Synthesis of Congestion Pricing-Related 

Environmental Impact Analyses 

Final Report 

Prepared for 

United States Department of Transportation 

Federal Highway Administration (FHWA) 

Office of Operations 

1200 New Jersey Avenue, S.E. 

Washington, DC 20590 

By 

Battelle Memorial Institute 

505 King Avenue 

Columbus OH 43201 

October 18, 2010
QUALITY ASSURANCE STATEMENT 

The U.S. Department of Transportation provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public 

understanding. Standards and policies are used to ensure and maximize the 

quality, objectivity, utility, and integrity of its information. U.S. DOT 

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ensure continuous quality improvement. 
Technical Report Documentation Page 

1. Report No. 

FHWA-HOP-11-008 

2. Government Accession No. 3. Recipient's Catalog No. 

4. Title and Subtitle 

Synthesis of Congestion Pricing-Related Environmental Impact 

Analyses – Final Report 

5. Report Date 

October 18, 2010 

6. Performing Organization Code 

7. Author(s) 

Matt Burt and Garnell Sowell, Battelle; Jason Crawford and Todd 

Carlson, Texas Transportation Institute. 

8. Performing Organization Report No. 

9. Performing Organization Name and Address 

Battelle 

505 King Avenue 

Columbus, OH 43201 

10. Work Unit No. (TRAIS) 

11. Contract or Grant No. 

DTFH61-06-D-00007 – 

Task T10001 

12. Sponsoring Agency Name and Address 

U.S. Department of Transportation 

Federal Highway Administration 

Federal Transit Administration 

1200 New Jersey Avenue, S.E. 

Washington, DC 20590 

13. Type of Report and Period Covered 

14. Sponsoring Agency Code 

HRT 

15. Supplementary Notes 

Gene McHale, COTM 

16. Abstract 

This report summarizes the state-of-the-practice and presents a recommended framework for beforeafter evaluations of the environmental impacts of congestion pricing projects, such as high-occupancy 

toll (HOT) lanes and cordon or area pricing schemes. The report focuses on the three environmental 

impact areas that have been most commonly examined in such evaluations: air quality, noise, and 

environmental justice (sometimes referred to as equity). Since environmental impacts are a function of 

the travel impacts of congestion pricing projects, this report also examines state-of-the-practice 

regarding evaluation of travel impacts such as traffic, transit and travel behavior. The state-of-thepractice results are based primarily on a review of the published literature associated with eight 

congestion pricing study projects from around the world. A number of gaps in existing practice and 

understanding are identified and recommendations are provided to address those gaps. 

17. Key Word 

Congestion pricing, road user charges, 

environmental impacts 

18. Distribution Statement 

No restrictions. This document is available to the 

public. 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif. (of this page) 

Unclassified 

21. No. of Pages 

96 

22. Price 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
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Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses i Final Report 

TABLE OF CONTENTS

Page

LIST OF ABBREVIATIONS ..................................................................................................... iii

EXECUTIVE SUMMARY .......................................................................................................... v

Study Process ...................................................................................................................... v

State-of-the-Practice Findings ........................................................................................... vi

Travel Impact Prevailing Practice .......................................................................... vi

Travel Impact Knowledge Gaps and Limitations .................................................. vi

Environmental Impact Prevailing Practice ........................................................... vii

Environmental Impacts Knowledge Gaps and Limitations ................................. viii

Recommended Evaluation Framework .............................................................................. ix

Air Quality ............................................................................................................. ix

Noise ....................................................................................................................... x

Environmental Justice ............................................................................................. x

1.0 INTRODUCTION.......................................................................................................... 1-1

1.1 Background and Purpose ..................................................................................... 1-1

1.2 Study Process ....................................................................................................... 1-3

2.0 PROJECT SUMMARIES ............................................................................................. 2-1

2.1 Oregon Mileage Fee Concept and Road User Fee Pilot Program ....................... 2-2

2.2 Puget Sound Traffic Choices Study ..................................................................... 2-3

2.3 Commute Atlanta Mileage Based Value Pricing Demonstration ........................ 2-6

2.4 Minnesota I-394 MnPASS HOT Lanes ............................................................... 2-8

2.5 San Diego Interstate-15 HOT Lanes .................................................................. 2-12

2.6 The Stockholm Trial .......................................................................................... 2-15

2.7 Central London Congestion Charging ............................................................... 2-18

2.8 Singapore Area Pricing ...................................................................................... 2-25

3.0 SYNTHESIS OF THE STATE OF THE PRACTICE ............................................... 3-1

3.1 Basic Similarities and Differences between Study Projects ................................ 3-1

3.2 Assessing Travel Impacts .................................................................................... 3-1

3.2.1 Impacts, Performance Measures and Data Collection Methods .............. 3-1

3.2.2 Reported Findings and Study Limitations ............................................. 3-11

3.3 Assessing Environmental Impacts ..................................................................... 3-12

3.3.1 Impacts, Performance Measures and Data Collection Methods ............ 3-12

3.3.2 Reported Findings and Study Limitations ............................................. 3-16

3.4 Knowledge Gaps ................................................................................................ 3-17

3.4.1 Travel Impacts ....................................................................................... 3-17

3.4.2 Environmental Impacts .......................................................................... 3-20
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses ii Final Report 

TABLE OF CONTENTS (CONTINUED)

Page

4.0 RECOMMENDED EVALUATION FRAMEWORK ................................................ 4-1

4.1 Air Quality Analysis Framework ......................................................................... 4-5

4.1.1 Ambient Monitoring versus Calculated Vehicle Emissions .................... 4-5

4.1.2 Dispersion Modeling ................................................................................ 4-5

4.1.3 Calculation of Vehicle Emissions ............................................................ 4-5

4.2 Environmental Justice Analysis Framework ....................................................... 4-9

4.2.1 The Prevailing, Fundamental Tools and Techniques Provide a 

Solid Foundation ...................................................................................... 4-9

4.2.2 Travel Impacts ......................................................................................... 4-9

4.2.3 Consider Broadly How Impacts Differ Among a Wide Range of 

Users ...................................................................................................... 4-10

4.2.4 Explicitly Consider the Uses of Charging Revenues ............................. 4-11

4.2.5 Collect Demographic and other User Data Wherever Possible ............. 4-12

List of Appendices

APPENDIX A: Summary of Study Project Reported Travel Findings .............................. A-1

APPENDIX B: Summary of Study Project Reported Environmental Findings ................ B-1

List of Tables

Table ES-1. Travel Impact Knowledge Gaps ............................................................................. vii

Table ES-2. Air Quality Knowledge Gaps ................................................................................ viii

Table 1-1. Types of Congestion Pricing Projects ................................................................... 1-2

Table 1-2. Summary of UPA/CRD Strategies by Site ............................................................ 1-4

Table 2-1. Study Project Key Characteristics ......................................................................... 2-1

Table 3-1. Travel Impacts, Measures and Data Collection Methods ...................................... 3-2

Table 3-2. Traffic Impact Performance Measures and Data Collection Methods .................. 3-7

Table 3-3. Transit Performance Measures and Data Collection Methods .............................. 3-9

Table 3-4. Traveler Behavior Impact Performance Measures and Data Collection 

Methods ................................................................................................................. 3-9

Table 3-5. Environmental Impacts, Measures and Data Collection Methods ...................... 3-13

Table 3-6. Travel Impact Knowledge Gaps .......................................................................... 3-17

Table 3-7. Air Quality Knowledge Gaps .............................................................................. 3-21

Table 4-1. Summary of Recommended Environmental Impact Evaluation Framework ....... 4-2

 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses iii Final Report 

LIST OF ABBREVIATIONS 

CARB California Air Resources Board 

CO carbon monoxide 

CO2 carbon dioxide 

CRD Congestion Reduction Demonstration 

CURACAO Coordination of Urban Road User Charging Organisational Issues. 

DSRC dedicated short-range communication 

EAs environmental assessments 

EISs environmental impact statements 

EMFAC EMission FACtors 

EPA Environmental Protection Agency 

FHWA Federal Highway Administration 

GPS global positioning system 

HOT high occupancy toll 

HOV high-occupancy vehicle 

I-15 Interstate-15 

IM inspection and maintenance 

MSATS mobile source air toxics 

Mn/DOT Minnesota Department of Transportation 

NEPA National Environmental Policy Act of 1969 

NOx nitrogen oxides 

OBU on-board unit 

PM2.5 fine particulate matter 

PM10 particulate matter 

ppm parts per million 

PSRC Puget Sound Regional Council 

RTMC Regional Transportation Management Center 

SDSU San Diego State University 

U.S. DOT United States Department of Transportation 

UPA Urban Partnership Agreement 

VMT vehicle miles traveled 

VOCs volatile organic compounds 
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Environmental Impact Analyses iv Final Report 

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Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses v Final Report 

EXECUTIVE SUMMARY 

This report presents the results of the United States Department of Transportation (U.S. DOT) 

Federal Highway Administration (FHWA) study of methods for before-after measurement of the 

travel and environmental impacts resulting from congestion pricing projects. Congestion pricing 

encompasses a variety of strategies which feature roadway facility charges to reduce traffic 

congestion, such as high occupancy toll (HOT) lanes which allow vehicles with fewer occupants 

to pay a charge to access lanes available to vehicles with more occupants at no charge or at a 

reduced charge. Other congestion pricing strategies include zone-based pricing where vehicles 

are charged to enter or drive within a specific geographic area and full roadway pricing in which 

a toll is imposed upon a previously un-tolled roadway. 

This report presents a summary and analysis of current practices as well as a set of recommended 

practices for conducting before-after evaluations of congestion pricing projects. This study 

focuses on the environmental impact areas most commonly considered in the literature: air 

quality, noise, and environmental justice—sometimes termed “equity”—which considers how 

impacts distribute across different types of people, especially low income and minority groups. 

Since environmental impacts are driven by the broader travel impacts of congestion pricing 

projects, this study also investigated state-of-the-practice and assessed gaps in travel evaluation 

methodologies, including traffic, transit and traveler behavior. 

Published literature providing detailed environmental evaluation methodology information is not 

plentiful and there are very few critical assessments of the state-of-the-art, limitations and best 

practices. This study is intended to address that gap and provide recommendations that will 

inform U.S. DOT congestion pricing evaluations such as the approximately $1B Urban 

Partnership Agreement and Congestion Reduction Demonstration (UPA/CRD) program and 

other future projects. 

Study Process 

A sample of eight projects from among the more than 70 projects that were identified worldwide 

was selected for analysis. The sample included only before-after evaluations, a variety of 

project/study types, and several high-visibility, frequently cited projects which have not been 

investigated from an environmental evaluation methodology perspective. The eight study 

projects are: 

 Oregon Mileage Fee Concept and Road User Fee Pilot Program 

 Puget Sound Traffic Choices Study 

 Commute Atlanta Mileage-Based Value Pricing Demonstration 

 Minnesota Interstate 394 MnPASS HOT Lanes 

 San Diego Interstate 15 HOT Lanes 

 The Stockholm Trial 

 Central London Congestion Charging 

 Singapore Area Pricing. 

The findings presented in this report are based on a review of the published literature associated 

with these eight study projects as well as some of the relatively scarce congestion pricing 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses vi Final Report 

synthesis reports. These include reports from the Federal Highway Administration Value Pricing 

Pilot Program and the European Commission’s “Coordination of Urban Road User Charging 

Organisational Issues” (CURACAO) reports. 

State-of-the-Practice Findings 

State-of-the practice and knowledge gaps and limitations are presented separately below for 

travel and environmental impacts. 

Travel Impact Prevailing Practice 

 The most common impact areas considered include traffic (either describing the usage of 

a roadway, such as traffic volumes, or the performance of a roadway, such as average 

speeds), transit (either describing usage, such as ridership, or performance, such as 

schedule adherence), and traveler behavior, e.g., route, mode, and time of travel. 

 The most common traffic impact performance measures, used in nearly every study 

project, are: traffic volumes, vehicle miles traveled (VMT) and average speeds. Travel 

time is also frequently considered. 

 Most data for traffic performance measures are objective data, that is, data collected in 

the field using a wide variety of mostly automated techniques. One important area, 

vehicle occupancy (key to mode share and other person trip considerations), is often 

collected manually through visual observation. Probe vehicles, whether driven by 

evaluators or general public volunteers, are becoming increasingly common for traffic 

data collection. 

 There is less variation and fewer performance measures in the area of transit impacts. 

The most common measure, included in most evaluations that examine anything other 

than traffic impacts, is transit ridership, which is often collected automatically using onboard sensors. Bus travel times, schedule adherence, and rider perceptions are less 

common. 

 Consideration of traveler behavior impacts is common, but it is not included in all 

evaluations. Most evaluations that consider traveler behavior impacts use similar 

measures, including time of travel, route, mode, origin and destination, and collect the 

data using traveler surveys. 

 Traveler behavior data are usually collected through panel (or “longitudinal”) surveys in 

which the same people participate in the before and after surveys. More robust 

evaluations survey all adult travelers within a household; other surveys include only one 

traveler from a household. More robust evaluations survey both general traveler behavior 

(i.e., focusing on “typical” travel) and collect detailed trip information for one to three 

specific days using travel diaries. Across evaluations in general, travel diaries are not 

common. Coupling travel diaries with instruments in the respondents’ vehicles to record 

actual mileage and other data is rare. 

Travel Impact Knowledge Gaps and Limitations 

Table ES-1 identifies those areas where the current understanding of the travel impacts of 

congestion pricing projects is stronger as well as the areas where there are gaps and limitations. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses vii Final Report 

Table ES-1. Travel Impact Knowledge Gaps 

Better Understood Impacts (Knowledge) Less Understood Impacts 

(Knowledge Gaps) 

Short-term impacts (from a few months up to a year after 

deployment) Long term impacts 

Localized impacts Regional impacts 

Cumulative impacts (projects plus exogenous factors) Project-attributable impacts 

Individual travel behavior changes Household travel behavior changes 

Vehicle volumes Person trips 

Average speeds Vehicle speed fluctuations (driving cycle) 

Average performance Variability in performance (reliability) 

Transit ridership changes Transit crowding implications 

Most of the gaps and limitations have implications for environmental impact evaluation. Long 

term impacts refers to the understanding of land use changes such as changes in home or work 

locations that will only fully manifest over time periods far beyond typical project evaluation 

timeframes. In the case of regional impacts, it is not that most evaluations are failing to consider 

expected regional impacts but rather that there has not been enough analysis to understand even 

whether such impacts are likely. The failure to fully understand the influence of exogenous 

factors is a pervasive problem. Few evaluations understand those influences well enough to 

quantitatively adjust observed impacts to reflect only the pricing project. Of significance to air 

quality is the fact that there is a poor understanding of how congestion pricing projects impact 

traffic flow in ways that significantly impact vehicle driving cycles. 

Environmental Impact Prevailing Practice 

 Most evaluations do consider environmental impacts; most commonly air quality, noise 

and environmental justice. 

 There is little variation in air quality or noise impact evaluation methodologies among 

evaluations. 

 Air quality analyses consider project-related vehicle emissions and/or ambient pollution 

concentrations; the former are always calculated and the latter are always measured using 

roadside monitors. Calculation of emissions is more common than monitoring, which 

normally does not allow differentiation of project-attributable changes. 

 There is little variation in methods used to calculate vehicle emissions. Emission rates 

(or “factors”) expressing emissions of various pollutants in grams per mile at various 

average speeds are derived using models and applied to roadway link-specific, observed 

VMT at various speeds (usually observed speeds) to determine emissions. Total 

emissions are determined by summing all of the study roadway links. 

 In the U.S., vehicle emission rates have been developed using the Environmental 

Protection Agency (EPA) MOBILE model or, if the project is in California, using the 

similar California Air Resources Board EMission FACtors (EMFAC) model. These 

models require region-specific inputs on temperature, vehicle fleets, fuel types and 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses viii Final Report 

vehicle inspection and maintenance programs. These models provide little ability to 

examine impacts of vehicle driving cycle (proportion of travel under acceleration, 

deceleration, cruise and idle) impacts. 

 Like air quality impacts, noise impacts are examined by calculating noise levels—often 

with the FHWA Traffic Noise Model—or by roadside monitoring of ambient noise 

levels. No examples of project-attributable, significant noise impacts were found in the 

literature. Most evaluations show no perceptible changes in noise levels. 

Environmental Impacts Knowledge Gaps and Limitations 

Table ES-2 shows those areas where the current understanding of the air quality impacts of 

congestion pricing projects is stronger as well as the areas where there are gaps and limitations. 

Some of the gaps, such as uncertainty regarding project-attributable changes in VMT and speeds 

and lack of driving cycle changes—flow directly from limitations in traffic impact evaluation. 

Others, such as under-consideration of hourly variations in VMT and speeds are less about a lack 

of traffic data and more about the choice of air quality impact methodology. 

Table ES-2. Air Quality Knowledge Gaps 

Better Understood Components of 

Congestion Pricing Vehicle Emission 

Changes 

Less Understood Components of Congestion 

Pricing Vehicle Emission Changes 

Cumulative impacts (VMT, speed) Project-attributable impacts (VMT, speed) 

Localized impacts Regional impacts 

Average daily impacts Hourly variation (VMT, speed) 

 Driving cycle changes (traffic flow change) 

 Vehicle mix 

It is unlikely that most congestion pricing projects will demonstrate the magnitude of traffic 

volume or speed changes necessary to produce perceptible changes in noise levels. The smallest 

noise level change perceptible to most people—about 3dBA—requires a doubling or halving of 

traffic volume. 

Gaps and limitations regarding environmental justice are somewhat less clear, but generally 

include the following: 

 The need for more results overall to support development of more standardized 

approaches and to solidify knowledge. 

 The need to more fully explore geographic location and other “horizontal equity” issues 

(issues unrelated to income levels and ability to pay) and focus less exclusively on the 

“vertical equity” issue of the varying incomes and abilities to pay of different stakeholder 

groups. 

 Greater investigation of long-term impacts. 

 More research into how the uses of pricing revenues impact perceived and actual equity. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses ix Final Report 

Recommended Evaluation Framework 

Air Quality 

Key air quality evaluation recommendations include the following: 

 Calculate vehicle emissions (ambient monitoring can also be performed if resources 

permit but the priority should be on emission calculations). 

 In those unusual cases where a congestion pricing project is likely to significantly 

increase localized traffic congestion, especially near sensitive land uses such as nursing 

homes or schools, consider using a dispersion model such as the EPA CAL3QHCR 

carbon monoxide model to estimate project-attributable pollutant levels. 

 Always use a “project-level” analysis that considers project VMT and speed impacts on 

individual roadway links. 

 Select pollutants for analysis based on local air quality attainment status and issues. 

Common pollutants of interest include the criteria pollutants carbon monoxide, nitrogen 

oxides (ozone precursors), volatile organic compounds, and particulate matter; the 

greenhouse gas-related pollutants carbon dioxide and methane; and the mobile source air 

toxic benzene. 

 The geographic area of analysis should include as many of the roadway links as possible 

that are expected to be significantly impacted (e.g., a +5 mile per hour change in average 

speed) as possible. Include at least all freeways and major arterials within the priced 

zone and the parallel routes that may experience significant traffic diversion. 

 Collect at least a couple of months of VMT and speed data and a full year’s worth if 

possible. Longer data collection time frames allow seasonal variation to be controlled 

and exploration of changes as travelers “settle into” their responses to the pricing project. 

 To the extent possible, utilize VMT and average speed data that reflect only projectattributable changes by controlling for exogenous factors. Methods for determining 

whether and how much exogenous factors have impacted observed traffic data include: 

o Comparisons to control roadways/corridors/areas 

o Statistical modeling that can remove or control for the effect of exogenous factors 

by including such variables in multivariate equations 

o Utilization of household survey data (travel diary data being ideal) to understand 

the causes behind reported changes in travel behavior 

o Tracking fuel prices and employment levels 

o Elimination of traffic data from times and locations within the study area 

characterized by severe weather, significant traffic incidents, and significant 

roadway construction 

o Collecting before and after tracking data for the same month(s) of the year 

o Examination of historic traffic trends. 

 Calculate total daily emissions by summing calculated hourly emissions based on hourly 

VMT and average speed data; as opposed to calculating daily emissions based on 24-hour 

VMT and average speeds. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses x Final Report 

 Test for possible driving cycle changes and if present, collect observed driving cycle data 

using “floating car” test vehicle procedures (in which vehicles are equipped with Global 

Positioning Systems and drive train sensor) and use the new EPA MOVES model (Motor 

Vehicle Emission Simulator) to calculate emissions, as MOBILE and EMFAC provide 

little to no consideration of driving cycle changes. 

 Understand and carefully consider the inputs and default variables and methods utilized 

in the emission rate (e.g., EMFAC or MOBILE) or emissions model (e.g., MOVES) 

utilized as they can have significant impacts on calculated emissions. Reflect all local, 

user-specified inputs as accurately as possible. 

 Test for before-after changes in vehicle mix (the proportion of different vehicle types) 

and if present, vary VMT-by-vehicle type breakdown accordingly when calculating 

emissions. 

Noise 

Congestion pricing project evaluations have not shown significant, project-attributable noise 

impacts and since few congestion pricing projects are likely to produce the dramatic increases in 

traffic volumes necessary to produce perceptible changes in noise levels, noise analysis is not 

recommended as a standard component of project evaluation. The recommended framework 

therefore focuses on air quality and environmental justice. 

Environmental Justice 

Key environmental justice recommendations include the following: 

 Include the common tools and techniques which provide a solid foundation for 

understanding environmental justice impacts: 

o Regional geographic information systems to map the locations of low-income and 

minority populations within the likely impact area. 

o Attitudinal surveys, interviews and focus groups of the general public, corridor 

travelers and specific types of residents and travelers to gather attitude and 

perception as well as general travel behavior data. 

o Travel diary surveys to gather detailed, specific travel behavior data of various 

groups of interest. 

 Consider broadly how the congestion pricing project impacts different types of people 

across a wide range of dimensions, not just income and minority status. Other important 

factors include access to transit, access to private vehicle, and residential and work 

locations. 

 Integrate the collection of demographic data as fully as possible into the overall 

evaluation data collection plan. Such data can and should be collected in any and all 

surveys, but also consider how other data of environmental justice importance can be 

collected in other ways, such as origin-destination information via license plate 

recognition technology. 

 Explicitly consider the transportation environmental justice implications of how 

congestion pricing project revenues are reinvested. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 1-1 Final Report 

1.0 INTRODUCTION 

This report presents the results of the United States Department of Transportation (U.S. DOT) 

Federal Highway Administration (FHWA) study of methods for before-after measurement of the 

travel and environmental impacts resulting from congestion pricing projects. Congestion pricing 

encompasses a variety of strategies which feature transportation facility charges to reduce 

demand during congested periods, such as high occupancy toll (HOT) lanes which allow vehicles 

with fewer occupants to pay a charge to access lanes available to vehicles with more occupants at 

no charge or at a reduced charge. 

This report presents a summary and analysis of current before-after practices as well as a set of 

recommended practices for evaluating the environmental impacts of deployed congestion pricing 

projects. The summary of current practice is based primarily on a review of published literature 

pertaining to eight congestion pricing projects from around the world. 

The remainder of this introductory chapter provides background information, elaborates on the 

purpose of this study and summarizes the study methodology. Chapter 2.0 presents narrative 

summaries of each of the eight study projects describing, for each project, the congestion pricing 

project, the travel and environmental impact evaluation methodologies, and the reported impacts. 

Chapter 3.0 draws upon the information presented in Chapter 2.0 to summarize the state-of-thepractice and presents a critical assessment of the strengths and weaknesses. Chapter 4.0 presents 

the recommended framework for before-after evaluations of the environmental impacts of 

congestion pricing projects. 

1.1 Background and Purpose 

Traffic congestion has proven to be a persistent, challenging problem throughout the world. 

Very significant levels of traffic congestion have persisted and, typically, have continued to 

increase in many urban areas over the last several decades. The Texas Transportation Institute 

analyzes traffic congestion data from agencies throughout the United States and publishes results 

in Urban Mobility Monitoring Reports. The latest available report1

, published in 2009 and based 

on 2007 data, show the following congestion increases between 1982 and 2007: 

 162 percent increase in annual congestion delay per traveler 

 427 percent increase in total delay 

 462 percent increase in total fuel wasted 

 422 percent increase in the total cost of congestion. 

Although advances in transportation facilities and operations practices have proven useful in the 

effort to manage traffic congestion, to date, no cost-feasible and politically and environmentally 

acceptable “solutions” to traffic congestion have been identified. In approximately the last 

decade, the search for additional strategies to reduce traffic congestion has led to a heightened 

focus on congestion pricing. Interest in congestion pricing strategies is also, to some degree, a 

function of increasing interest in roadway revenue collection and financing options—the two 

strategies can be closely linked. Table 1-1 identifies various types of congestion pricing projects 

 

1

 Schrank, David and Lomax, Tim, “Urban Mobility Monitoring Report 2009,” University Transportation Center for 

Mobility, Texas Transportation Institute, July 2009. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 1-2 Final Report 

and some examples of deployed projects and studies. The categories of congestion pricing 

projects used in Table 1-1 are those used by the FHWA in their Value Pricing Pilot Program.2

Table 1-1. Types of Congestion Pricing Projects 

Type of 

Congestion 

Pricing 

Summary Description Project or Study Examples 

HOT Lanes 

(Partial Facility 

Pricing) 

Conversion of highoccupancy vehicle (HOV) 

lanes into priced lanes 

called HOT lanes. 

Vehicles not meeting HOV 

occupancy requirements 

can pay a fee to use the 

HOT lane. 

 I-15 in San Diego, California 

 I-394 and I-35W in Minneapolis, Minnesota 

 I-25 in Denver, Colorado 

 I-95 in Miami, Florida 

 I-10 and US 290 in Houston, Texas 

 SR 167 in Seattle Washington 

 I-495 in Virginia 

 I-15 in Salt Lake City, Utah 

 I-85 in Atlanta, Georgia 

Express Toll 

Lanes (Partial 

Facility Pricing) 

Introduction of new 

roadway capacity that can 

be accessed only by 

paying a toll. 

 SR 91 in Orange County, California 

Full Roadway 

Facility Pricing 

Introduction of variable 

tolls on roads, bridges or 

tunnels that were formerly 

free, or making currently 

flat tolls variable. 

 San Joaquin Hills Toll Road in Orange County, 

California 

 Midpoint and Cape Coral Bridges in Lee County, 

Florida 

 New Jersey Turnpike 

 New York-New Jersey Interstate toll crossings 

 SR 520 Bridge in Seattle, Washington 

Zone-based 

Pricing, including 

Cordon and Area 

Pricing 

Variable or fixed charges 

to drive within or into a 

congested area within an 

urban region. Involves 

placing new tolls on 

multiple existing roads. 

 Central London Congestion Charging 

 The Stockholm Trial, Sweden 

 Milan, Italy “EcoPass” 

 Rome, Italy 

Regionwide 

Pricing 

Pricing at several locations 

within a region, including 

new and existing lanes or 

entire facilities. 

 Singapore 

Making Vehicle 

Use Costs 

Variable 

Conversion of fixed costs 

such as vehicle taxes and 

fees, auto insurance and 

lease costs, into costs that 

vary vehicle miles driven 

and/or time of day. 

 Oregon Mileage Fee Concept and Road User Fee 

Pilot Program 

 Puget Sound Traffic Choices Study 

 Commute Atlanta Mileage Based Value Pricing 

Demonstration 

 Minnesota Mileage-based User Fee Demonstration 

Parking Pricing 

and Other 

Market-Based 

Strategies 

Various parking and other 

market-based strategies 

(see examples at right). 

 Dynamically Priced Car Sharing in Tampa, Florida 

 New York City On-Street Parking Pricing 

 San Francisco Car Sharing 

 Los Angeles ExpressPark Variable Parking Pricing 

 San Francisco Downtown Parking Pricing 

 

2

 United States Department of Transportation, Federal Highway Administration, “Report on the Value Pricing Pilot 

Program Through May 2009,” September 17, 2009. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 1-3 Final Report 

An important manifestation of the increasing focus on congestion pricing in the United States is 

the U.S. DOT Urban Partnership Agreement (UPA) and Congestion Reduction Demonstration 

program. Under the UPA/CRD, U.S. DOT has provided a total of approximately $1B shared 

among six metropolitan areas (Atlanta, Los Angeles, Miami, Minneapolis, San Francisco and 

Seattle) to deploy integrated sets of congestion reduction strategies that feature various forms of 

congestion pricing coupled with supporting travel demand management, transit, and technologybased strategies. Table 1-2 summarizes the UPA/CRD deployments, with the congestion pricing 

strategies shown in bold type. An important part of the UPA/CRD program is the U.S. DOT 

evaluation of the impacts of each deployment. Comprehensive assessments of the impacts of the 

various strategies used at each site are critical both to inform U.S. Federal transportation policy 

and programs but also to provide guidance to operating agencies who may implement similar 

strategies. 

As congestion pricing projects are becoming more common there is a growing volume of 

literature describing the projects and their effects. However, there is little published literature on 

the strengths and weaknesses of prevailing congestion pricing evaluation methodologies. This 

study is intended to address that deficiency; to summarize current practice and recommend a 

framework that can inform the UPA/CRD evaluations that are currently in progress and which 

may also help guide future U.S. DOT or other evaluations. 

The primary focus of this study is on the environmental impacts of congestion pricing, including 

air quality, noise and environmental justice. However, environmental impacts are typically a 

direct result of travel impacts of projects, such as changes in traffic volumes and roadway 

speeds. As such, it was clear that this study must also consider how the travel impacts which 

underlie environmental impacts have been and can best be evaluated. 

1.2 Study Process 

The study process consisted of the following steps: 

 A scan of published literature on congestion pricing projects 

 Selection of study projects for detailed literature review 

 Detailed review of published literature on the study projects 

 Review of several general (not evaluation methodology-focused) congestion pricing 

references for possible information on evaluation 

 Development of the state-of-the-practice summary and recommended framework. 

The initial scan of published literature utilized extensive Internet-based literature searches as 

well as some searches of university library and technical journal databases. The initial scan was 

intended to provide a sketch-level understanding of the number and general nature of congestion 

pricing projects and studies of those projects worldwide. That understanding also informed the 

selection of a manageable number of study projects. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 1-4 Final Report 

Table 1-2. Summary of UPA/CRD Strategies by Site3 

UPA/CRD Strategies 

Site 

MN SF Sea Mia LA Atl 

Convert HOV lanes to dynamically priced high-occupancy 

tolling (HOT) lanes and/or new HOT lanes X X X X 

Priced dynamic shoulder lanes X 

Variably priced parking and/or loading zones X X 

Variably priced roadways or bridges (partial cordon) X 

Increase park-and-ride capacity (expand existing or add new) X X X X X 

Expand or enhance bus service X X X X 

Implement new, or expand existing, Bus Rapid Transit X X X 

Transit on special runningways (e.g., contraflow lanes, 

shoulders) X X 

New and/or enhanced transit stops/stations X X X X 

Transit traveler information systems (bus arrival times, parking 

availability) X X X 

Transit lane keeping/lane guidance X 

Transit traffic signal priority X X X 

Arterial street traffic signal improvements to improve transit 

travel times X 

Ferry service improvements X X 

Improved transit travel forecasting techniques X 

Pedestrian improvements X X 

“Results Only Work Environment” employer-based techniques X 

Work to increase use of telecommuting X X X X 

Work to increase flexible scheduling X X X 

Work to increase alternative commute programs, including car 

and van pools X X X X X X 

Vehicle infrastructure integration test bed X 

Active traffic management X X 

Regional multi-modal traveler information (e.g., 511) X X X 

Freeway management (ramp meters, travel time signs, 

enhanced monitoring) X X 

Enhanced traffic signal operations X 

Parking management system X X 

Integrated electronic payment for parking and transit X 

Automated enforcement of HOV and toll violations X 

Note: Strategies shown in bold type are congestion pricing strategies. 

 

3

 United States Department of Transportation, Federal Highway Administration and Federal Transit Administration, 

“Atlanta Congestion Reduction Demonstration National Evaluation Plan – Draft,” prepared by Battelle, May 2010. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 1-5 Final Report 

A number of conclusions were drawn based on the initial scan: 

 A large number of congestion pricing projects was found—about 70, too many to study 

in-depth as part of this study, and therefore a down-selection of study projects was 

necessary. 

 There was significant variation in congestion pricing projects in terms of the type of 

pricing (HOT lane, cordon, area, etc.), geographic location (there are many U.S. and 

international projects), deployment status (proposed/planned vs. operating), and 

consideration of environmental impacts. 

 There was a limited amount of literature focusing on the before-after evaluation of the 

environmental impacts (including the precipitating travel impacts) of congestion pricing 

projects. The authors of a 2008 FHWA evaluation of their Value Pricing Pilot Program4

reached the same conclusions. 

The following compiled lists of congestion pricing projects include the projects considered in the 

initial scan conducted for this study and are available on-line: 

 A list compiled by Mark W. Burris, Ph.D., P.E. of the Texas Transportation Institute: 

https://ceprofs.civil.tamu.edu/mburris/pricing.htm

 A list of Federal Highway Administration Value Pricing Pilot Program Projects: 

http://ops.fhwa.dot.gov/tolling_pricing/value_pricing/projects/allprojects.htm 

 A list of case studies examined through the Coordination of Urban Road User Charging 

Organisational Issues (CURACAO) program (see “Case Studies” list): 

http://www.curacaoproject.eu/downloads.php. 

Following the initial scan, a subset of congestion pricing projects was selected for detailed 

literature review based on consideration of the following factors: 

 A focus on analyses of deployed, operational congestion pricing projects (whether a 

short-term demonstration with simulated congestion charges or long-term, full 

deployment with real charges)—which is consistent with the fundamental study objective 

to inform the evaluation of the UPA/CRD field deployments. 

 The apparent extent to which environmental impacts were considered. 

 The desirability of including several highly visible, frequently cited pricing and/or 

revenue collection projects like the London, Singapore and Stockholm area pricing 

schemes and the Puget Sound and Oregon field studies. 

 A mix of pricing projects reflecting a variety of pricing strategies. 

 A mix of projects from throughout the United States and around the world. 

 

 

4

 United States Department of Transportation, Federal Highway Administration, “Value Pricing Pilot Program: 

Lessons Learned Final Report.” Prepared by K.T. Analytics and Cambridge Systematics, Inc. August 2008. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 1-6 Final Report 

Based on these factors, along with practical considerations encountered over the course of the 

research—namely difficulties in finding sufficient documentation for certain projects—the 

following eight study projects were selected. 

 Oregon Mileage Fee Concept and Road User Fee Pilot Program 

 Puget Sound Traffic Choices Study 

 Commute Atlanta Mileage Based Value Pricing Demonstration 

 Minnesota I-394 MnPASS HOT Lanes 

 San Diego I-15 HOT Lanes 

 The Stockholm Trial 

 Central London Congestion Charging 

 Singapore Area Pricing. 

Three of these projects—the Oregon, Puget Sound and Atlanta projects—consisted of beforeafter (or “with/without”) evaluations of short-term field demonstrations of congestion 

pricing/revenue collection schemes featuring simulated pricing charges. The other projects all 

consisted of before vs. after evaluations of fully-deployed congestion pricing schemes with real 

pricing charges. The eight study projects and associated evaluation methodology and pricing 

impact results information gleaned from the literature review are described in Chapter 2.0. 

After selecting the eight study projects, a second on-line literature search was conducted to 

obtain as many relevant project documents as possible. In addition to reports focusing on 

specific congestion pricing projects, this second search identified a small number of congestion 

pricing synthesis reports, including the following: 

 FHWA, Value Pricing Pilot Program Lessons Learned, Final Report (August 2008) 

 CURACAO reports (State of the Art Review, May 2009; Final Report, June 2009) 

 FHWA, Lessons Learned from International Experience in Congestion Pricing 

(December 2008). 

All of this project-specific and synthesis literature was analyzed and provides the basis for 

Chapters 2.0 and 3.0 of this report, and informs the recommendations presented in Chapter 4.0. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-1 Final Report 

2.0 PROJECT SUMMARIES 

This chapter describes the eight congestion pricing projects that were examined as part of this 

study. For each project, the overall objectives are summarized, along with the travel and 

environmental analysis methodologies and findings. The information presented in this chapter is 

strictly descriptive, that is, a summary of information contained in the reviewed literature. As 

such, the “findings” discussion within each project summary presents the findings reported in the 

literature, including any reported observations or conclusions pertaining to the strengths and 

weaknesses of the methodologies. Chapter 3.0 compiles the key project findings presented in 

this chapter and synthesizes the state-of-the-practice, including an assessment of collective 

strengths, weaknesses and gaps associated with those practices. 

The methodologies used in before-after evaluations of congestion pricing projects are the focus 

of this study, rather than the impacts themselves. However, the project summaries that follow as 

well as some of the summary information in Chapter 3.0 include findings (impact) information 

because the information was generally readily available from the same literature that was 

reviewed for methodologies. 

Table 2-1 presents basic characteristics of each of study project. Additional information on each 

project is presented in the summaries that follow. 

Table 2-1. Study Project Key Characteristics 

Study/Project Study/Project Type Study 

Timeframe 

Travel 

Impacts 

Analyzed? 

Environmental 

Impacts 

Analyzed? 

Oregon Mileage Fee 

Concept and Road User 

Fee Pilot Program 

Simulated Pricing Field 

Demonstration 2006-2007 Yes No 

Puget Sound Traffic 

Choices Study 

Simulated Pricing Field 

Demonstration 2005-2007 Yes No 

Commute Atlanta 

Mileage Based Value 

Pricing Demonstration 

Simulated Pricing Field 

Demonstration 2003-2006 Yes No 

Minnesota I-394 

MnPASS HOT Lanes 

Before-After Evaluation 

of an HOV to HOT Lane 

Conversion 

2003-2006 Yes Yes 

San Diego I-15 HOT 

Lanes 

Before-After Evaluation 

of an HOV to HOT Lane 

Conversion 

1997-2000 Yes Yes 

The Stockholm Trial Before-After Evaluation 

of Cordon Pricing 2003-2006 Yes Yes 

Central London 

Congestion Charging 

Before-After Evaluation 

of Cordon Pricing 2002-Present Yes Yes 

Singapore Area Pricing Before-After Evaluation 

of Area Pricing 1975-Present Yes Yes 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-2 Final Report 

2.1 Oregon Mileage Fee Concept and Road User Fee Pilot Program 

This project summary is based primarily on a 2007 report prepared by the project sponsor, the 

Oregon Department of Transportation.5

The Congestion Pricing Strategy and Objectives 

The Oregon Department of Transportation conducted a simulated field demonstration of a timeof-day and area-based congestion pricing scheme. The congestion pricing investigation, the 

“Road User Fee Pilot Test,” was part of a broader project—the Oregon Mileage Fee Concept—

which examined the general notion of mileage-based charges in lieu of traditional gas taxes. 

The congestion pricing demonstration was conducted in 2006-2007 and involved providing 

volunteer (general public) drivers of instrumented vehicles feedback on how much they would 

have paid for their travel under the traditional gas tax approach versus under a per-mile charging 

scheme in which charges were higher for travel during peak periods and within congested zones 

(within the Portland region). The drivers did not actually pay the congestion charges but were 

asked to make their travel decisions as if they were actually being charged. Feedback on what 

the mileage fee charges would have been was provided to drivers when they refueled at special, 

participating gas stations. Drivers were also updated monthly by program administrators as to 

the status of their charges. 

 This project was concerned only with understanding travel behavior changes and did not assess 

how those behaviors translated into traffic congestion or transit ridership changes. This project 

did not assess any environmental impacts. 

Methodology 

This project examined the following congestion pricing-related travel performance measures: 

 Changes in total vehicle miles traveled (VMT) 

 Time-of-day changes in vehicle miles traveled, e.g., shifts from the peaks (higher charge) 

to off-peaks (lower charge) 

 Mode shifts from driving to transit or bicycling 

 Route changes, e.g., taking routes that avoided the congestion pricing zone 

 Number of trips, e.g., foregoing trips that would have been made lacking the pricing. 

Changes in total VMT, time-of-day changes, and route changes were collected using the invehicle global positioning system (GPS) devices. Mode shifts were assessed qualitatively via 

traditional (non-travel diary) surveys of participants. 

The project included both a baseline (no pricing) and experimental phase. During the 

experimental phase, drivers were broken into three groups, a control group where no mileagebased or congestion pricing elements were introduced, a “VMT group” where flat, per-mile (not 

congestion) pricing was introduced, and a third group where time-of-day and area pricing was 

 

5

 Whitty, James M., “Oregon’s Mileage Fee Concept and Road User Fee Pilot Program: Final Report,” Oregon 

Department of Transportation, November 2007. 
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Environmental Impact Analyses 2-3 Final Report 

introduced. Changes in the performance measures were determined by comparing among the 

various phases and experimental groups: the baseline phase (no pricing), the experimental phase 

control group (no pricing), the experimental phase VMT group, and the experimental phase timeof-day/area pricing group. 

Findings 

Analysts concluded that the premium charged in the peak periods motivated participants to 

change the timing of their trips, seek alternate routes outside the congested zone, or use transit 

more. Participants in the time-of-day/area pricing group reduced their total VMT by 10 percent 

relative to the baseline (no pricing, pre-deployment) condition, with a peak hour VMT reduction 

of 13 percent. Study data also showed that the congestion pricing charges could impact mode 

choice during peak hours, with distance to transit influencing the extent of impact. Those who 

live closer to transit stops were more likely to use it during peak periods as an alternative to 

driving. 

2.2 Puget Sound Traffic Choices Study 

This project summary is based primarily on a 2008 report prepared by the project sponsor, the 

Puget Sound Regional Council.6

The Congestion Pricing Strategy and Objectives 

In 2002, the Puget Sound Regional Council (PSRC) received a grant from FHWA to conduct a 

pilot project to see how travelers change their travel behavior in response to variable charges for 

road use (variable or congestion-based tolling). Global positioning system tolling meters were 

placed in the vehicles of about 275 volunteer households. From July 2005 until February 2007, 

the project observed participant driving patterns before and after hypothetical tolls were charged 

for the use of all the major freeways and arterials in the Seattle metropolitan area. 

The primary aims of the Traffic Choices Study were to: 

1. Accurately describe the behavioral response to the congestion-tolling of roadways 

2. Better understand issues of policy related to the implementation of road network tolling 

3. Test an integrated system of technical solutions to the problem of tolling a large network 

of roads without deploying substantial physical hardware on the roadside 

4. Familiarize the public and policy makers with road network tolling 

5. Generate price response data for use in other modeling and analysis 

6. Develop an understanding of technological applications and standards 

7. Better define a set of policy issues to be addressed in actual program design. 

This study considered only travel behavior changes. It did not examine how travel behavior 

changes may translate into traffic or environmental impacts. 

 

6

 Puget Sound Regional Council, “Traffic Choices Study–Summary Report,” April 2008. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-4 Final Report 

The study recruited a sample of volunteers and, after establishing their baseline “before-tolling” 

driving routine, began imposing hypothetical charges (levied against an endowment account as a 

financial incentive) for access to selected roadway facilities at particular time periods in the day. 

The study monitored driving behavior of participants for an average of approximately 18 months 

per household. 

Methods 

The study goal was to determine how travel behavior (distance, timing, and number of vehicle 

trips) was affected by a range of other factors (e.g., household income, size, location; number of 

vehicles; availability of transit; day or time of travel; congestion price charged). The study 

formulated statistical models to explain how measures of travel demand, across households, 

vehicles, and workers (the dependent variables) are affected by changes in the generalized costs 

of travel (tolls, out-of-pocket costs and time costs), while controlling for household 

demographics (income and number of drivers), seasonal factors, and a measure of transit 

viability (the independent, explanatory variables). The study estimated the elasticities of travel 

demand with respect to changes in the price of travel (tolls). 

Characteristics of the study included: 

 Over 275 households; over 400 vehicles 

 Randomly selected from a pool of potential participant households 

 Each household was provided a unique travel endowment account, based on their 

baseline travel behavior 

 Hypothetical tolls were levied against the endowment account 

 450 on-board unit (OBU) installations and removals 

 System fully operational for over 18 months 

 Up to 18 months of trip data per household 

 Over 750,000 individual trip records 

 Household surveys and focus groups conducted. 

The billing system provided detailed physical and financial information on trip activity: 

 Tolls paid, VMT by link type, travel time, speeds 

 GPS provided information for reconstructing paths, trip ends, and times of travel. 

Trip purpose and traveler demographic attributes were appended to trip information: 

 Trip purpose had to be inferred using employment and land use records 

 Driving tours were constructed from trip data 

 Household income was both reported and inferred. 

 
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Environmental Impact Analyses 2-5 Final Report 

GPS tolling meters were placed in vehicles of 275 volunteer households: 

 Established baseline “before tolling” driving routine 

 Monitored “after tolling” driver response to pricing on all major freeways and arterials 

for 18 months. 

Findings 

The Traffic Choices study resulted in a number of changes in aggregate travel demand. Under 

the tolling policy established for the study, the changes included: 

 7 percent reduction in all vehicle trips per week 

 12 percent reduction in VMT per week 

 8 percent reduction in travel time per week 

 6 percent reduction in trip segments per week) 

 13 percent reduction in miles driven on tolled roads (tolled miles per week). 

The participating households altered the nature and amount of vehicle use in response to 

hypothetical tolls that increased the costs of travel but did not result in improved travel times. 

Many households made notable changes in their travel practices. Households that modified their 

travel did so in many different ways: taking fewer and shorter vehicle trips, choosing alternate 

routes and times of travel, or linking trips together to reduce vehicle use altogether. Some 

households altered their routine travel practices. On the other hand, other households had very 

limited opportunities to avoid using high demand roads during peak travel times. 

The results were consistent with the study team’s expectations. Researchers concluded “paying 

tolls that reflected the costs of congestion caused many travelers to change aspects of travel 

behavior, some more than others, depending on the usefulness and convenience of the 

opportunity for change.” 

A conservative analysis of the benefits of network tolling in the Puget Sound region indicates 

that the present value (2008) of net benefits would be $33.6 billion over a 30-year period. The 

implementation and operating cost of the system in present value was estimated at $5.5 billion. 

This provides a benefit/cost ratio of 6.1 for a variable toll network in the region. 

 Not all aspects of a road network tolling system were fully demonstrated, but the core 

technology for satellite-based (and whole road network) toll systems were mature and reliable. 

The tolling system performed as expected and met basic system operating requirements. Further 

work on system refinement and design of enforcement and billing systems would be required 

prior to any full system deployment. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-6 Final Report 

2.3 Commute Atlanta Mileage Based Value Pricing Demonstration 

The Congestion Pricing Strategy and Objectives 

“Commute Atlanta” refers to a multi-faceted, multi-phase program. The portion of the program 

of interest to this study is a field study of mileage-based value pricing that was carried out 

between 2004 and 2006. Participants in the overall Commute Atlanta Program include FHWA, 

the Georgia Department of Transportation and the Georgia Institute of Technology. 

The mileage-based value pricing strategy evaluated the effectiveness of a cash incentive to 

reduce the vehicle miles traveled by volunteer households. For each household, an incentive 

account was established based on the household’s actual number of miles traveled in the 

equivalent quarter of the previous, baseline year.7 The amount of the account varied quarterly 

and was determined by multiplying a dollar amount (which varied from quarter to quarter over 

the study period, starting at $0.05 per mile and concluding at $0.15 per mile) by the number of 

miles traveled in the baseline quarter. During the nine-month experiment, households were 

eligible for a payment from their account each quarter, with the amount of each payment 

dependent on how many miles they had driven. In the first quarter, $0.05 per mile driven was 

deducted from the payment. So, if a household had traveled 1,000 miles in the first quarter of 

the baseline year, and 900 miles in the first quarter of the experimental period, their total 

potential payment would have been $50 (1,000 miles x $0.05) but their actual payment would 

have been $5 ($50 – [900 miles x $0.05]). Households that traveled as many or more miles than 

in the baseline period received no payments. 

The evaluation of the mileage-based value pricing strategy used a before (no incentive) versus 

after (with incentive) methodology and focused strictly on household travel behavior. No 

investigation of environmental impacts was performed. However, as part of a separate study of 

the potential for congestion pricing in the Metropolitan Atlanta Area, an air quality evaluation 

framework was proposed and that proposed approach is summarized here. 

Methods 

The evaluation of the mileage-based value pricing component of Commute Atlanta considered 

the following travel-related performance measures and variables: 

 Household travel behavior 

o Vehicle miles driven 

o Number of trips (trip making rates) 

o Trip lengths 

o Durations 

o Intra- versus extra-regional travel activity. 

 Household demographic data, including: home location, work status, household 

structure, income, schools attended, and vehicle ownership.8

 

7

Georgia Institute of Technology, Commute Atlanta Study webpage, accessed July 2010: 

http://commuteatlanta.ce.gatech.edu/. 8

 Xu, Zuyeva, Kall, Elango, Guensler, “Mileage Based Value Pricing: Phase II Case Study Implications of the 

Commute Atlanta Project.” Transportation Research Board 2009 Annual Meeting. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-7 Final Report 

Household travel behavior data were collected using volunteers’ vehicles instrumented with GPS 

and data loggers which monitored travel parameters (position, speed, etc.) from which data could 

be accessed remotely. These data were collected from 95 households that constitute a subset of a 

much larger group of households who have participated in other aspects of the overall Commute 

Atlanta program data collection over a number of years.9

The collection of household socio-economic data was performed using longitudinal (panel) 

surveys and supported a detailed, case study analysis of each of the 95 households to understand 

the relationship between demographic changes over the course of the study and their impact on 

travel behavior. Participating households were surveyed monthly over the course of the study on 

household demographic parameters. It is important to note that although the household surveys 

included measurement of parameters that are believed to be closely linked to travel behavior, 

such as work status changes, the surveys do not appear to have specifically queried participants 

on the motivations behind travel decisions and changes. 

The overall Commute Atlanta program included additional data collection, including two-day 

travel diaries and surveys focusing on employer commute incentives, but it does not appear that 

those data were used in the analysis of the mileage-based value pricing demonstration. 

The air quality impacts of the Commute Atlanta mileage-based value pricing demonstration were 

not investigated. However, as part of a separate study of the potential for congestion pricing in 

the Metropolitan Atlanta Area,10 an air quality evaluation framework was proposed that focuses 

on two air quality performance measures: 

 Total vehicle emissions of: carbon monoxide (CO), particulate matter (PM10), fine 

particulate matter (PM2.5) and ozone 

 Localized CO levels (CO “hotspot” modeling). 

Had vehicle emissions been studied, the plan was to calculate them using emission rates (grams 

per mile) from the EPA MOBILE emission factor model multiplied by observed link vehicle 

miles traveled. Localized CO levels were to be calculated using the EPA CALINE4 model, 

which utilizes user supplied traffic, meteorological, and topographic inputs coupled with EPA 

CO emission rates to estimate CO concentrations at specific modeled locations associated with 

roadway intersections. 

Findings 

The data collection associated with the mileage-based value pricing demonstration included trip 

lengths, trip durations and other performance measures. However, the literature that was 

reviewed included only findings related to vehicle miles driven and the influence of household 

demographic factors on miles driven. The later findings are especially important as this study 

delved deeply into these particular exogenous factors (changes in household demographics) and 

 

9

 Xu, Zuyeva, Kall, Elango, Guensler. 2009 

10 Ross, Guensler, et al. 2008. “Final Report – Congestion Pricing Response: Study for Potential Implementation 

in the Metropolitan Atlanta Area.” Prepared for the Georgia Department of Transportation by the Center for Quality 

Growth and Regional Development & School of Civil and Environmental Engineering at the Georgia Institute of 

Technology. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-8 Final Report 

represents the most critical examination of these considerations that was found in the literature. 

In the case of this study, the findings related to exogenous factors are more significant than the 

travel impacts. 

It was reported that more than half of the mileage-based value pricing households reduced their 

travel and that, overall, vehicle miles driven was reduced by 3 percent relative to the baseline (no 

incentive) period. However, researchers concluded that the VMT reduction was not significant 

given the significant variability in before-after household travel changes among households.11

The researchers concluded that changes in household demographics over the course of their 

study had a significant impact on observed VMT changes and more of an impact than other 

exogenous factors. They found that of the 95 households in the case study, only 28 households 

remained stable with respect to all six major demographic characteristics: home location, work 

status, household structure, income, school(s) attended, and vehicle ownership. The most 

common change was vehicle ownership (40 percent), followed by work status (34 percent). The 

researchers concluded that among the demographic changes, the impact of work status change 

was most evident, but that home location and household structure changes were also important 

influences on VMT. Given the small sample size, they were not able to form conclusions about 

how the other demographic parameters affect travel. 

Based on these findings, the researchers identified a number of methodology enhancements that 

are necessary in order to form valid conclusions regarding the household travel impacts of 

congestion pricing projects. These recommendations focus on larger sample sizes and collection 

of more detailed information from participants to better understand the reasons behind the 

reported travel behavior. The researchers recommend using “case study” approaches such as 

theirs in which the impact of changes in household demographics are thoroughly explored at the 

individual household level. They also suggest that home interviews and focus groups would be 

helpful in understanding travel behavior changes. 

Finally, the researchers cast some degree of doubt on the results of other congestion pricing 

studies that may not have adequately controlled for household demographic changes (including 

two studies discussed in this report: Oregon and Puget Sound). Specifically, they state that: 

“...the findings of similar studies that have been conducted should be eyed with caution and 

researchers need to be careful in drawing any conclusions on the impact of pricing incentives 

from these studies.”12

2.4 Minnesota I-394 MnPASS HOT Lanes 

The Congestion Pricing Strategy and Objectives 

In May 2005, the Minnesota Department of Transportation (Mn/DOT) started operation of the 

State’s first high occupancy toll facility on a segment of the I-394 corridor in the Minneapolis/ 

St. Paul region. The system, known locally as MnPASS, was the first deployment of HOT lane 

strategies in Minnesota and the second in the United States that dynamically adjusts pricing 

 

11 Xu, Zuyeva, Kall, Elango, Guensler. 2009. 

12 Xu, Zuyeva, Kall, Elango, Guensler. 2009. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-9 Final Report 

levels in response to varying traffic conditions. The travel behavior/traffic objective of the 

congestion pricing was to adjust tolls so as to meter use of the HOT lane to levels that would 

provide consistent free-flow speeds. 

Mn/DOT conducted a comprehensive monitoring and evaluation effort to assess the I-394 

MnPASS system, including investigation of traffic impacts (using both pre- and post-deployment 

data); traveler behavior changes, including mode choice; and environmental impacts. 

Methods 

Travel related performance measures utilized by Mn/DOT in their evaluation included the 

following: 

 Reported travel behavior, including mode choice and vehicle occupancy 

 Traffic volumes 

 Speeds 

 Travel times. 

Reported travel behavior was collected through three waves of panel surveys of project corridor 

residents and, as a control group, users of HOV lanes in a different corridor, I-35W. Between 

800 and 900 residents participated in each wave. The first wave of surveying was conducted 

prior to HOT lane deployment and the second and third waves were conducted post-deployment. 

The survey effort included telephone surveys, mailed questionnaires, and travel logs. The travel 

logs included a travel diary for a single day and general travel behavior information for one 

week. 

Traffic volumes, speeds and travel times were collected directly, or derived, from Mn/DOT 

Regional Transportation Management Center (RTMC) detectors. The detectors provided a 

nearly continuous source of data on vehicle volumes for a period between January 2003 (predeployment) and July 2006 (post-deployment). Data were collected from all detectors located 

within the roadway project section. Data from selected stations upstream and downstream of 

I-394 were also collected to monitor vehicle volumes at adjacent bottleneck locations. Vehicle 

speed data, as derived from detector density data, were analyzed separately for the general 

purpose and MnPASS lanes based on the recorded influencing factors. Baseline detector data 

were compiled for all available days and time periods between July 2003 and May 2005. Similar 

data were compiled for the technical evaluation from the opening date through July 2006 to 

represent the after conditions.13

Environmental performance measures consisted of: 

 Noise levels 

 CO levels (the project was located within a CO non-attainment area) 

 Environmental justice (variation in survey responses for various demographics). 

 

13 Cambridge Systematics, Inc., Short-Elliott-Hendrickson, Inc., and LJR, Inc. “I-394 MnPASS Technical 

Evaluation-Final Report.” Minnesota Department of Transportation and the Metropolitan Council, Minneapolis, 

Minnesota. November 2006. 
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Environmental Impact Analyses 2-10 Final Report 

Before and after data on CO levels were collected with emissions sensing stations deployed at 

several strategic locations near the roadway. Pre-implementation data were supplemented by 

historical emissions data from existing sensor stations located in the corridor. One-hour CO 

averages were recorded for the a.m. and p.m. peak hours for the pre- and post-implementation 

lane operation. Each hour of data collected, plus the previous seven hours collected, were 

averaged to calculate the eight-hour CO average.14 The one-hour CO averages were compared 

for a.m. and p.m. peak hours, for pre- and post-MnPASS lane operation for the same dates that 

noise monitoring was conducted and traffic counts were taken. 

Before and after data on roadway noise levels were collected from field sensors temporarily 

deployed at several strategic locations adjacent to the roadway. The noise data were collected in 

close coordination with several detailed vehicle counts, documenting the number and type of 

vehicles using the roadway. These data were collected prior to the opening of the MnPASS 

lanes to provide an assessment of pre-implementation noise levels. Field noise data was again 

collected after implementation.15

To evaluate and explain specific noise level changes in the a.m. and p.m. peak hours, the 

MINNOISE model was used. The MINNOISE model uses geography, traffic, and vehicle 

speeds as input parameters for the program and is based on the FHWA Traffic Noise Model. 

Sound level differences between measured after and before, and modeled sound level differences 

between after and before were compared and tested for statistically significant changes in noise 

level.16

Environmental justice was examined through the same survey effort that collected data on 

traveler behavior and attitudes. Demographic data including income, education, employment 

status, gender, age and ethnicity were collected. These data allowed researchers to compare 

survey responses pertaining to social equity, traveling experiences, use of the HOT lanes and 

attitudes about MnPASS tolling operations across various demographics. 

Findings 

Findings related to traffic measures consisted of the following:17

 Corridor throughput increased during the peak hour by up to 5 percent. This increase 

occurred while regional volumes in other non-MnPASS corridors observed a decrease. 

 General purpose lane travel speeds were observed to increase at all study locations by an 

average of approximately 6 percent. Travel speeds in the MnPASS lanes either remained 

the same or increased slightly. 

 Average person travel time in the corridor decreased. 

 

14 Jordahl-Larson, Marilyn, et. al. “MnPASS Air & Noise Analysis—Final Draft.” Environmental Modeling and 

Testing Unit, Office of Environmental Services, Minnesota Department of Transportation, Minneapolis, Minnesota. 

October 2005. 

15 Jordahl-Larson, Marilyn, et. al., 2005. 

16 Jordahl-Larson, Marilyn, et. al., 2005. 

17 Cambridge Systematics, Inc., Short-Elliott-Hendrickson, Inc., and LJR, Inc. 2006. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-11 Final Report 

 Significant decreases in the numbers and mode shares of carpools were observed on 

I-394; however, a significant (yet tempered) decrease in carpool usage was similarly 

observed on I-35W, which was not equipped with MnPASS during the same time period, 

suggesting a regional shift in carpool usage. The snapshot nature of the available auto 

occupancy data, significant variations in the day-to-day usage of the lane by HOV users, 

and the change in operating hours between the pre-MnPASS and post-deployment 

periods all served to complicate the precise identification of carpool impacts. Therefore, 

it can neither be confidently proven nor refuted that the decrease on carpool usage on 

I-394 is directly attributable to the deployment of MnPASS as the observed decrease is 

within the margin of error of the analysis. Additionally, user survey results from the 

separately conducted I-394 MnPASS Attitudinal Evaluation did not reveal any changes in 

mode choice reported by corridor carpoolers. 

Findings related to travel behavior performance measures and travelers’ attitudes and opinions 

consisted of the following:18

 Support for the idea of allowing single drivers to use carpool lanes by paying a fee 

remained high one year after implementation. 

 Satisfaction with toll operations remained strong, with minimal levels of dissatisfaction 

voiced by all MnPASS lane users. 

 Traveling experiences of I-394 users have improved since fall 2004 – 71 percent reported 

no congestion delays on their reference trip compared to 62 percent in Wave 1 and 

61 percent of I-35W respondents. 

 The dynamic pricing formula was adjusted in January 2006 resulting in a higher average 

price for peak period users. The formula adjustment also resulted in less price 

fluctuations and more predictability. However, there was subsequently a slight decrease 

in the percentage of MnPASS subscribers who considered the MnPASS toll a good value 

– decreased from 71 percent to 61 percent. 

 The implementation of MnPASS did not have a negative impact on carpooling on I-394, 

nor on traveling experiences in the corridor. The current mode share of I-394 panelists 

was comparable to that captured in the Wave 1 survey: 81 percent drive alone and 

19 percent carpool. 

In regard to air quality, a 0.20 parts per million (ppm) CO one-hour average increase was found 

in the a.m. peak hours at the north monitoring site, with a 0.03 ppm CO decrease in the p.m. peak 

hours. At the south monitoring site a one-hour average increase of 0.29 ppm CO was found 

during a.m. peak hours and a 0.01 ppm increase during the p.m. peak hours. The increases in the 

one-hour average CO levels were considered minimal, and the CO concentrations remained well 

below the 30 ppm one-hour CO air quality standard for the State of Minnesota. It was concluded 

that the operation of the MnPASS lane did not result in a substantial impact on the air quality due 

to any changes in traffic patterns in the project area.19

 

18 Zmud, Johanna. “MnPASS Evaluation Attitudinal Panel Survey Wave 3—Final Report.” Humphrey Institute of 

Public Affairs, University of Minnesota; NuStats, Austin, Texas. August 2006. 

19 Jordahl-Larson, Marilyn, et. al., 2005. 
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Environmental Impact Analyses 2-12 Final Report 

In regard to noise levels, taking all sites into account and averaging the a.m. and p.m. noise level 

measurements, it was found that there was not a statistically significant change in the average 

neighborhood sound pressure level, during the peak hours. The analysis showed instances where 

noise level changes were confidently attributed to changes in traffic patterns due to the MnPASS 

lane; nevertheless, there was not a statistically significant change in average neighborhood sound 

pressure level.20

In regard to environmental justice, the evaluation did not identify any significant correlation 

between demographics and project benefits. It was noted that beneficiaries of the HOT lane 

include a diverse population across all income, age, race/ethnicity, employment, and mode usage 

groups. 

2.5 San Diego Interstate-15 HOT Lanes 

The Congestion Pricing Strategy and Objectives 

Eight miles of HOV lanes on Interstate-15 (I-15) were converted to HOT lanes (opened to 

paying single occupant vehicles) in December 1996. The I-15 HOT lane facility—“FasTrak 

Lanes”—uses a dynamic, real-time tolling structure in which tolls vary with the level of 

congestion in order to maintain free-flow traffic conditions. Fees can vary in 25-cent increments 

as often as every six minutes. All transactions are electronic; overhead antennas read a 

transponder affixed to the inside of a vehicle’s windshield and deduct the toll electronically from 

the driver’s prepaid account.21 Pricing is based on maintaining a Level of Service “C” in the 

HOT lanes. 

Methods 

San Diego State University (SDSU) researchers conducted an independent, multi-element, threeyear (1997-2000) evaluation to assess HOT lane impacts on the I-15 corridor and the San Diego 

region. The research team studied changes in I-15 corridor traffic, travel behavior, and attitudes 

toward the project throughout its duration. A control corridor (a portion of Interstate 8) was used 

for traffic-related analyses in order to help differentiate project-related changes from exogenous 

factors.22

The evaluation was conducted in a series of periodic waves, which generally occurred in the 

spring and fall of each year to avoid interference from the typical seasonal changes in traffic 

patterns. For most of the studies, SDSU conducted five waves of data collection between fall 

1997 and fall 1999. 

 

 

20 Jordahl-Larson, Marilyn, et. al. 2005. 

21 K.T. Analytics and Cambridge Systematics, Inc., 2008. 

22 Supernak, Janusz, et. al. “San Diego’s I-15 Congestion Pricing Project: Traffic-Related Issues.” Transportation 

Research Record, No. 1812, Paper No. 02-4169. Transportation Research Board, National Academies, Washington, 

D.C., 43-52. 2002. 
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Environmental Impact Analyses 2-13 Final Report 

Travel related performance measures consisted of the following: 

 Macroscopic (aggregate), for both study and control corridors 

o Distribution of traffic volumes by lane group during peak periods 

o Speeds 

o Travel time 

o Traffic incidents 

o Toll violations 

o Vehicle classification (type of vehicle, e.g., passenger versus heavy truck) 

o Vehicle occupancy. 

 Microscopic (disaggregate) data on individual travel behavior 

o Demographic characteristics 

o FasTrak use 

o Mode choice 

o Departure time 

o Time savings. 

Before-and-after traffic volume, speed, travel time, toll violations, and vehicle classification data 

were collected from various roadway detectors, including those associated with the HOT lane 

electronic toll collection system. The data on vehicle occupancy were objective—as opposed to 

estimated or modeled—but the specific data collection method was not identified in the literature 

that was reviewed. The source of incident data is unknown. 

Post-deployment travel behavior data were collected through a 5-wave panel survey of three 

groups: HOT lane users, I-15 general purpose lane users (both solo drivers and carpoolers), 

and I-8 (control corridor) travelers. Surveys were conducted between 1997 and 1999. 

Environmental performance measures were restricted to total emissions of volatile organic 

compounds (VOCs), nitrogen oxides (NOx), PM10, and CO. 

Total emissions of each pollutant were calculated as the product of emission factors—derived 

using the California Air Resources Board (CARB) EMission FACtors model (EMFAC)—

multiplied by the number of vehicles and by the length of the corridor segment. Total emissions 

for each peak period along the corridor were determined by aggregating emissions over all I-15 

segments in the corridor for all time periods and all vehicle types. 

Findings 

Travel Behavior 

Overall (all lanes) traffic volume increases along the I-15 corridor were attributed to the 

substantial volume increases in the I-15 express lanes (48 percent) during the 3-year study 

period. The I-15 pricing project alleviated congestion on the I-15 main lanes by redirecting an 

increasing share of volume onto the I-15 express lanes. The study team concluded the increases 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 2-14 Final Report 

in total I-15 corridor volume reflected more the pressures of population and employment growth 

in the travel corridor.23

In the monitoring period, the I-15 corridor experienced a substantial increase in SOV volume and 

a corresponding decrease in HOV volume during the a.m. peak period. The increase in SOV 

volume along the I-15 express lanes was attributed to scheduled program expansion, but could 

also have been a result of strong demographic and socioeconomic pressures in the corridor 

because of relatively high rates of commercial and residential development.24

A decline in HOV main lane volume along I-15 contrasted sharply with an observed rise in HOV 

volume along the I-8 control corridor from 1997 to 1999. The results strongly suggested 

corridor-specific factors, including the I-15 pricing project, were responsible for these 

differences. Unrewarded carpooling on the express lanes may have played a role plus limited 

access to the lanes in the study period, with only one entrance and one exit.25

LOS C, required by law to be maintained at all times on the express lanes, was sustained at 

virtually all times. There was a decrease in variance of volume distribution from fall 1996 to fall 

1997 in the a.m. peak period and a subsequent general increasing trend through fall 1999 in the 

variance of peak-period volume distributions in both a.m. and p.m. peak periods. This result 

strongly suggested that the dynamic pricing structure was able to create desirable redistribution 

of a portion of express-lane traffic from the middle of the peak to the shoulders. Researchers 

were unable to find a sufficient explanation for the HOV portion of the shift to shoulder 

periods.26

Researchers noted a significant increase in express lane use from spring 1998 to spring 1999. 

They concluded that it may have reflected the effectiveness of the shoulder pricing policy 

(further decreased toll prices in the off-peak hours) introduced in August 1998 to distribute 

traffic more evenly throughout the peak period away from the peak hour.27

The dynamic pricing influenced the times at which people traveled. FasTrak customers 

exhibited later departure times than did other I-15 users in all survey waves except for one. 

Researchers also found that 76 percent of FasTrak customers would leave at a different time in 

the morning if there were no FasTrak. The majority of those would leave earlier for work to 

account for the longer and highly unreliable travel times without FasTrak.28

Air Quality 

The SDSU evaluation team reported that data from the fall study waves from 1997 to 1999 

demonstrated that the FasTrak program moderated emission levels along the I-15 corridor during 

a period in which emission levels increased substantially along the I-8 corridor. The average 

relative increases along I-8 were three times larger than the average relative increases along the 

 

23 Supernak, Janusz, et. al. 2002. 

24 Supernak, Janusz, et. al. 2002. 

25Supermak, Janusz, et. al. 2002. 

26Supermak, Janusz, et. al. 2002. 

27Supermak, Janusz, et. al. 2002. 

28Supernak, Janusz, et. al. 2002. 
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Environmental Impact Analyses 2-15 Final Report 

I-15 corridor in the a.m. peak period. In the p.m. peak period, this difference was even greater 

(five times larger). The changes in average emission levels along the I-15 main lanes and 

express lanes over the same period reflected the influence of the FasTrak program in displacing 

traffic from the main lanes to the express lanes. Average emission levels of all four pollutants on 

the express lanes increased substantially from fall 1997 to fall 1999 in both peak periods.29

Since the study was observational in nature, and other potentially influential factors could not be 

controlled or measured precisely, the team could not definitively attribute all observed 

differences in I-15 and I-8 emission profiles to the HOT lane program. However, the effects of 

the corridor-specific factors were more pronounced along I-15 than I-8 and could be expected to 

have increased emission levels along the I-15 corridor. No factors, other than the FasTrak 

program, were identified that could have reduced or mitigated increases in I-15 emission levels.30

2.6 The Stockholm Trial 

The Congestion Pricing Strategy and Objectives 

In January of 2006, the City of Stockholm implemented a cordon/area congestion pricing project 

spanning seven months, known as The Stockholm Trial. The stated goals of the trial were:31

 A 10-15 per cent reduction in the number of vehicles that cross the Inner City segment 

during morning and afternoon rush hours. 

 Improved access on the busiest roads in Stockholm traffic. 

 Reduced emissions of carbon dioxide (CO2), NOx and particles in inner city air. 

 Better street-level environment perceived by people in the inner city. 

The congestion pricing component of the trial was to charge motorists a tax whenever they 

entered Inner City Stockholm. Inner City Stockholm borders or boundaries were defined, and 

were equipped with control points around the charging zone to monitor vehicles entering and 

exiting the zone; the vehicles were identified through photographing the license plates or via 

onboard units. Reducing traffic to improve traffic flow and manage congestion were clear 

expectations of this project. 

An extensive evaluation of the Stockholm Trial was performed using a wide variety of beforeafter data. 

Methods 

The evaluation of the Stockholm Trial included the following travel performance measures: 

 Traffic volumes 

 Vehicle kilometers traveled 

 

29 Supernak, Janusz, et. al. 2002. 

30 Supernak, Janusz, et. al. 2002. 

31 Stockholmsforsoket. “Facts and Results from the Stockholm Trials.” December 2006. 
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Environmental Impact Analyses 2-16 Final Report 

 Journey (travel) times 

 Vehicle queue lengths at intersections 

 Individual traveler behavior (demographics, number of trips, origins-destinations, mode, 

time of travel, travel time) 

 Transit ridership 

 Bus travel times 

 Transit rider perceptions. 

Traffic volumes were collected in the field using various data collection methods. Vehicle 

kilometers traveled were estimated using traffic models. Traffic queue lengths were measured 

with instrumented test vehicles. Journey times data were collected using two methods: 

1) Instrumented vehicles driven by volunteers (50 commuters), and 2) License plate reader 

vehicle matching. 

Individual traveler behavior data were collected through a travel diary (one day) panel study. 

The panel study included three waves of data collection—two before the pricing project and one 

after pricing began. More than 30,000 individuals participated in the panel study. 

Transit ridership and travel times were collected using automated on-board detectors, with the 

exception of ridership on underground rail which was collected manually. Transit rider 

perceptions of the pricing project were gathered through on-board surveys. 

The evaluation of the Stockholm Trial included the following environmental performance 

measures: 

 Total vehicle emissions 

 Pollutant levels 

 Noise levels 

 Environmental justice (equity) 

o Origins and destinations 

o Travel times 

o Congestion charges paid 

o Travel adaptation costs 

o Pricing revenue redistribution impacts. 

Vehicle emissions of PM10, NOx, NO2, CO2, CO, and VOCs were calculated using observed 

traffic data (vehicle kilometers traveled) and model-derived emission factors. Ambient pollutant 

levels were measured using roadside monitors. Estimates of exposure to vehicle-generated 

emissions were made using air quality dispersion models. Noise levels were measured using 

roadside monitors. 

The environmental justice impacts of the Stockholm Trial were evaluated using traveler origindestination data collected through a panel travel diary study conducted in two waves which 

included approximately 24,000 participants, coupled with a regional travel demand model. The 

travel-diary derived information on trip making was fed into a regional travel demand model and 
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Environmental Impact Analyses 2-17 Final Report 

the model was used to estimate the travel times, congestion charges paid, and adaptation costs 

(e.g., switching to transit) associated with the observed (travel diary) trips under both “with 

pricing” and “without pricing” scenarios. The travel diary-derived trip data were also used to 

calculate the impacts of three hypothetical pricing revenue redistribution scenarios: 1) Revenues 

distributed evenly to all county residents, 2) Reduction of transit fares, and 3) Reductions to 

income tax. 

Findings 

Evaluators concluded that the Stockholm Trial was able to manage congestion and increase flow 

and accessibility. The traffic volume in Inner City Stockholm decreased 16 percent in the 

morning and 24 percent in the afternoon and early evening. The sum of distances traveled by 

all motor vehicles (vehicle kilometers traveled) declined 14 percent within the charging zone 

from 2005 to 2006. Journey times decreased by 3 percent. Data on average queue lengths did 

not illuminate clear project impacts. Public transport utilization increased by 6 percent overall 

and by as much as 10 percent during peak hours. Transit customer satisfaction varied by route. 

Satisfaction among passengers on existing routes dropped slightly, from 66 percent to 

61 percent, while 87 percent of passengers on new routes were satisfied32. 

Travel behavior findings included the following: 

 Exogenous factors, including season differences between the before and after travel diary 

data collection and increases in fuel prices preclude a definitive accounting of person trip 

changes. However, car trips across the pricing zone decreased 20 percent and use of 

public transportation has increased. 

 No project-attributable changes in pedestrian or bicycle travel or telecommuting or car 

pooling can be attributed to the pricing projects. 

 Trips to and from work and school across the pricing zone did not decrease. 

 The coordination of carrying out several objectives in a travel chain may have increased 

slightly. 

 A majority of the “cancelled” work and school car trips across the zone have shifted to 

transit. 

Evaluators concluded that decreases in traffic volume and increases in traffic flow from the 

Stockholm Trial impacted air quality and noise. Reductions in VOC, CO, NOX, CO2, and PM10

ranged from 8.5 percent to 14 percent. Monitored noise levels showed minor declines. 

Major findings of the environmental justice evaluation consisted of the following: 

 A few drivers pay the majority of the congestion tax—but the majority pays sometimes. 

 There is great variation in how much congestion tax different people pay. 

 Wealthy men in the inner city pay the most. 

 

32 Stockholmsforsoket. December 2006. 
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Environmental Impact Analyses 2-18 Final Report 

 Residents of the inner city and Lidingo experience the greatest net loss per person when 

taking into account direct traffic effects (travel time, congestion tax and adaptation costs). 

 High income earners are affected more than low income earners. 

 The key to total cost-benefit effects is how charging revenues are redistributed. 

 Commercial traffic and business trips are “net winners” even before charging revenue 

redistribution is taken into consideration. 

Researchers identified a number of exogenous factors that probably significantly impacted 

evaluation findings, including increases in fuel prices, seasonal variation, weather conditions 

which impacted monitored air quality, and other transportation projects. These factors could not 

be controlled; however, when possible the evaluators attempted to isolate the effect of exogenous 

factors by comparing different monitoring occasions and different areas.33

2.7 Central London Congestion Charging 

The Congestion Pricing Strategy and Objectives 

London launched a cordon road pricing project focusing on Central London in February 2003 

and the charging zone has since been expanded—the “Western Extension.” The objective of this 

project was to reduce traffic, improve the speed of buses, create revenue, and improve quality of 

life.34 Motorists pay a standard, flat rate to drive cars within the congestion charging zone. The 

rates did not vary per location and after paying the vehicles can exit and enter as many times as 

desired. Charges are applied on weekdays from 7:00 a.m. to 6:30 p.m. Congestion charges are 

paid in advance or on the day of travel by telephone, regular mail, Internet or at retail outlets. 

There are no toll booths or other roadside payment infrastructure. To enforce and monitor the 

payments the system made use of networked video cameras (automatic license plate recognition) 

to record license plate numbers, then matched the license plate numbers to a paid list.35 Over the 

years, many aspects of the charging program have been modified, including increases in the daily 

charge. 

The London congestion charging projects have been rather extensively studied. These studies 

have included before-after evaluations of a variety of travel and environmental impacts. 

Methods 

The organization Transport for London has conducted a long-term and on-going evaluation of 

the London congestion charging initiative. Six annual reports on the monitoring efforts have 

been published to date, with the first report in 2003 describing baseline (pre-pricing) 

conditions.36 Although many evaluation methods have remained the same over time and as the 

 

33 Stockholmforsoket. “Evaluation of the Effects of the Stockholm Trial on Road Traffic.” June 2006. 

34 United States Department of Transportation, Federal Highway Administration. “Lessons Learned from 

International Experience in Congestion Pricing.” Prepared by K.T. Analytics. August 2008. 35 Litman, Todd. “London Congestion Pricing: Implications for Other Cities.” Victoria Transport Policy Institute. 

January 2006.

36 Transport for London, “Central London Congestion Charging – Impacts Monitoring, First Annual Report,” Mayor 

of London, 2003. 
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Environmental Impact Analyses 2-19 Final Report 

pricing was extended westward, some methods have evolved over time or have been applied 

only to the central London or Western Extension studies. Of course, different findings have 

emerged from the various studies. This summary endeavors to present a composite view of all 

of the travel and environmental impact evaluation methodologies that have been applied. 

Travel Impacts 

The London congestion pricing evaluations have included before and after measurement of the 

following travel-related performance measures: 

 Congestion (the “excess delay” or “lost travel time” defined as the difference between 

average network travel rates in uncongested versus congested conditions) 

 Average network speeds (vehicle kilometers divided by vehicle hours) 

 Average network travel rate (vehicle minutes divided by vehicle kilometers) 

 Speed distributions (the proportion of time spent driving within various speed bands) 

 Traffic density (number of vehicles per kilometer) 

 Number of vehicle trips 

 Journey (travel) times 

 Traffic volumes 

 Vehicle kilometers driven 

 Vehicle minutes driven 

 Average vehicle occupancy 

 Transit ridership 

 Average bus journey speeds 

 Mode of travel 

 Road traffic accidents 

 Parking and pedestrian activity 

 Number and type of roadway crashes 

 Bus reliability – passengers excess waiting time (difference between scheduled and actual 

bus arrival) 

 Bus reliability – operated mileage versus scheduled mileage (congestion can result in a 

bus covering fewer miles, completing fewer runs than scheduled). 

Over the years, a wide variety of data collection methods have been used to collect these various 

performance measures, with multiple data collection methods often used to collect the same 

performance measures. The vast majority of data for travel-related performance measures has 

been collected directly, either in the field using various detectors and manual methods or with 

surveys and interviews with travelers and other stakeholders. Although travel demand modeling 
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Environmental Impact Analyses 2-20 Final Report 

has been used to complement observed traffic data, very few of the travel-related performance 

measures have been derived solely through modeling or simulation. 

Data collection methods utilized for travel-related performance measures have included the 

following: 

 Instrumented floating car runs, license plate matching, and commercially purchased 

satellite vehicle tracking to collect vehicle speed/travel rate data 

 Volunteer, general public driver panels (100 participants) to collect journey time and 

route choice data 

 Various manual and automatic counting methods for traffic volume data 

 Visual observation to collect vehicle occupancy data 

 Calculation of vehicle kilometers traveled using traffic volumes and roadway lengths 

 Automated vehicle location systems for bus travel speeds and times 

 Bus station manual schedule adherence observations 

 Bus operating statistics to determine the amount of service delivered 

 Manual, on-board monitoring to collect bus delay data 

 Manual counts and fare collection data for transit ridership 

 Case studies with parking authorities to collect parking data 

 Manual counting of pedestrian volumes 

 Accident reports for data on the type and number of crashes. 

In addition, a wide variety of surveys, interviews and focus groups have been conducted to 

collect attitudinal, general travel behavior, and detailed (travel diary) travel behavior. Evaluation 

of the London congestion pricing scheme has featured the most extensive and sophisticated use 

of surveys, interviews and focus groups of all of the projects that have been reviewed as part of 

this study. These efforts are distinguished in the following respects: 

 The sheer number of different types of surveys, interviews and focus groups—both at any 

one time and cumulatively over the course of more than five years. 

 The variety of methods that have been used, including household as well as individual 

surveys; in-person as well as telephone survey administration; roadside recruitment as 

well as use of various databases and “snowball” sampling recruitment of hard to reach 

populations through coordination with “trusted organizations;” and general travel 

behavior/attitudinal surveys as well as detailed travel diaries. 

 An emphasis on the household as the unit of analysis and extensive use of household 

surveys—in which each adult member of the household participates—as a means to pick 

up on travel changes and trade-offs within households, such the question of how a vehicle 

is used that was formerly used by someone in the household to drive who is now, because 

of the congestion charge, taking transit. 
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Environmental Impact Analyses 2-21 Final Report 

 The extensive use of longitudinal, or panel surveys which survey the same specific 

people in successive waves before and after project implementation. 

 The extent of special, targeted efforts to reach traditionally under-represented or 

unrepresented populations such as disabled individuals, pedestrians, bicyclists and shift 

workers. 

Specific survey, interview and focus group activities used to collect travel behavior and 

attitudinal travel-related performance measures have included: 

 Household panel surveys of up to 2,300 households 

 Panel surveys of up to 2,400 individual travelers 

 En-route (at the destination stop) transit surveys to gauge attitudes (e.g., satisfaction) and 

general travel behavior (e.g., reason for mode choice) 

 Roadside traveler interviews with 15,000 or more participants 

 Focus groups, typically part of “special inquiries” targeting populations that are typically 

under-represented in general traveler or household surveys. 

Environmental Impacts 

Evaluations of Central London Congestion Charging have included before and after 

measurement of the following environmental impacts: 

 Total vehicle emissions (one component of a regional, all-source/all-pollutants inventory) 

of NO2, NOx, PM10, and CO2

 Pollutant levels (monitored) 

 Noise levels 

 Environmental justice (within a broader investigation of “social impacts”). 

Many data collection and analysis methods have changed over time, but cumulatively, the 

following methods have been used: 

 Calculation (estimation) of vehicle emissions using observed roadway link-level traffic 

data (volumes, speeds, vehicle types) multiplied by model-derived emission rates 

 Roadside monitoring of ambient pollutant levels 

 Roadside monitoring of ambient noise levels 

 Assessment of impacts and attitudes among various socio-economic groups 

(environmental justice) using surveys, interviews and focus groups. 

The methodology used to calculate emissions was compatible with the approach used in the 

Mayor of London’s Air Quality Strategy.37 The emissions estimation approach included 

breaking down vehicle emissions by specific traffic variable, e.g., traffic volume, speed changes 

 

37 Transport for London. 2003. 
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Environmental Impact Analyses 2-22 Final Report 

and emission rates (reflecting changes in vehicle fleet mix and emissions technology changes). 

This approach was not evidenced in any of the other study projects. From the beginning, 

monitored pollutant levels were not expected to reveal impacts that could be traced specifically 

to the congestion charging scheme, but were performed regardless. 

Original plans included both modeling and monitoring noise levels. Noise modeling was 

planned to utilize travel flow, composition, and speed to produce noise mapping and generate 

noise predictions. However, no results of any modeling efforts were located in the literature, 

which may indicate that only monitoring was performed. 

The consideration of environmental justice issues was conducted within the broader assessment 

of “social impacts”—the comprehensive assessment of the impact of the pricing on people’s 

attitudes, perceptions, and abilities. This analysis did consider differences among different 

income groups but income and race were not as central of a focus as is sometimes found in U.S. 

studies. Rather, the London analysis has focused on user groups defined by other criteria, such 

as transit users, people living outside the charging zone, the disabled, people lacking 

automobiles, and shift workers. Most of the data pertaining to these issues were collected 

through surveys, interviews and focus groups. Although general traveler/household surveys 

included demographic data allowing results to be sorted by various characteristics relevant to 

environmental justice, a number of special surveys and focus groups were conducted focusing 

specifically on user groups of interest. 

Findings 

A tremendous volume of evaluation results has been published over the course of six annual 

monitoring reports and numerous additional studies. Overall, the latest annual report (published 

in July 2008) concludes that congestion charging continues to meet its fundamental traffic and 

transport objectives and that the scheme continues to deliver congestion reduction generally 

equal to the 30 percent reduction achieved in the first year.38 The same report cites results from 

the Fifth Annual Report stating that, given the influence of many non-project related factors, it 

can be misleading to compare recent congestion levels (2006 data) to pre-charging levels but that 

nevertheless, such a comparison shows 2006 congestion levels to be 8 percent lower than precharging levels. The Fifth Annual Report (published in 2007) elaborates that charging has 

accentuated positive trends such as reduced accidents and emissions while mitigating negative 

trends like increasing congestion.39

Additional specific travel findings as well as environmental findings are summarized below. The 

specific findings that follow are adapted primarily from the two most recent annual reports—the 

fifth and sixth. 

 

38 Transport for London, “Central London Congestion Charging – Impacts Monitoring, Sixth Annual Report,” 

Mayor of London, July 2008. 

39 Transport for London, “Central London Congestion Charging – Impacts Monitoring, Fifth Annual Report,” Mayor 

of London, July 2007. 
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Environmental Impact Analyses 2-23 Final Report 

Travel Impacts 

After the first year of the project in the Central London charging zone, VKT decreased by 

15 percent for vehicles with four wheels or more and the number of vehicles entering the zone 

declined by 18 percent. A 14 percent decrease occurred in journey times. The average network 

speeds in 2003 were 14 kilometers per hour (9 miles per hour), which increased to 17 kilometers 

per hour (11 miles per hour) in 2006.40 Research found that in the beginning of the congestion 

pricing project the traffic volume reductions were significant and as the congestion pricing 

continued the reductions in traffic volume also continued, but at a slower rate. Overall, the 

charging zones that began in 2003 and continued through 2006 led to 21 percent less traffic 

entering the zones. 

In the Western Extension zone traffic volume decreased by 14 percent compared with precharging conditions in 2005-2006. Also an 11 percent decrease in VKT for vehicles with four 

wheels or more was reported. Average network speeds and journey time results for the Western 

Extension were not clearly represented. The volume of commuter trips increased 33 to 

38 percent.41

Examinations of mode split—the percentage of trips made by the various modes, including 

driving, public transportation and elimination of the trip entirely—were conducted in support of 

the second annual monitoring report which reported the first post-deployment year findings 

related to the central charging zone, and the sixth annual monitoring report, which reported 

results pertaining to the Western Extension of the pricing zone. Overall, the results suggest that 

the charging scheme has prompted significant shifting from driving to alternate modes, primarily 

bus transit. 

The early results for the central zone showed that 65,000 to 70,000 car trips no longer cross into 

the charging zone and estimated the displacement of those trips as follows:42

 50-60 percent shifted to public transportation (slightly more to rail than to bus) 

 20-30 percent kept driving but diverted around the charging zone 

 8-10 percent shifted to bicycle, motorcycle, walking or taxi 

 Less than 1 percent (less than 5,000 trips) shifted their car trips to outside of the charging 

hours 

 Less than 1 percent (less than 5,000 trips) eliminated trips (reduced travel frequency). 

 

 

40 Transport for London, 2007.

41 Transport for London, 2008. 

42 Transport for London, 2003. 
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Environmental Impact Analyses 2-24 Final Report 

The results for the Western Extension show that 32 percent of sampled drivers changed their 

behavior in response to the charge.43 Among that group that changed their behavior, the 

breakdown of specific changes was as follows: 

 38 percent changed to an alternative mode 

 28 percent chose not to make the trip at all 

 34 percent made other choices, such as changing the time, route or destination of trip. 

Examples of findings related to public transportation usage include the following: 

 Passengers entering the central charging zone by bus increased 37 percent during 

charging hours during the first year of charging; up to half of that increase was attributed 

to pricing. 

 Bus service reliability improved on routes in and around the charging zone; excess wait 

time fell by 30 percent the first year and an additional 18 percent the second year. 

 Bus kilometers not operated because of traffic congestion fell by 20 percent the first year. 

Environmental Impacts 

As anticipated, it has not been possible to distinguish project impacts from the impacts of 

exogenous factors in the monitored air quality results. However, results of the emissions 

calculations indicate that the project has contributed to emissions reductions. In Central London 

the overall traffic emissions change between 2002 and 2003 included a decrease in NOx of 

13.4 percent, a decrease in PM10 of 15.5 percent, and a decrease in CO2 of 16.4 percent. The 

Western Extension results comparing 2006 to 2007 also showed a decrease of 2.5 percent in 

NOx, a decrease of 4.2 percent in PM10, and a decrease of 6.5 percent in CO2 based on combined 

traffic volumes and composition change.44

Early noise results—changes from the baseline (2002) observed in the first year of postdeployment (2003) were small and considered imperceptible in typical urban conditions. No 

project-related impacts on noise were identified. The fourth annual report noted that “Limited 

sample surveys of ambient noise in and around the charging zone continue to suggest the 

absence of a detectable congestion charging impact.” Later reports do not contain any additional 

new noise findings. 

The various results related to environmental justice issues—the impact of the charging scheme 

on various types of people—do not identify broad, significant adverse impacts but do note some 

concerns. Explicit, prominent identification of “winners” and “losers” are not at all prominent in 

the Transport for London annual reports. This passage from the sixth annual report which 

focuses on the Western Extension is typical of the sorts of summations found in the Transport for 

London annual reports: 

 

 

43 Transport for London, 2008. 

44 Transport for London, 2007.
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Environmental Impact Analyses 2-25 Final Report 

“Overall, the evidence suggests that most London residents have been able to 

adapt to the introduction of charging in the Western Extension without any 

detriment to their quality of life, although some concerns remain about the impact 

of charging on the social interaction of vulnerable groups.”45

Examples of specific reported findings include the following: 

 Actual impacts of the scheme on individuals were generally less than expected by the 

same respondents. 

 Transportation issues that respondents felt most negatively about, such as a lack of 

parking spaces, were generally not related to the pricing scheme. 

 The majority of all respondents felt that the charge was affordable, although—despite the 

discount they received—more residents inside the charging zone found it difficult to 

afford. 

2.8 Singapore Area Pricing 

The Congestion Pricing Strategy and Objectives 

Singapore first implemented cordon congestion pricing in 1975 in order to better manage traffic 

and to reduce vehicle emissions. The initial pricing project was an Area Licensing Scheme in 

which vehicles were charged a fee for entering a 2.0-mile square central business area during the 

a.m. commute period. Vehicles entering the priced zone along any of 28 entry points were 

required to display a pre-purchased daily or monthly windshield license. Transit buses, 

motorcycles and vehicles carrying more than 4 people (high occupancy vehicle [HOV] 4+) were 

excluded from the charge. That initial scheme evolved through the late 1990’s, including 

extension of the charging periods, increases in the charges, and, by virtue of expansion of price 

points to roadways outside the central business area, evolution to an area-wide pricing scheme. 

In 1998, the system was converted to a fully automated, electronic system whereby charges are 

collected using vehicle transponders with smart cards, dedicated short-range communication 

(DSRC), and readers mounted on overhead gantries. 

Methodology 

No detailed information on evaluation methods was found in the published literature. Although 

general in nature, the bulk of the best information is found in the FHWA report “Lessons 

Learned from International Experience in Congestion Pricing.”46 That report summarizes 

various evaluations of the Singapore congestion pricing activities and indicates that the following 

travel performance measures have been investigated: 

 Traffic volumes 

 Mode share (HOV 4+, vehicles less than HOV 4+, bus) 

 Trip departure times 

 Routes 

 

45 Transport for London, 2008. Pg. 7. 

46 K.T. Analytics, 2008. 
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Environmental Impact Analyses 2-26 Final Report 

 Average speeds 

 Crashes. 

There is no specific information available on data collection, but based on the discussion of 

impacts, it appears that most of the performance measures were analyzed based on objective, 

observed data, e.g., traffic volumes and speeds derived from various detector data and traffic 

crashes based on police reports. It appears that at least some of the data, especially mode share 

information, were collected via traveler surveys. 

Environmental impacts considered in the Singapore evaluations include: 

 Vehicle emissions (CO, NOx, and smoke/haze) 

 Pedestrian safety 

 Equity. 

Analysis of vehicle emissions has included both roadside monitoring as well as calculation of 

emissions based on travel impacts. Perceived pedestrian safety was evidently assessed through 

the use of surveys. Equity implications were assessed via a modeling analysis and surveys of 

travelers. It appears that the modeling analysis utilized the geographic distribution of various 

travel impacts coupled with geographic socioeconomic data to infer how travel impacts 

distributed across various impact groups. In addition, equity implications—specifically, various 

types of travelers’ perceptions of and responses to congestion pricing—were assessed through 

surveys. 

Although published literature does not explicitly identify how exogenous factors were 

considered in the various evaluations of the Singapore congestion pricing projects, various 

summaries of project impacts include references to several types of exogenous factors. These 

factors include auto ownership and employment. 

Findings 

Overall, the Singapore congestion pricing projects have been effective in reducing congestion 

and vehicle emissions and are generally not believed to have significantly and disproportionately 

negatively impacted lower income populations. The initial system introduced in 1975 reduced 

traffic volumes entering the priced zone by 44 percent; the share of HOV 4+ trips increased from 

8 to 19 percent and bus share increased from 33 to 46 percent; a.m. peak speeds inside the priced 

zone increased by 20 percent or more; and speeds increased 10 percent on inbound roadways 

leading to the priced zone.47 Other travel responses to the initial system included motorists 

shifting their trips to just before or after the priced time periods and diversion of trips to 

alternate, non-priced routes.48 

Immediately following the introduction of the initial pricing project, measured CO levels in the 

morning peak period within the priced zone declined to below pre-project levels and monthly 

average NOx levels also decreased. These reductions were attributed to the large reduction in 

 

47 K.T. Analytics, 2008. 

48 Toh, Rex S. (2003), “Road Congestion Pricing in Singapore: 1975 to 2003.” Transportation Journal, March 22, 

2004. 
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Environmental Impact Analyses 2-27 Final Report 

automobile travel. Measurements of smoke and haze also showed declines but those declines 

could not be fully attributed to the pricing project.49

 Reported equity impacts include the following:50

 “Losers” associated with the initial project included those who switched from cars to 

buses or switched to non-priced travel time periods, those who encountered congestion 

on non-priced routes, and those for whom the cost of the charge is not fully offset by 

improved travel times. 

 After some initial crowding, transit riders enjoyed better service as service was expanded 

over time. 

 HOV 4+, motorists and pedestrians benefitted. 

 Car drivers and passengers perceived the initial project as mildly unfavorable; middle 

income travelers felt adversely effected; pedestrians, taxi riders and residents outside of 

the priced zone viewed the initial project as neural or negatively; travelers and residents 

within the priced zone viewed the initial project positively. 

 Shifts to transit were fairly uniform across income groups. 

 There was no evidence that any given income groups was more or less impacted by travel 

time changes. 

 

49 K.T. Analytics, 2008. 

50 K.T. Analytics, 2008. 
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Environmental Impact Analyses 3-1 Final Report 

3.0 SYNTHESIS OF THE STATE OF THE PRACTICE 

This chapter summarizes the state of the practice for evaluating the travel and environmental 

impacts of congestion pricing projects. The findings presented here are drawn primarily from a 

review of published literature associated with the eight study projects described in Chapter 2.0. 

This chapter is divided into three sections. The first highlights some of the fundamental 

differences and similarities in the evaluation approaches among the eight study projects. The 

second section focuses on travel impacts. The final section focuses on environmental impacts. 

3.1 Basic Similarities and Differences between Study Projects 

All eight of the study projects include before-after (or “with/without”) evaluations of deployed 

congestion pricing schemes: either short-term demonstrations with simulated congestion charges 

or long-term deployments with real charges. The Oregon, Puget Sound and Commute Atlanta 

mileage-based value pricing investigation are examples of the former (short-term, simulated) and 

the other five projects are of the latter type (long-term, non-simulated). 

Two of the projects—London and Singapore—have been evaluated in an on-going manner over 

many years, encompassing a number of expansions and other changes in the congestion pricing 

programs. Those projects, to varying extents, have produced a series of results reports which 

include comparisons and which draw conclusions based on many years of post-deployment data. 

The six other projects generally focus on shorter, finite, post-deployment evaluation periods of 

between a few months and, in the case of I-15, up to three years. Although the Minnesota I-394 

HOT lanes project is subject to on-going monitoring, the comprehensive evaluation effort was, 

essentially, a one-time effort. 

London demonstrates the most extensive evaluation effort among the study projects in terms of 

evaluation period (over five years) and the breadth of impacts, performance measures and data 

sources. The next most extensively studied projects are Stockholm and Singapore. 

The simulated pricing field deployment projects—Oregon, Puget Sound and Commute Atlanta—

focused more narrowly on individual traveler behavior than the other projects, that is, they did 

not consider the traffic or environmental ramifications of changes in travel behavior. Further, to 

varying degrees (Commute Atlanta less so), those three projects focused more narrowly on 

driving behavior and associated measures and less on other modes than did the other study 

projects. 

3.2 Assessing Travel Impacts 

This section contains two parts. The first summarizes travel impacts, performance measures and 

data collection methods and the second part summarizes travel findings and study limitations. 

3.2.1 Impacts, Performance Measures and Data Collection Methods 

Table 3-1 compiles the travel impacts, performance measures and associated data collection 

methods for each of the eight study projects. Among those projects, three broad types of travel 

impacts were found most commonly:
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Environmental Impact Analyses 3-2 Final Report 

 Traffic impacts – the impact on roadway usage, e.g., traffic volumes, and/or roadway 

performance, e.g., speeds and collisions. 

 Transit impacts – the impact on transit system usage, e.g., ridership and/or transit 

performance, e.g., schedule adherence. 

 Traveler behavior impacts – the impact on the behavior of travelers, e.g., routes, 

modes, time of trip. 

The travel impact most commonly considered in the eight study projects is traffic. Transit and 

traveler behavior impacts are less common, but far from unusual. Few study projects examined 

safety impacts. 

Table 3-1. Travel Impacts, Measures and Data Collection Methods 

Study/Project Impacts 

Analyzed 

Associated Performance 

Measures Data Collection Method 

Simulated Pricing Field Demonstrations 

Oregon 

Mileage Fee 

Concept and 

Road User Fee 

Pilot Program 

Traveler 

behavior 

(individual) 

 Vehicle miles traveled 

 Vehicle miles traveled by time-ofday (peak vs. off-peak) 

 Route choice 

 Number of trips 

 Demographics 

 Instrumented vehicles 

(GPS) driven by 

volunteer, general public 

travelers 

 Mode choice – stated inclination 

to use alternate modes (transit, 

bicycle) 

 Traveler surveys 

(attitudinal) 

Puget Sound 

Traffic Choices 

Study 

Traveler 

behavior 

(individual) 

 Vehicle miles traveled by road 

type 

 Vehicle hours of travel 

 Number of trips 

 Route choice 

 Trip purpose 

 Demographics 

 Instrumented vehicles 

(GPS) driven by 

volunteer, general public 

travelers 

Commute 

Atlanta 

Mileage Based 

Value Pricing 

Demonstration 

Traveler 

behavior 

(household) 

 Number of trips 

 Trip lengths 

 Trip duration 

 Intra- vs. extra-regional trip 

making 

 Demographics 

 Instrumented vehicles 

driven by general public 

travelers 

 Panel survey of the 

participating travelers 

Traffic  Total vehicle miles traveled 

 Instrumented vehicles 

driven by volunteer 

general public travelers 
Table 3-1. Travel Impacts, Measures and Data Collection Methods (Continued) 

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Environmental Impact Analyses 3-3 Final Report 

Study/Project Impacts 

Analyzed 

Associated Performance 

Measures Data Collection Method 

Before-After Project Evaluations – U.S. 

Minnesota I394 MnPASS 

HOT Lanes 

Traffic 

 Hourly traffic volumes by lane 

 Average vehicle speed by lane 

group (general purpose and HOT) 

 Travel time 

 Permanent roadway 

detectors 

Traveler 

behavior 

(individual) 

 Vehicle occupancy 

 Number of carpools 

 Mode choice (transit use) 

 Demographics 

 Traveler surveys 

(attitudinal) – panel – 800-

900 per wave 

 Travel diaries (1-day) with 

general travel behavior 

questions – 800-900 

participants 

San Diego I-15 

HOT Lanes 

Traffic 

 Traffic volumes 

 Time-of-peak distribution 

 Average speed 

 Vehicle classification 

 Roadway detectors 

 Vehicle occupancy  Unknown 

Safety  Incidents  Unknown 

Traveler 

behavior 

(individual) 

 Mode split 

 Traveler surveys 

(attitudinal) – panel – 

1,500 respondents per 

wave 
Table 3-1. Travel Impacts, Measures and Data Collection Methods (Continued) 

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Environmental Impact Analyses 3-4 Final Report 

Study/Project Impacts 

Analyzed 

Associated Performance 

Measures Data Collection Method 

Before-After Project Evaluations – International 

The Stockholm 

Trial 

Traffic 

 Traffic volumes 

 Objective data collection 

in the field (various 

methods used) 

 Vehicle kilometers traveled  Estimated using traffic 

models 

 Journey (travel) times 

 Instrumented vehicles 

(GPS) 

 Roadside detectors (traffic 

cameras used to match 

vehicle images at various 

points) 

 Vehicle queue lengths at 

intersections 

 Instrumented vehicle field 

data collection 

Traveler 

behavior 

(individual) 

 Demographics 

 Number of trips 

 Origin-destination 

 Mode 

 Time of travel 

 Travel time 

 (Stockholm County 

residents) Travel diaries 

(1 day) – panel study in 3 

waves (2 pre- and 1 post) 

– 30,000+ participants 

 (Commuters into pricing 

zone) – subset of County 

residents survey – 2,200 

participants 

 Demographics 

 Number of trips 

 Mode choice 

 Potentially other measures 

unspecified in literature 

 (Other County Residents) 

875 participants – study 

methodology unknown 

Transit 

 Ridership  Detectors  Travel times 

 Rider perceptions  On-board surveys 
Table 3-1. Travel Impacts, Measures and Data Collection Methods (Continued) 

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Environmental Impact Analyses 3-5 Final Report 

Study/Project Impacts 

Analyzed 

Associated Performance 

Measures Data Collection Method 

Before-After Project Evaluations – International (Continued) 

Central 

London 

Congestion 

Pricing 

Traffic 

 Congestion (the “excess delay” or 

“lost travel time” as defined as the 

difference between average 

network travel rates in 

uncongested versus congested 

conditions) 

 Calculated from other 

data 

 Average network speeds (vehicle 

kilometers divided by vehicle 

hours)  Instrumented floating car 

runs 

 Automated license plate 

matching (cameras) 

 Commercially purchased 

satellite vehicle tracking 

 Average network travel rate 

(vehicle minutes divided by 

vehicle kilometers) 

 Speed distributions (the 

proportion of time spent driving 

within various speed bands) 

 Traffic density (number of 

vehicles per kilometer) 

 Derived from traffic 

volume data 

 Number of vehicle trips 

 Derived from traffic 

volume data (may also 

have been measured 

through traveler surveys) 

 Journey (travel) times 

 Volunteer, general public 

driver panels (manual 

recording of times) 

 Traffic volumes 

 Various manual and 

automated (roadway 

detectors) methods 

 Vehicle kilometers driven  Derived from traffic 

volumes 

 Vehicle minutes driven 

 Derived from traffic 

volume and congestion 

data 

 Average vehicle occupancy  Visual observation 

 Parking and pedestrian activity  Manual counts 
Table 3-1. Travel Impacts, Measures and Data Collection Methods (Continued) 

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Environmental Impact Analyses 3-6 Final Report 

Study/Project Impacts 

Analyzed 

Associated Performance 

Measures Data Collection Method 

Before-After Project Evaluations – International (Continued) 

Central 

London 

Congestion 

Pricing (Cont.) 

Transit 

 Transit ridership  Manual counts 

 Fare collection data 

 Average bus journey speeds  Automatic vehicle location 

systems 

 Bus reliability – passengers 

excess waiting time (difference 

between scheduled and actual 

bus arrival) 

 Manual schedule 

adherence monitoring at 

bus stops/stations 

 Bus reliability – operated mileage 

versus scheduled mileage 

(congestion can result in a bus 

covering fewer miles, completing 

fewer runs than scheduled) 

 Transit agency databases 

Traveler 

behavior 

(household) 

 General travel behavior (modes, 

routes, times, etc.) 

 Panel surveys of up to 

2,300 households 

 Detailed travel behavior (modes, 

routes, times, etc.) 

 Panel surveys of up to 

2,300 households with 

1-day travel diaries 

Traveler 

behavior 

(individual) 

 General travel behavior (modes, 

routes, times, etc.) 

 Panel surveys of up to 

2,400 individuals 

 En-route transit rider 

surveys 

 Roadside interviews with 

up to 15,000 travelers 

(driving, cycling, walking) 

 Focus groups (generally 

targeting subpopulations 

like disabled people or 

shift workers) 

 Detailed travel behavior (modes, 

routes, times, etc.) 

 Panel surveys of up to 

2,400 individuals with 

1-day travel diaries 

Safety  Number and type of roadway 

crashes  Accident reports 

Singapore 

Area Pricing 

Traffic 

 Traffic volumes 

 Trip departure time 

 Average speed 

 Unknown, but likely that 

most data were objective 

data, e.g., traffic counts 

Traveler 

behavior 

 Routes 

 Modes  Unknown 

Safety  Number of crashes  Unknown, likely accident 

reports 
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Environmental Impact Analyses 3-7 Final Report 

Tables 3-2 through 3-4 summarize the state-of-the-practice for travel impacts in terms of the 

relative prevalence of various performance measures and associated data collection methods. 

This information is based primarily on the eight study projects. Greater variety was found in the 

area of traffic impacts than in transit and traveler behavior and therefore Table 3-2 uses three 

categories to assess prevalence and Tables 3-3 and 3-4 use only two. Assessments of the relative 

rarity of various measures are subjective and there are a few close calls. For example, 

categorizing travel times and speeds as “very common” versus “common.” Assessments for the 

performance measures are absolute in the sense that they reflect how commonly each measure 

appears in the evaluation reports that were reviewed. Assessments of methods are relative in the 

sense that they do not describe how often a particular data collection method appears in the 

literature overall, but rather, how frequently that method is used among those projects that 

include the associated performance measure. For example, a “very common” data collection 

method for an “uncommon” measure means that, in the literature overall, that data collection 

method is not common. 

Table 3-2. Traffic Impact Performance Measures and Data Collection Methods 

Performance 

Measures 

Associated Data Collection Methods (by prevalence) 

Very Common Common Less Common 

Very Common 

Traffic volumes 

 Permanent vehicle 

detectors (loops, radar, 

cameras, etc.) 

 Temporary vehicle 

detectors (radar, 

cameras, etc.) 

 Manual counts (visual 

observation) 

 Probe vehicles driven by 

travelers (e.g., toll tagequipped) 

Vehicle miles 

traveled 

 Derived from traffic 

volumes and roadway 

segment lengths 

 Probe vehicles driven by 

travelers 

Average speeds 

 Permanent vehicle 

detectors (loops, radar, 

cameras, etc.) 

 Temporary vehicle 

detectors (radar, 

cameras, etc.) 

 Probe vehicles driven by 

travelers 

 Probe vehicles driven by 

evaluators (i.e., “floating 

car”) 

Common 

Travel time 

 Probe vehicles driven 

by evaluators (i.e., 

“floating car”) 

 Vehicle detectors 

(loops, radar, cameras, 

etc.) 

 Probe vehicles driven by 

travelers 

Vehicle 

classification1

 Permanent vehicle 

detectors (loops, radar, 

cameras, etc.) 

 Temporary vehicle 

detectors (radar, 

cameras, etc.) 

 Manual counts (visual 

observation) 
Table 3-2. Traffic Impact Performance Measures and Data Collection Methods 

(Continued) 

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Environmental Impact Analyses 3-8 Final Report 

Performance 

Measures 

Associated Data Collection Methods (by prevalence) 

Very Common Common Less Common 

Less Common 

Vehicle 

occupancy 

 Manual counts (visual 

observation) 

Mode split2

 Derived from traffic 

counts coupled with 

average vehicle 

occupancy; transit 

passenger counts & 

other mode (bike, walk) 

 

Travel rate 

(distance 

per hour or 

minute) 

 Derived from other data, 

namely volumes, 

speeds, roadway link 

lengths 

 

Traffic density  Derived from traffic 

volume data 

Vehicle minutes 

or hours driven 

 Derived from vehicle 

miles driven and speeds 

Number of 

accidents or 

accident rates 

 Accident 

reports/databases 

Traveler and/or 

system operator 

perceptions of 

safety 

 Surveys, interviews or 

focus groups 

Notes: 

1

 Rare as an end measure, commonly collected to support environmental analysis (an input to emission rates) 2

 This measure appears both as a traffic impact measure as well as a traveler behavior impact measure (Table 3-4) to 

reflect the two different approaches to collecting these data (counts for traffic vs. surveys for travel behavior) and 

the different focus in traffic analysis (impact, e.g., person throughput, on roadways) versus travel behavior (impact 

on people). 
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Environmental Impact Analyses 3-9 Final Report 

Table 3-3. Transit Performance Measures and Data Collection Methods 

Performance Measures Associated Data Collection Methods (by prevalence) 

More Common Less Common 

Common 

Ridership  Automated passenger counters 

 Manual passenger counters 

Less Common 

Travel time  Automatic vehicle location systems 

Rider attitudes & 

perceptions  En-route surveys 

Bus speeds  Automatic vehicle location systems 

Bus schedule 

adherence: on-time 

performance 

 Automatic vehicle location systems  Visual observation in the field 

Bus schedule adherence 

– operated mileage 

 Transit agency vehicle operations 

database 

Table 3-4. Traveler Behavior Impact Performance Measures and Data Collection Methods 

Performance Measures Associated Data Collection Methods (by prevalence) 

More Common Less Common 

Common 

Individual, general travel behavior 

(typical routes, modes, time of trip, etc.)  Panel surveys (same 

sample before-after) 

 Cross-sectional surveys 

(different samples beforeafter) Individual traveler attitudes & 

perceptions 

Less Common 

Individual, specific travel behavior 

(routes, modes, etc. on specific sample 

day[s])  Panel travel diary (same 

people before-after) 

 Cross-sectional travel 

diary (different people 

before-after) Household, specific travel behavior 

(routes, modes, etc. on specific sample 

day[s]) 

Household, general traveler behavior 

(typical routes, modes, time of trip, etc.) 

 Panel surveys (same 

people before-after) 

 Cross-sectional surveys 

(different people beforeafter) 

Mode choice/mode split  Derived from household or 

individual travel diary data 

 Derived from household 

or individual general travel 

survey data 

As indicated in Tables 3-2 through 3-4, and as one would expect with evaluations of deployed 

projects, all of the traffic and transit measures utilize objective data rather than modeling, 

simulation or other estimated or derived sources. In contrast, travel behavior measures always 

rely on travelers’ self reports of their behavior, although in the case of travel diaries—where 
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Environmental Impact Analyses 3-10 Final Report 

travelers are asked to very accurately and specifically record the details of individual trips using 

paper or electronic forms—reported behavior is expected to be a fairly accurate reflection of 

actual behavior. 

Overall, explicit consideration of mode choice changes and the change in mode splits or shares—

the percentage of person trips made by various modes—is not extremely rare, but is far from 

standard. Although some evaluations do not consider mode changes at all, most of them do, with 

the smaller, less comprehensive studies often inferring some mode change effects based on 

changes in traffic volumes and transit ridership. The most comprehensive evaluations, such as 

London, do explicitly consider mode changes and attempt a complete accounting, e.g., of the X 

number of car trips that were eliminated, Y percent went to transit, etc. However, even among 

the more robust evaluations, comprehensive treatments which capture both the total change in 

person trips and trace all of the mode-to-mode changes are very uncommon. In London, the 

disposition of the car trips that were eliminated was examined, but a complete accounting of total 

person trips before and after by mode was not performed. 

Within the area of traveler behavior surveys, variations can be observed based on the following 

major variables: 

 Pre- and post-deployment surveying (before and after) versus pre-only or after-only. 

 Panel (longitudinal) samples (the same people participate in the before and after survey) 

versus cross-sectional samples (different people participate in the before and after 

survey). 

 Household surveys, in which each adult in the household is surveyed, versus surveys of 

only a single traveler. 

 General travel behavior information, where travelers describe their typical behavior, 

versus detailed and specific travel behavior information in which travelers record travel 

details for one or more specific days in a diary. 

 Travel diaries alone, versus travel diaries in conjunction with in-vehicle data collection. 

The state-of-the-practice in regard to these parameters can be summarized from the eight study 

projects as follows: 

 Pre- and post-deployment surveying is standard. 

 Panel (longitudinal) studies are typical. 

 The largest, most comprehensive and robust evaluations of large-scale pricing schemes 

(e.g., London and Stockholm) use both household and individual surveys. The less 

comprehensive evaluations and evaluations of smaller-scale pricing projects tend to use 

one or the other, with individual traveler surveys being somewhat more common. 

 Large, comprehensive evaluations utilize surveys gauging both general traveler behavior 

as well as specific travel behavior collected through diaries. 

 Use of instrumented vehicles in general is common, but instrumentation of vehicles 

driven by volunteers who are also maintaining travel diaries is uncommon. 
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Considering the full range of travel impacts (traffic, transit, traveler behavior, safety) the state of 

the practice in regard to instrumented vehicles, including traffic probes, can be summarized as 

follows: 

 Overall, instrumented vehicle data collection is common. 

 Collection of speed and/or travel time data from GPS-equipped buses and cars is 

common and transit ridership is often collected using on-board passenger counters. 

 For average roadway speeds and travel times, in the cases where instrumented vehicles 

are used, the most common approach is for the evaluators to perform a set number of data 

collection runs themselves. It is less common to recruit public volunteers or to purchase 

commercial data derived from various inputs, including traffic probes. 

 Instrumented vehicles for collecting detailed and specific traveler behavior are common 

in simulated congestion pricing field demonstrations. All three study projects of that type 

used instrumented vehicles driven by public volunteers. This is probably because data 

were collected over much longer periods than is possible using a travel diary and/or 

because a pricing changes were dynamic and a high degree of accuracy was needed, for 

example in the Puget Sound study. 

3.2.2 Reported Findings and Study Limitations 

Appendix A includes a table summarizing the main travel related findings of the eight study 

projects. Results indicate that a variety of congestion pricing projects have been shown to be 

effective in reducing traffic congestion. Highlights of reported findings include the following: 

 Significant reductions in vehicle travel (VMT or VKT) on the order of 10 percent are 

common. 

 Vehicle trips have been reduced by between 7 and 20 percent. 

 Travel reductions between 3 and 14 percent. 

 Speed increases between 6 and 21 percent. 

 Mode shift from driving to transit, with transit ridership increases between 6 and 

37 percent. 

In reviewing the findings of congestion pricing evaluations, the emphasis in this study was to 

understand how the evaluation methodologies and challenges impacted the ability of researchers 

to draw definitive conclusions. The table in Appendix A includes a column that summarizes 

major caveats or limitations relevant to specific findings reported for the eight study projects. 

These caveats and limitations can be summarized as follows: 

 Although some references to study limitations are common, detailed discussions of how 

various aspects of the evaluation methodology or context may impact conclusions are not 

common in the published literature. 

 Many evaluators acknowledge that exogenous factors have impacted their findings but it 

is very rare to quantitatively adjust results to eliminate variance related to exogenous 

factors. 
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 Commonly cited exogenous factors include fuel price changes, other transportation 

projects, seasonal variations, survey samples that do not accurately represent the 

population, and background traffic growth related to land development. 

 Few concerns are noted about the fundamental accuracy of objective data such as traffic 

volumes, speeds and travel times. 

 Some evaluations utilize control groups, but many do not. 

 Challenges in reconciling travel diary data with objective transit and traffic data as well 

challenges in collecting comprehensive carpooling, telecommuting, bicycle and 

pedestrian data make it very difficult to perform a comprehensive accounting of mode 

choice changes. 

3.3 Assessing Environmental Impacts 

This section contains two parts. The first part summarizes environmental impacts, performance 

measures and data collection methods and the second part summarizes environmental findings 

and study limitations. 

3.3.1 Impacts, Performance Measures and Data Collection Methods 

A 2008 FHWA lessons-learned report on their Value Pricing Pilot Program noted that congestion 

pricing evaluations have paid less attention to equity and environmental impacts than traffic 

impacts, project operations, and public and customer satisfaction.51 That is also generally the 

case among the eight study projects. 

Table 3-5 identifies the environmental impacts, performance measures and associated data 

collection methods for each of the eight study projects. Among those projects, three broad types 

of environmental impacts were common: 

 Air Quality – the impact on pollutant levels. 

 Noise – the impact on traffic noise levels. 

 Environmental Justice – the extent to which positive and negative impacts are 

disproportionate among people of different races and income levels, including the delay 

of benefits and/or a disproportionate share of adverse impact accruing to minority and 

low-income populations. 

 

51 K.T. Analytics and Cambridge Systematics, Inc., 2008. 
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Table 3-5. Environmental Impacts, Measures and Data Collection Methods 

Study/Project Impacts Analyzed Associated Performance 

Measures Data Collection Method 

Simulated Pricing Field Demonstrations 

Oregon 

Mileage Fee 

Concept and 

Road User 

Fee Pilot 

Program No Environmental Analysis Performed 

Puget Sound 

Traffic Choices 

Study 

Commute 

Atlanta 

Mileage Based 

Value Pricing 

Demonstration 

Air Quality 

(cumulative vehicle 

emissions) – 

methodology 

identified but analysis 

was not performed

 CO, PM2.5, PM10 and 

ozone emissions 

 Calculated (estimated) 

based on objective traffic 

data and regional emission 

rates 

Air Quality (CO 

hotspot microscale) – 

methodology 

identified but analysis 

was not performed

 Localized CO levels 

 Calculated (estimated) using 

EPA CALINE4 microscale 

model 

Before-After Project Evaluations – U.S. 

Minnesota I394 MnPASS 

HOT Lanes 

Air quality (cumulative 

vehicle emissions)  CO levels  Roadside monitors 

Noise  Sound levels 

 Roadside monitors 

 MINNOISE model (based on 

FHWA Traffic Noise Model) 

Environmental justice 

 Surveyed perceptions 

among different sociodemographics 

 Traveler surveys (attitudinal) 

– panel – 800-900 per wave 

 Travel diaries (1-day) with 

general travel behavior 

questions – 800-900 

participants 

San Diego I-15 

HOT Lanes 

Air quality (cumulative 

vehicle emissions) 

 VOC, NOx, PM10 and CO 

emissions. 

 Calculated (estimated) 

based on objective traffic 

data and regional emission 

rates 

Noise  Monitored sound levels  Roadside monitors 
Table 3-5. Environmental Impacts, Measures and Data Collection Methods (Continued) 

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Study/Project Impacts Analyzed Associated Performance 

Measures Data Collection Method 

Before-After Project Evaluations – International 

The Stockholm 

Trial 

Air quality (cumulative 

vehicle emissions) 

 Emissions of PM10, NOx, 

CO2, CO, and VOC 

 Estimated using the 

European Union “ARTEMIS” 

model, utilizing both 

monitored and estimated 

traffic inputs 

 Pollutant levels  Roadside monitors 

 Vehicle emission 

exposure levels 

 Dispersion models utilizing 

objective traffic data coupled 

with emission rate and 

meteorological inputs 

Noise  Sound levels  Roadside monitors 

Environmental justice 

(equity)  Origins and destinations 

 Travel times 

 Congestion charges paid 

 Travel adaptation costs 

 Pricing revenue 

redistribution impacts 

 Travel diaries (1 day) – two 

waves – 24,000 participants 

 Regional travel demand 

modeling of with and without 

pricing conditions using 

travel-diary derived specific 

travel behavior 

London 

Congestion 

Pricing 

Air quality (cumulative 

vehicle emissions) 

 Emissions of PM10, NOx, 

and CO2

 Roadside monitors to collect 

total concentrations (for 

reference; not expected to 

be conclusive) 

 Calculated (estimated) 

emissions to better 

understand project 

contributions to changes in 

emissions; used observed 

traffic impacts and regional 

emissions rates 

Noise  Sound levels  Roadside monitors 

Environmental justice 

 Perceptions of various 

types of travelers 

(varying by income, 

mode use, residence 

location, vehicle 

ownership, physical 

ability/disability, shift 

workers, etc.) 

 Individual traveler and 

household panel surveys 

 Roadside interviews 

 Focus groups 
Table 3-5. Environmental Impacts, Measures and Data Collection Methods (Continued) 

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Study/Project Impacts Analyzed Associated Performance 

Measures Data Collection Method 

Before-After Project Evaluations – International (Continued) 

Singapore 

Area Pricing 

Air quality (cumulative 

vehicle emissions) 

 Emissions of CO, NOx

and smoke/haze 

 Calculated (estimated) 

based on objective traffic 

data and regional emission 

rates 

 Roadside monitors 

Pedestrian safety 

(perceived) 

 Pedestrian perceptions of 

safety 

 Uncertain, but seemingly via 

interviews 

Environmental justice 

 Geographic distribution of 

traffic impacts 

 Travel modeling analysis 

(comparing travel impacts to 

geographic distributions of 

various income and other 

socio-economic variables) 

 Attitudes and perceptions 

of various types of 

travelers 

 Surveys 

Pre-deployment estimation of the environmental impacts of congestion pricing projects—such as 

environmental assessments (EAs) and environmental impact statements (EISs) developed in the 

U.S. in compliance with the National Environmental Policy Act of 1969 (NEPA)—do consider a 

much wider range of potential impacts, including land use. However, the present study focuses 

on measurement of the actual, post-deployment impacts of congestion pricing and, with one 

exception, there were no examples of those other types of environmental impacts among the 

study projects. The one exception—the one other environmental impact that was found in the 

study projects (London and Stockholm)—is the impact of congestion pricing on business and the 

economy. However, in neither London nor Stockholm were these impacts included within the 

“environmental” impact category. This state of the practice summary focuses on the more 

common impacts: air quality, noise and environmental justice. 

Some of the eight congestion pricing study projects—the simulated pricing field demonstrations 

in Oregon, the Puget Sound region, and Atlanta—did not consider any environmental impacts 

whatsoever. However, with the exception of the seeming omission of noise and the addition of 

pedestrians perceptions of safety in Singapore, all of the other study projects considered air 

quality, noise and—although under various names and varying emphases—environmental 

justice. In several cases, “environmental justice” impacts were termed “equity” impacts or were 

part of broader investigations such as “social impacts.” 
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In regard to performance measures and data collection methods, air quality and noise 

environmental impact analyses show less variation from study to study and fewer measures and 

methods overall than do travel impact analyses. The most common air quality performance 

measure—used in each air quality analysis that was reviewed—is the volume of pollutant 

emissions from roadway traffic. The only other performance measure that was found, and which 

is much less commonly considered, is ambient pollutant concentrations. Only one data 

collection method was found for vehicular pollutant emissions: calculating emissions by 

multiplying project-attributable changes in vehicle miles traveled on roadway links by modelderived emission factors (e.g., grams emitted per mile) corresponding to the observed speeds on 

the roadway links. Likewise, there was only one data collection method found for ambient 

pollutant concentrations: roadside pollution sensors. None of the study projects included indepth considerations of greenhouse gases. Rather, when greenhouse gases are addressed at all, it 

is typically done by including the precursor CO2 among the calculated vehicle emissions. No 

examples of the sort of atmospheric modeling necessary to actually estimate green house gases 

were found. 

There is even less variation in evaluation practices related to noise impacts. Noise impacts in all 

of the study projects were measured in terms of ambient sound levels, in decibels, and in all 

cases roadside noise monitors were used to collect the data. 

Pedestrian safety was only considered as an environmental impact and evaluated in Singapore. 

Pedestrian safety was measured in terms of pedestrians’ perceptions which were gathered 

through surveys, interviews or focus groups. 

In contrast to air quality and noise, analyses of environmental justice or equity impacts vary 

more from project to project. This may be because environmental justice analyses typically 

include more qualitative or subjective elements and, therefore, or more of an art than a science, 

or it may be that as a relatively new area of interest, fewer standardized approaches have thus far 

emerged. Although specific approaches vary, environmental justice analyses generally focus on 

two main areas. The first is to examine how travel impacts distribute geographically and, using 

geographic socioeconomic databases, infer whether projects differentially impact (both benefits 

and disbenefits) areas with concentrations of low income and/or minority populations. The 

second element employs public surveys and or focus groups to gauge the perceptions of low 

income and/or minority populations.

3.3.2 Reported Findings and Study Limitations 

Appendix B includes a table summarizing the main environmental impact findings of the eight 

study projects. Highlights of reported findings include the following: 

 Reductions in calculated vehicle emissions of various pollutants of up to 16 percent. 

 No project-attributable changes in monitored air quality levels. 

 No significant project-attributable changes in modeled noise levels. 

 No project-attributable changes in monitored noise levels. 
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 Benefits and costs of congestion pricing do impact different types of people differently, 

but negative impacts to lower income earners have generally been less than anticipated 

and generally not disproportional. 

 Horizontal equity considerations such as residential and work locations and access to 

travel alternatives play as much or more of a role than vertical equity considerations 

(namely ability to pay the pricing charge) in explaining differential impacts among 

various types of people. 

 How pricing revenues are spent can have a significant impact on the net costs and 

benefits for different people. 

Caveats and limitations associated with environmental impacts focus largely on the inability to 

differentiate project contributions from exogenous factor influences on monitored air quality 

impacts. Although some state-of-the-practice reviews have identified the failure to test for air 

quality implications of possible changes in traffic flow (e.g., more cruising and less stop and go) 

as a weakness, this issue is rarely noted by the evaluators of specific projects. There are limited 

discussions of caveats and study limitations in regard to environmental justice. When discussed, 

limitations sometimes focus on measurement issues such as survey sample limitations and the 

inherently subjective and “less scientific” nature of perception data. 

3.4 Knowledge Gaps 

This section identifies gaps in the understanding of the travel and environmental impacts of 

congestion pricing. 

3.4.1 Travel Impacts 

Table 3-6 summarizes the aspects of travel impacts that have generally been well established 

through before-after evaluations as well as those areas where understanding is less complete. 

Each of these gaps is discussed following Table 3-6. 

Table 3-6. Travel Impact Knowledge Gaps 

Better Understood Impacts (Knowledge) 

Less Understood Impacts 

(Knowledge Gaps) 

Short-term impacts (from a few months up to a 

year after deployment) Long term impacts 

Localized impacts Regional impacts 

Cumulative impacts (projects plus exogenous 

factors) Project-attributable impacts 

Individual travel behavior changes Household travel behavior changes 

Vehicle volumes Person trips 

Average speeds Vehicle speed fluctuations (driving cycle) 

Average performance Variability in performance (reliability) 

Transit ridership changes Transit crowding implications 
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Environmental Impact Analyses 3-18 Final Report 

Long Term Impacts 

Long-term impacts are not well understood because there have been relatively few long-term 

evaluations. Although the Singapore and London evaluations have continued over many years, 

the ability to draw conclusions is still limited by the fact that not all analyses have been 

continued and because over these longer periods the masking influence of exogenous factors has 

made isolation of project impacts especially challenging. In particular, there is not a good 

understanding of the long-term traveler behavior associated with congestion pricing, e.g., will 

travelers who, in the short term, are willing to continue driving and pay charges switch to other 

modes or make other changes, such as moving, switching jobs or telecommuting, over the long 

term? Conversely, will travelers who initially shift to transit or make other changes to avoid the 

charge eventually drift back to driving—and if so, how many of them and why? Even when 

long-term traffic and transit ridership data have been studied, only the aggregate change is 

usually considered and the components of the change are unclear. For example it is unclear 

whether static mode shares over time mean that travel behavior changes in response to pricing 

have ended or whether changes continue but off-set one another, e.g., drivers continue to switch 

to transit but as transit becomes crowded other travelers switch to driving. This area of 

uncertainty includes a lack of information on long-term impacts on auto ownership. 

Regional Impacts 

Another gap concerns the regional impacts of congestion pricing. Although some evaluations 

have considered travel impacts over a fairly large area (e.g., London and Stockholm), many 

evaluations have focused on the priced facilities/zone and the immediately adjacent portions of 

the transportation system. Of course, it is resource intensive to study larger areas, and most 

evaluations have focused their attention on the areas where the most significant impacts are 

expected, which is a logical strategy given constrained resources. Unfortunately, this has created 

something of a self-perpetuating cycle: evaluators do not examine regional impacts in part 

because there is not strong evidence that there will be regional impacts but the reason there is no 

strong evidence is not because evaluations have found few impacts but simply because those 

impacts are very seldom assessed. 

Project-Attributable Impacts 

Another significant gap in the understanding of travel impacts concerns the specific influence of 

the pricing project in observed changes. The combined or cumulative impact of pricing 

projects—the impact of the project coupled with the influence of a wide range of exogenous 

factors—has been relatively well established in many evaluations. However, most evaluations 

are not able to accurately isolate the discrete impact of the project. Most evaluations 

acknowledge one or two exogenous factors that may be relevant, e.g., gas prices or other 

transportation system changes, and some go as far as to describe the changes in those exogenous 

factors and qualitatively consider the potential general impact of those factors as they draw 

conclusions about the project impacts. But rarely are the impacts of the exogenous factors 

addressed quantitatively. The 2008 FHWA Value Pricing Pilot Program Lessons Learned Final 

Report came to similar conclusions, noting that: 

 
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Environmental Impact Analyses 3-19 Final Report 

 Attempts to distinguish the effects of pricing from outside influences such as gas prices 

or economic swings have been modest at best. 

 Use of controls is limited. 

 Opportunities for improvement include attention to controls and statistical tests to insure 

valid results and to rule out influences of ongoing swings in gasoline prices and economic 

conditions. 

Even in the few cases where evaluators have estimated the quantitative impact of certain 

exogenous factors, results have sometimes been challenged. For example, different researchers 

disagree about the how much of the traffic reductions were due to fuel increases.52

Use of household travel diaries in conjunction with conventional surveys which focus on the 

influences on travel behavior can be a powerful means for improved understanding of exogenous 

factors. However, as the evaluators of the Commute Atlanta mileage-based value pricing 

program evaluation found, use of household travel diaries is not effective unless changes in 

households between the before and after periods are carefully considered and unless sample sizes 

are large enough to balance significant demographic variation among households. The Commute 

Atlanta researchers concluded that the several well known and frequently cited U.S. congestion 

pricing evaluations have not sufficiently controlled for such factors. 

Household Travel Behavior Changes 

Use of household traveler surveys and travel diaries is not rare, but it is far from commonplace. 

Also, when household travel behavior has been investigated, there is often insufficient focus on 

shifts and trade-offs within the households, such as how a vehicle is used by family member X 

which was formerly driven by family member Y who has shifted to transit in response to pricing. 

Likewise, there has been little to no significant investigation of how total household travel 

budgets—in terms of time and money—factor into these intra-household changes and the 

connection to specific pricing strategies. As a result, the understanding of household impacts of 

congestion pricing projects is not complete. 

Person Trips 

The understanding of the impact on congestion pricing projects on person trips, especially person 

throughput and overall mode shares is incomplete. Many evaluations focus foremost on traffic 

impacts, or vehicle trips. Many of those evaluations that have included consideration of other 

modes have focused on transit ridership. Some of the largest and most robust evaluations, like 

London, have tracked person trip shifts to some degree—e.g., tracing X number of curtailed 

driving trips into the pricing zone—but those analyses have not included a truly comprehensive 

accounting of all person trips and their shifts. There has also been very limited consideration of 

person throughput. Challenges in cost-effectively collecting average vehicle occupancy data and 

data from travelers who telecommute, forego trips, bicycle, or walk likely contribute to the under 

consideration of person trip impacts. 

 

52 Coordination of Urban Road User Charging Organisational Issues (CURACAO), “Deliverable D2: State of the 

Art Review (FINAL). Prepared by the Institute for Transport Studies, University of Leeds. May 2009. 
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Vehicle Speed Fluctuations (Driving Cycle) 

Most evaluations focus on the before-after changes in the average speeds on specific roadway 

links or across roadway networks and these changes are relatively well understood. However, 

there is not yet a sufficient understanding of impacts on vehicle driving cycle (proportion of 

vehicle operation in acceleration, deceleration, idle and cruising modes) that are related to 

changes in traffic flow characteristics and which may not be accompanied by significant changes 

in average speeds. A roadway that shows little to no change in average speed may in fact 

demonstrate improved flow and a significantly different driving cycle profile. For example, prepricing, a road may have an average speed of 30 miles per hour (mph) that reflects brief bursts of 

45 mph travel punctuated by frequent stops (idle). After pricing, the average speed may still be 

30 mph but it may reflect a steady, 30 mph flow with no stops and starts. To date, evaluations 

have neither clearly identified the significance of traffic flow improvements on driving cycle and 

emissions nor eliminated the possibility that they may be as or more important than reductions in 

traffic volumes.53

Variability in Performance (Reliability) 

Most evaluations focus on average or typical transportation system performance. There has been 

far less attention paid to the variability in transportation performance, that is, reliability. Gaps in 

this area include both objective quantification of reliability as well as thorough understanding of 

traveler attitudes and responses to varying levels of reliability. 

Transit Crowding Implications 

In so much as one objective of many pricing strategies is to shift some travel from driving to 

public transportation, transit services and capacity play a key role in congestion pricing success. 

Although evaluations often document the net changes to transit ridership, the implications of 

transit capacity and crowding are not well understood. As many transit agencies across the U.S. 

are implementing or considering service cut-backs, understanding these issues is especially 

important now. 

3.4.2 Environmental Impacts 

This section discusses gaps in the understanding of the air quality, noise, and environmental 

justice (equity) impacts of congestion pricing projects. 

Air Quality 

What is currently understood regarding the impact of congestion pricing projects on air quality is 

based on the analyses that have calculated vehicle emissions. As noted in Section 3.2, roadside 

monitoring of before and after air quality has not enhanced that understanding. 

Overall, the calculated vehicle emissions analyses that have been done have provided an 

understanding of the approximate or partial air quality impacts of congestion pricing projects. 

Inaccuracies and incompleteness stem from a failure to accurately specify all of the key input 

parameters—both traffic and emission rate-related. 

 

53 Institute for Transport Studies, University of Leeds, 2009. 
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Environmental Impact Analyses 3-21 Final Report 

Table 3-7 identifies those determinants of congestion pricing project vehicle emission impact 

that are usually well represented in analyses as well as those that are not. It is the latter that 

underlie the gaps or uncertainties in the current understanding of the air quality impacts of 

congestion pricing projects. 

Table 3-7. Air Quality Knowledge Gaps 

Better Understood Components of Congestion 

Pricing Vehicle Emission Changes 

Less Understood Components of Congestion 

Pricing Vehicle Emission Change 

Cumulative impacts (VMT, speed) Project-attributable impacts (VMT, speed) 

Localized impacts Regional impacts 

Average daily impacts Hourly variation 

 Driving cycle changes (traffic flow change) 

 Vehicle mix 

Project-Attributable VMT. As discussed in Section 3.3.1, most analyses acknowledge a 

number of exogenous factors impacting observed, before-after changes in traffic volumes and 

average speeds, but very rarely are the traffic inputs to emissions volume quantitatively adjusted 

to eliminate the portion of variation attributable to exogenous factors. Indeed, analysts very 

seldom understand (or agree on) exactly how much of the observed variation is due to factors 

such as fuel price changes or employment changes. 

Regional VMT and Speed Changes. Also as noted in Section 3.3.1, the analysis of the traffic 

impacts of congestion pricing projects typically focus on the priced facility/area and, somewhat 

less typically, may also include the immediately adjacent roadways. Examinations of potential 

impacts farther away, throughout the region, are rare. Correspondingly, emissions analyses have 

been unable to capture any of more distant impacts that may be created. 

Hourly Variation. Many congestion pricing projects can be expected to have significantly 

different impacts during different times of day. It does not appear that hourly variations in VMT 

and or link speeds are standard considerations in congestion pricing project air quality analysis, 

and thus the understanding of these impacts is incomplete. 

Driving Cycle Changes (Traffic Flow Change). The “grams per mile” emission rates 

(“factors”) used in emission calculations are almost always derived from emission factor models 

such as the U.S. Environmental Protection Agency (EPA) MOBILE6 model or the California Air 

Resources Board EMFAC model. Those models utilize assumptions—which, to varying 

degrees, can be manipulated by users—regarding the “driving cycles” of vehicles. Driving cycle 

refers to the proportion of a vehicle’s travel (VMT) under acceleration, deceleration, idle, and 

cruise (constant speed). Evaluations of congestion pricing project emissions impacts seldom 

include adjustments to reflect driving cycle assumptions in the emission factor models based on 

project-attributable impacts to driving cycles. The likely reasons for omitting such potentially 

important probably changes include: 1) It is usually unclear whether a project has impacted 

vehicle driving cycles (most traffic analysis look only at net changes in average roadway link 

speeds), and 2) Some analysts do not understand the significance of driving cycle in the emission 
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Environmental Impact Analyses 3-22 Final Report 

factor estimation process, which is opaque in so much as it occurs internal to the emission factor 

model. 

Vehicle Mix. Vehicle emission rates—grams per mile or grams per hour (idle)—vary 

significantly by vehicle type. The traffic analyses within most evaluations of congestion pricing 

projects do not appear to explicitly study project impacts on vehicle mix and, as a result, these 

changes are usually not included in the air quality analysis. That is, the breakdown of total 

observed link VMT for the before and after scenarios utilize the same vehicle mix. To the extent 

that congestion pricing projects do not differentially impact different vehicle types, it is of course 

appropriate to use the same mix, but to the extent that projects do impact this area, these impacts 

are seldom reflected in the emissions analyses. 

Noise 

There are no gaps, per se, in the understanding of the noise impacts of congestion pricing. This 

is because, even allowing for the likely inaccuracies in calculated (modeled) noise levels and, in 

the case of monitored noise levels, the inability to differentiate project impacts from exogenous 

impacts, congestion pricing projects have not been shown to, and are unlikely to, generate the 

magnitude of traffic changes needed to produce a change in noise levels that is perceptible to 

most people. Hearing sensitivity among humans is non-linear in that very large increases in the 

noise-generating activity are necessary to produce even the smallest perceptible changes in noise 

levels. In the case of traffic, at least a doubling (or halving) of traffic volume will be necessary 

to produce a change in noise levels that is noticeable to most people.54 Unless a congestion 

pricing project is expected to increase or decrease traffic levels by 50 percent or more, and/or 

noise is an extremely significant concern in a community, there is little value in even attempting 

to gauge the noise impacts of congestion pricing projects. 

Environmental Justice 

Overall, review of the published literature associated with the eight study projects as well as 

other documents assessing congestion pricing project effects and evaluation methods yielded 

fewer insights into knowledge gaps in the area of environmental justice than in the areas of travel 

impacts and air quality. That may be due in part to the fact that, although there is considerable 

information on environmental justice (or “equity” as it is often termed), there has been somewhat 

less focus on this topic than on travel impacts, a conclusion shared by a recent report on lessons 

learned from the FHWA Value Pricing Pilot Program.55 It may also be a function of the fact that 

much of the focus on environmental justice topics has been on predicting the impacts as part the 

design of the scheme so as to maximize public acceptance rather than solely on measuring the 

impacts of deployed projects. Predicting impacts has been a particular focus among European 

congestion pricing researchers. 

 

 

54 Institute for Transport Studies, University of Leeds, 2009. 55 K.T. Analytics and Cambridge Systematics, Inc., 2008. 
Synthesis of Congestion Pricing-Related October 18, 2010 

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Although there is not extensive information identifying gaps in the environmental justice 

knowledgebase, four specific areas can be identified: 

 The need for more results, overall, and the importance of considering environmental 

justice issues in all evaluations. 

 The need for particular focus on “horizontal equity” issues, which pertain to those aspects 

of equity or environmental justice that pertain to issues other than income (vertical 

equity), including geographic locations and auto access. 

 Greater investigation into the long-term equity implications of congestion pricing 

projects, including on land use and population. 

 Greater emphasis on how the uses of congestion charging revenues can impact both the 

perceived and actual equity of pricing projects. 

The importance of continued examination of horizontal equity issues is based in part on 

evaluation findings that have shown that the vertical equity issues associated with congestion 

pricing projects may not be as great, or at least not as singular of a focus as had been expected.56 

The need to gather more information on the long-term environmental justice impacts of 

congestion pricing reflects a concern common to essentially all impact areas. The importance of 

an improved understanding of the impacts of pricing revenue redistribution has been cited by 

several researchers, including the 2008 FHWA Value Pricing Pilot Program lessons learned 

report, the CURACAO study and a 2009 study by the RAND Corporation.57

 

56 K.T. Analytics and Cambridge Systematics, Inc., 2008. 57 Ecola, Lissa and Light, Thomas, “Technical Report – Equity and Congestion Pricing, A Review of the Evidence,” 

RAND Corporation, 2009. 
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4.0 RECOMMENDED EVALUATION FRAMEWORK 

This chapter presents a recommended framework for before-after evaluations of the air quality 

and environmental justice impacts of congestion pricing projects. The recommendations 

presented here represent a general framework that provides the foundation for the development 

of project specific evaluation approaches. This framework is intended to stimulate, rather than 

replace, explicit project-specific evaluation methodology development processes that will 

include a wide range of stakeholders and which will carefully consider local conditions, project 

objectives and potential impacts, evaluation objectives, and evaluation resources. 

The framework recommended here is consistent with the evaluation methodologies being 

utilized in the U.S. DOT evaluation of the Urban Partnership Agreement and Congestion 

Reduction Demonstration deployments. The general evaluation approaches are presented in the 

UPA/CRD National Evaluation Framework 

(http://www.itsdocs.fhwa.dot.gov/JPODOCS/REPTS_TE/14446.htm). The detailed evaluation 

methods are described in a series of test plan documents that are being developed for each 

UPA/CRD. Test plans for the Minneapolis UPA site are currently available, and plans for the 

other sites will be made available as they are completed, on the U.S. DOT UPA/CRD 

“Publications, Legislation and Guidance” webpage: http://www.upa.dot.gov/pub.htm. 

In keeping with this study’s interest in travel impacts in so much as they relate to environmental 

impact evaluation, recommendations for assessing travel impacts in and of themselves are not 

presented here. Rather, those travel impacts that are directly relevant given the recommended 

evaluation methodologies are discussed within the context of the environmental impact 

framework. 

Congestion pricing projects rarely can be expected to produce significant noise impacts and 

therefore noise analysis is not recommended as part of a standard analysis framework. 

Consideration of other impacts which may or may not be universally categorized as 

“environmental impacts,” such as impacts on business and the economy may be appropriate for 

many congestion pricing projects but were not considered in this study. 

Table 4-1 summarizes the overall recommended framework. Recommendations are elaborated 

in the text that follows (Section 4.1 and 4.2). The recommendations presented in Section 4.1 and 

4.2, generally describe recommended best practice without regard to project-specific resource 

availability. Table 4.1 includes recommendations for cost-savings when resources are especially 

constrained. 
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Table 4-1. Summary of Recommended Environmental Impact Evaluation Framework 

Evaluation 

Consideration Recommended Approach Options for Limiting Costs 

Air Quality 

Ambient 

Monitoring versus 

Calculated Vehicle 

Emissions 

 Calculate project-related vehicle 

emissions rather than trying to discern 

them within monitored ambient pollutant 

levels 

 None (vehicle emission 

calculation is not resource 

intensive) 

Dispersion 

Modeling 

 Only perform if significant increases in 

local traffic delay are expected, especially 

near sensitive land uses 

 Will not be needed for most 

evaluations 

Vehicle Emission 

Calculation 

Procedures 

 Use a project-level analysis that sums 

emissions among individual study 

roadway links under before (without 

project) and after 

 None 

Pollutants  Consult with state/local and Federal 

agencies within the analysis region 

 Typically include criteria pollutants (CO, 

NOx, VOC and PM), greenhouse gas 

related pollutants (CO2, methane) and 

mobile source air toxics (benzene) 

 None (very little cost implication 

for calculating one versus several 

pollutants) 

Geographic Area 

of Analysis 

 As many impacted roadway links 

(+ 5 percent project-attributable traffic 

volume change) as possible; at least all 

major roadways in the priced zone and all 

major, adjacent alternate routes 

 Focus on only the most 

significantly impacted roadway 

links and caveat conclusions 

appropriately 

Traffic Data 

Collection 

Timeframe 

 More data is better—a minimum of 

several months with a full year being best, 

so as to control for seasonal and other 

cyclical changes 

 Limit to a few days or weeks of 

data collection, making sure to 

control for seasonal and other 

cyclical changes impacted beforeafter data. 

Traffic Inputs and 

their Derivation 

 Use observed rather than modeled data 

 At a minimum, include roadway linkspecific VMT and average speeds; include 

driving cycle data when impacts are 

present and if resources permit collection 

of observed data 

 Use any of various, proven speed data 

collection methods including probe 

vehicles or various roadway detectors 

(e.g., license plate readers, inductive 

loops, microwave, magnetic, Bluetooth, 

etc.) 

 Calculate VMT based on actual link 

lengths and observed traffic volumes 

collected using any of various proven, 

specific data collection methods, e.g., 

inductive loops, microwave, Bluetooth, 

etc. 

 Eliminate driving cycle data and 

caveat findings appropriately 

 Minimize or eliminate special data 

collection on less important links 

(rely mostly or entirely on existing 

detector data) 
Table 4-1. Summary of Recommended Environmental Impact Evaluation Framework (Continued) 

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Evaluation 

Consideration Recommended Approach Options for Limiting Costs 

ProjectAttributable Traffic 

Changes 

 Base the vehicle calculations on projectattributable rather than cumulative or total 

observed before-after changes 

 Consider and apply a wide range of 

techniques to control for exogenous 

factors, including use of controls, 

statistical modeling, household travel diary 

data, etc. 

 Use cumulative, observed 

changes but qualitatively assess 

the potential influence of 

exogenous factors and caveat 

findings appropriately 

Hourly Emission 

Estimates 

 Calculate total daily emissions as the sum 

of calculated hour-by-hour emissions 

 Assuming traffic data is available, 

there are limited cost implications 

of calculating by hour 

Vehicle Mix  Break link VMT into VMT by major vehicle 

types and apply appropriate vehicle typespecific emission factors if project has 

impacted vehicle mix 

 Assume no project change in 

vehicle mix and use a single allvehicle VMT figure 

Emission Rates  Derive using an emission rate model 

selected based on local preference and 

familiarity 

 If observed vehicle driving cycle data is 

available, utilize EPA MOVES model 

 Carefully review and understand all model 

inputs, including default values 

 If MOVES not used, there are few 

cost implications because 

emission factors are often 

available from regional air quality 

agencies and/or can be fairly 

easily developed 

 Collection of observed driving 

cycle data and use of MOVES 

should only be eliminated if no 

significant driving cycle changes 

are present and if resources 

preclude MOVES modeling 

Noise 

Inclusion in the 

Environmental 

Analysis 

 Not recommended as a “standard” 

practice because most congestion pricing 

projects will have little or no discernable 

impact 

 Include only if it is a key local issue 

 If included at all, either monitor or 

model, but not both 
Table 4-1. Summary of Recommended Environmental Impact Evaluation Framework (Continued) 

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Evaluation 

Consideration Recommended Approach Options for Limiting Costs 

Environmental Justice 

Use of Prevailing, 

Fundamental 

Tools 

 Prevailing methods and tools provide a 

solid foundation and should be utilized in 

most analyses; tools/techniques include 

mapping of travel impacts in relation to 

minority and low income populations, 

attitudinal surveys and focus groups with 

various populations, and travel diaries 

completed by various populations 

 GIS mapping is more powerful, 

but simpler manual overlays may 

be substituted 

 Panel surveys are best but crosssectional surveys may be 

substitute 

 Travel diaries are best but general 

stated behavior surveys may be 

substituted 

Travel Impacts to 

Consider 

 Consider the potential environmental 

justice implications of any and all 

documented travel impacts (see text for 

recommended measures) 

 When household travel 

diaries/surveys are costprohibitive, may use individual 

travel diaries/surveys 

 Eliminate travel diaries completely 

if resources preclude them and 

rely more on general stated 

behavior (from surveys and/or 

focus groups) 

 Leverage existing system-based 

data collection and cut back on 

“special” data collection as 

resources dictate 

 When resources dictate “picking 

and choosing” of impacts to 

consider, focus on those that are 

expected to be most significant 

and which can be most accurately 

measured, such as traffic volumes 

and speeds and transit ridership 

Populations to 

Consider 

 Consider as many different populations as 

possible (see text), including those based 

on socio-economic, transportation mode, 

employment type, and trip purpose factors 

 If resources require “picking and 

choosing,” focus on socioeconomic factors, especially 

income and race 

Charging 

Revenues 

 Explicitly consider how charging revenues 

will be reinvested and relationship 

between who pays charges and who 

benefits from sharing revenue 

investments 

 In most cases, the scope and 

scale of the consideration of 

reinvestment will be much less 

extensive than the consideration 

of the direct travel impacts of the 

congestion pricing project itself 

and may be subjective 

Sources of 

Demographic Data 

 Build in as much demographic data 

collection as possible into all manner of 

travel and other evaluation data collection; 

not just surveys 

 When resource constraints 

dictate, surveys or even zip code 

data can be used as a minimum 
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4.1 Air Quality Analysis Framework 

This section presents a general recommended framework for evaluating the air quality impacts of 

deployed congestion pricing projects such as the U.S. DOT Urban Partnership Agreement 

deployments. 

4.1.1 Ambient Monitoring versus Calculated Vehicle Emissions 

Experience from other congestion pricing evaluations indicates that roadside monitoring of 

ambient air quality levels is not an effective approach to gauging project impacts; it is simply 

impossible to differentiate project-related impacts from other, exogenous factors. As such, the 

first and most fundamental recommendation is that the air quality impacts of congestion pricing 

projects be evaluated using the one method that allows direct estimation of project-attributable 

air quality impacts: by comparing before (without pricing) and after (with pricing) calculated

vehicle emissions. 

4.1.2 Dispersion Modeling 

Dispersion models, or hot spot models, estimate the localized ambient concentrations of vehicle 

emissions, as compared to the “calculated vehicle emissions” discussed above which calculate 

the volume of pollutants being emitted directly from vehicles. Dispersion modeling takes into 

account atmospheric and site topography considerations to estimate roadside concentrations of 

pollutants emitted from all traffic. No examples of dispersion modeling for before-after 

congestion pricing projects were found among the eight study projects or in the general 

literature. 

It is recommended that dispersion modeling only be performed if the traffic analysis indicates 

that the congestion pricing project has created significant increases in localized traffic delay, 

especially near sensitive land uses such as nursing homes, parks, or schools. Such impacts may 

be possible with some congestion pricing projects, such as those that may divert significant 

traffic away from a priced facility onto one or two already congested parallel routes. If 

dispersion modeling is appropriate selection of a model and specific methodologies should be 

based on local considerations and should reflect an interagency consultation including state and 

local air quality and traffic agencies and regional U.S. DOT representatives. Examples of 

dispersion models include the EPA CAL3QHCR or CARB CALINE4 carbon monoxide 

dispersion models. 

4.1.3 Calculation of Vehicle Emissions 

This section presents the recommended framework for what will, in most cases, constitute the air 

quality evaluation: calculation of before and after vehicle emissions. The recommended 

framework is as follows: 

 Project-level Analysis – vehicle emission calculations for deployed congestion pricing 

projects should, logically, use a project-level analysis. A project-level approach 

calculates project-related changes in traffic volumes and speeds on specific affected 

roadway links and calculates total vehicle emissions as the sum of calculated emissions 

for each link. 
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 Pollutants – the selection of pollutants for consideration in the air quality analysis will be 

driven by local air quality issues. The selection of pollutants should be made via an 

interagency consultation including state and local air quality and traffic agencies and 

regional U.S. DOT representatives. Many analyses will likely focus on all or some of the 

following pollutants associated with vehicle activity: 

o Some criteria pollutants (pollutants associated with National Ambient Air Quality 

Standards): carbon monoxide, ozone precursors nitrogen oxides, volatile organic 

compounds, and particulate matter 

o Greenhouse gas related pollutants: carbon dioxide and methane 

o Mobile source air toxics (MSATS): benzene. 

 Geographic Area of Analysis – The geographic area of analysis should include as many 

of the roadway links as possible that are expected to be affected by the project, a 

determination that will be made in the traffic analysis that precedes the air quality 

analysis. Generally, at a minimum, the air quality analysis should include the major 

roadways (highway and major arterials) within the priced zone as well as the major likely 

alternate routes to those roadways. It has been suggested that “affected” roadways could 

be defined as those links where the average annual daily traffic is expected to change by 

more than +5 percent as a result of the project.58 Experience has shown that traffic 

diversion can be significant: in pre-deployment surveys for the Seattle region UPA 

congestion pricing deployment, 40 percent of respondents indicated that they will take an 

alternative, non-priced route;59 in London, it was estimated that 20-30 percent of car trips 

no longer made into the priced zone are now made on non-priced roads.60

 Data Collection Timeframe – A minimum of several months of before and after data is 

recommended and up to a full year of data pre- and post-pricing project implementation 

is better. Collection of a full year of before and after data allows for seasonal variation to 

be controlled for or explicitly evaluated, allows random variations to be averaged out, 

and allows examination of both the immediate (first few weeks/months) as well as 

somewhat more mature (one year) impacts of the pricing project be investigated. If using 

only a few months of data, it is important to compare before and after data that are from 

the same season or month to control for seasonal variation. 

 Traffic Impacts and their Derivation – At a minimum, observed rather than modeled 

roadway link-specific VMT and average speeds should be utilized. Link speeds can be 

collected using any of various, proven speed data collection methods including probe 

vehicles (e.g., floating cars operated by the evaluators, GPS-equipped vehicles operated 

by public volunteers, or toll-tag equipped vehicles operated by the general public) or 

various roadway detector types such as license plate readers, inductive loops, Bluetooth, 

microwave, infrared, acoustic, etc. Link VMT should be calculated based on actual link 

 

58 Claggett, Michael and Miller, Terry, “A Methodology for Evaluating the Mobile Source Air Toxic Emissions 

Among Project Alternatives,” May 2006. 

59 Washington State Department of Transportation, “SR 520 Bridge Tolling Good to Go! Baseline Survey – 

Telephone Survey Report, Draft,” prepared by Pacific Rim Resources, Inc. May 2010. 

60 Transport for London “Central London Congestion Charging Impacts Monitoring Second Annual Report,” April 

2004. http://www.tfl.gov.uk/assets/downloads/Impacts-monitoring-report-2.pdf 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses 4-7 Final Report 

lengths and observed traffic volumes. Traffic volumes should be collected using any of 

various proven, specific data collection methods, e.g., inductive loops, microwave, etc. 

If the project has been shown by the traffic analysis to have significantly impacted traffic 

flow (i.e., driving cycle), observed driving cycle data should be collected and used in the 

calculation of vehicle emissions (see discussion of Emission Rates, below). 

 Project-Attributable Traffic Changes – Emission calculations should utilize projectattributable changes in link speeds, VMT (and, if applicable, driving cycle) rather than 

total observed changes in these metrics. That is, ideally, the influence of exogenous 

factors should be controlled in such a way that observed traffic data can be quantitatively 

adjusted to eliminate the non-project related portion of total before-after variability. 

If exogenous factors such as fuel price changes, employment changes, and other 

transportation projects and programs are believed to have exerted little or no influence on 

travel in the study area, then observed post-deployment VMT and speeds can be used 

directly. However, if—based on thorough tracking from the pre-deployment through the 

post-deployment data collection period—there is reason to believe that exogenous factors 

have significantly impacted observed post-deployment traffic data, efforts should be 

made to adjust the post-deployment traffic data to eliminate the influence of exogenous 

factors. If that is not possible, the results of the emissions calculations should caveat the 

results appropriately. The influence of exogenous factors on driving cycle is especially 

problematic. If it is determined that exogenous factors have significantly impacted traffic 

conditions, in many cases consideration of driving cycle impacts may need to be 

eliminated. This is because it is much harder to quantitatively adjust driving cycle data 

than volume or average speed data—if possible at all it would require resource-intensive 

traffic simulation. Further, even if adjustments can be made, the resulting estimates may 

be so uncertain as to eliminate the fundamental value in considering driving cycle data at 

all. Recommended methods for determining whether and how much exogenous factors 

have influenced traffic volume and speed changes include: 

o Comparisons to control roadways/corridors/areas 

o Statistical modeling that can remove or control for the effect of exogenous factors 

by including such variables in multivariate equations 

o Utilization of household survey data (travel diary data being ideal) to understand 

the causes behind reported changes in travel behavior, including the following 

considerations: 

 Using adequate sample sizes given intra and inter-household changes over 

the analysis period. 

 Collection of detailed information from participants to better understand 

the reasons behind the reported travel behavior. 

 Consideration of case study approaches in which the impact of changes in 

household demographics are thoroughly explored at the individual 

household level, potentially including home interviews and focus groups. 

 
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o Tracking fuel prices and employment levels 

o Elimination of traffic data from times and locations within the study area 

characterized by severe weather, significant traffic incidents, and significant 

roadway construction 

o Collecting before and after tracking data for the same month(s) of the year 

o Examination of historic traffic trends. 

 Hourly Emission Estimates – It is recommended that total daily vehicle emissions for 

both the before and after periods be developed by summing hourly emission estimates. 

Those hourly estimates should use hourly VMT and speed data. 

 Vehicle Mix – Traffic analyses of congestion pricing projects should test for before-after 

changes in vehicle mix and any changes should be reflected in the air quality analysis by 

breaking VMT down by vehicle type. 

 Emission Rates (Factors) – Emission factors should be derived from an emission model 

such as the EPA MOBILE6, MOVES or California Air Resources Board EMFAC 

models. Selection of the model will be driven by local preference and familiarity (that is, 

using a model that is accepted and well adapted to the analysis region) as well as the 

approach taken to driving cycle. 

o Resources permitting and assuming that a traffic analysis has shown that driving 

cycle impacts (changes in flow—the pattern of acceleration, deceleration, idling 

and cruising on study roadway links) are likely, these impacts should be explicitly 

considered in the air quality analysis. That will require collection of before and 

after driving cycle data using instrumented test vehicles performing floating car 

runs on all of the study roadways and during all of the time periods of interest. 

Multiple runs will be required on each link at different times of the day, made by 

at least a couple of different types of vehicles. When observed driving cycle data 

are available, it will be important to utilize the EPA MOVES model to derive 

emissions factors because the MOVES model provides by far the most effective 

means for taking driving cycle changes into account. 

o Collection of observed driving cycle data can be expensive. For example, as part 

of the preliminary planning for the U.S. DOT evaluation of the Seattle-Lake 

Washington Corridor Urban Partnership Agreement, it was estimated that 

collection of driving cycle data for that analysis would cost between $50,000 and 

$100,000.61 In those cases where resources do not permit the collection of driving 

cycle data, the selection of the emission factor model should be based on local 

considerations. 

o Regardless of which emission factor model is selected for a specific analysis, 

evaluators should carefully review and understand the model inputs and default 

and user-defined inputs and options. Local inputs such as fleet registration and 

fuel-type distributions, vehicle emission inspection and maintenance (IM) 

programs, and vehicle fuel programs should be accurately reflected in the model. 

 

61 Unpublished technical memorandum, “Decision Support Information for UPA/CRD Environmental Analysis 

Approach,” prepared by Battelle for the United States Department of Transportation, November 2009. 
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4.2 Environmental Justice Analysis Framework 

This section presents recommendations for evaluating the environmental justice impacts of 

congestion pricing projects. Perhaps more so than any other areas of evaluation, the specific 

issues to be considered in the environmental justice evaluation should be driven by local, sitespecific issues and objectives. However, there are several principles that will be widely 

applicable. 

4.2.1 The Prevailing, Fundamental Tools and Techniques Provide a Solid Foundation 

In addition to the recommended enhancements noted below, the fundamental tools and 

techniques that currently constitute state of the practice for investigating environmental justice 

are useful and should continue to be utilized. These methods include: 

 Using regional geographic information systems to map the locations of low-income and 

minority populations within the likely impact area. 

 Using attitudinal surveys, interviews and focus groups of the general public, corridor 

travelers and specific types of residents and travelers to gather attitude and perception as 

well as general travel behavior data. 

 Using travel diary surveys to gather detailed, specific travel behavior data of various 

groups of interest. 

4.2.2 Travel Impacts 

The specification of travel impacts relevant to an environmental justice analysis is more complex 

than the specification of traffic impacts relevant to an air quality analysis. In the case of air 

quality, only a few “bottom line” traffic impacts (VMT, speeds and driving cycle) manifest 

directly in terms of air quality. Consideration of other travel impacts (e.g., mode choice) is 

irrelevant because such changes either ultimately translate to changes in VMT, speed and/or 

driving cycle or they are totally unrelated to air quality. In the case of environmental justice, it is 

not the case that only certain travel impacts are relevant, although certainly some, such as 

charges paid by socio-economic category, are more relevant. Rather, an environmental justice 

analysis seeks to understand a particular dimension (differential impacts among populations) of 

essentially any and all significant travel impacts. 

As such, the first and most fundamental consideration in regard to assessing environmental 

justice impacts is to start with a comprehensive travel impacts evaluation that assesses as many 

potentially significant project-related travel changes as possible. These impacts will vary 

according to the type of project and its regional setting, but generally, a comprehensive travel 

impacts analysis (and one which will support a robust environmental justice evaluation) will 

consider the following impacts: 

 Traffic volumes 

 Vehicle miles traveled 

 Average speeds 

 Person and vehicle throughput 
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 Travel times, including some “indexed” measure such as the travel time index utilized 

by the Texas Transportation Institute in their urban traffic monitoring program for 

U.S. DOT 

 Travel time reliability, such as represented by a “buffer index” or “planning index”, 

both of which capture the extra increment of time travelers need to plan for given 

observed variability in travel conditions 

 Geographic and temporal extent of congestion, e.g., hours of congestion and miles of 

congested roadway 

 Vehicle classification/vehicle mix 

 Average vehicle occupancy 

 Mode choice/mode split 

 Accident rates and contributing factors 

 System operator and/or traveler (all modes) perceptions of safety and congestion 

 Transit ridership 

 Transit travel time 

 Transit schedule adherence/on-time performance 

 Household traveler behavior (travel diaries completed by each member of the 

household documenting routes, modes, foregone trips, times of travel, etc. with 

accompanying attitudinal surveys) 

 Congestion pricing charges paid 

An environmental justice analysis should consider how each of these travel impacts associated 

with the project in question impacts different populations (see Section 4.2.3). For example, what 

types of people use the roads where traffic volumes decreased and increased? What types of 

people made what sorts of mode choice changes and how did those changes impact the quality of 

their travel experience? Which types of people paid various amounts of congestion charging 

fees? 

Note that depending on the project, it may be useful to collect additional travel impacts—what 

could be considered first order impacts—that improve the understanding of the project impact 

(and exogenous factor impact) on the “bottom line,” or second order, impacts. Consider the 

example of a congestion pricing project that is accompanied by supporting transit improvements 

including park-and-ride lot enhancements. In that case, collecting data on park-and-ride lot 

utilization in addition to transit ridership will help explain whether it was the project (in this case 

the park-and-ride lot enhancements) or other factors (e.g., fuel prices) that drove any ridership 

changes. 

4.2.3 Consider Broadly How Impacts Differ Among a Wide Range of Users 

One of the primary recommendations is that evaluations of environmental justice should focus 

more broadly on understanding how impacts will vary for a wide range of users rather than only 
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Environmental Impact Analyses 4-11 Final Report 

on how impacts may vary based on income and minority status. Income and minority status are 

certainly very important categories to consider. However, the investigation of differential 

impacts in those areas should be part of a broader area of enquiry that permeates many different 

individual evaluation analyses (e.g., traffic, travel behavior) and which seeks to understand all of 

the ways in which some people may be impacted differently than other people by the project. 

Depending on the project, the types of differential impacts which should be considered for 

investigation include: 

 People of varying income and education levels 

 People of various racial groups 

 People with various employment status, including full-time, part-time and unemployed 

 Users of different transportation modes, including drive alone, rideshare, telecommuters, 

bicyclists, users of various transit services, and pedestrians 

 People with varying travel origins and destinations (namely residential and work 

locations) 

 Users with varying degrees of flexibility in changing their time, route or mode of travel 

 Different trip purposes 

 Travel during different days of the week and time of day 

 Frequent travelers versus occasional travelers 

 People with disabilities 

 People with differential access to various travel modes, including transit and private auto 

 New residents versus long-term residents 

 Visitors versus permanent residents. 

Understanding which of these sorts of distinctions are going to be important will have significant 

implications on the development of the evaluation plan, as the data needs associated with these 

distinctions will impact various data collection areas across the evaluation. Surveys will of 

course be significantly impacted, where it will be important to categorize the respondent 

according to all of the demographic and other characteristics of interest, but so will the collection 

of objective data such as traffic data. For example, understanding how impacts differ between 

carpoolers and single occupant vehicles could mean that collecting average vehicle occupancy 

data is important. 

4.2.4 Explicitly Consider the Uses of Charging Revenues 

Evaluations should endeavor to take into consideration how any public revenues raised by the 

congestion pricing scheme will be reinvested in any transportation programs or projects and the 

potential implications of those investments on the net environmental justice impacts of the 

pricing project. Reinvestment can significantly impact net equity effects. 
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4.2.5 Collect Demographic and other User Data Wherever Possible 

Key to understanding environmental justice impacts of congestion pricing projects is the ability 

to associate specific impacts, e.g., changes in traffic volumes and speeds, with various user 

groups (demographics), including those that vary by income, minority status, access to transit, 

access to private auto, residential location, work location, etc. Therefore, it is important build in 

as much demographic data collection as possible into all manner of travel and environmental 

data collection throughout the evaluation. This includes the obvious example of including 

demographic questions in all surveys. But other opportunities should also be investigated, for 

example, objective traffic data collected using license plate readers may—if supportable under 

applicable state and local privacy laws—also provide some understanding, through vehicle 

registration data, of the residential locations associated with the vehicles. That information in 

turn could provide some understanding of origin-destination. 
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 APPENDIX A 

Summary of Study Project Reported Travel Findings 

Study/Project Results Conclusion Major Caveats/Limitations

Simulated Pricing Field Demonstrations 

Oregon 

Mileage Fee 

Concept and 

Road User Fee 

Pilot Program 

 10% reduction in 

total VMT 

 13% reduction in 

peak hour VMT 

 Peak hour mode 

choice influenced 

by the pricing 

 Mileage price incentives can 

be expected to impact 

travelers’ total amount of 

driving, the timing of their 

trip making, and, potentially, 

their mode of travel 

 None reported 

Puget Sound 

Traffic Choices 

Study 

 7% reduction in 

total weekly vehicle 

trips 

 12% reduction in 

weekly VMT 

 8% reduction in 

total weekly travel 

time 

 13% reduction in 

weekly VMT on 

tolled roads 

 Motorists made small-scale 

adjustments in travel that, in 

aggregate, would have a 

major impact on 

transportation system 

performance 

 Households that modified 

their travel did so in many 

different ways: fewer and 

shorter vehicle trips, 

alternate routes and times 

of travel, or linking trips 

together to reduce vehicle 

use altogether 

 Responses to congestion 

charging may be 

underestimated in so 

much as some 

households who may 

have been inclined to 

avoid the peak period 

charges did not have the 

flexibility to do so 

Commute 

Atlanta 

Mileage Based 

Value Pricing 

Demonstration 

 3% reduction in 

total VMT 

 Little if any project impact. 

Observed VMT reduction 

thought to be a function of 

non-project related changes 

in travel behavior 

 Inter- and intra-household 

variability and 

demographic instability 

obscured any project 

impact 

 Higher income 

respondents were 

somewhat overrepresented in the survey 
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Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – U.S. 

Minnesota I394 MnPASS 

HOT Lanes 

 Up to 5% increase 

in peak hour 

corridor throughput 

 6% average 

increase in speeds 

in general purpose 

lanes 

 Speeds in the 

MnPASS lanes 

either remained the 

same or increased 

slightly 

 Average person 

travel time in the 

corridor decreased 

 Project benefits 

distributed relatively 

evenly amongst 

population 

 The public supported the 

HOT lane concept 

 MnPASS users were 

satisfied with toll operations 

 None reported 

San Diego I-15 

HOT Lanes 

 48% increase in 

express lane traffic 

volumes 

 76% of FasTrak 

customers would 

leave at a different 

time in the morning 

if there were no 

FasTrak. 

 I-15 pricing project 

alleviated congestion on the 

I-15 main lanes by 

redirecting an increasing 

share of volume onto the I15 express lanes 

 Dynamic pricing structure 

was able to create desirable 

redistribution of a portion of 

express-lane traffic from the 

middle of the peak to the 

shoulders 

 Exogenous factors played 

a more significant role 

than the project in regard 

total traffic increases in 

the I-15 corridor 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses A-3 Final Report 

Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – International 

The Stockholm 

Trial 

 16-24% reduction in 

peak hour traffic 

volumes 

 14% reduction in 

VKT in charging 

zone 

 33-50% reduction in 

peak hour average 

queue wait times 

 3% reduction in 

average journey 

(travel) times 

 The project was successful 

in managing congestion and 

increasing flow and 

accessibility 

 The impact of other 

projects and fuel price 

changes were not 

completely controlled 

 Car trips across the 

pricing zone 

decreased by 

20 percent 

 No projectattributable 

changes in walking, 

bicycling, 

telecommuting or 

carpooling 

 Trip chaining 

increased slightly 

 The pricing project shifted 

trips to transit 

 Exogenous factors, 

including fuel price 

changes and seasonal 

variation limit the strength 

of conclusions 

 6% increase in total 

transit ridership 

 4% decrease in the 

proportion of transit 

users that are 

satisfied with 

service quality 

 Increases in transit use met 

or exceed expectations 

 Goals for maintaining transit 

rider satisfaction were not 

achieved due to crowding 

and reduced schedule 

adherence 

 Increases in transit uses 

may also have been 

impacted significantly by 

fuel prices and economic 

development 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses A-4 Final Report 

Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – International (Continued) 

London 

Congestion 

Pricing 

 15% reduction in 

VKT after first year 

 18% reduction in 

number of vehicles 

entering the pricing 

zone 

 25% reduction in 

delays 

 14% reduction in 

journey times 

 21% increase in 

speeds 

 The project has succeeded 

in its fundamental objectives 

in reducing congestion 

 Impossible to precisely 

and definitively isolate 

project impacts from 

exogenous factors 

impacts 

 37% increase in 

passengers 

entering central 

zone by bus 

 Transit has accommodated 

significantly increased 

passenger levels with 

limited adverse impacts 

 Transit performance has 

been improved in some 

respects as a result of 

reduced roadway 

congestion and transit 

service enhancements 

 Exogenous factors have 

influenced transit 

ridership and 

performance but some 

estimation of projectspecific impacts are 

possible 

 30% decrease in 

excess bus wait 

time in first year 

 20% reduction in 

bus kilometers not 

operated due to 

congestion 

 (Central charging 

zone) 50-60% of 

trips formerly made 

by car now made 

by transit; 20-30 

percent driving 

around the charging 

zone; 8-10% 

bicycling, 

motorcycling or 

walking; <1% 

eliminated trips; 

and <1 shifted car 

trip to non-priced 

times 

 The charging scheme has 

resulted in significant travel 

behavior changes, with 

most trips shifting to transit 

 Being based largely on 

surveys, despite best 

efforts, some groups are 

likely over or underrepresented 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses A-5 Final Report 

Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – International (Continued) 

Singapore 

Area Pricing 

 44% reduction in 

traffic volumes into 

the priced zone 

 Share of HOV 4+ 

trips increased from 

8 to 19%; bus share 

increased from 33 

to 46% 

 A.m. peak speeds 

inside priced zone 

increased by 20% 

or more 

 Speeds increased 

10% on inbound 

roadways leading to 

the priced zone 

 Motorists shifted 

trips to non-priced 

times and routes 

 The pricing projects, 

coupled with other 

strategies, have been 

effective in providing lasting, 

significant reductions in 

traffic congestion 

 None reported. 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses A-6 Final Report 

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Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses B-1 Final Report 

 APPENDIX B 

Summary of Study Project Reported Environmental Findings 

Study/Project Results Conclusion Major Caveats/Limitations

Simulated Pricing Field Demonstrations 

Oregon 

Mileage Fee 

Concept and 

Road User Fee 

Pilot Program 

No Environmental Analysis Performed Puget Sound 

Traffic Choices 

Study 

Commute 

Atlanta 

Mileage Based 

Value Pricing 

Before-After Project Evaluations – U.S. 

Minnesota I394 MnPASS 

HOT Lanes 

 Small increases 

and decreases in 

one-hour average 

CO levels, ranging 

from +0.29 to -.01 

parts per million 

 HOT lanes had no 

substantial impact on air 

quality 

 None reported 

 Small projectrelated increases in 

noise levels found 

at three sites 

 HOT lanes caused no 

statistically significant 

change in average 

neighborhood sound levels 

 None reported 

 Beneficiaries of the 

HOT lane included a 

diverse population 

across all income, 

age, race/ethnicity, 

employment, and 

mode usage groups 

 No significant correlation 

between sociodemographics and project 

benefits and attitudes 

 None reported 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses B-2 Final Report 

Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – U.S. (Continued) 

San Diego I-5 

HOT Lanes 

 Estimated a.m. 

peak emissions on 

the control corridor 

increased three to 

five times more 

than emissions on 

the project corridor 

 The HOT lanes moderated 

emission levels in the 

project corridor 

 Since the impact of 

exogenous factors could 

not be precisely 

controlled or measured, 

all observed differences 

between the control and 

project corridors could not 

be attributed to the 

project. 

 On the study 

roadway, emissions 

increased 

significantly more 

on the HOT lanes 

than on the general 

purpose lanes 

 Consistent with the traffic 

data showing increased use 

of the HOT lanes 

Before-After Project Evaluations – International 

The Stockholm 

Trial 

 8.5 -14% decrease 

in emissions 

depending on the 

pollutant 

 The project had a positive 

impact on emissions 

 Weather conditions 

thought to contribute to 

emissions reductions to 

some degree 

 Minor reduction in 

noise levels 

 The project did not 

significantly impact noise 

levels 

 None reported 

 Great variation in 

congestion charges 

paid by individual 

 Wealthy, inner-city 

men pay the most 

 Higher income 

earners pay more 

than lower income 

earners 

 Commercial traffic 

and business trips 

are “net winners” 

 How pricing revenues are 

redistributed is the key to 

total cost-benefit effects on 

different people 

 None reported 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses B-3 Final Report 

Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – International (Continued) 

London 

Congestion 

Pricing 

 Emissions 

decreased by 

between 13 and 

16% depending on 

the pollutant, for the 

original project 

 Emissions 

decreased by 

between 2 and 6%, 

depending on the 

pollutant, for the 

Western Extension 

 The project had a positive 

impact on air quality 

 Roadside monitoring 

results inconclusive 

(unable to differentiate 

project impacts from 

exogenous factors) 

 Calculated emissions did 

estimate project impacts 

 No significant, 

project-attributable 

changes in noise 

levels 

 The project did not impact 

perceptible noise levels 

 Roadside monitoring 

results inconclusive 

(unable to differentiate 

project impacts from 

exogenous factors) 

 Significant reductions in 

traffic volumes are 

necessary to reduce 

noise levels (to get the 

smallest discernable 

change in noise levels—

3 dBA—traffic volumes 

must be cut in half) 

 Actual impacts 

were less than 

travelers 

themselves 

expected 

 Issues of greatest 

concern are not 

project related 

 Majority of 

respondents found 

the charge 

affordable 

 No significant adverse and 

disproportionate impacts on 

environmental justice 

populations 

 Despite best efforts, 

some groups are likely 

over or underrepresented in data 

collection 

 Perception and attitude 

data are not as “scientific” 

as quantitative data 
Synthesis of Congestion Pricing-Related October 18, 2010 

Environmental Impact Analyses B-4 Final Report 

Study/Project Results Conclusion Major Caveats/Limitations

Before-After Project Evaluations – International (Continued) 

Singapore 

Area Pricing 

 CO reductions in 

a.m. peak, monthly 

average NOx 

reductions, and 

reduced smoke and 

haze (immediately 

after first project) 

 Project had a positive 

impact on air quality 

 Declines in smoke and 

haze could not be fully 

attributed to the project 

 Some people did 

not benefit from the 

initial project, e.g., 

those for whom the 

cost of the charge 

is not off-set by 

reduced travel time 

 After some initial 

crowding, transit 

riders enjoyed 

better service as 

service was 

expanded over time 

 Middle income 

travelers felt 

adversely effected 

 Shifts to transit 

were uniform 

across income 

groups 

 Although not all people 

benefitted equally, overall, 

the project did not 

significantly and 

disproportionately impact 

lower income people 

 None reported 
 
U.S. Department of Transportation 

Federal Highway Administration 

Office of Operations 

1200 New Jersey Avenue, SE 

Washington, DC 20590 

Toll-Free "Help Line" (866) 367-7487 

www.ops.fhwa.dot.gov

FHWA-HOP-11-008