How do traffic lights, road conditions, traffic congestion, and driving
behavior influence motor vehicle emissions out in the real world? Drs.
H. Christopher Frey and
M. Rouphail are faculty members in the Department
of Civil Engineering at North Carolina State
University and co-principal investigators of a recently completed project
that was aimed at answering these types of questions. The project
team included two graduate students, Alper Unal and James Colyer at NC
State. The project, titled "Emissions Reduction Through Better Traffic
Management," was sponsored by the North Carolina Department of Transportation.
The final report (6.35
MB) is available on-line.
The NCSU project was aimed at measuring real-world on-road vehicle emissions
with a focus on characterizing the effect of traffic signal timing on emissions.
For example, we were interesting in knowing how the timing and coordination
of multiple traffic signals affects vehicle emissions, both at specific
intersections and when driving along a traffic corridor (e.g., a stretch
of roadway that has many signals). How important are driving modes
such as deceleration, idling, and acceleration when stopping at, waiting
for, or leaving a signalized intersection? Do emissions vary for
Examples of Results
In our study, we found that an effective signal timing and coordination
plan can reduce real-world on-road emissions. We also observed that
emissions are lower on average for uncongested versus congested traffic
on a particular corridor. Emission rates on a mass per time basis
are highest during vehicle acceleration, and lower by a factor of five
to ten, on average, for idling. Emissions are influenced by the number
of stops and the amount of delay time experienced at intersections.
A key difference between this study and many other vehicle emissions projects
is that our results are based upon real-world on-road measurements of vehicle
tailpipe emissions on a second-by-second basis. These measurements
were made during actual driving, under actual traffic conditions, at any
location along a route, with different drivers, and at various times of
the day, days of the week, and months of the year. In fact, we made
over 1,200 one-way trips while collecting data for this study. Many
other studies are based upon measurements made on a dynamometer in the
laboratory, remote sensing measurements which are obtained at specific
locations representing only a snap shot of emissions, or tunnel studies
that are not representative of driving on many other types of roadway facilities,
such as signalized corridors. The results we obtained were based
upon measurements, not models.
Key Findings of the Study
Some of the key findings of the study were:
This study has established the feasibility of using on-board emissions
measurements to collect real-world on-road tailpipe emissions data for
carbon monoxide (CO), nitric oxide (NO), and hydrocarbons (HC).
Emission rates for different driving modes (acceleration, deceleration,
idle, cruise) emission rates are for the most part stable for the same
Measured emission rates (on a gram per second basis) are highest during
the acceleration driving mode and lowest for the idle driving mode.
The difference between the two is typically a factor of five to ten on
average, depending on the pollutant.
Measured emissions tend to increase with traffic congestion since there
are more acceleration events, as observed on Chapel Hill Road.
Signal improvements such as coordination and retiming have resulted in
lower real-world emissions on Walnut Street.
There are emissions "hotspots", which are locations of higher than average
emissions, at specific locations on the corridors studied. These
hotspots are typically associated with a signalized intersection.
The key recommendations based upon the study work are:
On-board emissions measurement methods should be used in future studies
to improve knowledge of real-world on-road tailpipe emissions.
On-road measurement studies should be carefully designed taking into account
well-defined study objectives.
Objectives for future studies should include but not be limited to empirical
evaluation of Transportation Control Measures (TCMs) and Transportation
Improvement Projects (TIPs) and plans; assessment of emissions hotspots;
evaluation of driver behavior; validation of emission factor models;and
development of public education tools to educate drivers about their role
in pollution prevention.
Appropriate and thorough data screening, reduction, and analysis protocols
should be used.
Variability and uncertainty should be accounted for in the study design
and when making inferences based upon measured data.
State departments of transportation and others should use on-road emissions
data to aid in the design and real-world evaluation of TCMs and TIPs.
US EPA should use on-board emissions measurements to validate its emission
factor models and to develop new emission factor models.
In addition to the importance of traffic signal timing with respect to
vehicle emissions, the work we are doing has many other implications and
possible future applications. For example, the data we collect can
be used to characterize actual on-road emissions, as opposed to having
to rely solely on computer models to make such predictions. The most
commonly available and widely used computer models are based upon data
obtained in laboratories for standardized driving cycles (which are typically
trips or segments of trips). In contrast, our work is based upon
measurements taken under real world driving conditions, including effects
of road grades, roadway design, traffic signal timing, traffic conditions,
weather conditions, etc. Thus, our data are more representative of
real world emissions than the predictions of computer models. An
important need for on-road emissions estimates is to predict the impact
of vehicle emissions on air quality. It is also important to understand
the relationships between traffic flow and emissions in order to develop
effective air quality management strategies.
Another important implication of our work, aside from the potential
for improving air quality by developing a basis for improved traffic signal
timing, is to develop the data needed to understand the relationship between
roadway design and vehicle emissions.
A third implication of on-board emissions measurements is that it can
be an important way to supplement or replace existing emissions inspection
If you have any suggestions for how to use this data, please feel free
to let us know. You can contact members of the project team via the
Miscellaneous Links portion of the web site.
Guide to this Web Site
For an overview of the equipment that used in this project, please
click here or on the "Measurement
Instrument" link below. For some sample results of measurements
that we have taken, please click here or on the "Example
You can also obtain a copy of a presentation giving an overview of the
methods, some example results of this project, and the project final report,
from the "Presentations"
As we obtain results from this project that may be of general interest
to the public, we will post them on the "Low
Emissions Driving Tips" portion of the web site.
You can access other information related to this project via the "Miscellaneous
Links" portion of the web site.
This web page was designed by H.C. Frey
All items on this web site are Copyright (c) 1999 by
H.C. Frey and NC State University
If you wish to use any materials from this web site,
such as for publication or presentation, please contact Dr. H. C. Frey