EFFORTS To Reduce Co 2 in the Transportation Field

REDUCING GREENHOUSE EMISSIONS AND
FUEL CONSUMPTION– Sustainable Approaches for Surface Transportation –Susan A. SHAHEEN, Ph.D.

Timothy E. LIPMAN, Ph.D.

	Honda Distinguished Scholar in Transportation  	
Research Director
University of California, Davis, & 	 Transportation Sustainability Research Center
Policy and Behavioral Research Program Leader, California PATH	
University of California, Berkeley
University of California, Berkeley	California, USA
	California, USA(Received March 14, 2007)

Climate change is rapidly becoming known as a tangible issue that must be addressed to avoid major environmental consequences in the future. Recent change in public opinion has been caused by the physical signs of climate change–melting glaciers,
rising sea levels, more severe storm and drought events, and hotter average global temperatures annually. Transportation is a major
contributor of carbon dioxide (CO2) and other greenhouse gas emissions from human activity, accounting for approximately 14 percent of total anthropogenic emissions globally and about 27 percent in the U.S.
Fortunately, transportation technologies and strategies are emerging that can help to meet the climate challenge. These include
automotive and fuel technologies, intelligent transportation systems (ITS), and mobility management strategies that can reduce thedemand for private vehicles. While the climate change benefits of innovative engine and vehicle technologies are relatively well understood, there are fewer studies available on the energy and emission impacts of ITS and mobility management strategies. In the future,
ITS and mobility management will likely play a greater role in reducing fuel consumption. Studies are often based on simulation models, scenario analysis, and limited deployment experience. Thus, more research is needed to quantify potential impacts. Of the nine
ITS technologies examined, traffic signal control, electronic toll collection, bus rapid transit, and traveler information have been deployed more widely and demonstrated positive impacts (but often on a limited basis). Mobility management approaches that haveestablished the greatest CO2 reduction potential, to date, include road pricing policies (congestion and cordon) and carsharing (shortterm auto access). Other approaches have also indicated CO2 reduction potential including: low-speed modes, integrated regional
smart cards, park-and-ride facilities, parking cash out, smart growth, telecommuting, and carpooling.
Key Words: Greenhouse gas emissions, Carbon dioxide, Vehicle technology, Alternative fuels, Intelligent transportation systems,
Mobility management

1. INTRODUCTION
The use of energy accounts for a major fraction of
all anthropogenic emissions of greenhouse gases (GHGs),
and in most industrialized countries transportation fueluse produces a major fraction of all energy-related emissions. In the U.S., for example, emissions of GHGs fromtransportation accounts for over 27 percent of anthropogenic GHG emissions, while globally, transportation contributes approximately 14 percent of GHG emissions1.
Figure 1 shows the various sources of global GHG emissions from human activity and which specific GHGs areultimately emitted.
Furthermore, transportation sector emissions are
expected to increase rapidly over the next few decades.
The International Energy Agency (IEA) projects thatenergy use and CO2 emissions in developed countries

IATSS Research Vol.31 No.1, 2007

will rise by approximately 50 percent between 2000 and
2030. Emissions in developing countries are expected torise even faster, in some cases (such as in China and Indonesia) more than doubling between 2000 and 20202.
These increases are due to a combination of increases inpersonal travel and goods movement, coupled with continued heavy reliance on fossil fuels for transportationenergy.
Worldwide personal transportation is expected toincrease 1.7 percent annually from 2000 to 2050, whileworldwide freight transportation is expected to increaseby 2.3 percent annually during the same timeframe.
Worsening this issue, transit modal share has decreased
due to lower density land use and the greater convenienceof private vehicles3. Given these trends, solutions areneeded to reduce emissions and energy consumption
from the transportation sector, now widely believed to be

1.6%

9.9%

Air

Residential Buildings

9.0%

10.4%

3.9%

3.4%

Other fuelCombustion

Industry

Fugitive Emissions

Industrial Processes

3.6%

Waste

1.0%
1.0%

1.4%

1.5%
0.9%

2.0%
1.6%

Landfills
Wastewater, Other Waste

5.1%

6.0%

1.4%

Rice Cultivation
Other Agriculture

Livestock & Manure

Agriculture Soils

Agricultural Energy Use

Deforestation
18.3%
Afforestation-1.5%
Reforestation-0.5%
Harvest/Management 2.5%
-0.6%
Other

Oil/Gas Extraction,
6.3%
Refining & Processing

1.9%

5.0%

Other Industry
Coal mining

3.8%

CementT&D Losses

4.8%

Chemicals

1.0%

1.4%

Food & Tobacco

Machinery
Pulp, Paper & Printing

3.2%

Aluminum/Non-Ferrous Metals

Iron & Steel

Unallocated Fuel Combustion 3.5%

Commercial Buildings 5.4%

Nitrous Oxide(N 2O) 8%

Methane(CH 4) 14%

Carbon Dioxide(CO 2) 77%

Gas

IATSS Research Vol.31 No.1, 2007

Fig. 1 Flow chart of global GHG emissions by sector and end use activity

Sources & Notes: All data is for 2000. All calculations are based on CO2 equivalents, using 100-year global warming potentials from the IPCC
(1996), based on a total global estimate of 41,755 MtCO2 equivalent.

13.5%

Agriculture

Land Use Change18.2%

24.6%

Electricity & Heat

Rail, Ship, & Other Transport 2.3%

9.9%

Road

Transportation

E N E R G Y

13.5%

End Use/Activity

SectorWorld GHG Emissions Flow Chart

HFCs, PFCs,
SF6 1%

REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –S. A. SHAHEEN, T. E. LIPMANEFFORTS To Reduce Co 2 in the Transportation Field



IATSS Research Vol.31 No.1, 2007

2. BACKGROUND
Global emissions of CO2 and other GHGs havebeen steadily increasing with population growth and development. The Intergovernmental Panel on Climate
Change (IPCC) has examined the potential global temperature impacts of future GHG emissions scenarios,
including those with unabated emissions and those where
atmospheric concentrations of CO2 are stabilized at 450
and 550 parts per million (ppm) (compared with an actual level of 383 ppm at the start of 2007). As shown in
Figure 2, stabilizing atmospheric concentrations at 450
ppm implies a mean temperature change of 1-2 °C by
2100, while stabilizing CO2 concentrations at 550 ppm
implies a 1.5-3 °C increase. Meanwhile, the unabated“Special Report on Emissions Scenarios (SRES)” highemissions case results in a mean temperature increase ofover 5 °C by 2100 4.
Over the past few years, dramatic weather events
such as hurricanes and droughts along with the alarming
breakup of polar ice sheets have many scientists andmembers of the general public concerned about the potential impacts of climate change. Potential effects include rising ocean levels, more severe tropical storms andhurricanes, more pronounced heat waves, droughts, andwildfires, and a wide range of other potential impacts onhumans and wildlife in environments that are likely tofeel the strongest effects (e.g., arctic/polar regions, deserts/drought prone areas, etc.).
Concern about the steady increase in global GHG
emissions has been most directly addressed at the international level, through the efforts of the IPCC and theUnited Nations Framework Convention on Climate
Change (UNFCCC). A specific set of GHG emission reduction goals, known now as the “Kyoto Protocol,” was6

Temperature change (°C)

contributing to climate change.
The production and use of fuels for transportation
also results in emissions of other important GHGs besides CO2, including methane (CH4) and nitrous oxide(N2O). These emissions can be significant, especially forsome types of vehicles and fuels. Furthermore, other aspects of transportation, such as the use of refrigerants forautomotive air conditioners, also cause significant releases of GHGs. While smaller in quantity, these emissions areimportant because of the relatively high “global warming
potential” values of these gases (i.e., on a 100-year assessment basis a CH4 molecule has about 23 times theeffect of a CO2 molecule, and an N2O molecule has about
296 times the effect of a CO2 molecule4). For conventional vehicles, these non-CO2 GHG emissions can contribute
approximately a quarter of the value of overall vehicle
emissions, but for alternative fuel vehicles the contribution can be much higher or lower, in the range of 1 to 57
percent5.
In light of the importance of the transportation sector as an emitter of GHGs, and in the face of growing
concern about climate change, analysts have been evaluating long-term transportation and energy policies fortheir potential impact on global climate change. This
paper provides an overview of transportation GHG emissions and a range of emerging technologies that could
help to reduce negative transportation sector impacts andultimately contribute to climate stabilization. These technology approaches include: 1) engine technology andfuels, 2) intelligent transportation systems (ITS), and 3)
mobility management. The authors review each of theseareas and their GHG reduction potential, as possible. It is
important to note that the ITS and mobility management
sections are based on limited study, deployment experience, and overall understanding.
There are five main sections to this article. First, theauthors provide a background discussion on global climate change and climate change policies since the early
1990s. Next, engine technologies and fuels are described
as a key supply-side strategy to reducing GHG emissions
and fuel consumption. Third, nine ITS technologies are
explored (consisting of a mix of supply and demand
management approaches). In the following section, nine
mobility management strategies (demand-side approaches aimed at changing behavior) are presented. They range
from more traditional approaches, such as carpooling andpark-and-ride facilities, to more innovative policy andtechnology solutions including: road pricing policies,
telecommuting, and smart cards. Finally, the authors
present conclusions.

5
4
3

SRES high
SRES low
IPCC 450 ppm high
IPCC 450 ppm low
IPCC 550 ppm high
IPCC 550 ppm low
Hansen 475 ppm
Hansen 560 ppm

2
1
0
1980

2000

2020

2040
Year

2060

2080

2100

Fig. 2 IPCC mean average global temperature rise
predictions by emissions scenario (°C)4

REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –established during the UNFCCC 3rd “Council of the Parties” (or “COP-3”) meeting of the United Nations on climate change in Kyoto, Japan, in December 1997. The
protocol has now been ratified by 168 countries, but notably not by the U.S. or Australia, which together accountfor over 22 percent of global emissions1. If ratified, theagreement would have the U.S. reduce GHG emissions
by seven percent, relative to 1990 levels, between 2008
and 2012, compared with an average for all nations of afive percent reduction below 1990 levels. The COP meetings have continued steadily since Kyoto to advance international progress in reducing GHG emissions, withthe latest meeting being the COP-12 conference in Nairobi, Kenya in Fall 20066.
The IPCC has made increasingly firmer statements
over the past two decades about its certainty with regard
to the effects of the large magnitude of GHG emissions
that are emitted each year around the globe from humanactivity.
In 1990, the IPCC said:“The unequivocal detection of the enhanced greenhouse effect from observations is not likely for a decade ormore”7.
Then, five years later, the IPCC stated that:“The balance of evidence suggests a discernablehuman influence on global climate”8.
Six years later, in 2001, the IPCC took an even stronger
stance with its statement that:“There is new and stronger evidence that most of
the warming observed over the last 50 years is attributableto human activities4.
Most recently, in early 2007, the IPCC made its strongest
statement yet on the likelihood of human-induced climatechange:“Most of the observed increases in globally averaged temperatures since the mid-20th century is very likely
due to the observed increase in anthropogenic greenhousegas concentrations”9.
Recently, the “Stern Review on the Economics of
Climate Change” conducted by the treasury of the U.K.
concluded that the likely future economic impacts of climate change are far greater than the cost of stabilizing
emissions. The report estimates that the costs of stabilizing atmospheric CO2 concentrations at around 550 ppm
would be about one percent of global gross domestic
product by 2050. Meanwhile the report estimates that the

S. A. SHAHEEN, T. E. LIPMAN

economic cost of a “business as usual” scenario of continued increases in emissions could be as high as thevalue of reducing global consumption by five to 20 percent. The report concludes that the costs of taking action
are potentially much lower than those of inaction and that
immediate steps are needed to have a chance of restraining CO2 concentrations to the 550-ppm level10.
While mandatory actions to reduce GHG emissions
in the U.S. have been lacking at the national level, U.S.
state-level activities have progressed significantly over the
past few years. California has recently taken an aggressive policy stance to limit GHG emissions, and several
other states are pursuing similar courses, particularly in
the Northeast with the Regional Greenhouse Gas Initiative (RGGI). Currently, Connecticut, Delaware, Maine,
New Hampshire, New Jersey, New York, and Vermont are
participating in the RGGI effort, which is targeted at developing a cap-and-trade program for CO2 emissions
from the electrical power sector11.
The most dramatic policy measure at the U.S. statelevel has been the passage of the California Global Warming Solutions Act (Assembly Bill (AB) 32), which seeks
to limit GHG emissions from a wide range of industrial
and commercial activities. AB 32 requires that California’s GHG emissions be reduced to 1990 levels by 2020
through an enforceable statewide cap and in a mannerthat is phased in starting in 2012 under rules to be developed by the California Air Resources Board (CARB).
AB 32 requires that CARB use the following principles to implement the California GHG emissions cap:
• Distribute benefits and costs equitably;• Ensure that there are no direct, indirect, or cumulative
increases in air pollution in local communities;• Protect entities that have reduced their emissions
through actions prior to this regulatory mandate; and• Allow for coordination with other states and countries
to reduce emissions.
CARB is required to adopt the formal AB 32 regulations by January 1, 2008, and to produce a plan forachieving the targeted emission reductions, through market mechanisms and other actions, by January 1, 200912.
The expectation is generally for a plan that includes amarket-based emission credit-trading scheme under thestatewide cap, marking the first serious effort to address
climate change at a large scale in the U.S.
Finally, a recent international meeting on greenhouse gases from the transportation sector resulted in the“Asilomar Declaration” as a consensus statement amonga high level group of scientists, engineers, and policy
IATSS Research Vol.31 No.1, 2007



EFFORTS To Reduce Co 2 in the Transportation Field

analysts in the transportation and environmental fields.
While focused on the U.S., rather than globally, this declaration is strongly worded and instructive for other settings as well. The declaration reads:
DECLARATION 1: It is the consensus of the 10th
Biennial Conference on Transportation and Energy
Policy that climate change is real. Transportationrelated GHG emissions are a major part of thisglobal problem, and they must be reduced.
DECLARATION 2: U.S. national policy has so
far failed to adequately address the role of transportation in climate change. This must be remedied.
DECLARATION 3: By judiciously crafting aportfolio of solutions, it is possible to reduce transportation-related GHG emissions while creating anefficient and effective transportation system forcurrent and future generations.
Various papers presented at the 10th Biennial Conference on Transportation and Energy Policy in relation
to the Asilomar Declaration examine aspects of the transportation and climate change nexus and were compiled
into a book. These include issues such as potential policy
measures to restrain emissions (cap-and-trade, feebates,etc.), transportation finance, vehicle technology and consumer response, and “peak oil” and energy considerations13.

3. ENGINE TECHNOLOGIES & FUELSRoad transportation, as shown in Table 1, accounts
for the majority of transportation-sector GHG emissions.
As a result, motor vehicles are often among the first targets of efforts to reduce emissions from the transportation sector.
Table 1 Transportation sector contributions tooverall GHG emissions1
Transportation Sector

Global

U.S.

Road

9.9%

21.6%

Air

1.6%

3.3%

Rail, Ship, and Other
Transportation

2.3%

2.3%

13.8%

27.2%

Total Contribution

A wide range of technologies exists to address GHG
emissions from vehicles, with some being commerciallyavailable and others still under development. Efforts to

10

IATSS Research Vol.31 No.1, 2007

address GHG emissions through the introduction of newvehicles can be highly effective in the long term, but they
are somewhat slow due to the nature of motor vehicle
fleet turnover and the penetration of new vehicles into theoverall vehicle fleet. Some new vehicle technologies also
suffer from limited refueling infrastructure (e.g., biofuels
and hydrogen) and others suffer from other important
limitations (e.g., short driving range and long refuelingtime for battery electric vehicles). These intricacies makethe introduction of new vehicle and fuel types complex,
as this involves a combination of technological, economic, social, and political factors.
The most straightforward way to reduce GHGs
from motor vehicles is to simply mandate greater vehicle
fuel economy. This translates more or less directly into
reduced CO2 emissions, but may or may not significantly
affect emissions of other GHGs such as CH4, N2O, andrefrigerants. In the U.S., Corporate Average Fuel Economy (CAFE) standards have been constant since the mid1980s, despite considerable technological progress overthe past twenty years. Standards for light trucks havebeen increased slightly in recent years. Other nations andregions, such as the European Union, Japan, and China,also have vehicle fuel economy standards that are currently somewhat more stringent than those in the U.S. In
the U.S., the shift toward purchases of light trucks andsport-utility vehicles has resulted in an actual decrease in
on-road vehicle fuel economy, from a peak of 26.2 miles
per gallon on average in 1987 to 24.6 miles per gallon in
200414.
With regard to the introduction of new fuel andvehicle types, GHG emissions can be addressed throughthe introduction of new fuels (e.g., electricity, biofuels,hydrogen, etc.), different “end-use” technologies (e.g.,better or different “prime mover” engines and motors,
energy storage systems, etc.), or a combination of both
fuel and vehicle changes. For example, more efficienthybrid vehicles can be developed that burn gasoline, but
the vehicles could also be designed to burn a fuel mainlycomposed of ethanol, biodiesel, natural gas, or hydrogen.
Methods of producing some new types of transportation fuels (especially electricity and hydrogen) at large
central plants have the potential of being able in principle
to separate out and “sequester” the CO2 emissions, though
the cost and feasibility of this is still being proven. Somefuels can also be produced in a more decentralized fashion, such as small-scale production of hydrogen throughsteam methane reforming; however, these CO2 emissions
would be harder to capture and remove.

REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –The primary types of vehicle technologies currently
being explored include:• Combustion engine (typically Otto, Diesel, or Atkinsoncycle) vehicles running on gasoline, diesel, bio-diesel,
ethanol, methanol, compressed natural gas, liquefied
propane gas, or hydrogen (or some blend of these fuels);• Electric-drive vehicles, powered by batteries, ultracapacitors, fuel cells, or a combination of power sources;• Hybrid gasoline-electric vehicles that combine both of
the above, with a wide range of potential ratios between the combustion engine and electric drive; and• Other “kinetic” storage/propulsion systems, such as
those based on compressed air or mechanical flywheels.

S. A. SHAHEEN, T. E. LIPMAN

Figure 3 shows the expected GHG emissions from
19 different vehicle type and fuel combinations, compared with current and future gasoline vehicles. Theseestimates are based on the “Greenhouse Gases, Regulated
Emissions, and Energy Use in Transportation” (GREET)
model developed at Argonne National Laboratory15.
Other full fuel cycle GHG emission models, such as the
UC Davis “Lifecycle Emissions Model,” typically show
similar results, but with some differences due to differing
input assumptions that can then get magnified as total
emissions are calculated through the fuel-chain analysis16.
As shown in this figure, the GREET model estimates that conventional gasoline vehicles produce about

PTW

1,000
OiI

Natural Gas

Ethanol

WTP

Electricity

GHG Emissions, g /mile

800
600
400

Net Result

200
0

C
ur

re
n
Fu t G
tu V
re
D GV
G IC
so I D
lin
V
e
D
H
ie
EV
se
St
lH
at
io
EV
St n
at NG CNio
G
St n N to H V
at
G
2
io
n to H ICE
N
G 2H
to
E
St
H V
C
or 2 F
at
n
i
E CV
St on
at Ce Ce 85
io
ll
F
ll
St n C . Et . E8 FV
O
at
el
5
H
io
l
FF
n . EttoVCel OH H2
l.
I
t
C
o
Et
E
H
2
R
U O
en .S H to HE
ew . kH V
ab Wh 2 F
le
to CV
H
R
U k
en .S Wh 2 I
ew . kto CE
ab Wh H2
le
IC
t
k o
E
R
U Wh H2
en .S
H
t
E
.
o
ew
k
V
ab Wh H2H
let
kW o H EV
h 2F
U to H CV
.S
.k 2F
W
C
V
h
BP
EV

-200

Notes
BPEV : battery-powered electric vehicle
CNGV : compressed natural gas vehicle
DI CI DV : direct-injection compression-ignition diesel vehicle
E85 : a mixture of 85% ethanol and 15% gasoline (by volume)
FCV : fuel-cell vehicle
FFV : flexible fuel vehicle
GV: gasoline vehicle
HEV : hybrid electric vehicle
ICE : internal combustion engine
NG : natural gas
PTW : pump-to-wheels
WTW : well-to-wheels
WTP : well-to-pump

Fig. 3 GREET model GHG emissions estimates for conventional and alternative fuel lightduty vehicles (grams/mile)15
IATSS Research Vol.31 No.1, 2007

11

EFFORTS To Reduce Co 2 in the Transportation Field

440 grams per mile on a full fuel cycle (or “well-to-wheel”)
basis. Technological options exist to almost eliminate
these emissions, through the use of renewable energy to
produce electricity or hydrogen. However, these renewable fuel pathways are at present relatively expensive
for both vehicles and fuels (with the exception of wind
generated electricity in some areas) and include otherbarriers, such as limits on vehicle driving range and (forelectricity) refueling time.
Incremental vehicle technology options, such as
operating on diesel fuel or “hybridizing” the combustion
engine with an electric motor and battery system, can reduce GHG emissions to 220 to 300 grams per mile or toabout 57 to 65 percent of the emission levels expectedfrom future gasoline vehicles. Compressed natural gas(CNG) vehicles offer similar emission reductions toabout 300 grams per mile.
Vehicles operating on ethanol (with 85 percent ethanol mixed with 15 percent gasoline) produce similar
GHG emission levels as CNG vehicles and diesel vehicles or about 300 grams per mile. However, if the ethanol
can be made from “cellulosic” rather than corn-basedsources, emissions can be dramatically reduced to about
100 grams per mile.
Hydrogen-powered vehicles can either burn the hydrogen directly in a combustion engine or convert it toelectricity using a fuel cell system to drive an electricmotor. Emissions from these vehicles can vary dramatically depending on how the hydrogen is produced. On
one hand, as noted above, emissions can be nearly eliminated if the hydrogen is produced from renewable sourcesof electricity and the electrolysis process of splitting water molecules. Using cellulosic ethanol to produce hydrogen reduces emissions to 100 to 150 grams per mile orsimilar levels as burning ethanol. However, if instead ofrenewable electricity, hydrogen is made through electrolysis using the current mix of generating sources for the
U.S. power grid, GHGs are significantly increased toabout 500 grams per mile (fuel cell vehicle), 750 grams
per mile (hydrogen combustion hybrid), or even 980
grams per mile (hydrogen combustion without hybrid).
Finally, vehicles running directly on electricity withbatteries also have emissions that vary greatly with how
the electricity is produced. Emissions can range fromnear zero, again with renewable electricity, to about 240
grams per mile with a typical U.S. power grid fuel mix.
3.1

Summary
In summary, both incremental and revolutionary
options are possible for reducing the GHG emissions im-

12

IATSS Research Vol.31 No.1, 2007

pacts from motor vehicles. Incremental approaches are
estimated to be capable of reducing emissions by up to
about 25 percent over a several year period2. More dramatic and revolutionary options, such as powering electric vehicles from solar or wind power or converting thatelectricity to hydrogen to power fuel cell vehicles, could
essentially eliminate GHG emissions from the full vehicle fuel cycle. However, there are major barriers to sucha dramatic transition, including economic, technical, andconsumer acceptance obstacles. To address the transportation energy and climate change challenge, both nearterm options–with more modest impacts but with a highchance of success–and longer-term but more dramatic
options should be considered. Based on the resource base,land form, and demographic and socioeconomic conditions in a given setting, options for introducing new fuels
and vehicle technologies can be selected that are the mosteffective and likely to be adopted.

4. INTELLIGENT TRANSPORTATION SYSTEMSIntelligent transportation system (ITS) technologies include state-of-the art wireless, electronic, and automated technologies. Collectively, these systems havethe potential to integrate vehicles (transit, trucks, and personal vehicles); system users; and infrastructure (roads
and transit). Automated and in-vehicle technologies include precision docking for buses, automated guideways,
and collision avoidance systems. When ITS is applied tohighway and transit system management and vehicle design, it can reduce fuel consumption and emissions by:• Facilitating optimal route planning and timing;• Smoothing accelerations/decelerations and stop-andgo driving;• Reducing congestion;• Enabling pricing and demand management strategies;• Increasing attractiveness of public transportation modeuse;
• Adjusting vehicle transmission for varying road conditions and terrain; and• Facilitating small platoons of closely spaced vehicles(i.e., safer vehicles could enable weight reduction without compromising occupant safety).
While ITS technologies are still in the early phasesof deployment, many have the potential to reduce energy
use and CO2 emissions. During the last decade, fuel consumption (and to a lesser extent CO2) impacts of a wide
range ITS technologies have been considered including:1) traffic signal control, 2) ramp metering, 3) automatedREDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –S. A. SHAHEEN, T. E. LIPMAN

Table 2 ITS strategies associated with reduced fuel use and CO2 emissions
ITS Area

Definition

Traffic signal
controlTraffic signal controls can integrate freeway and surface street systems to improve traffic flow and vehicular andnon-motorized traveler safety and provide priority services for transit or high occupancy vehicles. They can manage
traffic speeds, vehicle merging and corridor crossings, as well as interactions among vehicles and low-speed or
non-motorized modes, such as bicycles, pedestrians, and wheelchairs at intersections.

Ramp metering

Ramp metering is one of several ITS technologies designed to manage traffic flow. The goal of ramp metering is tosafely space vehicles merging onto a highway, while minimizing speed disruptions to existing flows. Considerations
include: 1) public misunderstanding and system dislikes, 2) overflow of cars onto surface streets while waiting toenter ramps, and 3) driver use of arterial streets to avoid ramp meters. The most significant benefit of ramp metering
is passenger time savings.

Automated
speed
enforcement

Automated speed enforcement (ASE), also known as photo-radar or speed camera enforcement, combines speeddetecting radar and light detection and ranging (LIDAR) units with image capturing technologies, such as film anddigital cameras17. Photographs of vehicles and/or drivers taken at the time of the violation, along with data from theradar device, are used as evidence in the issuance of citations18. ASE programs have been widely applied inAustralia, France, Germany, and the U.K. to address speeding-related safety problems19. In the U.S., ASE programs
are currently operating in only six states and in Washington, D.C., and most of these are located on residential
streets and not highways20.

Incident
management

ITS traffic surveillance technologies—such as radar, lasers, and video image processing used to collectinformation—can help to reduce detection and incident clearance costs. Incident management consists of three key
areas: traffic surveillance (incident detection and verification), clearance, and traveler information. Also covered bythis area are emergency management services, which coordinate local and regional incident response to traffic
accidents, security threats, and hazardous material spills. ITS technologies employed can include traffic surveillance,
digital and dispatch communications (including route guidance to the site of an incident), and signal priority(optimization of traffic signal timings along routes traveled by emergency vehicles).
ITS contributions to incident management include improved surveillance, verification, and dispatch to manage an
incident. The use of changeable message signs (CMSs) and personal communication devices, such as mobile
phones and personal digital assistants (PDAs), can assist with early notification for upstream drivers resulting in
reduced incident-related congestion, as drivers have more time to select an alternate route.

Electronic tollcollection

Electronic toll collection (ETC) allows for electronic payment of highway and bridge tolls as vehicles pass througha toll station. Vehicle-to-roadside communication technologies include electronic roadside antennas (or readers)and pocket-sized tags containing radio transponders (typically placed inside a vehicle’s windshield).

Traveler
information

ITS-based traveler information technologies—such as traffic surveillance and transit management systems—
support the collection, processing, and dissemination of real-time information about travel modes and conditions.
The objective of traveler information is to provide the traveling public with information regarding available modes,
optimal routes, and costs in real time either pre-trip or en-route via in-vehicle information and CMSs along roadsides
or at transit stations. Effective traveler information requires the accurate collection and dissemination of real-timetravel information to transportation managers and the public to aid them in making informed decisions about travel
time, mode, and route. A wide array of ITS technologies assist with traveler information including in-vehicle guidance,
web sites, mobile phones, PDAs, and CMSs to distribute user information.

Bus rapid transit

Bus rapid transit (BRT) encompasses the use of a series of ITS technologies, route planning, exclusive rights-ofways, and management to improve service—each of which can reduce travel times. Increases in bus ridership due
to BRT implementation have been reported in the U.S., Australia, and Europe. If a mode shift occurs from a single
occupancy vehicle to BRT, there is an efficiency benefit. If the previous mode was non-motorized, such as walking
or cycling, the impact on fuel efficiency/CO2 emissions is negative. If additional riders are attracted from anotherbus route, the impact is neutral.

Weigh-in-motion
technologies

The purpose of automatic identification and weigh-in-motion (WIM) technologies is to enable the weighing andcataloging of trucks without causing vehicles to stop and queue in line. A WIM scale imbedded in the pavement
triggers a camera when an overweight truck passes over (so that a citation may be issued later). In addition, thiscan result in fewer trucks being forced to bypass weigh stations due to full queues at static scales.

Vehicle control
technologies

ITS technologies that automate vehicle control systems aim to improve vehicle safety, efficiency, and comfort.
These technologies include intelligent cruise control, speed alert, collision avoidance, anti-lock brakes, electronicsystem malfunction indicators, and automated highway systems (e.g., platooned vehicles). The concept behind
automated highways is to employ technologies that facilitate vehicle-to-vehicle and vehicle-to-roadsidecommunication to improve safety and system efficiency, called Vehicle Infrastructure Integration (VII). “VII offers theopportunity to know much more about traffic and roadway conditions than ever before. Vehicles equipped with VII
technology will be able to anonymously send information that includes travel time and environmental conditions”21.
In this way, vehicles can operate in very close proximity to each other.

IATSS Research Vol.31 No.1, 2007

13

EFFORTS To Reduce Co 2 in the Transportation Field

Table 3 ITS energy and CO2 impacts: a summary of early findings
ITS Strategy

Energy/CO2 Emission Impacts

Traffic signal
control

Overall, traffic signal control studies reveal fuel savings ranging between 1.6 to 50 percent, with most results at lessthan 20 percent 23-27.
In addition, results from a signalized intersection, using a real-time control strategy, resulted in a “four percent
reduction for CO2 emissions in peak traffic, corresponding to a 14 percent reduction in the part of costs due to stops
and delays.” These effects are reduced by approximately one half when traffic is fluid24 (p. 4).

Ramp metering

Emission and fuel consumption impacts of ramp meters are mixed. Ramp metering causes vehicles on ramps tostop-and-go, and this behavior consumes more fuel than free flow driving. Ramp metering also results in smoothervehicle flow on freeways because vehicles enter in a staggered and controlled manner, reducing bottlenecks thatwould otherwise impede traffic. This results in reduced fuel consumption. These two factors (increased stop-and-go
traffic on on-ramps and decreased traffic flow disruption on highways) appear to negate each other28.

Automated
speed
enforcement

The authors identified only a few estimates of CO2 reduction due to automated speed enforcement (ASE). Meers
and Roth (2001) found that speed cameras saved 400 kilotonnes of CO2 per year between 1998 and 2000 in
Queensland, Australia29 (as cited in Haworth and Symmons30). In addition, an ASE application employed to reduce
vehicle accidents and improve traffic flow, particularly stop-and-go traffic, in the Kaisermühlen Tunnel in Austria
has been projected to reduce more than 12,000 tons of CO2 emissions between 2003 and 201331.

Incident
management

Improved incident management has the potential to decrease fuel consumption by reducing the delay andcongestion associated with blocked traffic. While incident delay reductions are limited, model calculations for a
Maryland initiative (called CHART) have shown fuel savings of 5.06 million gallons per year32.

Electronic tollcollection

Studies show that electronic toll collection (ETC) saves time and reduces energy consumption and emissions by
reducing the stop-and-go traffic associated with vehicle queues approaching toll plazas, stopping to pay a toll, andaccelerating to rejoin regular traffic flow3.
One recent study along the New Jersey Turnpike found savings of 1.2 million gallons of fuel per year due to reduced
delays at toll plazas employing ETC. Approximately three-fourths of the reported savings accrued to passenger
cars and one-fourth to commercial vehicles33.

Traveler
information

The actual impact of traveler information on fuel consumption and CO2 emissions depends on a number of factors.
For example, if ITS technologies assist drivers with route selection and guidance, benefits will likely be greater theless familiar a driver is with an area. Fuel economy benefits of route guidance systems could reduce non-optimalroute driving and save up to 10 percent of miles driven and proportional fuel consumption34. The timeliness anddelivery of information will also influence the degree to which travelers use it and subsequent energy/CO2 emission
impacts. Benefits might result from mode shifts (e.g., from a single occupancy vehicle to transit or bicycle) andsavings proportional to travel time reductions achieved by taking alternate routes.

Bus rapid transit

Bus ridership increases due to bus rapid transit (BRT) implementation in five cities ranged from 18 to 76 percent(Houston, Los Angeles, Adelaide, Brisbane, and Leeds)35. Furthermore, faster journey times and reduced
acceleration, deceleration, and idle times—resulting from fewer stops and signal priority—have been shown to
reduce fuel consumption. Signal priority modeling results indicate a five percent reduction in fuel consumption36.
Using data from the 2001 National Household Survey and emissions data from the Department of Environmental
Protection and the Energy Information Administration, Vincent and Jerram37 concluded a BRT system, employing
40-foot compressed natural gas buses, provides the greatest decrease in CO2 emissions when compared to lightrail and 40- and 60-foot hybrid diesel BRT buses37. The 40-foot CNG buses used in a BRT system exceed light rail
CO2 reductions by approximately 300 percent.

Weigh-in-motion
technologies

Simulation modeling and on-road testing reveal increased fuel efficiency due to weigh-in-motion (WIM)
technologies38. It is important to note, however, that an expert interview with California Air Resources Board (CARB)
mobile sources enforcement personnel revealed that WIM technologies that identify gross polluters still require
more research and are not very reliable at present. For instance, remote sensing technology used to detect CO2
emissions is not effective on multi-lane roads or freeways (Denise Allen, unpublished data, August 2006).

Vehicle control
technologies

One recent simulation study showed fuel savings ranging from 8.5 to 28.5 percent when 10 percent of vehicles ina lane are equipped with intelligent cruise control39. In-vehicle electronics that smooth acceleration/deceleration
and anticipate changes in terrain could also reduce fuel consumption 34, 40. Furthermore, simulations of automatedhighways indicate a five to 15 percent reduction in fuel consumption due to aerodynamic drafting effects41.

14

IATSS Research Vol.31 No.1, 2007

REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –speed enforcement (ASE), 4) incident management, 5)
electronic toll collection (ETC), 6) traveler information,7) bus rapid transit (BRT), 8) commercial vehicle weighin-motion (WIM), and 9) vehicle control technologies.
Definitions of each of these areas appear in Table 2 (onpage 13). This array of ITS technologies is the focus of
this section. At present, ITS impacts—including benefits,
unintended consequences, and aggregate effects—arestill not well understood.
In 1998, the U.S. Environmental Protection Agency(U.S. EPA) released a technical report that examined
methodologies and research efforts aimed at evaluating
the energy and environmental impacts of ITS. The reportconcluded that it was exceptionally challenging to assess
ITS fuel consumption and emission impacts due to thecomplex relationship among ITS, travel behavior, andtransportation system management22. In addition, impacts vary among regions that reflect different traffic patterns and system use. While traffic simulation and travel
demand models can aid in this understanding, more research is needed23.
In Table 3 (on page 14), the potential energy andCO2 impacts of nine ITS strategies are examined. Data
presented typically reflect early modeling, field test, anddeployment findings. While this analysis spans a wide
range of ITS approaches, the literature on the energy andCO2 impacts of ITS is rather limited. Overall, fuel consumption impacts are more commonly found (and canserve as a proxy for CO2 emissions). In fact, CO2 reduction estimates were obtained for just three of the nine ITS
approaches examined.
4.1

Summary
Across the nine strategies presented, more studies
were found on traffic signal control, BRT, and vehicle
control technologies. A large range in fuel saving estimates was reported for traffic signal control, BRT, andintelligent cruise control, reflecting modeled scenarios or
the specific deployments evaluated. While ramp metering
is widely deployed today, energy and emission impacts are
mixed. Several technical and institutional issues must be
addressed prior to widespread deployment of ASE, WIM,
and vehicle control technologies, such as improving remote sensing technologies for WIM and garnering political support for ASE. Traffic signal control, ramp metering,
BRT, and traveler information are more widespread andhave demonstrated positive deployment results.
While several of the ITS approaches presented have
reduced fuel consumption and CO2 emissions (electronic
tolling, traffic signal control, and signal priority for bus-

S. A. SHAHEEN, T. E. LIPMANes), modeling studies and early deployments are stilllargely focused on discrete applications rather than on
integrated regionwide networks. The full energy and CO2
effects of ITS cannot be known until multiple strategies
are deployed on a large scale and complex interactions,
including human factors, can be modeled and tested.

5. MOBILITY MANAGEMENT
This section is focused on mobility management,
which encompasses a range of strategies for helping tochange driving consciousness and behavior. The total energy and emission reduction potential of this area has
typically been more limited due to less availability anddemand for such alternatives. It has been suggested that anational GHG reduction strategy should consider investment in a range of innovative mobility approaches, suchas transit, ridesharing, park-and-ride facilities, bicycling,etc.42. Nevertheless, it is important to note that some mobility management strategies, if more widely adopted,
such as telecommuting, could potentially encourage more
tripmaking due to latent demand effects (less cars on theroad during peak travel times).
The authors present nine mobility management
strategies, providing fuel and CO2 emission estimateswhen available. Similar to the ITS section, the literatureon the energy and emission impacts of mobility management approaches is more limited at present. Even so,these strategies have the potential to impact fuel consumption and CO2 emissions, particularly if their use becomes more widespread. Options include: 1) carsharing,2) ridesharing (or carpooling), 3) park-and-ride facilities,4) parking cash out, 5) smart cards, 7) telecommuting, 8)
smart growth and transit villages, and 9) road pricing
policies.
5.1

Carsharing
Through carsharing (or short-term vehicle access)individuals gain the benefits of private vehicle use without the costs and responsibilities of ownership. Carsharing is most commonly deployed in locations wheretransportation alternatives are easily accessible and iscomplementary to transit43, 44. Carsharing has been documented to reduce vehicle ownership and vehicle miles/
kilometers traveled as trips are shifted to transit, biking,and walking. This results in lower greenhouse gas emissions.
In Europe, carsharing is estimated to reduce theaverage user’s CO2 emissions by 40 to 50 percent 45. In
addition, many carsharing organizations include lowIATSS Research Vol.31 No.1, 200715

EFFORTS To Reduce Co 2 in the Transportation Field

emission vehicles, such as gasoline-electric hybrid cars,in their fleets. More recently, Communauto announced a
13,000-ton reduction in CO2 emissions as a result of
their 11,000 carsharing users in the province of Quebec,
Canada. Communauto calculates that each carsharing
user reduces his or her distance traveled by car by 2,900
kilometers per year on average. Furthermore, they anticipate with a potential market of 139,000 households inQuebec that annual CO2 emission reductions could be as
high as 168,000 tons per year 46.
5.2

Ridesharing (or carpooling)
Ridesharing (or carpooling) is an arrangement
where two or more individuals agree to share a vehicle
for tripmaking (typically commute trips). Frequently, themotivation for this is to save money, spend less time intraffic by traveling on a high occupancy vehicle lane, or
reduce hassle (e.g., searching for a parking space at theoffice).
A carpooling project in Stockholm, Sweden allows
carpools, carrying three or more people, to travel in bus
lanes into the city. It is estimated that this effort will reduce CO2 emissions by 15 tons per year by 2050 47.

U.S. the option to cash out their parking subsidies could
lead to a reduction in 40 million tonnes of CO2 emissions
per year 52.
5.5

Smart cards
Another strategy to reduce CO2 emissions is smart
cards. Smart cards contain electronic chips. They areused for a variety of applications, such as transit, tolling,
and parking payments. Stockholm is interested in integrating smart cards for use on transit, taxis, and carpools
throughout the city. This approach is estimated to reduce
CO2 emissions by 1,500 tons per year by the 2030 to2050 timeframe47.

Park-and-ride facilities
Park-and-ride lots are public parking facilities thatenable commuters to leave their personal vehicles in suchlots and transfer to transit or a carpool for the rest of theirtravel. Private vehicles are parked in the facility throughout the day; they are picked up when travelers return atthe end of the day. Typically, such facilities are found in
the suburbs of large metropolitan areas. Development
and management of park-and-ride lots is important topromoting sustainable transportation 48. Increasing parkand-ride facility capacity in Stockholm is estimated toreduce CO2 emissions by 600 tons per year by the 2030
to 2050 timeframe47.

Telecommuting
Telecommuting is “generally defined as work at aremote location or home office rather than working at a
fixed employer-provided site or office”53. Estimated fuelsavings per telecommuter range from 49 to 177 gallons
per year across three studies54 -56 (as cited in Shafizadeh,
et al.57). This range converts to approximately a 0.5 to 1.7
ton CO2 reduction using a standard assumption of 19.4
pounds of CO2 emitted for every gallon of gasoline combusted58.
Kitou and Horvath59 used a systems model to evaluate the greenhouse gas emissions from business-sector energy (e.g., commuting, office temperature control, lighting, and electric office equipment) in telecommuting andnon-telecommuting scenarios. Both deterministic andprobabilistic analyses were conducted and evaluated. The“probabilistic analysis [Monte Carlo simulation] over a
set of likely parameters” demonstrated that telework may
reduce CO2 emissions59 (p. 3467). While telecommuting
could potentially reduce CO2 emissions related to commuting, reductions may be offset by increased home office energy use and/or commercial electricity use at thebusiness office.

5.4

5.7

5.3

Parking cash out
Parking cash out offers “commuters the option to‘cash out’ their employer-paid parking subsidies. [Itgives] commuters the choice between free parking or its
equivalent cash value….The cash option also rewards
those who carpool, ride public transit, walk, or bike towork” 49 (p. 262).
Estimates of CO2 reduction from parking cash out
programs range from 123 tons annually in Pleasanton,
California (offered to city employees) to 200 tons in
Santa Monica, California50, 51. Furthermore, Donald
Shoup has estimated that offering all employees in the

16

IATSS Research Vol.31 No.1, 2007

5.6

Low-speed modes
Low-speed modes are motorized and non-motorized devices that travel at lower speeds, such as bicycles,
electric bicycles, Segway Human Transporters, andneighborhood electric vehicles. Many involve active
movement by users and do not produce CO2 emissions.
By enhancing the bicycle and pedestrian environment, it
is possible to encourage travelers “to take entire trips orpartial trips with non-motorized modes that link withmass transit”40 (p. 120). One way to encourage bicycling
as an alternative mode is through a better low-speed mode
infrastructure, particularly on-street bike lanes 60, 61.

REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –The city of Stockholm’s long-term plan to reduce
CO2 emissions includes replacing 30 million short car
trips with bicycling annually. For longer trips, the City’s
goal is to encourage an additional 2,000 cyclists to giveup car travel or public transit use every day during thesummer months. Not surprisingly, this will require improving the low-speed mode infrastructure. It is estimatedthat such improvements will reduce CO2 emissions by
2,900 tons per year by 2050 47.
5.8

Smart growth & transit villages
Smart growth is an urban planning and transportation strategy that emphasizes growth near city centers toprevent urban sprawl. This approach includes promoting
mixed-use development, transit and bicycle-friendly infrastructure, and other land-use strategies, such as reduced non-residential speed limits, roundabouts, “parking
maximums, shared parking, flexible zoning for increased
densities and mixed uses, innovative strategies for landacquisition and development, and design emphasis onsense of place” 62, 63 (p. 61).
Transit villages are generally mixed-use (residential and commercial) areas that are designed to maximize
transit access and encourage ridership. They are typicallylocated within one-quarter to one-half mile (0.4 to 0.8
kilometer) of a transit station. Such strategies can reduce
CO2 emissions and vehicle miles traveled. Not surprisingly, “there is a direct correlation between low CO2
emissions and the reductions in the auto use that accompany transit friendly neighborhoods with high residential
densities” 63 (p. 41). More specifically, the California Department of Transportation estimates that the average
household living in a transit village “could emit 2.5 to 3.7
tons less CO2 yearly” than a traditional household 64 (p.
43). This estimate is based on a California Air Resources
Board (CARB) study estimating transit village household
private vehicle mileage reductions of approximately 20
to 30 percent annually65.
Road pricing policies
Road pricing policies induce shifts from autos topublic transportation, including cordon pricing (toll ringsin high-activity centers like central business districts thatcharge drivers for entry into a specific area), FAIR lanes(fast and intertwined regular lanes that charge drivers touse express lanes and transfer a portion of the collected
money to drivers using the non-express or regular lanes),and HOT lanes (or high occupancy toll lanes that enable
drivers without the minimum number of passengers access to high occupancy vehicle lanes)66. Roadway pric-

S. A. SHAHEEN, T. E. LIPMAN

ing makes drivers more aware of the true cost of driving
and may ease congestion as they switch modes40 (p. 100).
Transport for London reports that the central London congestion charging program was responsible for a
16 percent reduction in CO2 traffic emissions within the
charging zone during 2002 and 2003 (annual averages)67.
In addition, the city of Stockholm implemented a sixmonth trial of cordon pricing in January 2006, including
provisions for expanded transit services and park-andride facilities. Using emission models, the Stockholm
trial is estimated to have reduced CO2 and particle emissions by “approximately 100 tons per weekday 24-hour
period or by 14 percent”68 (p. 89).
5.10 Summary
Based on limited study and real-world experience,
mobility management strategies appear to have the potential to reduce energy and CO2 emissions in the future.
Of the nine approaches reviewed, road pricing policies(congestion and cordon) and carsharing already havedemonstrated notable CO2 reduction potential in both
Europe and North America. Low-speed modes, integrated regional smart cards, and park-and-ride facilities are
estimated to produce CO2 emission reductions ranging
from 600 to 2,900 tons per year in Stockholm, Sweden in
the 2030 to 2050 timeframe. Other strategies that could
result in noteworthy CO2 reductions, including parking
cash out (123 to 200 tons per two California cities), smart
growth (2.5 to 3.7 tons per transit village households in
California), and carpooling (15 tons in Stockholm in
2050, reflecting a limited project), are expected to impact
CO2 emissions. Finally, telecommuting impacts could
range from a 0.5 to 1.7 CO2 ton reduction by household
per year, based on three U.S. studies conducted in the early
1990s. While these options show potential, their impact
is dependent upon demand for such options throughout
regions. Further study is needed to better understand thefuel consumption and CO2 reduction potential of these
options.

5.9

6. CONCLUSION
Carbon dioxide emissions from the transportation
sector are projected to rise due to ongoing reliance on
fossil fuels and increases in vehicle miles traveled. Projections are also expected due to growth in the developing world. A range of strategies is needed to address fuelconsumption and emissions in the future. In this paper,
the authors examined three strategies to addressing GHG
emissions including: 1) engine technology and fuels, 2)
IATSS Research Vol.31 No.1, 200717

EFFORTS To Reduce Co 2 in the Transportation Field

ITS, and 3) mobility management. In the future, the ultimate mix of emission reduction measures will depend
upon a number of factors including: technology development costs; comparative costs among modes/solutions;interaction effects, such as latent demand; and support
for governmental policies. These policies might include
broad approaches, such as sector or inter-sector cap-andtrade programs and carbon taxation schemes, and/or more
specific policies for road pricing and ASE, for instance.
Given the complex interaction of ITS technologies,
mobility management, and human factors, development
and use of suitable tools to measure environmental consequences will remain important. This makes analyzing andmeasuring the environmental consequences of transportation systems a challenging endeavor. Interrelationships
among various vehicle, ITS technology, and mobility
management strategies will determine the ultimate direction and degree of impacts. Overall, wider deployment of
individual strategies can be expected to multiply benefits
by providing the traveling public with a wider array ofchoices and real-time information. Near term, the greatest
travel time and energy benefits are likely to come fromtraveler information persuading travelers to use public
transportation or other available mobility alternatives or
to postpone their trip until congestion has cleared. In thelonger term, major switches to low carbon vehicles andfuels could have a major impact. These could be enhanced
through artful integration of the vehicle and fuel systems
with ITS to lower adoption barriers and enhance theirprospects for major market penetration.

REFERENCES
1. WRI. Navigating The Numbers: Greenhouse Gas Data andInternational Climate Policy. World Resources Institute (WRI).
(2005).
2. IEA. Transport Technologies and Policies for Energy Security and CO2 Reductions. International Energy Agency (IEA),
Organization for Economic Cooperation and Development,
France. ETPC Paper No. 02/2003. (2003).
3. WBCSD. Mobility 2030: Meeting the Challenges to Sustainability. World Business Council for Sustainable Development(WBCSD), Geneva, Switzerland. http://www.wbcsd.org/web/
publications/mobility/mobility-full.pdf (2004).
4. IPCC. Climate Change 2001: The Physical Science Basis –Summary for Policymakers. Intergovernmental Panel on
Climate Change (IPCC). (2001).
5. Lipman, T. and Delucchi, M. Emissions of nitrous oxide andmethane from conventional and alternative motor vehicles.
Climatic Change 53: pp.477-516. (2002).
6. UNFCCC. Kyoto protocol. United Nations Framework Convention on Climate Change (UNFCCC). http://unfccc.int/kyoto_protocol/items/2830.php. (2007).
7. IPCC. Climate Change 1990: The Physical Science Basis –18

IATSS Research Vol.31 No.1, 2007

Summary for Policymakers. Intergovernmental Panel on
Climate Change (IPCC). (1990).
8. IPCC. Climate Change 1995: The Physical Science Basis –Summary for Policymakers. Intergovernmental Panel on
Climate Change (IPCC). (1995).
9. IPCC. Climate Change 2007: The Physical Science Basis –Summary for Policymakers. Intergovernmental Panel on
Climate Change (IPCC). (2007).
10. HM Treasury. Stern Review on the Economics of Climate
Change. http://www.hm-treasury.gov.uk/independent_reviews/stern_review_economics_climate_change/stern_review_report.cfm. (2006).
11. RGGI. Regional Greenhouse Gas Initiative (RGGI): An Initiative of the Northeast and Mid-Atlantic States of the U.S.
http://www.rggi.org. (2007).
12. CARB. AB 32 Fact Sheet: California Global Warming Solutions Act of 2006. California Air Resources Board (CARB),
Sacramento, California. http://www.arb.ca.gov/cc/factsheets/
ab32factsheet.pdf. (2006).
13. Sperling, D. and Cannon, J. Driving Climate Change: Cutting
Carbon from Transportation. Academic Press, London, UK.
(2007).
14. Davis, S. and Diegel, S. Transportation Energy Data Book:
25th Edition. Center for Transportation Analysis, Oak Ridge
National Laboratory. ORNL-6974. (2006).
15. ANL. The Greenhouse Gases, Regulated Emissions, andEnergy Use in Transportation (GREET) Model. Argonne
National Laboratory (ANL) Transportation Technology R&D
Center. http://www.transportation.anl.gov/software/GREET.
(2007).
16. Delucchi, M. A Lifecycle Emissions Model (LEM): Lifecycle
Emissions from Transportation Fuels, Motor Vehicles, Transportation Modes, Electricity Use, Heating and Cooking Fuels,
and Materials – Documentation of Methods and Data. Instituteof Transportation Studies. Davis, California. UCD-ITS-RR03-17. (2003).
17. Savage, M. Automated Traffic Enforcement. National Convergence of State Legislatures and the Insurance Institute forHighway Safety. http://www.ncsl.org/programs/transportation/
0700trnrv.htm. (2003).
18. Lynn, C., Garber, N., Ferguson, W., Lienau, T., Lua, R., Alcee,J., Black, J., and Wendzel, P. Automated Speed Enforcement
Pilot Project for the Capital Beltway: Feasibility of Photo-Radar. Transportation Research Council, Charlottesville, Virginia. (1992).
19. Gains, A., Heydecker, B., Shrewsbury, J., and Robertson, S.
The National Safety Camera Programme: Three-Year Evaluation Report. Department of Transport, London, United
Kingdom. (2004).
20. Retting, R. and Farmer, C.M. Evaluation of speed camera
enforcement in the District of Columbia. “Transportation
Research Record” No.1830: pp.34-37. (2003).
21. FHWA. Vehicle Infrastructure Integration. Federal Highway
Administration (FHWA), Washington, D.C. http://ops.fhwa.
dot.gov/travelinfo/infostructure/aboutinfo.htm. (2006).
22. U.S. EPA. Assessing the Emissions and Fuel Consumption
Impacts of Intelligent Transportation Systems (ITS). EPA
231-R-98-007. U.S. Environmental Protection Agency (U.S.
EPA), Washington, D.C. (1998).
23. Shaheen, S.A., Troy M. Young, D. Sperling, D. Jordan, andT. Horan. Identification and Prioritization of Environmentally
Beneficial Intelligent Transportation Technologies. Research

REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION – Sustainable Approaches for Surface Transportation –Report UCD-ITS-RR-98-1. Davis, California, Institute ofTransportation Studies-Davis, University of California, Davis.
(1998).
24. Midenet, S. Boillot, F. and Pierrelée, J-C. Signalized intersection with real-time adaptive control: on-field assessment of
CO2 and pollutant emission reduction. “Transportation Research Part D: Transport and Environment” 9(1): pp.29-47.
(2004).
25. Rakha, H., Van Aerde, M., Ahn, K. and A. A. Trani. Requirements for evaluating traffic signal control impacts on energy
and emissions based on instantaneous speed and acceleration measurements. “Transportation Research Record” 1738:
pp.56-67. (2000).
26. Rakha, H., Medina, A, Sin, H., Dion, F., Van Aerde, M., andJenq, J. Traffic signal coordination across jurisdictional boundaries: field evaluation of efficiency, energy, environmental, andsafety impacts. “Transportation Research Record” 1727:
pp.42-51. (2000).
27. Skabardonis, A. ITS benefits: the case of traffic signal control
systems. Paper No. 013286 in Transportation Research Board
80th Annual Meeting Conference Proceedings. (2001).
28. Kang, S. and D. Gillen. Assessing the Benefits and Costs ofIntelligent Transportation Systems: Ramp Meters. UCB-ITSPRR-99-19. Richmond, California, California Partners for
Advanced Transit and Highways (PATH), University of California, Berkeley. (1999)
29. Meers, G. and Roth, M. Road safety and ecological sustainability working together in Australian Transport Research
Forum: Zero Road Toll—A Dream or a Realistic Vision? Conference Proceedings. (2001).
30. Haworth, N. and Symmons, M. The Relationship Between
Fuel Economy and Safety Outcomes. Report No. 188. Monash
University Accident Research Centre, Victoria, Australia.
http://www.monash.edu.au/murarc/reports/murarc188.pdf.
(2001).
31. Stefan, C. Section Control: Automatic Speed Enforcement in
the Kaisermühlen Tunnel. Kuratorium für Verkehrssicherheit,
Vienna, Austria. http://www.kfv.at/fileadmin/Publikationen/Studien/VM/SectionControl-Kaismtunnel.pdf. (2006).
32. Chang, G-L, Liu, Y., Lin, P-W, Zou, N. Performance Evaluationof CHART (Coordinated Highways Action Response Team)Year 2002 (Final Report). University of Maryland, Adelphia,
Maryland. http://www.chart.state.md.us/downloads/readingroom/CHART_II_Documents/Final_Evaluation_Report_0304.doc. (2003).
33. Wilbur Smith Associates. Operational and Traffic Beneftis of
E-ZPass Deployment to the New Jersey Turnpike. Prepared
for the New Jersey Turnpike Authority. (2001).
34. ITSA. National Intelligent Transportation Systems Program
Plan: A Ten-Year Vision. Intelligent Transportation Society ofAmerica (ITSA), Washington, D.C. http://www.itas.org/itsa/
files/pdf/Nation10YearPlanITSFull.pdf. (2002).
35. Levinson, H., Zimmerman, S., Clinger, J., and Gast, J. (2003).
Bus rapid transit: synthesis of case studies. “Transportation
Research Record” No.1841: pp.1-11. (2003).
36. Lehtonen, M. and Kulmala, R. Benefits of pilot implementationof public transport signal priorities and real-time passenger
information. “Transportation Research Record” No.1799:
pp.18-25. (2002).
37. Vincent, W. and Jerram, L. The potential for bus rapid transit
to reduce transportation-related CO2 emissions. “Journal of
Public Transportation” 9(3): pp.219-237. (2006).

S. A. SHAHEEN, T. E. LIPMAN

38. Maze, T., McCall, B., Nelson, M., and Kamyab A. Oregon
Green Light CVO Evaluation Final Report Detailed Test Plans
7 and 9: Simulating the Impact of Electronic Screening on
Travel Time, Fuel Consumption and Weigh Station Efficiency.
Transportation Research Report No. 00-016. Center for Transportation Research and Education, Iowa State University,
Ames, Iowa. (1999).
39. Bose, A. and P. Ioannou. Analysis of Traffic Flow with Mixed
Manual and Intelligent Cruise Control Vehicles: Theory andExperiments. Research Report UCB-ITS-PRR-2001-13.
Richmond, California, California Partners for Advanced Transit and Highways (PATH), University of California, Berkeley.
(2001).
40. IEA. Saving Oil and Reducing CO2 Emissions in Transport:
Options and Strategies. International Energy Agency (IEA),
Organization for Economic Cooperation and Development,
France. http://www.iea.org/textbase/nppdf/free/2000/savingoil2001.pdf. (2001).
41. Barth, M. An emission and energy comparison between asimulated automated highway system and current traffic
conditions in 2000 IEEE Intelligent Transportation Systems
Conference Proceedings. (2000).
42. FHWA. Transportation and Global Climate Change: A Review
and Analysis of the Literature. Federal Highway Administration(FHWA), Washington, D.C. http://www.fhwa.dot.gov/environment/glob_c5.pdf. (1998).
43. Shaheen, S., Cohen, A., and Roberts, J.D. Carsharing in North
America: market growth, current developments, and future
potential. “Transportation Research Record,” No.1986: pp.116124. (2006).
44. Shaheen, S., Sperling, D., and Wagner, C. Carsharing inEurope and North America: past, present, and Future. “Transportation Quarterly” 52(3): pp.35-52. (1998).
45. Rydén, C. and E., Morin. Mobility Services for Urban Sustainability. Environmental Assessment. Report WP 6. Trivector
Traffic AB. Stockholm, Sweden. http://213.170.188.3/moses/
Downloads/reports/del_6.pdf. (2005).
46. Communauto. CO2 Emissions Reduced by 168,000 Tons Per
Year Thanks to Car-Sharing. Press Release. Montreal,
Canada. http://www.communauto.com/premiereetude.html.
(2007).
47. City of Stockholm. Stockholm’s Action Programme Against
Greenhouse Gas Emissions. City of Stockholm, Stockholm,
Sweden. http://www.miljo.stockholm.se/ext/klimat/pdf/Stockholm_ActionProgramme_against_Greenhouse_Gases_2002.
pdf. (2002).
48. Mattrisch, G. and Hoffman, C. Future aspects of sustainableurban mobility. In L.J. Suchraov, C.A. and F. Benitez (Eds.)
Urban Transport VIII: Urban Transport and The Environmentin The 21st Century. WIT Press, South Hampton, United
Kingdom, pp.3-14. (2002).
49. Shoup, D. The High Cost of Free Parking. American Planning
Association Planners Press, Chicago, Illinois. (2005).
50. Grant, M., and Ecola, L. Parking Cash Out: Implementing
Commuter Benefits Under the Commuter Choice Leadership
Initiative. EPA Rep. No. 420-S-01-006. U.S. Environmental
Protection Agency (EPA), Washington, D.C. http://www.commutesolutions.com/letsride/Resources/commuterchoice/parkingcash.pdf. (2001).
51. Drumheller, B., Quaid, A., Wyman, M., Liljenwall, J., andYoung, A. Sustainable Transportation Options for Protecting
the Climate. International Council for Local Environmental

IATSS Research Vol.31 No.1, 2007

19

EFFORTS To Reduce Co 2 in the Transportation Field

Initiatives (ICLEI), Berkeley, California. http://www.iclei.org/
documents/Global/Progams/CCP/Sust_Trans_Options.pdf.
(2001).
52. Shoup, D. C. Cashing Out Employer-Paid Parking: A Precedent for Congestion Pricing? UCTC Report No. 205. University of California Transportation Center (UCTC), Berkeley,
California. http://www.uctc.net/papers/205.pdf>http://www.
uctc.net/papers/205.pdf. (1993).
53. GAO. Telecommuting: Overview of Potential Barriers Facing
Employers. Report No. GAO-01-926. U.S General Accounting
Office (GAO). Washington, D.C. http://www.gao.gov/new.
items/d01926.pdf. (2001).
54. Boghani, A.B., Kimble, E.W., and Spencer, E.E. Can Telecommunications Help Solve America’s Transportation Problems?
Reference No. 65740. Arthur D. Little, Inc., Cambridge, Massachusetts. (1991).
55. U.S. DOT. Transportation Implications of Telecommuting. U.S.
Department of Transportation (DOT). U.S. Government Printing Office, Washington, D.C. (1993).
56. U.S. DOE. Energy, Emissions, and Social Consequences ofTelecommuting. U.S. Department of Energy (DOE). U.S.
Government Printing Office, Washington, D.C. (1994).
57. Shafizadeh, K., Niemeier, D., Mokhtarian, P., and Salomon,
I. Costs and benefits of home-based telecommuting: amonte carlo simulation model incorporating telecommuter,
employer, and pubic sector perspectives. “Journal of Infrastructure System” 13(1): pp.12-25. (2007).
58. U.S. EPA. Emission facts: calculating emissions of greenhousegases: key facts and figures. EPA420-F-05-003. U.S. Environmental Protection Agency (U.S. EPA), Washington, D.C. http://
www.epa.gov/omswww/climate/420f05003.htm. (2005).
59. Kitou, E. and Horvath, A. Energy-related emissions fromtelework. “Environmental Science & Technology” (37)16:
pp.3467-3475. (2003).
60. CARB. Bicycle Fact Sheet. California Air Resources Board(CARB), Sacramento, California. http://www.arb.ca.gov/
plannng/tsaq/bicycle/facsht.htm. (2005).
61. Jakowitsch, N. Charting a course for transportation in the newworld of climate change. In Harrington-Hughes, K. (Ed.)
Global Climate Change and Transportation: Coming to Terms.
Eno Transportation Foundation, Washington, D.C., pp.87-97.
(2002)
62. Feigon, S., Hoyt, D., McNally, L., Campbell, S., and Leach, D.
Travel Matters: Mitigating Climate Change with Sustainable
Surface Transportation, Transit Cooperative Research Program Report 93. National Research Council, Transportation
Research Board, Washington, D.C. http://ttap.colostate.edu/
Library/TRB/tcrp_rpt_93.pdf. (2003).
63. CNT. Combating Global Warming Through Sustainable
Surface Transportation Policy. Center for Neighborhood Technology (CNT), Chicago, Illinois. http://www.travelmatters.
org/about/final-report.pdf. (2003).
64. Parker, T., McKeever, M, Arrington, G.B., and Smith-Heimer,
J. Statewide Transit-Oriented Development Study: Factors for
Success in California. Business Transportation and Housing
Agency and California Department of Transportation, Sacramento, California. http://www.dot.ca.gov/hq/MassTrans/doc_
pdf/TOD/Statewide_TOD_Study_Final_Report_Sept%2002.
pdf. (2002).
65. JHK and Associates. Transportation-Related Land Use Strategies to Minimize Motor Vehicle Emissions. California Air
Resources Board, Sacramento, California. http://safety.fhwa.

20

IATSS Research Vol.31 No.1, 2007

dot.gov/ped_bike/docs/landuse.pdf. (1995).
66. GAO. Reducing Congestion: Congestion Pricing Has Promisefor Improving Use of Transportation Infrastructure. Report
No.GAO-03-735T. U.S. General Accounting Office (GAO).
Washington, D.C. http://www.gao.gov/new.items/d03735t.pdf.
(2003).
67. TfL. Central London Congestion Charging Impacts Monitoring:
Fourth Annual Report. Transport for London (TfL). London,
England. http://www.tfl.gov.uk/tfl/cclondon/pdfs/FourthAnnualReportFinal.pdf. (2006).
68. City of Stockholm. Facts and Results from the Stockholm
Trials. Stockholm, Sweden. http://www.stockholmforsoket.
se/upload/Sammanfattningar/English/Final%20Report_
The%Stockholm%20Trial.pdf. (2006).

ACKNOWLEDGEMENTS
The authors would like to thank the Honda Endowment for
New Mobility Studies at the University of California, Davis forgenerously funding this research. The authors also would like toacknowledge Charlene Kemmerer, Rachel Finson, and Denise Allen of the Innovative Mobility Research (IMR) Group of California Partners for Advanced Transit and Highways (PATH) at the
University of California, Berkeley for their assistance in collecting literature for this paper. The contents of this report reflect theviews of the authors, who are responsible for the facts and the accuracy of the data presented herein.