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NATIONAL
NCHRP REPORT 535
COOPERATIVE
HIGHWAY
RESEARCH
PROGRAM
Predicting Air Quality Effects
of Traffic-Flow Improvements:
Final Report and User's Guide
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TRANSPORTATION RESEARCH BOARD EXECUTIVE COMMITTEE 2004 (Membership as of July 2004)
OFFICERS
Chair: Michael S. Townes, President and CEO, Hampton Roads Transit, Hampton, VA
Vice Chair: Joseph H. Boardman, Commissioner, New York State DOT
Executive Director: Robert E. Skinner, Jr., Transportation Research Board
MEMBERS
MICHAEL W. BEHRENS, Executive Director, Texas DOT
SARAH C. CAMPBELL, President, TransManagement, Inc., Washington, DC
E. DEAN CARLSON, Director, Carlson Associates, Topeka, KS
JOHN L. CRAIG, Director, Nebraska Department of Roads
DOUGLAS G. DUNCAN, President and CEO, FedEx Freight, Memphis, TN
GENEVIEVE GIULIANO, Director, Metrans Transportation Center and Professor, School of Policy, Planning, and Development,
USC, Los Angeles
BERNARD S. GROSECLOSE, JR., President and CEO, South Carolina State Ports Authority
SUSAN HANSON, Landry University Professor of Geography, Graduate School of Geography, Clark University
JAMES R. HERTWIG, President, CSX Intermodal, Jacksonville, FL
GLORIA J. JEFF, Director, Michigan DOT
ADIB K. KANAFANI, Cahill Professor of Civil Engineering, University of California, Berkeley
RONALD F. KIRBY, Director of Transportation Planning, Metropolitan Washington Council of Governments
HERBERT S. LEVINSON, Principal, Herbert S. Levinson Transportation Consultant, New Haven, CT
SUE MCNEIL, Director, Urban Transportation Center and Professor, College of Urban Planning and Public Affairs and Department
of Civil and Materials Engineering, University of Illinois, Chicago
MICHAEL D. MEYER, Professor, School of Civil and Environmental Engineering, Georgia Institute of Technology
CAROL A. MURRAY, Commissioner, New Hampshire DOT
JOHN E. NJORD, Executive Director, Utah DOT
DAVID PLAVIN, President, Airports Council International, Washington, DC
JOHN H. REBENSDORF, Vice President, Network Planning and Operations, Union Pacific Railroad Co., Omaha, NE
PHILIP A. SHUCET, Commissioner, Virginia DOT
C. MICHAEL WALTON, Ernest H. Cockrell Centennial Chair in Engineering, University of Texas, Austin
LINDA S. WATSON, Executive Director, LYNX--Central Florida Regional Transportation Authority, Orlando, FL
MARION C. BLAKEY, Federal Aviation Administrator, U.S.DOT (ex officio)
SAMUEL G. BONASSO, Acting Administrator, Research and Special Programs Administration, U.S.DOT (ex officio)
REBECCA M. BREWSTER, President and COO, American Transportation Research Institute, Smyrna, GA (ex officio)
GEORGE BUGLIARELLO, Chancellor, Polytechnic University and Foreign Secretary, National Academy of Engineering (ex officio)
THOMAS H. COLLINS (Adm., U.S. Coast Guard), Commandant, U.S. Coast Guard (ex officio)
JENNIFER L. DORN, Federal Transit Administrator, U.S.DOT (ex officio)
EDWARD R. HAMBERGER, President and CEO, Association of American Railroads (ex officio)
JOHN C. HORSLEY, Executive Director, American Association of State Highway and Transportation Officials (ex officio)
RICK KOWALEWSKI, Deputy Director, Bureau of Transportation Statistics, U.S.DOT (ex officio)
WILLIAM W. MILLAR, President, American Public Transportation Association (ex officio)
BETTY MONRO, Acting Administrator, Federal Railroad Administration, U.S.DOT (ex officio)
MARY E. PETERS, Federal Highway Administrator, U.S.DOT (ex officio)
SUZANNE RUDZINSKI, Director, Transportation and Regional Programs, U.S. Environmental Protection Agency (ex officio)
JEFFREY W. RUNGE, National Highway Traffic Safety Administrator, U.S.DOT (ex officio)
ANNETTE M. SANDBERG, Federal Motor Carrier Safety Administrator, U.S.DOT (ex officio)
WILLIAM G. SCHUBERT, Maritime Administrator, U.S.DOT (ex officio)
JEFFREY N. SHANE, Under Secretary for Policy, U.S.DOT (ex officio)
CARL A. STROCK (Maj. Gen., U.S. Army), Chief of Engineers and Commanding General, U.S. Army Corps of Engineers (ex officio)
ROBERT A. VENEZIA, Program Manager of Public Health Applications, National Aeronautics and Space Administration (ex officio)
NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM
Transportation Research Board Executive Committee Subcommittee for NCHRP
MICHAEL S. TOWNES, Hampton Roads Transit, Hampton, VA JOHN C. HORSLEY, American Association of State Highway
(Chair) and Transportation Officials
JOSEPH H. BOARDMAN, New York State DOT MARY E. PETERS, Federal Highway Administration
GENEVIEVE GIULIANO, University of Southern California, ROBERT E. SKINNER, JR., Transportation Research Board
Los Angeles C. MICHAEL WALTON, University of Texas, Austin
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NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM
NCHRP REPORT 535
Predicting Air Quality Effects
of Traffic-Flow Improvements:
Final Report and User's Guide
RICHARD DOWLING
Dowling Associates
Oakland, CA
ROBERT IRESON
Greenbrae, CA
ALEXANDER SKABARDONIS
Department of Civil and Environmental Engineering
University of California, Berkeley
Berkeley, CA
DAVID GILLEN
Sauder School of Business
University of British Columbia
Vancouver, British Columbia, Canada
PETER STOPHER
Institute of Transport Studies
University of Sydney
Sydney, New South Wales, Australia
S UBJECT A REAS
Planning and Administration · Energy and Environment · Highway and Facility Design
Research Sponsored by the American Association of State Highway and Transportation Officials
in Cooperation with the Federal Highway Administration
TRANSPORTATION RESEARCH BOARD
WASHINGTON, D.C.
2005
www.TRB.org
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NATIONAL COOPERATIVE HIGHWAY RESEARCH NCHRP REPORT 535
PROGRAM
Systematic, well-designed research provides the most effective Project 25-21 FY'99
approach to the solution of many problems facing highway
administrators and engineers. Often, highway problems are of local ISSN 0077-5614
interest and can best be studied by highway departments ISBN 0309088194
individually or in cooperation with their state universities and
Library of Congress Control Number 2004117941
others. However, the accelerating growth of highway transportation
develops increasingly complex problems of wide interest to © 2005 Transportation Research Board
highway authorities. These problems are best studied through a
coordinated program of cooperative research. Price $28.00
In recognition of these needs, the highway administrators of the
American Association of State Highway and Transportation
Officials initiated in 1962 an objective national highway research
program employing modern scientific techniques. This program is
supported on a continuing basis by funds from participating
member states of the Association and it receives the full cooperation
and support of the Federal Highway Administration, United States NOTICE
Department of Transportation.
The project that is the subject of this report was a part of the National Cooperative
The Transportation Research Board of the National Academies
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was requested by the Association to administer the research
approval of the Governing Board of the National Research Council. Such approval
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NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM
Cooperative Highway Research Program can make significant
contributions to the solution of highway transportation problems of are available from:
mutual concern to many responsible groups. The program,
however, is intended to complement rather than to substitute for or Transportation Research Board
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The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished schol-
ars engaged in scientific and engineering research, dedicated to the furtherance of science and technology
and to their use for the general welfare. On the authority of the charter granted to it by the Congress in
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emy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration
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COOPERATIVE RESEARCH PROGRAMS STAFF FOR NCHRP REPORT 535
ROBERT J. REILLY, Director, Cooperative Research Programs
CRAWFORD F. JENCKS, NCHRP Manager
MARTINE MICOZZI, Senior Program Officer
EILEEN P. DELANEY, Director of Publications
BETH HATCH, Assistant Editor
KRISTIN SAWYER, Contract Editor
NCHRP PROJECT 25-21 PANEL
Field of Transportation Planning--Area of Impact Analysis
EDWARD A. MIERZEJEWSKI, University of South Florida, Tampa, FL (Chair)
MARK LOMBARD, AASHTO Monitor
LAWRENCE W. BLAIN, Puget Sound Regional Council, Seattle, WA
RONALD COLLETTE, Quebec Ministry of Transportation, Montreal, Quebec, Canada
KAREN HEIDEL, Tucson, AZ
ROBERT B. NOLAND, Imperial College of Science, Technology & Medicine, London,
United Kingdom
MARION R. POOLE, Raleigh, NC
E. JAN SKOUBY, Missouri DOT
DOUGLAS R. THOMPSON, California Air Resources Board, Sacramento, CA
CECILIA HO, FHWA Liaison Representative
KIMBERLY FISHER, TRB Liaison Representative
AUTHOR ACKNOWLEDGMENTS
The research reported herein was performed under NCHRP Proj- Ms. Gail Payne prepared Section 3.3, "Modeling Non-Motorized
ect 25-21 by Dowling Associates, Inc., in Oakland, California. Travel," and Section 3.4, "Modeling Truck Traffic." Dr. David
Dr. Richard G. Dowling, Principal, was the principal investigator. Gillen prepared the majority of Chapter 6, "Land Use Models."
The other authors of this report are Dr. Robert Ireson, a self-employed Dr. Alexander Skabardonis prepared major portions of Chapter 8,
consultant; Dr. Alexander Skabardonis, Adjunct Professor of Civil "Traffic Operations Models." Dr. Robert Ireson prepared the major-
and Environmental Engineering at the University of California, ity of Chapter 9, "Mobile Emission Models."
Berkeley; Dr. David Gillen, YVR Professor of Transportation Policy The following research team members provided advice and
at Sauder School of Business, University of British Columbia; and review at key stages of the research: Dr. Alan Horowitz, University
Dr. Peter Stopher, Professor of Transport Planning at the Institute of of Wisconsin, Milwaukee; Dr. John Bowman, Massachusetts Insti-
Transport Studies at the University of Sydney, Australia. tute of Technology; Dr. Elizabeth Deakin, University of California,
In the final report, Dr. Stopher prepared major portions of Chap- Berkeley; and Mr. Robert Dulla, Sierra Research.
ter 2, "The Impacts of Traffic Improvements on Emissions."
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This report contains a user's guide and case studies, providing a recommended
FOREWORD methodology to predict the long- and short-term mobile source emission impacts of
By Martine Micozzi traffic-flow improvement projects. Guidance is provided to evaluate the magnitude,
Staff Officer scale, and duration of such impacts for a variety of representative urbanized areas.
Transportation Research
Board
The report is based on an in-depth exploration of methodologies used to estimate
the impacts of traffic-flow improvement projects on mobile source emissions. It eval-
uates varying strategic approaches used to develop such methodologies, reviews
advanced methodologies used by leading metropolitan planning agencies, and offers
suggestions to improve conventional travel models.
With major metropolitan areas striving to meet increasing travel demand while
improving mobility and maintaining conformity with air quality regulations, this report
offers guidance of special interest to metropolitan planning agencies, transportation
engineers, urban designers, and public officials and policymakers.
The report offers analysts considering a proposed traffic-flow improvement a com-
prehensive methodology composed of five modules to assess potential impacts on air
quality.
The analysis of the effects of traffic-flow improvements on mobile source emis-
sions focuses on four areas: operational improvements, travel time savings impacting
traveler behavior, travel time savings increasing total demand for travel, and travel time
savings stimulating growth and new development in specific areas within the metro-
politan region.
This report, prepared by Dowling Associates, features a sound methodology that
was created, applied, and tested in a dozen case studies. This methodology improves
the prediction model for assessing impacts of corridor-level transportation projects and
provides an effective tool for estimating the range of impacts possible when traffic-flow
improvements are considered in metropolitan areas.
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CONTENTS FINAL REPORT
1 SUMMARY
3 CHAPTER 1 Introduction
1.1 Organization of this Report, 3
1.2 Summary of Problem Being Researched, 3
1.3 Objectives of the Research, 4
1.4 Overview of the Work Plan, 4
5 CHAPTER 2 The Impacts of Traffic Improvements on Emissions
2.1 Problem Statement, 5
2.2 Relationship Between Traffic-Flow Improvements and Emissions, 11
2.3 Empirical Studies of the Impact of Highway Improvements on
Travel Demand, 11
2.4 Behavioral Studies of the Impact of Travel Time on Travel Demand, 16
2.5 Studies of the Urban Form Impacts of Transportation Improvements, 18
2.6 Examples of the Impacts of Traffic-Flow Improvements on Emissions, 19
2.7 Conclusion, 21
24 CHAPTER 3 State of the Practice
3.1 Review of Conventional Practice, 24
3.2 Critique of Conventional Practice, 29
3.3 Modeling Nonmotorized Travel, 31
3.4 Modeling Truck Traffic, 32
3.5 NCHRP Project 8-33 Recommendations for Improved Procedures, 34
3.6 Environmental Protection Agency Analysis, 35
37 CHAPTER 4 Available Methodologies
4.1 Typology, 37
4.2 Overview of Available Methods, 37
41 CHAPTER 5 Sketch-Planning Approaches
5.1 HERS, 41
5.2 Traveler Response to Transportation System Changes Interim Handbook,
TCRP Project B-12, 41
5.3 SPASM, SMITE, and Other Sketch-Planning Tools, 42
5.4 Sketch-Planning Postprocessors, 42
5.5 Assessment, 43
44 CHAPTER 6 Land-Use Models
6.1 Integrated Land-Use and Transportation Models, 45
6.2 The Highway Land-Use Forecasting Model, 47
6.3 The UrbanSim Model, 48
6.4 The Ideal Model, 51
6.5 Model Review, 52
6.6 Assessment, 54
6.7 Summary and Recommendations: Land-Use Models, 60
6.8 Demographics: A Brief Discussion, 63
66 CHAPTER 7 Travel Demand Models
7.1 TRANSIMS, 66
7.2 Portland Tour-Based Model, 66
7.3 The STEP Model, 70
7.4 Assessment, 75
76 CHAPTER 8 Traffic Operation Models
8.1 The BPR Equation, 76
8.2 Highway Capacity Manual, 76
8.3 Planning Model to HCM Link, 77
8.4 Microsimulation Models, 79
8.5 Linkages Between the Planning Model and the Microsimulation, 84
8.6 Assessment of Methods for Estimating Modal Activity, 85
8.7 Conclusions, 89
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90 CHAPTER 9 Mobile Emission Models
9.1 Background--Vehicle Emission Processes, 90
9.2 MOBILE6, 92
9.3 The MOVES Model, 92
9.4 The MEASURE Model, 92
9.5 The NCHRP 25-11 Modal Emission Model, 93
9.6 The NCHRP 25-6 Intersection CO Emission Model, 95
9.7 The NCHRP 25-14 Heavy-Duty Vehicle Emission Model, 96
9.8 Assessment, 96
97 CHAPTER 10 Strategic Approach to Methodology
10.1 Project Objective and Requirements for Methodology, 97
10.2 Methodology Evaluation Criteria, 97
10.3 Evaluation of Current Practice Against NCHRP 25-21 Objectives, 98
10.4 Evaluation of Strategic Approaches, 98
10.5 Macroscopic Sketch-Planning Approach, 98
10.6 Mesoscopic Conventional Model Approach, 100
10.7 Microscopic Approach, 102
10.8 A Blended Microscopic/Mesoscopic Approach, 102
103 CHAPTER 11 Recommended Methodology
11.1 Research Objectives for Methodology, 103
11.2 Theoretical Foundation, 103
11.3 Outline of Methodology, 104
11.4 HCM Assignment Module, 106
11.5 Traveler Behavior Response Module, 106
11.6 Growth Redistribution Module, 107
11.7 Vehicle Modal Activity Module, 107
11.8 Vehicle Emission Module, 107
109 CHAPTER 12 Derivation of HCM Assignment Module
12.1 HCM/Akcelik Speed-Flow Equation, 109
12.2 Free-Flow Speeds, 111
12.3 Capacities, 112
12.4 Signal Data Required by HCM/Akcelik, 113
12.5 Constraining Demand Downstream of Bottlenecks, 114
116 CHAPTER 13 Derivation of Travel Behavior Response Module
13.1 Overview of Portland Tour-Based Model, 116
13.2 Microsimulation Model Implementation, 116
13.3 Derivation of Elasticities, 121
13.4 Final Elasticities, 125
126 CHAPTER 14 Derivation of Growth Redistribution Module
14.1 Module Description, 126
14.2 Module Application, 127
14.3 Equilibration, 128
130 CHAPTER 15 Derivation of Modal Activity Module
15.1 Methodology Development, 130
15.2 Modal Operations Tables, 132
141 CHAPTER 16 Derivation of Vehicle Emission Module
16.1 Overview of Emission Estimation Methodology, 141
16.2 Estimation of Start Exhaust Emissions, 142
16.3 Estimation of Running Exhaust Emissions, 143
16.4 Estimation of Off-Cycle Emissions, 143
16.5 Estimation of Running Evaporative Emissions, 143
16.6 Estimation of Hot Soak, Diurnal, and Resting Evaporative Emissions, 143
16.7 Estimation of Fuel-Dependent Emissions, 144
16.8 Estimation of PM10 Emissions, 144
16.9 Estimation of Heavy-Duty Vehicle Emissions, 144
16.10 Final VHT-Based Emission Rates, 144
16.11 Treatment of Emission Rate Updates, 144
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149 CHAPTER 17 Validation of Methodology
17.1 Validation Objectives, 149
17.2 Evaluation Against Expectations for Facility-Specific Impacts, 149
17.3 Evaluation Against Prior Studies of Systemwide Elasticities, 151
17.4 Conclusions, 154
155 CHAPTER 18 Conclusions and Recommendations
18.1 Overview of the NCHRP 25-21 Methodology, 155
18.2 Exclusions from the NCHRP 25-21 Methodology, 155
18.3 Accomplishment of NCHRP 25-21 Methodology Objectives, 156
18.4 Validation of the NCHRP 25-21 Methodology, 156
18.5 Case Study Results, 157
18.6 Implementation Plan, 157
159 REFERENCES
164 GLOSSARY OF ACRONYMS
USER'S GUIDE
1 CHAPTER 1 Introduction
1.1 Objectives of the NCHRP 25-21 Methodology, 1
1.2 Organization of User's Guide, 1
2 CHAPTER 2 The Methodology
2.1 Theoretical Foundation, 2
2.2 Outline of the Methodology, 3
2.3 HCM Assignment Module, 4
2.4 Traveler Behavior Response Module, 5
2.5 Growth Redistribution Module, 5
2.6 Vehicle Modal Activity Module, 6
2.7 Vehicle Emission Module, 6
7 CHAPTER 3 The HCM Assignment Module
3.1 Free-Flow Speeds, 7
3.2 Capacities, 7
3.3 HCM/Akcelik Speed-Flow Equation, 8
3.4 Signal Data Required by HCM/Akcelik, 10
12 CHAPTER 4 The Travel Behavior Response Module
4.1 Overview of the Portland Tour-Based Model, 12
4.2 Derivation of Elasticities, 12
4.3 Elasticities, 14
4.4 Alternate Methods for Deriving Elasticities, 14
16 CHAPTER 5 The Growth Redistribution Module
5.1 Module Description, 16
5.2 Module Application, 17
19 CHAPTER 6 The Modal Activity Module
6.1 Methodology Development, 19
6.2 Methodology Application, 19
24 CHAPTER 7 The Vehicle Emission Module
7.1 Methodology Development, 24
7.2 Methodology Application, 24
7.3 Nontechnology Updates to Vehicle Emission Module, 24
7.4 Technology Updates to Vehicle Emission Module, 25
7.5 Additions to Vehicle Emission Module, 25
28 CHAPTER 8 Base Case
8.1 Input, 28
8.2 Application of the HCM Assignment Module to the PSRC Data Set, 28
33 CHAPTER 9 Case Study 1: Add Freeway Lane--Rural
9.1 Application, 33
9.2 Case Study Results, 33
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36 CHAPTER 10 Case Study 2: Close Freeway Lane--Urban
10.1 Application, 36
10.2 Case Study Results, 36
39 CHAPTER 11 Case Study 3a: Remove Freeway HOV Lane
11.1 Application, 39
11.2 Case Study Results, 39
42 CHAPTER 12 Case Study 3b: Remove Freeway HOV Lane
12.1 Application, 42
12.2 Case Study Results, 42
45 CHAPTER 13 Case Study 4: Narrow Street
13.1 Application, 45
13.2 Case Study Results, 45
48 CHAPTER 14 Case Study 5: Access Management
14.1 Application, 48
14.2 Case Study Results, 48
51 CHAPTER 15 Case Study 6: Intersection Channelization
15.1 Application, 51
15.2 Case Study Results, 51
54 CHAPTER 16 Case Study 7: Signal Coordination
16.1 Application, 54
16.2 Case Study Results, 54
57 CHAPTER 17 Case Study 8: Transit Improvement
17.1 Application, 57
17.2 Case Study Results, 57
59 CHAPTER 18 Case Study 9: Remove Park-and-Ride Lot
18.1 Application, 59
18.2 Case Study Results, 59
61 CHAPTER 19 Case Study 10: Long-Range Regional Transportation Plan
19.1 Application, 61
19.2 Results of PSRC Model Runs, 61
19.3 NCHRP 25-21 Methodology Results, 61
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156
· The potential impact on the overall growth of a metro- model upon which the NCHRP 25-21 methodology is based
politan region of significantly different levels of invest- (CMEM).
FINAL REPORT
ment in traffic-flow improvements between regions and
· The potential indirect impact of traffic-flow improve-
ments on actual or perceived accessibility (via nonmo- 18.3 ACCOMPLISHMENT OF NCHRP 25-21
torized modes) for transit, pedestrian, and bicycle modes. METHODOLOGY OBJECTIVES
The accomplishment of the NCHRP 25-21 methodology
The potential impacts of major deviations in infrastructure objectives by the proposed methodology is outlined in
investment levels on interregional competitiveness have been Table 56.
excluded because of the added data requirements of model-
ing variations in growth between the metropolitan regions of
the United States. 18.4 VALIDATION OF THE NCHRP 25-21
The potential indirect impacts of traffic-flow improvements METHODOLOGY
on nonmotorized modes have been excluded because of a lack
of data on these effects and project resource limitations. The NCHRP 25-21 methodology was applied to a series
The emission estimates are limited to running exhaust of case studies, and the results were compared with more
emissions because of the limitations of the modal emission general results reported in the literature.
TABLE 56 Accomplishment of NCHRP 25-21 methodology objectives
NCHRP 25-21 Methodology Accomplishment by Proposed Methodology
Objectives
Predict short- and long-term The methodology predicts traveler behavior response for the short
effects term and growth redistribution impacts for the long term.
Be accurate Available data sets do not generally support determination of the
accuracy of the methodology. The methodology employs generally
advanced techniques, which are expected to be more accurate
than less sophisticated and more aggregate approaches.
Cover a wide geographic scale The methodology covers highway segment, corridor, and regional
of impacts impacts.
Predict the duration of impacts The methodology does not directly predict duration, but duration
can be inferred from the short-term and long-term "snapshots"
provided by the methodology.
Be suitable for small and large The methodology requires a regional transportation network (with
MPOs transit) and a regional OD table. As such, the methodology can
best be employed by medium to large MPOs.
Cover a range of projects The methodology is best suited to projects that change capacity or
speed.
Include land-use effects Land-use effects are included in the Long-Term Response Module,
but no explicit land-use model is included.
Include pedestrian/bicycle/transit The impacts of traffic-flow improvements on nonmotorized use are
access/safety effects not currently included in the methodology because of a lack of data
on the subject. Because of the same lack of data, the methodology
does not incorporate perceived or actual safety effects.
Use commonly available data All of the required data (regional highway network and regional OD
table) are routinely gathered by large MPOs in the region. The
required data exceed the capabilities of small MPOs.
Be implementable in commonly The methodology can be implemented in commonly used software
used software for travel demand modeling.
Be compatible with modal The methodology is specifically designed to use a light-duty vehicle
emission model modal emission model.
Include heavy-duty vehicle Because of a lack of data on modal emissions for heavy-duty
emissions vehicles, the methodology does not include a specific heavy-duty
vehicle demand response model, modal activity, or emission model.
Include PM emissions The methodology does not address PM emissions because of a
lack of emission rate data compatible with the CMEM methodology.
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157
The facility-specific results showed travel time and volume This section presents the recommended implementation
changes for the specific facility that were quite consistent with plan for disseminating the results of this research project to
FINAL REPORT
theory and expectation. It was difficult, though, to validate the the community of practitioners.
methodology's predictions for system level (regionwide) per-
formance. Some of the results fell within the broad range of
results that have been reported in the literature. Other results 18.6.1 Research Product
fell outside the range of results reported in the literature.
The research product is a comprehensive methodology to
Indeed, application of the methodology to the same traffic
predict the short-term and long-term effects of corridor-level,
improvement to different locations in the region showed a
traffic-flow improvement projects on CO, VOCs, and NOX).
wide range of predicted system impacts. An HOV lane was
(PM is not estimated because of a lack of data.) The method-
added at two locations. In both cases, the HOV lane caused
ology can be used to evaluate the magnitude, scale (such as
net increases in traffic volumes on the facility. However, at regionwide, corridor, or local), and duration of the effects for
one location, the systemwide result was a net decrease in a variety of representative urbanized areas. The methodology
VMT for the region, while the other location caused a net is documented in this final research report and user's guide.
increase in regional VMT.
The validation was limited because of the data require-
ments of the new methodology and the lack of the necessary 18.6.2 Expected Audience and Market
data in available "before and after" studies of traffic-flow for the Research Product
improvements. More work could and should be done to val-
idate the methodology in other regions of the United States The target audience for the new methodology is all agen-
and against datasets gathered specifically for the purpose of cies currently performing air quality conformity analyses and
validating the NCHRPH 25-21 methodology. project-level environmental impact analyses. These agencies
are primarily the 350 MPOs and 50 state DOTs in the United
States, plus cities, counties, and private consultants.
18.5 CASE STUDY RESULTS
The NCHRP 25-21 methodology was applied to 10 case 18.6.3 Possible Impediments to Successful
studies. The impacts of individual traffic-flow improvement Implementation
projects on regional daily VMT were on the order of a few
hundredths of 1 percent. A 30-year improvement program Most MPOs and state DOTs already have a significant
impacted VMT by less than 1 percent. The impacts varied investment in existing transportation and air quality analysis
from a reduction in VMT to an increase in VMT, depending methodologies and software. This fact represents a significant
upon the specifics of each case study. The variation in the amount of institutional inertia, but the inertia can be overcome
predicted VMT impacts for the same traffic-flow improve- by training and dissemination of the NCHRP air quality
ment (HOV lanes) applied at different locations was greater analysis methodology to public agencies. Further validation
than the magnitude of the predicted impact itself. information is necessary to demonstrate the superior accuracy
The case study results suggest that more applications of of the methodology over current conventional methods.
each traffic-flow improvement type on different facility types Another likely impediment to general application of the
(i.e., radial and peripheral facilities), in different area types NCHRP 25-21 methodology is that the methodology is likely
(i.e., urban, suburban, and rural), and at different congestion to estimate more adverse air quality impacts than current
levels are needed to better understand the conditions under simplistic methods. If this happens, then there may be sig-
which traffic-flow improvements contribute to an overall net nificant institutional resistance to adoption of a more accu-
increase or decrease in vehicle emissions. rate methodology that results in more conformity problems.
This resistance can be overcome by FHWA and EPA adopt-
ing the NCHRP 25-21 methodology as one of the methods
18.6 IMPLEMENTATION PLAN
that constitute the state of the practice for evaluating the air
The NCHRP 25-21 research makes a critical contribution to quality impacts of highway projects.
current practice, providing a model of how to analyze the long-
and short-term air pollutant emission impacts of corridor-level 18.6.4 Likely Institutional Leaders
transportation projects. The methodology is implementable in Application
within a stand-alone software product or can be incorporated
as a postprocessor (or preprocessor) for current transportation The FHWA and EPA, by specifying acceptable method-
network analysis and air quality analysis software. Applica- ologies for use in conformity analyses, will be the institutional
tion of the methodology to the study of the impacts of traffic- leaders in promoting the application of the recommended
flow improvements will contribute to the accomplishment of methodology. These two agencies are already promoting the
national air quality goals. TRANSIMS research package of programs as the ultimate
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158
replacement for the old UTPS package, upon which most of of the NCHRP 25-21 methodology to validate its results
today's software and transportation models are based. for different areas of the country.
FINAL REPORT
TRANSIMS, however, still has a few more years of pilot · Publish the research results and user's guide as an offi-
testing and refinement before it will be ready for general cial NCHRP research report.
distribution. · Present the NCHRP 25-21 methodology at the TRB
It will be necessary to demonstrate to the EPA and FHWA Annual Meeting.
that the NCHRP 25-21 methodology will play a valuable · Present a 1-day training course on the NCHRP 25-21
role as a medium between the detailed data and analytical methodology and software for FHWA, TRANSIMS,
requirements of TRANSIMS and the simplistic approaches and EPA personnel, perhaps offered in Washington D.C.,
contained in many available sketch-planning methods. The in coordination with the TRB Annual Meeting and
NCHRP 25-21 methodology will also be available to the plan- opened to other professionals as well.
ning community in a usable form much sooner than TRAN- · Include a regular training course on the NCHRP 25-21
SIMS will, and it will be applicable by the large number of
methodology and software in the FHWA's National
small and medium-size MPOs that may not have the resources
Highway Institute course list.
or analytical needs for a more sophisticated package like
TRANSIMS.
18.6.6 Indicators of Progress and Success
18.6.5 Recommended Follow-On Activities
for Successful Implementation
Adoption of the NCHRP 25-21 methodology by the EPA
The following follow-on activities are recommended for and FHWA as a state-of-the-practice methodology for per-
successful implementation of the NCHRP 25-21 methodology: forming conformity analyses would be an immediate and com-
plete indicator of the success of the research project in devel-
· Demonstrate, through more cases studies and validation oping a methodology for use in general practice. Another
data sets in other regions of the United States, that the indicator of success would be adaptation of various modules
NCHRP 25-21 methodology gives more reliable results of the NCHRP 25-21 methodology by MPOs and software
than currently available methods do. This demonstra- developers to various existing transportation planning models
tion would involve data collection tailored to the needs and software packages.
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GLOSSARY OF ACRONYMS
FINAL REPORT
ABAG = Association of Bay Area Governments LEV = low-emission vehicle
AirQ = Air Quality LOS = level of service
API = application program interface LRTP = long-range transportation plan
BART = Bay Area Rapid Transit LUTRAQ = Land Use Transportation Air Quality
BEA = Bureau of Economic Affairs LUTRIM = Land Use Transportation Interaction Model
BPR = Bureau of Public Roads MEASURE = Mobile Emission Assessment System for
BTS = Bureau of Transportation Statistics Urban and Regional Evaluation
CARB = California Air Resources Board MEPLAN = Marcial Echenique Plan
CATS = Chicago Area Transportation Study METROPILUS = Metropolitan Integrated Land Use
CMEM = Comprehensive Modal Emission Model System
CMSA = Consolidated Metropolitan Statistical Area MOBILE = EPA vehicle emission factor model
CO = carbon monoxide MOVES = Motor Vehicle Emission Simulator
CORSIM = Corridor Simulation MPO = metropolitan planning organization
CTA = Chicago Transit Authority MSA = method of successive averages
CUF = California Urban Futures MTC = San Francisco Metropolitan Transportation
DoT = U.K. Department of Transport Commission
DRAM/ EMPAL = Disaggregate Residential Allocation MWCOG = Metropolitan Washington Council of
Model/Employment Allocation Model Governments
DVRPC = Delaware Valley Regional Planning NCTCOG = North Central Texas Council of Governments
Commission NEMA = National Electrical Manufacturers Association
E/I/E = external/internal/external NETSIM = Network Simulation
EMFAC = Emission Factor NOX = oxides of nitrogen
NYMTC-LUM = New York Metropolitan Transportation
EMME/2 = Equilibre Multimodal, Multimodal Equilibrium
Council Land Use Model
EPA = Environmental Protection Agency
OD = origin-destination
FORTRAN = Formula Translation
OMSI = Oregon Museum of Science and Industry
FREESIM = Freeway Simulation Model
ORNL = Oak Ridge National Laboratory
FTP = Federal Test Procedure
PART5 = Particulate Emission Factor Model
GIS = geographic information systems
PCE = passenger car equivalent
GUI = graphical user interface
PM = particulate matter
HC = hydrocarbons
POLIS = Projective Optimization Land Use Information
HCM = Highway Capacity Manual System
HERS = Highway Economic Requirements System PSRC = Puget Sound Regional Council
HLFM II+ = Highway Land Use Forecasting Model PUMA = Public Use Microdata Area
HOV = high-occupancy vehicle PUMS = Public Use Microdata Sample
HPMS = Highway Performance Monitoring System QRS = Quick Response System
HYROAD = Hybrid Roadway Intersection Model RTP = regional transportation plan
IDAS = ITS Deployment Analysis System SACMET = Sacramento Metropolitan Travel Demand
ICC = Interstate Commerce Commission Model
I/I = internal/internal SACOG = Sacramento Area Council of Governments
ILUTE = Integrated Land Use, Transportation, SACTRA = Standing Advisory Committee on Trunk Road
Environment Assessment
INTRAS = Integrated Traffic Simulator SAFD = speed and acceleration frequency distribution
IO = input output SCAG = Southern California Association of Governments
IPF = iterative proportional fit SIC = Standard Industrial Classification
ISTEA = Intermodal Surface Transportation Efficiency Act SMD = strategic model database
of 1991 SMITE = Spreadsheet Model for Induced Travel
ITLUP = Integrated Transportation and Land Use Package Estimation
ITS = intelligent transportation systems SOV = single-occupancy vehicle
LANL = University of California Los Alamos National SP = stated preference
Laboratory SPASM = Sketch Planning Analysis Spreadsheet Model
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STEAM = Surface Transportation Efficiency Analysis Model TRANSYT-7F = Traffic Network Study Tool, Release #7
STEP = Short-Range Transportation Evaluation Program TRANUS = an integrated land-use and transportation
FINAL REPORT
SUE = static user equilibrium model developed by Dr. Tomas de la Barra (formerly
TCM = transportation control measure known as "Transporte y Uso del Suelo," or
TDM = transportation demand management "Transportation and Land Use")
TEAPAC = Traffic Engineering Application Package Tranplan = Transportation Planning
TEA-21 = Transportation Equity Act for the 21st Century TSM = transportation system management
THC = total hydrocarbons TTI = Texas Transportation Institute
TIP = Transportation Improvement Program UTPS = Urban Transportation Planning System
TLUMIP = Transportation and Land Use Model Integration VDF = volume-delay function
Project VHT = vehicle-hours traveled
TMIP = Travel Model Improvement Program VMT = vehicle-miles traveled
TRAF-NETSIM = Traffic Network Simulation VOC = volatile organic compound
TRANSIMS = Transportation Analysis Simulation System WTP = willingness to pay
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