputs represent the results of the most successful allocation of
travel, not a prediction of the speed that results from each particular level of travel."
In the case of vehicle speed data, it is apparent from this review that many agencies
recognize problems with regard to its accuracy, and that some agencies have developed
algorithms outside of the transportation model framework based on volume to capacity
ratios to develop improved estimates of speed. Since these refined methodologies may be
beyond the resources of some agencies, EPA now recommends using speed values
produced by the transportation planning model unless better information is available.
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network. VMT and travel speeds can then be generated by the model for individual
roadway links or roadway classes.
Various issues relevant to the network modeling process are identified. Frequently, the
base year of the transportation model does not correspond to the required base year of the
emissions inventory. Local road activity often is not included in the network model and
must be quantified manually. Furthermore, the air quality planning area may extend
beyond the boundaries of the transportation network model due to the requirement that
the entire MSA/CMSA is to be included in the inventory.
Rural
For estimating VMT in rural areas, the guidance recognizes the difficulty in developing
inventories of vehicular miles of travel due to the limitations of available data. It is
recommended in these cases that statewide VMT data, developed by all state transportation
agencies for FHWA, be apportioned to the ceunty or district level. Four methodologies for
developing apportioning factors are described: fuel sales, roadway mileage by functional
category, motor vehicle registrations, and population. Each of these methodologies has
advantages as well as inherent weaknesses, yet provides a means of estimating VMT
without a sizable expenditure of resources. A similar procedure is described for dis-
aggregating VMT by roadway category and vehicle type.
Emission Factors
The remaining sections of Chapter 4 discuss in greater detail specific inputs used in
developing MOBILE4 emissions factors. Much of the material is based on the MOBILE4
User's Guide. As in the User's Guide, derivation of the average speed assumed as a default
in MOBILE4 is discussed and the significance of varying speed conditions is emphasized.
Reference is made to the preceding discussion of methodologies for obtaining more
accurate speed data for input into MOBILE4.
Potential Areas of Additional Information
The existing EPA guidance documents generally provide the essential information
necessary to develop the traffic data and emission factors required for the preparation of a
mobile source emissions inventory. There are, however, possible technical areas in which
additional information potentially could be provided.
Information on UTPS and similar transportation network models is widely available to
transportation planners. While it is not the responsibility of EPA to provide a detailed
handbook for the use of the UTPS planning model or its variations, it may be useful for
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EPA to identify what those sovirces of information are in order to assist those state and local
agency staff who would like a more in-depth understanding of transportation planning
model concepts.
Despite the availability of information related to transportation network modeling
procedures and the widespread availability of micro computer-based network models, a
number of urban areas over 50,000 population do not utilize network model data in the
preparation of their inventory. In some areas, a transportation network model does not
currently exist. In other areas, a network model may exist for only a portion of the air
quality planning area. In these cases, procedures similar to those now recommended for
rural and small urban areas are generally applied. It would be useful to provide guidelines
for those urban areas which are unable to use a network model, similar to those now
described for rural areas. Of particular use would be methodologies for calibrating and
verifying VMT data through the use of field surveys. In addition, these guidelines should
be extended to cover use of both FHWA's HPMS dataset and a state DOT's computerized
database of traffic counts in preparing the highway vehicle portion of a mobile source
emissions inventory. This information could build upon existing U.S. Department of
Transportation guidelines for estimating vehicle miles of travel.
An important area in which the guidance could be expanded is in regard to development
of speed data. While the guidance document states the improved procedures are available
for estimating speed, such as those based on use of the Highway Capacity Manual, it does
not actually describe these approaches. In this context, consideration could be given to the
use of field measurements to assess the accuracy of existing speed assumptions and results.
The importance of improved accuracy in the temporal and geographic distribution of both
VMT and speed is stressed in the growing body of research which quantifies trends of
increasing highway congestion and longer peak travel periods. Given the non-linear
relationship of speed and emissions, the methodology by which speeds are averaged over
time may result in significant underestimation of emissions.
One way of introducing greater precision in estimating emissions in relation to speed is to
disaggregate VMT by facility type and by daily time periods (i.e., AM peak, PM peak, and
off-peak). By averaging speeds over specified periods of the day, rather than averaging
over an entire day, a more accurate estimate can be made of VMT produced under
congested operating conditions, when emission levels are peaking. Separate emission
factor estimates could then be made to represent each of these periods that can better
account for the non-linear relationship of emissions to speed. Additional information could
be provided on procedures for disaggregating VMT by time period and methodologies for
using available data to temporally distribute VMT and speeds.
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4.0 Recommendations
The observations presented in Section 2.0 and 3.0 imply the following recommendations
with respect to the preparation of mobile source emission inventories:
1. UTPS-style model systems, while representing one available current methodology for
urban area emission inventories, generally are not totally satisfactory in their current
form for air quality purposes. Refinements and a post-processor vehicle speed
estimation capability can be added. In addition, improved vehicle fleet information will
be required as more emphasis is placed on the production of dean alternative fuels and
low emission vehicles;
2. Emission inventory procedures should be oriented to the categories of non-attainment
severity as defined by the new Clean Air Act. Different methodological approaches will
be appropriate for different urban areas, and possibly even within an area. In some
situations, a hybrid of procedures will be appropriate; for example, in a situation where
the non-attainment area is significantly larger in size than the geographic area covered
by the UTPS-network.
3. Mobile source inventory methodologies should support future as well as current year
baseline projections. In addition, whenever possible, the same quantitative meth-
odology as is used for preparation of the inventory also should be utilized for
forecasting the effectiveness of alternative transportation control strategies.
4. Monitoring or tracking of travel and emission trends will become increasingly
important at the urban area level with the new Clean Air Act. This monitoring will
have to relate to the overall emissions inventory, but be able to be efficiently performed
on an annual basis. Use of the Federal Highway Administration's Highway Per-
formance Monitoring System (HPMS) represents an available, nationally consistent,
statistically sound methodology for monitoring vehicle miles of travel.
5. The desired level of inventory accuracy and disaggregation should dictate the choice of
inventory methodology. If grid-based urban area dispersion modeling is going to be
done, then mobile source emission inventory methodologies that are accurate at a zonal
level of disaggregation will be necessary. This generally will imply use of a UTPS-style
approach.
6. Institutional and resource considerations may be barriers in some urban areas to
achieving satisfactory emissions inventories. Priority, care, and sensitivity need to be
devoted to establishing a long-term cooperative working relationship of shared
responsibilities between transportation and air quality agencies at the state and local
levels of government. To satisfy the requirements of the new Clean Air Act, it is
essential that emission inventory and other related transportation air quality data
represent the best available.
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Appendix
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Appendix Contents
Houston, Texas A-l
Phoenix, Arizona A-4
Detroit, Michigan A-6
Hartford, Connecticut A-8
Los Angeles, California A-10
Portland, Oregon 1 A-13
San Francisco, California A-16
Nashville, Tennessee A-18
Atlanta, Georgia A-20
Denver, Colorado A-22
Tampa, Florida A-25
Boston, Massachusetts A-28
Fresno, California A-31
Chicago, Illinois A-33
Pittsburgh, Pennsylvania A-36
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- Urban Area Case Studies
Houston, TX
Responsible Agencies and Funding
The Houston-Galveston Area Council (HGAC), the Metropolitan Planning Organization for
the Houston-Galveston MSA, is under contract with the Texas Air Control Board (TACB) to
develop all traffic data used in the preparation of the mobile source emissions inventory.
HGAC is responsible for running the areawide traffic model and also for development of
demographic data. HGAC is assisted by the Texas Transportation Institute, a research
group affiliated with Texas A&M University. TACB then uses the data developed by
HGAC to run MOBILE4 and prepare the mobile source emissions inventory.
Funding for HGAC's activities is made available through TACB, although the amount of
funding has been reduced substantially from 1981 when HGAC was responsible for an
extensive traffic data collection program for the preparation of the SIP. At that time, HGAC
was responsible for analysis of a single county. Currently, HGAC is analyzing traffic data
for an eight county area.
Modeling Process: General
Traffic data are developed in the Houston-Galveston area utilizing the Texas Planning
Package (TPP) network model. This model was developed by the Texas State Department
of Highways and Transportation and is similar to UTPS. UTPS is used in the analysis of
transit trips because TPP does not have a transit component. Data for running the model
are collected from the Texas Department of Motor Vehicles (auto ownership and vehicle
age data), and also are based on a 1984 household travel survey which identified the
distribution of trips over time and a 1985 travel time and speed survey. Traffic data
collected in 1985 have been updated to a 1988 baseline using population and employment
data, as available.
The traffic model consists of 2,600 analysis zones. In developing the emissions inventory,
vehicle emissions from each of the traffic zones is aggregated into 5km grid cells and
quantified for a typical summer weekday on an hourly basis.
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The issue of resource availability was a primary concern raised by HGAC. This has caused
serious problems with the agency's ability to comply with EPA requirements. HGAC
stated that they had $1 million in 1981 to prepare SIP related analyses for a one county area.
Currently, HGAC has $40,000 available to prepare analyses for an eight county area.
Contact:
Transportation Manager
Houston-Galveston Area Council
P.O. Box 22777
3555 Timmons
Houston, Texas 77227
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Phoenix, AZ
Responsible Agencies and Funding
The Arizona Department of Environmental Quality (AZDEQ) is the Agency responsible for
running the MOBILE4 emission model. Through an inter-agency memorandum of
agreement, local traffic data are provided by the Arizona Department of Transportation
(ADOT) and the Maricopa Association of Governments (MAG). In addition, the Arizona
Department of Environmental Quality and the Maricopa Air Pollution Control Admin-
istration (MAPCA) participate in evaluating the input traffic data.
MAG is responsible for operating the areawide transportation demand network model, and
utilize the UTPS battery of software programs. Financing is through Federal, State and
local funds as part of the Metropolitan Planning Organization (MPO) process. According
to the MAG representative, the inter-agency cooperation maximizes available resources by
providing a process of internal checks to. the input data which leads to inter-agency
confidence in the final inventory.
Modeling Process: General
According to the AZDEQ representative, different emission inventory procedures are used
for SIP modeling than are used for evaluating potential control measures and developing
RFP reports. A "Quick and Dirty" method assumes an average speed of 28 MPH for all
facility types. Vehicle miles of travel (VMT) are multiplied by the corresponding emission
factors to calculate emissions for each pollutant.
The "Full Scale" emission inventory method utilizes the Link Attribute Files of the UTPS
system. Network VMT is calculated and summed on a link by link basis, representing 24
hours or daily vehicle miles of travel (DVMT). At this step in the inventory, a "Traffic
Conversion Interface" computer program converts network DVMT output to peak period
and off-peak period VMT that can be utilized by MOBILE4.
Speed Inputs
According to the AZDEQ representative, ongoing traffic counts and speed studies
conducted by MAG are used to validate network speeds. For the "Full Scale" emission
inventory, speeds are calculated by the Traffic Conversion Interface which utilizes the VMT
output from the Transportation network model and calculates a volume to capacity ratio
(V/C) for each link and assigns a corresponding speed value by means of a "Look Up"
table. For SIP emission inventory modeling, traffic data are adjusted for month of year, day
of week, and hour of day using adjustment factors developed from traffic count surveys.
The adjusted volumes are then used to compute vehicle speeds by link from V/C ratios for
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each hour of analysis. These link volume and speed' values interface with MOBILE4
emission factors using design day hourly ambient temperatures.
The AZDEQ representative elaborated that the modeled speed output is fairly accurate for
the congested core area. In the central core area the Traffic Conversion Interface calculates
10-15 MPH in the peak hour, which is close to observed speeds. Speeds are also estimated
to decline in the future. The current average speeds for all facility types are estimated to
range between 25-30 MPH, and in the future the range is 15-20 MPH.
VMT Inputs
Ongoing traffic counts, household driver surveys (1981 and 1988), and the mid-decade state
census are data sources used to validate the travel assumptions in the areawide trans-
portation network model. ADOT in coordination with MAG are responsible for updating
and evaluating traffic data for the mobile emission inventory process. VMT are calculated
by the Traffic Conversion Interface on a link by link basis for the following highway
classifications: Expressway, Freeway, Arterial 1, Arterial 2, Collector, and Centroid.
Approximately, 15% of total VMT is estimated to occur on non-network local streets.
Geographic Coverage
The transportation planning boundary is basically consistent with the air quality planning
area, an area which covers 31 by 18 miles. All developed areas are included in the trans-
portation planning area.
General Issues and Summary
The AZDEQ representative said they are confident of the results from the modeling process
used to predict VMT and travel speeds in the August 1988 SIP for CO. It is also reported
that the USEPA Office of Mobile Source Emissions in Ann Arbor, which was involved in
the inventory process, was also confident in the results obtained.
Contacts:
Manager of Air Quality Assessment
Arizona Department of
Environmental Quality
Central Palm Plaza Building
2005 North Central Avenue
Phoenix, Arizona 85004
(602) 257-2346
Manager of Transportation Planning
Maricopa Association of Governments
1820 West Washington
Phoenix, Arizona 85007
(602) 254-6308
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Detroit, MI
Responsible Agencies and Funding
The Southeast Michigan Council of Governments (SEMCOG) is responsible for running and
maintaining the MOBILE4 emission model for the Detroit non-attainment area, and is the
recognized transportation Metropolitan Planning Organization for the Detroit urbanized
area. SEMCOG is also responsible for operating and maintaining the area-wide
transportation network model. Currently, SEMCOG is using TRANPLAN, a commercially
available micro-computer based network model software package. The transportation
network model is financed through Federal, State and local funds as part of the MPO
transportation planning process.
Modeling Process: General
Urban area VMT inputs are produced by the TRANPLAN package. Speed values are
calculated independently using volume to capacity curves established by the Highway
Capacity Manual. A "Look Up" procedure has been developed which uses the volumes
that are output from the TRANPLAN package and calculates speed by facility type
according to the V/C ratio. The procedure represents a "normal work day" and is not
seasonally adjusted to reflect temporal variations.
Speed Inputs
The "Look Up" procedure uses the forecasted VMT values for a specific link (facility) and
calculates the percentage of VMT that would occur in the peak hour and then uses a V/C
ratio to forecast the corresponding speed on the facility. The MOBILE4 emission factor
(corresponding to the estimated speed) is then multiplied by the VMT generated by that
link to calculate the emissions produced by the link for the peak hour. This procedure is
repeated for all links in all directions in the network for all hours. Speeds for non-network
VMT are estimated using free-flow or posted conditions. Emissions are summed for all
links for all hours to produce the total mobile source inventory.
VMT Inputs
VMT inputs are generated by the SEMCOG area-wide network model. Volumes are
validated with Michigan Department of Transportation traffic counts, local counts and
professional judgement. VMT is calculated for the following facility types: Freeway,
Expressway, Major Arterial, Minor Arterial, and Major Collector. As a rule, local
residential streets and minor collectors are not coded in the network. In the previous SIP,
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6.6% of all VMT was considered off-network. VMT is distributed according to the traffic
assignment procedure and is reported by traffic analysis zones.
Geographic Coverage
The SEMCOG transportation planning network corresponds geographically to the air
quality planning area. The lowest level of disaggregation for emissions is the traffic
analysis zone, which typically is approximately 1 /2 mile square.
General Issues and Summary
The SEMCOG representative indicated that they are confident "on a regional basis" of the
VMT estimation procedure developed for their mobile source inventory. However, it also
was indicated that more ground counts would be useful to assist in the calibration process
of the model.
In contrast to a capacity restraint function for assigning speeds, SEMCOG relies on a post-
processing volume to capacity calculation to predict speed by facility class. The SEMCOG
experience warrants further investigation because their speed estimation procedure
appears to simulate "real" traffic conditions; i.e., traffic volumes and speeds fluctuate over a
course of a day with vehicle speeds declining as volumes increase.
SEMCOG representatives expressed concern about the utility of using coarse aggregate
transportation data from transportation models as input for a detailed grid-based air
quality dispersion model. Another general point involved the establishment of guidance
for emission inventories. SEMCOG recommended that FHWA, UMTA, and EPA coor-
dinate and establish one comprehensive set of planning guidelines that would satisfy all
agencies.
Contact:
Southeast Michigan Council of Governments
Air Quality Planning Division
Suite 1900 Edison Plaza
660 Plaza Drive
Detroit, Michigan 48226
(313) 961-4266
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Hartford, CT
Responsible Agencies and Funding
The Connecticut Department of Environmental Protection (DEP) is responsible for running
and maintaining the MOBILE4 emission model for the current "Post 1987 Emission
Inventory." According to the DEP representative, the entire State of Connecticut is in non-
compliance with the national air quality standards for ozone. Unlike must other states, the
State of Connecticut utilizes a state-wide transportation network model for transportation
and air quality purposes. The DEP, with traffic input from the Connecticut Department of
Transportation (ConnDot), developed the 1987 base year emissions inventory that has been
used in post 1987 SIP-related work.
Modeling Process: General
The process in which the transportation inventory is annually updated is a product of the
Statewide Person Forecasting Model (PERFORM). This model is used to forecast travel
(auto and transit) for all ConnDot activities including: highway and transit planning,
design, permit applications, and environmental assessment. The input data which drive
the model are updated as new information becomes available. In addition, the models are
periodically recalibrated to reflect ground counts, and estimates of current vehicle miles of
travel (VMT) based on ground counts. Validity checks are based on secondary sources,
such as motor fuel consumption. The model output includes all travel in Connecticut
including thru trips and intrazonal trips. Estimates of current VMT and forecasts of future
VMT are based on the following model procedures: socio-economic trend extrapolation
estimation, person trip generation, trip distribution, modal split, trip assignment and
vehicle mile travelled by speed.
Speed Inputs
Vehicle miles of travel by peak and off-peak speed categories are calculated by multiplying
the volumes (developed in the trip assignment phase) by the link length to produce VMT.
A peak period percentage which is a function of the classification and area type is then
applied. This results in an off-peak VMT which is assumed to operate at free flow speeds.
The VMT which occurs during the peak period is assigned to operate under the level of
service (and speed) which is appropriate for its volume to capacity ratio as defined in the
Highway Capacity manual. Intrazonal trips (short trips which stay within a traffic zone
and are not captured by the network model) are assumed to be .96 miles long and operate
at a level of service "C."
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VMT Inputs
Vehicle miles of travel (VMT) data for three highway classifications — Expressways,
Arterial/Collector and Non-Expressway — are obtained from ConnDOT. Average daily
VMTs are adjusted seasonally for day of the week and month of the year for six classes of
highways: Rural Interstate, Urban Interstate, Recreational Interstate, Other Urban, Other
Rural, and Rural Recreational. For the typical ozone summer day, the values in the three
summer months for a weekday are averaged. Similarly, for a typical winter day value, the
factors for the three winter months are averaged. The resulting values are as follows:
Ozone Summer Day Seasonal Adjustment Factor = 0.91
Winter Day Seasonal Adjustment Factor = 1.07
The VMTs are then multiplied by these seasonal adjustment factors to obtain the
applicable VMT.
Geographic Coverage
Both transportation network model and the air quality area cover the entire state and
therefore are consistent. The lowest level of data disaggregation for transportation and
emissions is the individual link. VMT and emissions are reported on a county basis.
General Issues and Summary
The DEP representative said that "In general he was fairly confident in the VMT and speed
outputs obtained for the mobile source emission inventory process." He also indicated,
though, that "closer coordination is necessary among the agencies that provide the traffic
input information and the agency that runs the actual MOBILE4 model. If any information
is missing, it is more of a institutional mis-understanding than an intentional omission. The
level of detail is directly proportional to the amount of resources that can be spent.
The following general concerns were expressed by DEP as potential areas for improvement.
Additional disaggregation of traffic volume data by time period is needed to develop a
better classification of speeds and avoid underestimating speeds on congested streets in
urban areas. Improved vehicle classification data are needed, as well as information on the
mix of hot and cold starts. •
Contact:
Connecticut Department of Environmental Protection
Bureau of Air Management
165 Capitol Avenue
Hartford, Connecticut 06106
(203) 566-2690
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Highway Vehicle Emission Inventories
Los Angeles, CA
Responsible Agencies and Funding
Travel data are prepared by the Southern California Association of Governments (SCAG)
using the SCAG Regional Transportation Demand model. Vehicle emission rates are
developed by the California Air Resources Board (ARB). By applying these emissions
factors to SCAG travel data, SCAG uses the Direct Travel Impact Model (DTIM) to estimate
light-duty vehicle emissions. DTIM data are then used as input to the ARB's BURDEN
model to develop the statewide county-based emission inventory. Funding for SCAG's
modeling effort is through Caltrans and FHWA.
Modeling Process: General
The SCAG travel demand model is based oh the Urban Transportation Planning System
(UTPS), as adapted by the California Department of Transportation (Caltrans) for the Los
Angeles Regional Transportation Study (LARTS). The models were developed using
household surveys and roadside interviews in 1967 and updated using information from a
1976 household survey and 1980 census journey-to-work data. Each base year model run is
validated against traffic counts at selected screenline locations. Transit passenger estimates
are compared with data from transit companies.
ARB maintains an emissions inventory for all counties and air basins in the State. The last
comprehensive emission inventory was published in 1983. An updated inventory is being
prepared for 1987 and is scheduled to be published in 1991. The inventory will be grid
based model by hour of the day.
Speed Inputs
Link travel times developed in the traffic assignment process are adjusted based on vehicle
to capacity ratios. The weighted average speed is output for each link and is considered the
congested speed. Model base year results are compared with ground counts at selected
screenline locations throughout the region to assess the accuracy of the modeled data.
The DTIM model developed by Caltrans is then used to apply emission factors to VMT for
each period based on average speeds specified for each individual link in the highway
network.
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VMT Inputs
The mode split model which allocates person trips to travel mode utilizes algorithms from
three separate mode split models that separately account for drive alone, shared-ride,
carpool, and transit. A specialized methodology developed by LARTS is then used to
allocate ADT to peak and off-peak periods to account for travel that may occur over two
analysis periods. Highway assignment procedures then assign trips to the appropriate
network and calculates VMT for each of the three travel periods for each link in the
highway network. Vehicle trips are assigned separately to the network for AM and PM
peak and for off-peak periods using an equilibrium assignment for the peak periods and a
probabilistic multipath assignment for the off-peak period. Link-based VMT and speed are
then used as input to DTEM.
Geographic Coverage
The SCAG region includes 6 counties, containing about 38,500 square miles. The region's
air quality planning area covers 5 of these 6 counties, excluding Ventura County. All travel
within the air quality planning area, therefore, is accounted for in the SCAG traffic model.
Information on trips into and out of the modeling area are represented at 30 cordon
stations. Information about external trips, those outside of the SCAG region, were
developed from the 1967 external roadside interview. In that survey, all roads crossing the
study area boundaries which carried significant traffic volumes were identified. 13
locations were used as interview sites, representing 98% of total vehicles crossing the study
area. From the data gathered from the interview process, total daily external vehicle trip
tables were developed and allocated to the three time periods (AM and PM peaks, and off-
peak).
Local roads, including minor arterials and collectors, are not included within the traffic
network model. However, to account for local travel, additional traffic and capacity are
assigned to pre-existing links in the network, depending upon the orientation of the local
road being accounted for.
General Issues and Summary
Based on the documentation describing SCAG's modeling process, the procedures used in
developing the mobile source emission inventory for Los Angeles appear to use modeling
techniques which are more advanced than those generally being applied in other urban
areas where resources may be more limited. Speed inputs, as developed for peak
conditions, use vehicle to capacity ratios to replicate congested operations. VMT is
developed throv eh a series of steps which involve an advanced mode-split model to
allocate trips by rideshare modes as well as transit. Speeds and VMT are calculated for
each travel period for each link in the network and DTIM then applies emission factors at
the link level rather than aggregated by facility type.
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Contacts:
Southern California Association of Governments
818 West 7th
Los Angeles, California 90017
(213) 236-1800
South Coast Air Quality Management District
Planning Division
9150 E. Flair Drive
El Monte, CA 91731
(818) 572-2160
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Highway Vehicle Emission Inventories
Portland, OR
Responsible Agencies and Funding
Because of Portland's location on the border between Oregon and Washington, agencies
from both states are involved in the development of Portland's air quality inventory.
METRO, Portland's Metropolitan Planning Organization, is responsible for producing
VMT and speed data within a three county area. However, in order to compile data for the
MSA, these data must be obtained from a variety of sources. The Oregon Department of
Environmental Quality, Air Quality Division, produces the MOBILE4 emission factors. The
emission factors are then applied by METRO to produce the areawide inventory.
Modeling Process: General
Various sources of traffic data must be utilized for the Portland area given the geography
of the MSA. The traffic modeling procedures from which these data are derived are not yet
fully consistent among the responsible agencies. Three agencies are involved in the traffic
modeling process. METRO has developed a model for both metropolitan areas but the
model is much coarser on the Vancouver, Washington side.
METRO uses the EMME2 transportation modeling system. The Intergovernmental
Resource Center, the transportation planning agency for Vancouver, Washington, also uses
the EMME2 model. METRO is currently setting up for a Bi-State (Columbia River
Crossing) Study from which will come a single regional model with appropriate detail for
Washington State. Because a substantial portion of the MSA is not included in Portland's
EMME2 network, additional data must be obtained from the Oregon Department of
Transportation.
Speed Inputs
The method of calculation of speed is linked-based, but is applied through a matrix. The
link times are calculated post equilibrium assignment for the peaks and for the base. These
link times are used to create peak and base travel time matrices, which with the distance
matrix, translate to average zone-to-zone speeds for these time periods. These speeds are
then used (with distance) and the 24-hour trip table broken into the peak and base regimes
to calculate the emissions at these time-specific average speeds.
METRO does informal spot checks on zone to zone travel speed using the floating car
technique. They feel that the matrix based travel times are within 10% of true.
MOBILE4 emission factors are generated in 2 1/2 MPH speed increments, starting at
5 mph, up to 55 mph. National default values for all inputs are applied in calculating these
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factors with the exception of temperature and the vehicle age distribution for light duty
vehicles.
VMT Inputs
VMT data are available from the traffic network models for urban and some rural areas for
the following functional class categories:
Interstate
Principal Arterial
Minor Arterial
Major Collector
However, it was stressed by ODEQ that there data are not available for many rural areas
outside of the transportation planning areas and that, in general, data are not available on a
county-wide basis as required by EPA.
Local road VMT are developed by the Oregon Department of Transportation on a state-
wide basis and then disaggregated to counties using population and vehicle registration.
Geographic Coverage
There is a problem related to the geographic coverage of, and coordination between,
transportation planning areas with respect to air quality modeling in the Portland MSA.
Because the MSA covers an interstate area, the transportation modeling process involves
two separate regional planning agencies. Even with the availability of data from these
sources, there is a substantial rural area outside of the area covered by the network models
for which no data are generated. For these areas, statewide travel data are disaggregated
by the Oregon Department of Transportation.
General Issues and Summary
The process by which travel speed data are calculated based on a post equilibrium link-
based analysis represents an improvement over the use of purely network-based estimates.
The generation of speed data through a traffic network model has been criticized in that the
individual link speeds are adjusted through the calibration process to reflect travel volumes
as opposed to actual observed travel speeds.
ODEQ's primary concern relates to the geographic coverage required for the mobile source
air quality inventory. In general, county-based VMT information, as required by EPA, does
not exist for the entire Portland MSA. Many rural portions of the counties for which data
are required are outside of the transportation planning areas and, according to ODEQ,
these areas are not significant contributors to areawide emissions. As a result, a substantial
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amount of effort is required in order to generate what is considered to be unreliable data
for areas producing minimal impacts.
With respect to EPA guidance, ODEQ indicated that the EPA appears to assume a greater
level of sophistication concerning analytical operations than is currently available in the
various planning agencies within the Portland MSA.
Contacts:
Oregon Department of Environmental Quality
Air Quality Division
811 Southwest 6th Ave.
Portland, Oregon 97204
(503) 229-5696
METOO
2000 SW First Avenue
Portland, Oregon 97201-5398
(503) 221-1646
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Highway Vehicle Emission Inventories
San Francisco, CA
Responsible Agencies and Funding
The preparation of the mobile source air quality inventory for the San Francisco MSA is a
coordinated effort involving various environmental and transportation planning agencies.
Base traffic count data are developed by the California Department of Transportation
(Caltrans). The Metropolitan Transportation Commission (MTC) is an independent agency
created by the California Legislative and conducts its own traffic network modeling process
and associated travel surveys. It is MTC which has primary responsibility for developing
regional forecasts of traffic volumes. MTC's modeling program is funded through the state
and FHWA. The Association of Bay Area Governments (ABAC) is a voluntary association
for regional coordination. The California Air Resources Board (ARB) has developed a
California-specific emission factors computer program, EMFAC, which incorporates the
results of the state's own vehicle testing program. The San Francisco Air Quality
Management District (AQMD) will be responsible for preparing the current mobile source
inventory, using traffic data from MTC and emission factors generated by ARB.
Modeling Process: General
MTC uses a travel demand model, MTC FCAST/80-81 which is based on UTPS, to produce
trip tables by purpose and mode. Population and employment data to run the model are
prepared by the Association of Bay Area Governments approximately every 2-3 years. The
model currently is based on a 1981 home interview survey, although this will be updated
based on new survey data now being collected. Traffic data, provided by Caltrans and
others, include average daily traffic (ADT) from permanent counter locations and speed
data gathered through floating car observations. Traffic data is updated annually.
Speed Inputs
Average travel speeds are calculated within the MTC traffic demand model system for four
highway classifications (freeway, expressway, major arterial, and minor arterial) in 5
different area types (CBD, Outlying CBD, Residential, Rural, and one other). Free flow
speeds are determined separately for each classification and area based on volume/
capacity ratios and other more detailed data. Separate speed conditions are assumed for
daily and AM/PM peak operating conditions. There is no seasonal differentiation
assumed. Using factors to simulate congested operating conditions, speeds are adjusted by
route through a capacity restraint process to reassign traffic by route and mode. Estimated
speeds also are compared to observed speeds and the model recalibrated as needed. The
travel demand model also is used to simulate future travel speeds.
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VMT Inputs
Link VMT data calculated by the traffic demand model can be summarized in the same
categories as travel speeds. ADT data gathered by Caltrans and others are used for
validation purposes.
Geographic Coverage
The urban air quality area is smaller than the geographic area modeled by MTC's traffic
demand model. The entire San Francisco air quality planning area, thus, is encompassed
by the model. Minor arterials, collectors, and local roads are in part represented by access
links to the network. To the degree that these local roads are not covered by the model,
they require a less precise county-wide procedure to estimate VMT.
General Issues and Summary
MTC has expressed a high degree of confidence in the accuracy of both VMT and speed
data estimated by their traffic demand model. On the other hand, they are not as confident
with their vehicle classification data, which could have significant implications for their
emission inventory.
Contacts:
Emission Control Section
Air Quality Management District
939 Ellis Street
San Francisco, California 94109
(415) 771-6000
Metropolitan Transportation Commission
Metro Center
101 8th Street
Oakland, California 94607
(415) 464-7731
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Highway Vehicle Emission Inventories
Nashville, TN
Responsible Agencies and Funding
The Metropolitan Health Department is the agency responsible for running and
maintaining the MOBILE4 model for the current baseline mobile source emission
inventory. The Metropolitan Planning Commission (MFC) is the recognized transportation
Metropolitan Planning Organization for the greater Nashville region, and utilizes the
MINUTP transportation network modeling software. The regional transportation network
model is financed through Federal, state and local funds as part of the Metropolitan
Planning Organization process.
Modeling Process: General
MPC traffic volume data sources are validated by the Tennessee Department of Trans-
portation's (TDOT) annual average daily traffic counting program. TDOT utilizes the
Urban Transportation Planning System (LIU'S) network modeling software.
Urban area VMT and speed estimates utilized in the emissions inventory are produced by
the State using the UTPS traffic assignment model. Emissions are calculated for each of six
functional classifications and reported for 15 air quality zones. The air quality zones are an
aggregate of the traffic zones.
Speed Inputs
MPC funded, until budget cutbacks in 1988, special speed studies for air quality analysis
that were used to validate the speed output from the network model. According to the
MPC representative, the special speed studies provided the vehicle speed data input to the
emissions inventory. No speeds from the regional model are used in the emission
inventory. AM and PM peak periods representing "congested conditions" are modeled, as
well as, off-peak traffic conditions. Speeds are calculated by facility type and are compiled
on a link by link basis and are reported by traffic zones. Local non-network speeds in the
the urban core are assigned a value of 15 MPH, and in rural areas a value of 25 MPH.
VMT Inputs
Network VMT is calculated and summed on a link by link basis for the following facility
types: Freeway, Expressway, Major Arterial, Minor Arterial Collector, and local. In the
current SIP, local off-network VMT was estimated to be 8% of total VMT. Seasonal
variation factors for volumes were supplied by TDOT. VMT output is validated against
traffic counts supplied by TDOT.
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Geographic Coverage
The transportation planning area and the air quality planning area are equivalent in the
Nashville area, but smaller than the metropolitan statistical area (MSA). The pre-1990 CAA
air quality analysis area included five counties: Davidson, Wilson, Williamson, Rutherford
and Sumner. The MSA includes these five counties plus three other counties: Dickson,
Cheatham, and Robertson. The lowest level of disaggregation is the individual air quality
analysis zone.
General Issues and Summary
From a regional perspective, the MFC representative is more confident in the VMT output
data generated by the network model than in the speed data. Link by link speed data
generated by a network model may be of questionable validity. Speed output for each link
is based on a region-wide travel time equilibrium adjustment that allocates trips across the
entire network rather than "observed" speeds on that facility. Speeds on congested links
where the majority of VMT is generated may be overestimated by a traffic assignment
model if an averaging period longer than an hour is used. If speeds are overestimated, the
corresponding emissions will be underestimated.
Contacts:
Metropolitan Planning Commission
730 Second Avenue, South
Nashville, Tennessee 37201
(615) 259-6349
Metro Health Department
Air Pollution Control Division
311 23rd Avenue, North
Nashville, Tennessee 37203
(615) 340-5653
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Highway Vehicle Emission Inventories
Atlanta, GA
Responsible Agencies and Funding
The Georgia Environmental Protection Division (GEPD) is the Agency responsible for
running and maintaining the MOBILE4 emission model. The Atlanta Regional
Commission (ARC) is the agency responsible for running and maintaining the areawide
transportation network model. Currently ARC is converting from the main-frame UTPS
software format to TRANPLAN, a micro-computer based network model. The trans-
portation network model is financed through Federal, state and local funds as part of the
Metropolitan Planning Organization process. The air quality planning area encompasses a
total of 12 counties.
ARC is responsible for providing the traffic input data for the 8 urban counties which are
under their auspices. Traffic data for the remaining 4 non-urban counties in the air quality
planning area are provided by the Georgia Department of Transportation and compiled by
the GEPD.
Modeling Process: General
Urban area VMT and speed inputs are derived from the network assignment model.
Networks that represent "typical" PM peak hour traffic conditions are utilized for base year
and year 2010 traffic assignments.
The traffic assignment model provides volume, distance, speed, and VMT (Vehicle Miles of
Travel) for each link in the network. Vehicle miles of travel (VMT) by facility type are
multiplied by unit emission factors on a link by link basis to calculate total link emissions.
Link emissions are compiled and converted to a corresponding 5 square kilometer cell
which is part of a 25 by 25 kilometer air quality grid. Outside the 8 urban county area,
speeds and VMT are provided by GDOT and compiled manually by the GEPD.
Speed Inputs
Inside the 8 county urban area, speeds are based on the ARC traffic assignment model.
Speeds are disaggregated by peak and off-peak periods. Peak period speeds are based on
ARC's capacity restraint algorithm. Trip tables were calibrated against 1980 travel survey
data. In addition, network volumes are periodically validated with GDOT's traffic
counting program. Outside the 8 urban county area, speeds are provided by GDOT and
compiled manually by the GEPD.
Speeds are estimated to decline across most facility types in the future. On a regional or
county-wide basis, ARC is confident with the results of the estimated speeds. However,
there are wide variations in travel time (speeds) for individual links which are not
consistent with observed "real" conditions for those links.
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VMT Inputs
Network VMT and speeds are calculated and summed on a link by link basis for the
following facility types: Freeway, Ramp-Low Speed, Ramp-High Speed, Arterial-Low,
Arterial-Medium, Arterial-High, Collector, and Centroid Connector. The model also has
the capability to aggregate link data into the following geographic divisions: CBD, CBD
Fringe, Urban, Residential and Rural. Seasonal or temporal variations in travel are not
accounted for.
Traffic counts from the GDOT and local jurisdictions and a travel survey conducted by
ARC in 1980 are resources that are used to validate the travel assumptions in the ARC
transportation network model.
Geographic Coverage
The ARC transportation planning area is smaller than the air quality planning area. The air
quality planning area covers 12 counties and ARC covers 8 of the core urbanized areas in
the Atlanta region.
General Issues and Summary
The ARC representative said on a regional, or even a county basis, they are confident of the
VMT and average speed estimates produced by the traffic assignment model. However,
when links are examined on an individual basis, there can be a wide variation between
model output and observed conditions. According to the capacity constraint algorithm
used in the ARC traffic assignment model, the final assignment for the network may result
in a reasonably accurate allocation of trips across the entire region. The speed output for
each link is based more on the equilibrium adjustment necessary to obtain a reasonable trip
allocation rather than on an accurate estimate of "real" speed.
Contacts:
Atlanta Regional Commission
3715 Northside Parkway
Suite 300
Atlanta, Georgia 30327
(404) 364-2568
Georgia Environmental Protection Division
5291 Memorial Drive, Suite M
Decatur, Georgia 30032
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Denver, CO
Responsible Agencies and Funding
Travel volume data used in the preparation of the mobile source emissions inventory for
the Denver MSA are developed by the Denver Regional Council of Governments (DRCOG)
with funding provided through the Federal Highway and Urban Mass Transportation
Administrations. MOBILE4 emission factors and the preparation of the emissions
inventory are the responsibilities of the Air Pollution Control Division (APCD) of the State
Health Department. The APCD is funded through the State Health Department from
general funds, auto registration fees, and by the EPA.
Modeling Process: General
DRCOG uses the UTPS travel modeling package to develop and analyze travel speed and
VMT data. The Denver model system was originally developed in 1971 and has been
updated based on the 1980 census, a 1985 household travel survey, and a 1986 on-board
transit survey. The model is calibrated based on road counts and population and
employment data. Current forecasts are for 1987 although the model is presently being
updated to a 1989 base.
The developed network covers the Denver Urbanized Area. However, the air quality
planning area extends beyond these boundaries due to the EPA's requirement that
inventories be prepared on a county-wide basis. This has resulted in various problems of
coordination and coverage.
Speed Inputs
The UROAD program within UTPS is used to develop speed data on a link by link basis.
For air quality modeling purposes, speeds are averaged by functional roadway class, area
type, and by time of day for a typical weekday. Time of day is broken into three periods:
AM peak, PM peak, and off-peak. Five area classifications are identified: CBD, urban,
suburban, rural, and fringe. Seven roadway classifications are identified.
DRCOG performed a recent field survey of travel speeds within the region and found a
correlation with modeled speeds which averaged within 1-2 mph.
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VMT Inputs
Link-level VMT data calculated through UTPS are aggregated into grid cells using the
classifications identified above. Traffic distribution factors are applied by the APCD to
break VMT into hourly increments. Approximately half of actual local road VMT is
represented within the traffic network. As a result, DRCOG doubles local road VMT
generated by the model to approximate total local road conditions.
Both the APCD and DRCOG expressed confidence in the accuracy of regional and corridor
level VMT estimates, indicating that these estimates were probably within 5% of actual.
However both agencies expressed reservations concerning the accuracy of the VMT
estimates when disaggregated to a smaller level of geographic definition.
Geographic Coverage
Because of EPA requirements to prepare inventories on a county-wide basis, the trans-
portation planning area covered by the DRCOG traffic network no longer covers the entire
air quality planning area. As a result, the inventory is prepared in two phases. The first is
for the urbanized area covered by DRCOG's traffic network. The second phase is county-
wide and uses available data from outside of the area modeled by DRCOG's network. This
has resulted in problems of technical coordination in efforts to merge data generated
through various networks and modeling processes, since different travel demand model
systems currently are in use by planning agencies in Denver, Boulder, Castlerock, and
Longmont.
General Issues and Summary
The process used for the Denver MSA to disaggregate speed and VMT by area, roadway
classification, and time period generally appears to provide for a reasonably high level of
confidence. Based on field observations, DRCOG has found a good match between model
results and survey data.
The primary issue raised by both DRCOG and APCD relates to EPA requirements for
county-wide analyses. In the Denver MSA, this has resulted in problems of data
availability and reliability for those areas outside of the area covered by DRCOG's network
model. It is generally felt that a great deal of effort is necessary to develop information for
these areas which, overall, make a minimal contribution to total emissions. It was felt that
the EPA should either limit requirements in these situations or provide better guidance on
the procedures to be used for assessing emissions in rural areas.
A further issue raised by both agencies is the availability of funding. As expressed by
DRCOG, the EPA has imposed requirements that exceed the existing capabilities of the area
agencies, yet provides insufficient funding to meet these requirements.
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Contact:
State Health Department
Air Pollution Control Board
Suite 300 West
3773 North Cherry Creek
Denver, Colorado 80209
(303) 331-8264
Denver Regional Council of Governments
2480 West 26th Street
Denver, Colorado 80211
(303) 455-1000
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Tampa, FL
Responsible Agencies and Funding
The Hillsborough County Environmental Protection Commission (HCEPC) is responsible
for running and maintaining the MOBILE4 emission model for the Tampa area portion of
the SIP. The Tampa Urban Area Transportation Study (TUATS) is the agency responsible
for running the area-wide transportation network model. Through an inter-agency
agreement, TUATS provides the traffic data to HCEPC for input to the MOBILE4 runs. The
transportation network model is financed through Federal, state and local funds as part of
the Metropolitan Planning process. Air quality plans are coordinated with and funded by
the state Florida Department of Environmental Regulation.
Modeling Process: General
HCEPC has had difficulty in estimating VMT for emission inventory purposes. HCEPC
used an updated and validated TUATS adopted highway network model to estimate VMT
and speed for the current emission inventory. However, they also are investigating
alternative approaches that may be more cost effective. For example, the utility of a fuel
apportionment model is being explored as an alternative approach. According to the
HCEPC representative, it takes eighteen months to produce a highway network model that
meets air quality criteria.
Speed Inputs
For the current inventory, network speeds are based on a capacity restraint traffic
assignment algorithm of the network model that replicates congested conditions. For non-
network traffic, speeds are split according to VMT. It is estimated that 15% of total VMT is
accounted for by non-network travel, 60% of which in urban areas and 40% in rural areas.
Non-network speeds in urban areas have been assigned a default of 19.6 MPH. Rural areas
have been assigned a value of 41 MPH, which is based on ITE's Highway Capacity Manual
average free flow running speed of a 2 lane rural roadway. Speed inputs were reviewed by
a regional task force which included members from Hillsborough County Environmental
Protection Agency, Florida Department of Transportation-District 7, Florida Department of
Environmental Regulation and TUATS.
VMT Inputs
The newly updated network model will be used to interface with MOBILE4 to produce
emissions by facility type for each motor vehicle class based on worst-case peak operating
conditions (congested speeds).
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VMT and the corresponding emissions will be compiled by vehicle class for following
facility classifications:
1 - Freeway and Expressway emissions
2 - Divided arterial emissions
3 - Undivided arterial emissions
4 - Collector emissions
5 - Centroid connectors (VMT is zeroed out in network analysis)
6 - One-way road emission
7 - local roads
Geographic Coverage
The TUATS transportation planning area is not consistent with the HCEPC air quality
planning area. The TUATS network model covers only the urbanized area of Hillsborough
county.
General Issues and Summary
The HCEPC representative has confidence in their method of estimating urban area VMT
and speeds using this process, and in the VMT estimates supplied by the Florida
Department of Transportation for the roads directly under their jurisdiction. However,
there is a lower level of confidence in the local traffic data that FDOT supplies because
these data are not under their jurisdiction and there is no easy way to validate them.
The validation process for the transportation network modeling process is very labor
intensive and is estimated to take approximately one person-year to complete. The fuel-
apportionment model being explored by HCEPC could be a cost-effective technique for
non-attainment areas that.have less sophisticated transportation resources and capabilities.
The HCEPC representative discussed the general advantages and disadvantages of speed
and VMT inputs derived from a network based system. The transfer of technology from
transportation planning to air quality planning was seen as an advantage. Air quality
planners can learn a great deal about the behavior of transportation from reviewing
network based output. Network based systems provides a consistent reporting format.
The biggest advantage is the ability of a network system to provide spatial distribution of
traffic and therefore emissions.
Disadvantages of network based systems from the perspective of HCEPC include: high
cost, long lead time for results, and low confidence of mid-term projections. Other
disadvantages are that the network speed algorithms do not represent "real" traffic
conditions. A network model is static and does not accurately replicate constraints present
in the actual traffic stream such as accidents or traffic signals. Network based systems
provide only limited temporal distribution of traffic, usually only peak and off-peak
Cambridge Systematics, Inc. -••••-.-.. . A-26
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Highway Vehicle Emission Inventories
periods. Network models also can not now evaluate transportation control measures
(TCMs) precisely.
Contact:
Hillsborough County (Tampa, FL)
Environmental Protection Commission
1600 9th Avenue
Tampa, Florida 33605
(813) 272-5960
Cambridge Systematic*, Inc.
A-27
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Highway Vehicle Emission Inventories
Boston, MA
Responsible Agencies and Funding
Preparation of the mobile source emissions inventory for the Boston area has been a joint
effort in which the Massachusetts Department of Public Works (MDPW) develops VMT
data and the Massachusetts Department of Environmental Protection (MDEP) develops
MOBILE4 emissions factors and then calculates mobile source emissions based on the
traffic data provided from the MDPW.
Modeling Process: General
The traffic data used in Massachusetts' most recent air quality inventory are based on data
collected for the Highway Performance Monitoring System (HPMS), a database developed
and maintained nationally by the U.S. Federal Highway Administration. Although certain
urbanized areas within Massachusetts have traffic network models in operation such as
UTPS, the state as a whole is not modeled. Therefore, HPMS was used as a standardized
means of developing traffic data in the preparation of a statewide mobile source air quality
inventory.
Speed Inputs
Although MDPW collects speed data on various roadways, it has not updated speed factors
by functional class as part of the process of updating traffic data for air quality analyses.
According to MDEP, speeds were originally calculated for each roadway class in 1982 for
the NCRMP study and have not been updated since. For the NCRMP study, MDPW
conducted hourly speed runs at 81 locations in the Boston AQCR. Outside of the Boston
AQCR, data were collected from a variety of sources. Average daily speeds are averaged
by roadway class separately for each of the state's 13 planning regions. Adjustments are
not made to account for congested roadway conditions during peak versus off-peak
periods.
VMT Inputs
In accordance with HPMS procedures, VMT data are generated at the regional level by the
MDPW through samples of daily traffic at permanent and temporary counter locations.
These are first factored to represent average annual daily traffic (AADT) volumes, and then
refactored to daily VMT for a particular pollutant design day. This process is applied to
both urban and rural areas. Traffic counts are maintained only on highways, arterials and
collector roadways. No traffic information is developed for local roads. VMT 4ata are
disaggregated by 7 urban and 7 rural roadway classes in the mobile source emissions
Cambridge Systematic, Inc. A-28
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Highway !'"<.-,':'c/t tr-.i^fi'-r inventories
inventory. Gasoline sales are used as the basis for determining seasonal variation, with
separate factors being applied for winter and a typical summer days.
While urban and rural local road VMT is identified in the statewide emissions inventory,
neither MDPW nor MDEP was dear on the derivation of local road VMT.
Geographic Coverage
Although the Boston area is modeled in a UTPS-based traffic network model, traffic data
for the Boston urban area portion of the statewide emissions inventory are derived through
use of HPMS rather than the traffic network model. Data instead are generated in con-
junction with the MDPW's roadway inventory.
General Issues and Summary
Staff turnover has been a problem in Massachusetts. Although training in the running of
MOBILE4 has been available from EPA Region I, it is apparent that expertise in the use of
MOBILE4 and the preparation of a mobile source emissions inventory is not now fully
developed.
In general, the MDEP staff person expressed reservations concerning the accuracy of both
vmt and speed data used in developing the HPMS-based emissions inventory, empha-
sizing the problems inherent in assigning VMT to 7 different urban and rural roadway
classes. To some extent, these concerns were reiterated by the MDPW staff person who
stressed the lack of adequate funding to collect accurate traffic data.
Because of the decision not to use modeled traffic data for the Boston area, the accuracy of
the VMT data contained in the mobile source emissions inventory is entirely dependent
upon the limited traffic counts performed by the MDPW and the accuracy of projection
factors contained in the HPMS dataset.
A further issue is raised by the lack of disaggregation of VMT data between peak and off-
peak period travel. As a result, it is likely that the average daily speed assumptions used in
developing the emission factors do not represent realistic operating conditions and
emissions levels, especially within the boston urbanized area.
Cambridge Systematic*, Inc. A-29
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Highway Vehicle Emission Inventories
Contacts:
Massachusetts Department of Environmental Protection
Division of Air Quality Control
1 Winter Street, 8th Floor
Boston, Massachusetts 02108
(617) 292-5776
Massachusetts Department of Public Works
Bureau of Transportation Planning and Development
10 Park Plaza
Boston, Massachusetts
(617) 973-7330
Cambridge Systematic*, Inc. A-30
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Highway Vehicle Emission Inventories
-• Fresno, CA
Responsible Agencies and Funding
The mobile source emissions inventory for the Fresno area is jointly developed by the
California Air Resources Board (ARE) which refines available traffic data and prepares the
emissions inventory, and the California Department of Transportation (Caltrans) which
develops statewide travel data.
Modeling Process: General
An extensive transportation air quality study (SARMAP) for the San Joaquin Valley,
covering an eight county area, is currently being funded by Caltrans. Data were collected
in the summer of 1990 to develop an improved areawide emissions model accounting for
recent population and housing trends as well as recreation area characteristics. This study
is expected to produce more detailed trave"! and speed data than currently are available,
including updated network model systems for at least some of the urbanized areas within
the region.
The Fresno area has not had a regional transportation network moc? •••''• •.-- :e. Con-
sequently, past emissions inventoried have been traffic count based. Lv. \ roc;onal
travel data are derived primarily from statewide data developed by Caltrans through the
Highway Performance Monitoring System (HPMS). Field data to operate HPMS are
collected from California's 600 permanent statewide counter locations and from county
highway traffic counts. Caltrans disaggregates statewide data to the county level by
applying factors derived from auto registrations and gasoline sales.
Speed Inputs
Although Caltrans has generated specific speed data on a planning district level, ARB has
used MOBILE4 default speed values to calculate emission factors. Overall emission factors,
however, are calculated with all other variables specific to California due to the state's own
vehicle emissions requirements, resulting in fleet characteristics that are different than the
national norm. Separate factors are generated for urban and rural areas, with six highway
classes being used for each type of area.
VMT Inputs
Caltrans allocates statewide VMT to the county level by applying local auto registration
and gasoline sales factors to VMT data developed through HPMS. California has not
collected HPMS traffic count data that are statistically significant at the urban area level.
Cambridge Systematics, Inc. A-31
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Highway Veluciz Emission Inventories
The new Caltrans study of the San Joaquin Valley is expected to generate detailed VMT
data specific to local traffic operations.
Geographic Coverage
Because statewide travel data are disaggregated to the county level, overall coverage of
travel data has been geographically complete for the Fresno MSA. Local traffic data are
collected from county engineers to account for local road conditions not available in the
statewide traffic dataset.
General Issues and Summary
The San Joaquin Valley study currently being conducted by Caltrans is developing more
detailed speed and VMT data than currently are available. The traffic analysis for this
study will be based on a network model similar to UTPS. Until the results of this study are
complete, the primary source of data is the statewide HPMS dataset, disaggregated to the
county level.
Contact:
Emissions Inventory Branch
California Air Resources Board
P.O. Box 2815
Sacramento, California 95812
Cambridge Systematic*, Inc.
A-32
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Highway Vehicle Emission Inventories
Chicago, IL
Responsible Agencies and Funding
The Illinois Environmental Protection Agency (IEPA) is the agency responsible for
maintaining the MOBILE4 emission model and for compiling the State Implementation
Plan for the Chicago region. The mobile source emission inventory is being funded by the
State. The current mobile source inventory is traffic count based with the Illinois
Department of Transportation (IDOT) supplying the necessary traffic input data. These
data are derived from the Highway Record Data Bank (HRDB) which contains information
on every roadway (with some municipal exceptions) in the state. IDOT developed this
system and maintains the data.
The Chicago Area Transportation Study (CATS) is responsible for maintaining and
operating the transportation network model for the urbanized Chicago region. However,
CATS modeled network data is not now being used for the mobile source emissions
inventory purposes. In previous SIPs, CATS has been funded to provide transportation
expertise as well as output from the traffic assignment model to develop the mobile source
inventory. Currently, CATS is working closely with all the agencies and has reviewed all
the data supplied.
Modeling Process: General
The process of developing traffic input data for the emissions inventory can be described as
an aggregate "manual" method. Daily vehicle mile of travel (DVMT) data are provided to
IEPA from IDOT for each facility type, by county. This represents the level of geographic
disaggregation in current SIP-related work.
Speed Inputs
A default speed value of 19.6 MPH is being used for all facility types for the baseline
inventory as well as for future year inventories. According to the IEPA representative, the
justification for using the default speed of 19.6 MPH for all facility types is as follows:
1) 19.6 MPH closely represents congested urban traffic conditions on practically all
facilities, 2) the majority of emissions are generated in urban areas, 3) default speeds are
conservative estimates, 4) it is better to overestimate rural speeds because they represent a
small fraction of total emissions, and 5) the lack of available data on actual speeds in
urbanized areas.
Cambridge Syst ana tics, Inc. A-33
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Highway Vehicle Evussior I;,ttntories
VMT Inputs
The annual traffic counting program conducted by IDOT is the source of information used
by IEPA for the mobile emissions model. Daily vehicle miles of travel (DVMT) are
reported by county for the following 11 facility classifications: Rural Federal Aid Interstate,
Urban Federal Interstate, Urban other Expressway and Freeway, Rural Minor Arterial,
Urban Minor Arterial, Urban Other Principal Arterial, Rural Major Collector, Rural Minor
Collector, Local Roads, Urban Collector, and Local Streets. According to the IEPA
representative, the IDOT source of traffic data was utilized because it represents the official
state inventory of traffic data and provides a complete coverage of all facility types from
interstate to local streets. The CATS transportation network model lacks a significant
portion of the local street system and, thus, does not account for the VMT so generated.
IDOT supplies seasonal variation factors to adjust the DVMT for the MOBILE4 runs. IDOT
does not make forecasts of future VMT. Instead, growth factors are developed by IEPA
based on past trends and extrapolated into the future. The IDOT representative is very
confident of the base corridor VMT data as developed and maintained in their traffic
database.
Geographic Coverage
The SIP air quality planning area covers the following 6 urbanized counties in Northeastern
Illinois: Cook, Dupage, Lake, Kane, McHenry, and Will, and 2 rural counties: Kendall and
Grundy. This is larger than the geographic area covered by the CATS network model
system.
General Issues and Summary
IDOT VMT data are reported on a county-wide basis by facility type. This aggregate
method of developing the VMT and speed inputs for the emission inventory may not
adequately represent the effect that congested traffic has on current and future mobile
source emissions. Further, it may not be realistic to estimate future VMT based solely on
past trends, especially when capacity is being constrained by lack of funding.
According to representatives at CATS, they see difficulties in relying on a transportation
network forecasting methodology to provide VMT inputs to MOBILE4. Different
assignment models yield different results. The time frames that transportation network
models use also complicate the matter. An average day model must be adjusted to provide
peak or off-peak data. Similarly, a peak hour model must be extended to account for the
entire day. There is no model that can account for daily, weekly, monthly and seasonal
variations. It is the recommendation of CATS, therefore, that factual empirical data based
on traffic counts should be used for purposes of developing a mobile source emissions
inventory.
Cambridge Systematic, Inc. A-34
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Highway Vehicle Emission Inventories
CATS also believes that it is erroneous to use what the network models refer to as speed in
developing an emissions inventory. A network assignment's output is not speed in the
sense that it is describing the velocity of a vehicle traversing a given link. Instead, the
speed output is a measure of impedance used to allocate travel across the network. This
impedance is adjusted so that reasonable trip allocations are made by the model, but it does
not mean that the actual speed of vehicles in the traffic stream has changed. The purpose of
the modeling process is not to estimate speed, but vehicle trips.
CATS believes the uniform default MOBILE4 speed of 19.6 MPH used in the current
emission inventory may be too low. However, the default value of 19.6 MPH may
overestimate vehicle speeds on congested urban freeways and arterials during peak
periods. Recent national analyses have suggested that speeds in urban areas will decline in
the future due to increased volumes on roadways with fixed capacities.
Contacts:
Illinois Environmental Protection Agency
Division of Air Pollution Control
Air Quality Planning Division
P.O. 19276
Springfield, Illinois 62794-9276
(217) 785-5151
Chicago Area Transportation Study
300 West Adams Street
Chicago, Illinois 60606
(312) 793-3467
Cambridge Systematic*, Inc. A-35
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Highway Vehicle Emission Inventories
Pittsburgh, PA
Responsible Agencies and Funding
The preparation of a new mobile source air quality inventory for the Pittsburgh area has
not yet begun, pending the completion of inventory work for Philadelphia. The issue of
which agency will be responsible for running MOBILE4 has not yet been decided. One
plan discussed is for the Southwest Pennsylvania Regional Planning Commission (SPRPC)
to provide the transportation data for compiling the inventory and for the Pennsylvania
Department of Environmental Resources (PennDER) to run MOBILE4 and prepare the final
inventory. According to PennDER, it has been difficult in the past to coordinate with the
transportation agencies in developing emissions factors and preparing the actual
inventories. Therefore, PennDER now prefers to run MOBILE4 and prepare the inventories
in-house. Another option is for SPRPC to run MOBILE4. In either case, PennDER will be
providing funding to SPRPC to develop the necessary transportation data for the emissions
inventory.
Modeling Process: General
A 1987 emissions inventory utilized traffic data interpolated (straight-lined) from data
developed for the 1980 inventory and State Implementation Plan. Because a new inventory
process has not yet gotten underway, decisions have not yet been made with respect to
specific methodologies. While SPRPC has not discussed the specifics of the modeling
procedure with PennDER, it is assumed that a basic transportation network modeling
procedure will be utilized.
Speed Inputs
PennDER is assuming that new vehicle speed data will be collected for the new inventory,
and that it will not be based on the 1980 data as was the 1987 inventory. The collection of
new speed data would be the responsibility of SPRPC, but decisions have not yet been
made about exactly what new data will be collected.
Although it is assumed that specific data will be available for each of the required roadway
classifications, PennDER is unsure how data will be disaggregated temporally or
geographically for each class.
Cambridge Systematics, Inc. . A-36
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Highway Vehicle Emission Inventories
VMT Inputs
New data will be developed for the preparation of the next inventory; it will not be based
on an interpolation of the 1980 data as was the 1987 inventory. The development of new
VMT data will be the responsibility of SPRPC and likely will be based on the results of a
network traffic assignment model. VMT data will be available by roadway classifications,
with at least some temporal and geographic disaggregation for each class.
Geographic Coverage
Portions of six counties are covered within SPRPC's planning area. Although portions of
two additional counties are within the Pittsburgh SMSA and are outside of the SPRPC
planning area, only one of these counties is not included in SPRPC's traffic network.
PennDOT data will be used to develop the necessary data for this area. Local road data
will be derived from both PennDOT and SPRPC data.
General Issues and Summary
PennDER is not totally confident about the accuracy of the speed and VMT data that will be
used in developing a new mobile source inventory for the Pittsburgh area, but says that no
other data are available. Overall, PennDER does not see improving the quality of data in
the Pittsburgh area to be a high priority, in large part due to funding limitations. Generally,
PennDER feels that minor changes in the highway network should not necessitate a revised
inventory in a low growth area, and that an updated inventory on a three year cycle is too
frequent. Under these requirements, funding on an on-going basis is a significant problem.
A problem identified by SPRPC are the incompatibilities between the transportation
modeling process and the needs of a mobile source emissions inventory. The existing
transportation modeling process has evolved over the 25 years with significant com-
mitment of resources from FHWA and UMTA. Its primary orientation is to support the
construction of new highway and transit facilities. If EPA requires a modified process to
address its issues, then EPA should commit the resources necessary to modify the process
to meet these needs.
Another problem identified by SPRPC is the interface between the transportation modeling
process and MOBILE4; specifically the desired accuracy of the estimates for VMT and
speed. According to SPRPC, the desire is for only "perfect" estimates of VMT and speed.
While it is acknowledged that VMT and speed are critical variables for estimating mobile
sources emissions, rather gross estimates are allowed for many of the remaining MOBILE4
inputs. Increasing the accuracy of VMT and speed estimates could be an expensive
undertaking, and errors inherent in other MOBILE4 variables may negate much of this
effort.
Cambridge Systcmatics, Inc. A-37
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Highway Vehicle Emission Inventories
A specific problem identified by PennDER is staff turnover, particularly at the trans-
portation planning agency. As a result, procedures cannot become institutionalized and
must be reestablished for each new inventory.
Contacts:
Pennsylvania Department of Environmental Resources
Bureau of Air Quality Control
Division of Air Resource Management
P.O. Box 2357
Executive House
2nd and Chestnut Streets
Harrisburg, Pennsylvania 17120
(717) 787-4310
Southwestern Pennsylvania Regional Planning Commission
200 First Avenue
Pittsburgh, Pennsylvania 15222-1573
(412) 391-5590
Cambridge Systematic!, Inc. A-38
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TECHNICAL RE-PORT DATA
(Please read Instructions on ifie reverie before completing)
1. REPORT NO.
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
A Study of Highway Vehicle Emission Inventory
Procedures for Selected Urban Areas
5. REPORT DATE
January, 1993
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Office of Air Quality Planning & Standards
Environmental Protection Agency
Research Triangle Pk., NC 27711
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68D90073
12. SPONSORING AGENCY NAME AND ADDRESS
Director, Office of Air Quality Planning & Standards
Office of Air & Radiation
US EPA
Research Triangle Pk. NC. 77711 ,
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
68A
15. SUPPLEMENTARY NOTES
16. ABSTRACT
This report identifies potential areas where additional information could be developed
that would assist states and urban areas in the preparation of mobile source emissions
inventories. It includes a review of current mobile source emissions inventory
practices in fifteen urban areas. Existing guidance-related materials were assessed
in light of the results of this review, and recommendations for improved emissions
inventory information or procedures were developed.
This report describes the findings from the review of existing mobile source inventory
practices. The problems and solutions uncovered from the state and local areas inves-
tigations provide a base of comparison for assessing both current and proposed EPA
mobile source inventory preparation procedures.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Mobile Sources
Emission Inventories
Mobile Source Emissions
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EPA Form 2220-1 (R«». 4-77) PREVIOUS EDITION i* OBSOLETE
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EPA Form 2220-1 (Rev. 4-771 (R*v«rs«)
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