United States
Environmental Protection
Agency
Office Of The Administrator
(A-101F6)
101/F-90/043
November 1990
&EPA
A Study Of
Freeway Capacity Increases
In The San Francisco Bay Area
And Greater Sacramento
Printed on Recycled Paper
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A Study of Freeway Capacity increases in the San Francisco Bay
Area and Greater Sacramento Area
Tom Addison
NNEMS Fellow
U.S. EPA, Region IX
US Environmental Protection Agency Air Programs Branch
Region 5 Library (PL-12J) September 28, 1990
77 West Jackson Blvd., 12th Floor
Chicago, IL 60604-3590
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DISCLAIMER
This report was furnished to the U.S. Environmental Protection
Agency by the student identified on the cover page, under a National
Network for Environmental Management Studies fellowship.
The contents are essentially as received from the author. The
opinions, findings, and conclusions expressed are those of the author
and not necessarily those of the U.S. Environmental Protection
Agency. Mention, if any, of company, process, or product names is
not to be considered as an endorsement by the U.S. Environmental
Protection Agency.
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Abstract
This study evaluates the adequacy of freeway capacity increases' air quality
analyses and the accuracy of their predictions of future traffic volumes. New-
alignment freeways, freeway lane additions, and freeway interchange additions or
expansions in the greater Sacramento and greater San Francisco Bay Areas,
planned in the last 10 years, were all included in the study. The CEQA and/or
NEPA documents for these projects gave the needed air quality analyses and
traffic predictions.
The study revealed simplistic air quality analyses. Only 22% of the projects
analyzed mesoscale emissions of CO, NO0 and hydrocarbons; the rest of the
projects had only microscale analysis of CO emissions or no quantitative emissions
analysis whatsoever. Despite a shortage of detailed traffic count data in the Bay
Area, the study showed a pattern of traffic projections that significantly
underpredicted the observed actual volumes. Thus, these freeway capacity
increases appear not to have had the predicted regional air quality benefits, but
instead have likely worsened air quality.
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Acknowledgements
This work was supported by a grant from the National Network for
Environmental Management Studies program of the U.S.
Environmental Protection Agency. Numerous officials of differenl
governmental organizations as well as academic institutions
contributed to this study by sharing their insights, data, and
time. I would particularly like to thank Julia Barrow, Mark
Brucker, Jennifer Dill, and Frances Wicher of the U.S. EPA's
Region IX Air Programs Branch, who all found the time and
patience to meet regularly with me and provide invaluable advice.
Additionally, staff from the following organizations born
allowed me access to the files and information I needed ~or rr.is
study, as well as generously volunteering their time and years c;
experience and insights:
-California Department of Transportation (Caltrans) District 4,
San Francisco. Environmental, Highway Operations, Transportation
Planning, and Traffic Branches.
-Caltrans District 3, Marysville. Environmental and Traffic
Census B Branches.
-Caltrans Headquarters, Sacramento. Offices of Environmental
Analysis and Traffic.
-Federal Highway Administration, Region IX, San Francisco.
Despite the assistance provided by the above individuals'as
well as dozens elsewhere, any errors in this study are solely
attributable to the author. Furthermore, the views and opinions
expressed herein are not those of the U.S. EPA, but are rather
those of the author alone.
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EXECUTIVE SUMMARY
The purpose of this research is to evaluate, for projects
that increase freeway capacity, the adequacy of their air quality
analyses and the accuracy of their traffic predictions. The
study examines three types of capacity-increasing measures on
limited-access, divided highways ("freeways") in the greater San
Francisco Bay Area and greater Sacramento regions: 1) new-
alignment freeways, 2) expansion of existing freeways by adding
"mixed-flow" and/or high-occupancy vehicle (HOV, or diamond)
lanes, and 3) adding or expanding interchanges on existing
freeways. Such projects are required under the California
Environmental Quality Act (CEQA) and/or the National
Environmental Policy Act (NEPA) to undergo environmental review
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prior to their construction.
By limiting the study to all such projects for which the
final environmental document is less than 10 years old (and
adding a few additional projects that were one or two years
older), there exist 27 such freeway projects. I looked at the
level of detail of the air quality analysis for all these in Part
I of the study. In Part II I compared, for those projects on
which construction had been completed, the projected future
traffic volumes with actual volumes as determined by traffic
counts.
The large majority (63%) of the 27 capacity-increasing
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projects analyzed only carbon monoxide (CO) air quality in ~ne
immediate freeway vicinity. 22% of the projects had more
detailed air quality analysis, which typically also involved
mesoscale analysis of outputs of GO, hydrocarbons (HC), and
oxides of nitrogen (NOJ . 15% of the projects had no
quantitative studies of air quality effects.
The second half of the study, comparing traffic projections
to observed volumes, revealed serious shortages of traffic count
information, as well as extremely simplistic projections in the
original environmental documentation. Because of ~hese and "~er
problems with the data, a precise quantitative assessment of ~he
accuracy of traffic volume forecasting was not possible.
However, in 5 of the 6 cases in this portion of the study,
traffic projections underpredicted the later observed volumes.
This study does not determine the reason for the
underprediction. Induced trips or latent demand, unexpected ,
growth, and other factors are all probable partial causes.
Whatever the reasons for repeated underprediction, the predicted
air quality benefits that were used to justify the projects'
construction may never have materialized. In fact, these
projects likely had overall negative impacts on air quality in
the short run. Their long run effect on air quality, while still
undocumented, may be even more negative, since travel and
population growth are likely to continue to exceed the forecasts
made in these projects' environmental documents.
Given the past underprediction of traffic volumes, future
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freeway projects analyzed using standard traffic forecasting
techniques that advertise regional air quality benefits should be
viewed cautiously by air pollution officials. The environmental
planning process would benefit greatly from improved traffic
forecasting. Improving traffic count data is a critical step
toward achieving this goal. Additionally, the air quality
analyses of all these projects should model the consequences of
the freeway expansion not only on the emissions of CO, but on the
emissions of HC, NOX, and PM-10 (small particulates) as well.
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PURPOSE
Despite the toughest air pollution regulations in the U.S.,
most Californians are still forced to breathe unhealthy air. The
total annual costs of this pollution have been estimated by many
economists to be in the billions of dollars. Countless studies
have documented that this sorry state of affairs is largely a
result of motor vehicle use.
Increases to freeway capacity have the potential to
significantly affect air quality. The environmental planning
process under the National Environmental Policy Act (NEPA) and/cr
the California Environmental Quality Act (CEQA) is the only pcinn
at which the air quality effects of capacity increases are
examined on an individual project, as opposed to a regional,
basis. Thus, it is imperative that the air quality analyses in
this planning process be accurate, as well as adequate.
I undertook a two-part evaluation of the adequacy of the/
environmental planning process for projects that increase freeway
capacity. First, I evaluated the project's air quality analysis,
and then compared the traffic volumes projected for the improved
freeway to the actual traffic volumes observed after it was
completed. I present the background information, the findings,
and a discussion of the findings for each of these two halves of
the study in Parts I and II below.
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PART I.
A. Background and Methodology
The analysis included the following three types of projects
in the greater San Francisco Bay Area and the greater Sacramento
regions: 1) new freeways; 2) expansions of existing freeways by
adding mixed flow (i.e., no restrictions on use) and/or HOV (use
limited to vehicles with a minimum number of passengers) lanes;
and 3) projects that added new freeway interchanges or expanded
existing interchanges. I included only projects for which the
final environmental document had been completed in the last 10 to
12 years. Today these projects are in various stages of
development. Some projects are completed, some are under
construction, and some are still in the planning stage.
The National Environmental Policy Act (NEPA), and the
California Environmental Quality Act (CEQA), NEPA's state
corollary, require that the environmental consequences of freeway
expansion projects be evaluated prior to the project's
initiation. Both laws require similar environmental documents
for these projects. First, a federal Environmental Assessment
(EA) or a state Initial Study (IS) must be prepared. If the
environmental consequences of the planned work are deemed
relatively insignificant, the final federal document is a Finding
of No Significant Impact (FONSI) while the final state document
is a Negative Declaration (ND). If the consequences are deemed
to be more major, then the federal and state documents prepared
are an Environmental Impact Statement (EIS) or Report (EIR),
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respectively.
Some of the roadwork I looked at was subject to both laws,
whereas other projects were only covered by one. In the 1950's
and 1960's when the U.S. interstate program was under full
construction, the bulk of the funding for such projeer3 was
federal. Under the Reagan-era "new Federalism" of the 1980's,
the federal money was very limited.
For projects that are built without any federal funds, ana
that are not connected ro federal or federal aid highways, only
CEQA applies. In the Bay Area, the number of projeers subjecr
only to CEQA is rising dramatically. The majority of planned
capacity increases are being financed by local or countywide
initiatives that raise sales taxes for highway dollars. This
shift in freeway funding is of significance to the EPA, for
virtually all projects subject only to CEQA regulation are not
routinely reviewed by Region IX. Also, the EIR's prepared
directly by or for county or local governments are increasing.
With Caltrans no longer being the sole preparer, there will
likely be an increasing range in the quality of the EIR's.
There were 21 projects in the Bay Area and 6 projects in the
greater Sacramento region that met the previously stated
criteria. These are listed in Table 1.
In reviewing the environmental documents for each of these
27 projects, the first part of this study looked at the level of
detail of the air quality analysis of each project. In addition
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TABLE 1: The Title, Type, and Date of the Projects'" Environmental Documents
Abbreviations: I/C = interchange EA = Environmental Assessment IS = Initial Study ND =
Negative Declaration FONSI = Findings of No Significant Impact DEIS/FEIS = Draft/Final
environmental impact statement FEIR = Final Environmental Impact Report
Greater Bay Area projects:
1. EA and IS for two new I/C's at Stonendge Drive on J-680 and Hacienda Drive on 1-580
in Pleasanton, modify existing I/C on 580, and build auxiliary lanes on 580 and 680, 12/ST.
2. EA/IS for Widening from 4 to 6 Lanes and Construction of 2 Sound Barrier Walls on I-
880 in Alameda and Santa Clara Counties, 6/88.
3. DEIS: 1-80 and 1-180. Operational Improvements in Alameda and Contra Costa Counties,
1/83.
4. FEIS and 4ff) Statement. Route 101 in Santa Clara County, 0.6 miles '.ami: nf C.jcnranc
Road in Morgan Hill to 0.7 miles Nonn of Route
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TABLE 1 (continued)
19. ND/FONSI. Proposed Widening of Route 152 in Santa Clara County, 4/87.
20. EA. Proposed Ramp Connection for Route 238 West to Route 17/I-MO South, in and near
San Leandro, Alameda County, 3/85. i
21. ND/FONSI. Ramp, Road, Overcrossing and Signals Construction, Modification, IVidenmq,
and Installation on Route 237 in Santa Clara County at Fair Oaks Avenue, 2/33. '
Greater Sacramento region projects:
22. Environmental Reevaluation. Route 99 [rural highway convened to 4-lane freeway], 12/83.
[FEIS, 8/75].
23. FEIS. Roseville Bypass (Route 65], 9/84.
24. ND/FONSI. Route 99. Build 2 lanes in the meaian in ^acramcntu OKtr.'.v rcr^ccn Macx
Road ovcrcrosstng and Sacramento Blvd. ovcrcrossurj, :!i/X7.
25. FEIR. Silva Valley Parkway I/C with 1-50, 2/90.
26. IS. Laguna Blvd./Route 99 l/C Reconstruction, 2/88.
27. FONSL North Natomas Freeway Improvements, 1/90.
to a final EIS/R or FONSI/ND, most of the projects had at least
one supplementary technical report. These reports present the
results of the air quality models used to predict the effect of
the increased freeway capacity on the emission of pollutants.
Additionally, these reports often contained the traffic forecasts
used in Part II of this study.
B. Findings and Discussion
All of the 27 air quality analyses in this report concluded
that the project would improve air quality (although not
necessarily by a significant margin), or would result in no
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significant change in air quality. For 17 of the 27 projects
(63%), the air quality analysis consisted of a microscale study
of only CO (carbon monoxide) emissions. Analyzing the effects of
only one pollutant often was justified by the inaccurate
conclusion that CO serves as an "indication of the full range of
pollutants"1. The effects of a project on the full range of air
pollutants, however, can not be estimated by CO emissions. In
general, increasing the average travel speed on a freeway fro:?, a
congested, stop-and-go condition to a steady flow decreases tr.e
emissions of both CO and total HC (hydrocarbons), but increases
the emissions of NOX (oxides of nitrogen). Furthermore, the
impacts of CO are localized, but the formation of ozone from HC
and NOX affects the larger air basin.
Only 6 of the 27 projects (22%) had both a microscale
analysis of CO emissions and a mesoscale analysis of emissions of
/
CO, HC, and NOK. Five of these 6 projects were of enough
significance to require an EIS. Two projects requiring an EIS did
only a microscale CO analysis. One of the 5 mesoscale analyses
projected emissions of SO, and particulate matter, and divided HC
predictions into total and nonmethylated hydrocarbons. Another
included a prediction of project-caused lead emissions.
Four of the 27 projects (15%) had no quantitative analysis
of air quality. One such project justified this minimalist
approach as follows: "Based on previous analysis [of different
1 (EA, Construct 4-Lane Freeway from Mini Dr. to Sage St.
Overcrossing... in Vallejo. Solano Countyr 11/85).
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projects]... no significant impact... is anticipated"2. Anotr.er
justification was that because the project was predicted to
decrease total vehicles miles traveled (VMT) as well as
congestion, the project will benefit air quality, and thus
quantitative analysis is not required3. Of these 4 projects with
no quantitative analysis, 3 were interchange projects, while the
fourth was a freeway-to-freeway ramp project. Given that both
the Bay Area and Sacramento are violating federal and state
standards for ozone and CO, adequate air quality analyses for all
these projects would have predicted the effect ^n er.icsicr.s of
CO, and the ozone building blocks HC and NO,. Additionally,
Sacramento is violating the federal standard for small
particulate matter (PM-10)\ Only one of the 27 projects
modeled what its consequences would be for either PM-10 or TSP.
A shortcoming of these models is that, for interchange
additions or expansions, they tend not to model the consequences
of additional traffic on the mainline, but simply look at the
emissions of the cars on the ramp. This is a significant
oversight. If the mainline is congested or nearly so, these
entering vehicles can bog down the mainline enough so that total
emissions of CO and HC may increase dramatically. Thus the
2 (EA/IS, Reconstruction of the 80/Alamo Drive Interchange
(I/O in Vacaville. Solano County. 10/86).
3 (EA/IS, Two new I/C's at Stoneridge Dr. on 680 and Hacienda
Dr. on 580 in Pleasonton. modify existing I/C. and build auxiliary
lanes..., 12/87).
4 PM-10 replaced total suspended particulates (TSP) as a
criteria pollutant in 1987.
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addition of exrra vehicles to a freeway near saturation nor only
negatively affects air quality through the emissions from the new
traffic, but also by increasing emissions from all the vehicles
on the freeway. Although ramp metering might mitigate this
problem, many interchanges and ramps are still being buil~
without ramp metering, and the air quality analyses are typically
done for a scenario without metering.
None of the projects gave a qualitative, let alone
quantitative, analysis of the effects of the increased capacity
on carbon dioxide emissions. This is a serious snorrco-ir.g, fcr
CO2 is the primary "greenhouse gas," which wnen emitted
contributes to the problem of global warming. Carbon dioxide is
not directly harmful to individuals, but rather in sufficient
quantities damages our planet's atmosphere.
While both the Reagan and Bush administrations have shown
great reluctance to limit CO, emissions, these emissions will
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have to be reduced. In California, over half the carbon
emissions are from our transportation network.5 C02 emissions are
tied directly to fuel consumption. Thus, a vehicle idling in
stop-and-go, congested traffic is maximizing CO2 output.
Another shortcoming concerned mitigation of project-caused
air quality declines. One air quality analysis stated that "air
quality will be monitored to determine the need for ramp metering
8 The Impacts of Global Warming on California. California
Energy Commission, p. c-1. August, 1989.
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to avoid significant air quality impacts."0 No timetable of -,;nen
or where such monitoring would be done was provided, however.
Nor were critical pollutant levels specified which would trigger
the installation of ramp metering. Without a specified
implementation plan, it is unclear whether mitigation measures
will be actually carried out. Therefore, it is questionable
whether the measures should be given much weight when evaluating
the project impacts. A recent CEQA amendment now requires
monitoring plans for mitigation measures in final CEQA documents,
which may improve the situation.
PART II.
A. Background
A wide number of varying factors, such as average fuel /
economy, percentage trucks, and pollution control standards, are
used in the air quality analysis for a capacity-increasing
highway project. The most critical component of these models are
traffic volumes for both the build and no build scenarios. Thus a
critical first step to check the accuracy of the air quality
impact analysis for a project is to compare actual traffic to the
predicted traffic used in the emissions model. The second major
part of the study did just that and compared the projected
a (ND, Widening 101... in Santa Clara County from the Lawrence
Expressway to the San Mateo County Line. 10/86).
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traffic volumes to the actual volumes as measured by counts on
completed projects.
Before presenting the results of these comparisons, I first
discuss problems in the modeling process as well as limitations
to the data used in this part of the study.
Traffic modeling is a complex process, but its essence is
that land use, growth forecasts, and socioeconomic data are used
to predict numbers, origins, and destinations of future trips.
Various models then assign these trips to nodes ftransit, private
vehicles, carpools, etc.), times, and roadways, using travel
time, expenses, and other factors. Certainly any attempt to
predict the future is an inexact art, and predicting traffic
volumes is especially tricky, given the enormous range of
variables that potentially affect travel. These factors include
gas, transit, parking, and toll prices, changes in regional
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growth patterns, new travel options, earthguakes, etc.
Although these models are highly sophisticated, they contain
two serious flaws. First, they treat land use strictly as an
explanatory variable for highway use. Although land use
certainly helps explain observed highway use, it is also true
that freeway location and congestion levels influence the land
use decisions.
Historically, land use decisions in this country have been
made at the local level. Regional or state planning attempts at
more centralized land use planning are typically controversial
and are often challenged successfully in the courts or through
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voter initiatives. Caltrans and FHWA are thus extremely
reluctant to appear to be making land use decisions. Officials
at these agencies maintain that roads are expanded to meet rhe
demand provided by present and future land uses, as decided by
local governments. Their position is that these projects are
often undertaken to fulfill existing needs for greater freeway
capacity, so any influence on land use is minimal.
While it may be acknowledged that highways influence land
use through market forces, highway agencies maintain ~har ~ne
responsibility for changes in land use that arise lie with the
local governments who set policy through zoning and other
mechanisms. An apolitical examination reveals that where and
when roads are expanded or built has the potential for tremendous
impacts on regional growth and development. Several senior
Caltrans officials agreed off-the-record that this is the case,
>
but agency policy refuses to acknowledge this.
This debate, over whether growth causes the highways or
highways cause the growth, is often polarizing and acrimonious,
with Caltrans and environmental groups exchanging heated rhetoric
both in the press and in the courts. Rarely does either side
cite controlled or quantitative studies to reinforce their
position, although there is a body of literature on this subject.
(See Appendix A). Certainly the issue does not lend itself
readily to quantitative study. Difficulties include the
abundance of confounding variables, and the need for controls
combined with the problem of finding areas similar in all aspects
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but for freeway improvements. After reviewing the literature, it
appears that the effects of roadwork on growth are variable and
site specific. While growth is limited without an adequate
transportation network, such a network is not of itself
sufficient to ensure that growth will follow. Other factors,
such as sewage lines and nonrestrictive zoning, are also
required.
The second theoretical flaw in traffic models is that the
models do not include feedback loops to racord the effect of
increased capacity on the public's demand for or use of the
facility. Demand, and thus the trips generated, are assumed to
be the same both before and after the capacity increases are
completed. Most models in use today do allow and account for
diversion of trips to other routes or modes, but not for new
trips. Thus, the models show that increased freeway capacity may
increase traffic volumes, but only by diverting (capturing) '
vehicles from, e.g., local arterials, or capturing trips from
existing transit riders.
In highly congested areas such as the urban regions of
California, many individuals are either foregoing automobile
trips altogether or have altered their destinations and/or travel
times to avoid peak hour congestion. Called "discouraged
drivers," they create a "latent demand" for improved road
conditions. These phenomena are not addressed by traffic
projection models currently in use. When the capacity on a
freeway is increased, very likely some of these discouraged
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drivers will return to their vehicles on the expanded roadway,
leading to new "induced trips."
Even if transportation agencies were to acknowledge the
existence of pre-construction latent demand and post-construction
induced trips, the new trips would be difficult to quantify. One
hypothetical way to measure induced trips would be to observe
traffic volumes on the freeway or ramp immediately prior to
construction commencing, and then to record the volumes after
construction. Any increase in ..traffic could be attributed
directly to induced trips. This information could then be used
to develop models to predict induced trips.
The problem with this approach is that other variables
besides induced trips could explain the difference between these
two volumes. For example, unexpected regional growth including
increased housing and commercial, industrial, or retail
development would increase traffic, while improved transit or
traffic signal coordination on parallel arterials would decrease
traffic.
This problem would be minimal if the planning and
construction periods were very short, and the traffic was counted
immediately before and shortly after construction. Most of the
freeway capacity increases studied, however, took a year or often
much longer to complete, allowing greater amplitude in the
confounding variables. Also, as will be discussed in detail
later, traffic counts are done very infrequently in the Bay Area.
Another problem in quantifying induced trips is in
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accurately measuring the types of responses to road expansions:
shifts in mode, travel time, route, and destination. Route
shifts, for example from arterials to the improved freeway, prove
difficult to assess since few arterials are regularly counted.
In the Bay Area, few towns other than Berkeley and San Jose have
regular counts of their arterials, although this non-freeway
network is included in the traffic models. Mode shifts, e.g.,
from vanpocls to single occupant vehicles, would also confuse the
issue, in this example by having some of the traffic increases
due not to induced trips.
One theoretically valid way to quantify induced trips is to
conduct interviews with drivers. Interviews could take place on
the completed roads that have a tollbridge or plaza;
realistically, this seems unlikely because of the time required.
A large cohort study might also yield useful data. Regional t
travelers could be questioned on their behaviors before and after
the roadwork. Problems with this approach include the high tine
costs of gathering the data and the possibility of unreliable
data, due to respondents' untruthfulness or forgetfulness.
The primary rationale for the construction of the vast
majority of the 27 freeway projects examined was decreased
congestion. The benefits attributed to reduced congestion are
better service to the drivers and improved air quality. Two
problems underlie this reasoning. First the assumption that
lessened congestion equals improved air quality is problematic.
Although CO and hydrocarbon emissions are reduced as congestion
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decreases, NOX emissions are increased. Ozone, the major snog
ingredient, is produced by the sunlight-aided reaction of
reactive organic gases (from hydrocarbons) with oxides of
nitrogen. While both smog ingredients have a number of sources
other than vehicles, and high levels of NO, may curb ozone
levels, it is simplistic to say that decreasing one ingredient at
the expense of the other improves air quality.
Secondly, as mentioned previously, capacity increases do not
always result in decreased congestion, especially in the long
run. Reiterating, roadway improvements have the ability to spur
regional growth and thus attract more trips, and the latent
demand for better roads creates post-completion induced trips.
In the short run, before development can occur and before people
change their driving habits to take advantage of the uncongested
road, emissions of CO and hydrocarbons may very well decrease.
However, in the long run, as induced trips and/or regional growth
occur, these emissions may go up. The roadway may end up
congested, but now with more vehicles and thus more emissions
than it had previously.
Despite the problems mentioned previously with quantifying
induced trips, it is still valuable to compare traffic
projections to actual counts. I could only find two instances
where this has ever been done in the U.S., and both are small,
limited studies. The Transportation Studies Center, a research
branch of the Department of Transportation, has agreed to provide
FHWA's Office of Planning with such a study. The research will
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tentatively look at 7 or 8 major highway projects from around the
country, and will compare actual costs to predicted costs in
addition to traffic volumes. The results from this modestly-
sized study (FHWA HPN-23) will not be available for perhaps a
year, however.
B. Limitations of Data
Comparing traffic projections to volumes was difficult.
Due to lengthy construction time, unresolved environmental
problems, or shortage of funds, 21 of the 27 projects I examined
were not yet completed. One of the projects actually raaae no
prediction of future traffic volumes7.
Often the traffic projections in the EA/IS or EIS/R were not
predictions of volumes (numbers of cars on the road), but rather
of minutes of delay. Underlying this delay data were the volume
predictions, but locating the volume numbers was not
straightforward. Sometimes they could be found in one or more of
the technical appendices, such as the Noise/Air/Energy reports.
For other projects, I obtained the needed data from the original
computer model printouts.
To accurately model vehicle emissions at any point, at the
barest minimum, projections of the following are required for
each of the freeway's directions of travel: the average annual
daily traffic (AADT; given in total vehicles per day), and the
7 (Environmental Document, Ramp... on 237 in Santa Clara County
at Fair Oaks Avenue. 2/83).
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a.m. and p.m. peak hour volumes. This latter figure is usually
defined for urban areas as the number of vehicles passing the
point in the tenth busiest hour of the year3.
Sometimes the traffic predictions were extremely crude. For
example, some projects did not make predictions for each travel
direction on the freeway, but rather lumped both directions into
ADT (average daily traffic) and peak hour projections9.
Sometimes the ADT figure was stated to be the AADT; other tines
it was unclear if the ADT was the AADT or the ADT for -he busiest
month. Other projects had no peak hour information, cur only ADT
projections10. Other projects gave peak hour projections for the
a.m. only, ignoring the p.m. peak11.
The major problems I encountered, however, were a result of
Caltrans1 District 4's (Bay Area) troubled traffic count program.
Over the last decade the program has been understaffed,
underfunded, and its information undervalued. While recently
this trend has been partially reversed, the office is still low
on hardware and skilled staff. California's traffic census
8 Personal communications with Emory Stoker, Research Analyst,
Traffic Engineering Branch, Caltrans Headquarters, Sacramento;
August 1990.
9 (FEIS, Roseville Bypass. 9/84).
10 (ND/FONSI, Proposed Widening of 152 in Santa Clara County,
4/87).
11 (FEIS, Route 101 in Santa Clara County; fnew alignment
freeway from! Cochrane Rd....to 82. 7/78; ND, Widening 101 ...in
Santa Clara County from the Lawrence Expressway to the San Mateo
County Line. 10/86).
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program calls for at least a third of the state highways and
interstates to be counted each year. Thus the allowed maximum
time between counts on a roadway is three years. In District 4,
during the last decade these requirements were rarely met. Cfzen
traffic on a road went uncounted for 5 or more years.
The lack of up-to-date traffic counts created problems when
trying to match a prediction to a count. Predictions are always
made for a year at least 20 years in the future, and on some
projects for intermediate years also, often at 5 or "_ "D year
intervals. Growth (or decline) in freeway traffic volumes is not
always linear, but is often exponential or logarithmic. Thus, in
the typical case when the traffic was counted in a year for which
there was no projection, simply interpolating the accuracy of the
prediction based on straight-line traffic increases between the
present and the predicted year(s) is somewhat inaccurate.
t
Furthermore, the census program calls for the highway under
study to be counted for a period of at least a week; in each of
the quarters of the year. Unfortunately, some of the District 4
traffic counts were less than one week, and some were as short as
3 1/2 days. On most urban freeways and ramps, traffic varies
substantially throughout the week, typically with highest volumes
on Friday and other weekdays, and a marked drop in Saturday and
especially Sunday traffic. In all cases where counts were made
for less than a full week, the number of days is noted in the
following Tables of results. The ADT figures I calculated from
these short counts were not straight averages of the daily
22
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traffic totals, but were adjusted using knowledge of weekly
variations on adjacent ramps and freeway sections to provide a
best estimate of an accurate ADT volume. Similarly, for counts
of more than 7 days, the ADT's given are not a straight average
of daily traffic totals, but are averages of the averaged weekday
totals.
Traffic volumes fluctuate not only with the day of the week,
but also by the season. While seasonal fluctuation is generally
less on urban as opposed to rural roads, in California with our
emphasis on recreation, urban seasonal variations are still
significant. These variations are usually not recorded in zhe
Bay Area, though, since the counts are made only once in the year
of the count.
Another major obstacle to comparing predictions with counts
was that even if the predictions were fairly extensive,
frequently count information was available for only a small
i
portion of the project. Basing a decision on the accuracy of an
entire project's traffic predictions on the validity of a small
portion's (e.g., one interchange) prediction is risky business.
As seen in the findings discussed below, on many of the projects
some predictions seemed reasonable while others were inaccurate.
On one project, the only portions to be counted were those for
which no predictions had been made12.
Another problem in the data arises from the fact that
12 (DEIS, 92 Gap Closure and 92/101 Interchange Completion Fin
San Mateo County1. 2/79).
23
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traffic on freeway ramps is counted with rubber air hose
counters, instead of wire loops buried in the roadway. The loops
record passing vehicles. However the air hoses count, axles, not
vehicles, and record 2 axles as 1 vehicle. Therefore each truck,
which has up to 5 axles, incorrectly triggers the ramp hose
counter, into thinking that 2.5 vehicles have passed. There is no
separate or additional tally of truck traffic on ramps. Thus,
the ramp volumes in the data actually overstate the number of
vehicles. Of course, if the percentage of ramp traffic that: is
trucks is very low, this problem is minimized.
However, I chose not to use some arbitrary truck percentage
to adjust the ramp volumes down, because of other problems that
cause these figures to be too low. Measuring only one week out
of the year and recording the highest observed volumes as the
peak hour volumes is inaccurate. This is because the actual peak
hour volume is the volume recorded if the highway were to be ,
continuously monitored for an entire year and the tenth highest
volume was selected. If the volumes were randomly distributed,
the highest volume in a week of counting would be only 28% of the
actual peak hour volume13.
However, peak hour volumes are not randomly distributed,
13 Actual peak hour = 10th highest hour
8670 hrs. each year
and 240 hours in 10 days. So observed peak hour is x of actual
peak hour, where: 10 = x x=.28
8670 240
24
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because freeways have a finite carrying capacity. While the peak
hour volumes I use as actual volumes are certainly more than 28%
of the real peak hour figures, they are still probably
underestimates. Thus this error tends to counteract the effect:
of not adjusting ramp counts downward to account for the presence
of trucks on the ramp.
C. Findings
Because of ~he reasons described above, it was possible re
include only 5 of the 27 projects in Part II of this szuay. Four
were located in the Bay Area, and one was in the greater
Sacramento region. Figures 1 and 2 show the location of the
proj ects.
The first project was on 1-680 in eastern Contra Costa
County. In 1985, a new interchange at Bollinger Canyon Road was
added to the freeway, and two existing interchanges, at Crow ,
Canyon and Sycamore Valley Roads, were expanded. The FONSI/ND
prepared in 1983 predicted traffic levels on all the ramps for
the year 2005. (See Figure 3 for diagrams of all the ramps). In
late April and early May of 1986, Caltrans crews counted traffic
volumes on all the ramps, with their data collection varying from
10 to 3 1/2 days for different ramps. The 1986 ADT, and a.m. and
p.m. peak hour volume counts are compared with the 2005
projections in Table 2.
For these three interchanges, there was a total of 18 ramps.
For 11 of these ramps, the 1986 volumes were significantly less
25
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Figure 1: Greater Bay Area Capacity Increases
included in Part II
MONTEREY
AREA
.
v*£' I/1'580 [Hoffman Freeway]
' -° ° •*
fefpX/:-^r^
fm^SE-rM-I
. - • . ,
iW^-—a , -• \ .\ •U.I,*^. •. 1 '
fOo.-.^-, , , --. --_ ,•-.,,' 'iUm,', -.
•'-' ! ' OaitlcnaJ ^ -—i-\ \ •";-^-• -.
-^i^t^---'1- ••/~X-'--'N- \ --^-^
ii "'"-1*11
S«fL,; ~|»J-§;'^r* i :ir^^r W~fe^ I-680 Interchanges {
;,%«.,:r^ ^Y"'''^^^ II- Leanor° - 15S lv-f""' J^*^ '" y^43
wN-j-H^-d -r:i^m-,LKi
ZfL^'x&iST? &%*''
11 J ---.... mr^B^ '-^-^ «*- ^^ MI i" .r -_1 -J_
\ Route 101- new alignment freeway
/ >^»-w<»ft.//cr"jrf.. ,---- •—»". \ \«. v.
26
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Figure 2: Sacramento Area Capacity Increase
included in Part II
_^ii !——=• Roseville Bypass [Route 65]
i \ V ^V s
.? /' !•' U
••,. '.-«„..' I1, s " -^ ,.•••'
27
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Figure 3: Ramp Configurations for 1-680 Interchanges
SB off ramp'
SB on loop
SB on
1-680
1-680
SB off ramp
SB on loop
SB off loop,
SB on ramp
on ramp
on loop
off ramp
Bellinger Canyon Interchange
Crow Canyon Interchange
1-680
Sycamore Valley
t,
>f>iB on ramp
NB off loop
,NB off ramp
Road
SB off ramp
SB on ramp
SB off loop
Sycamore Valley Interchange
28
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Table 2: Predicted and Observed Traffic Volumes on 3 1-680 Interchanges
Note: Predicted volumes are for the year 2005, and observed volumes are from counts
in April and May of 1986. Ramp configurations are shown in Figure 3. North and
southbound are abbreviated NB and SB, respectively. Interchange is abbreviated I/C.
ADT a.m. peak hour p.m. peak hour
Ramp Observed Predicted Observed Predicted Observed Predicted
1986 2005 1986 2005 1986 2005
(Bellinger Cyn. I/C:)
NB off ramp 5,890 18,950 1,435 2,285 714 1,505
NB on loop' 2,186 1,850 488 130 189 240
NB on ramp2 4,045 12,325 239 650 S95 1,515
SB off ramp 5,458 15,175 1.097 2.U10 'i22 :,025
SB on loop2 3.296 15,500 373 1.250 I.U56 l.cSO
SB on ramp1 2,275 2,320 322 250 233 260
(Crow Canyon I/C:)
NB on loop 9,038 15,350 840 1,315
NB off ramp2 3,686 20,175 577 2,270
NB on ramp2 7,054 15,625 432 1,760
SB off ramp2
plus off loop 16,880 29,525 2,344 2,640
SB on loop2 3,105 13,175 245 1,200
SB on ramp1 5,976 6,775 491 535
(Sycamore Valley Rd. I/C:)
NBofframp1J 3,180 2,520 209 250
NBoffloopu 3,682 3,990 387 245
NB on ramp2 9,803 18,060 1,135 1,420
SB off ramp1-2 4,534 3,890 367 995
SB off loop2 6,313 9,770 358 995
SB on rampu 7,226 4,510 672 715
1,074 1,755
521 1,765
1,078 1,365
1,383 3,265
394 1,435
770 820
304 275
353 440
880 1,985
415 430
717 1,075
672 495
1 indicates a ramp with a significant underprediction for one or more parameters.
2 indicates a ramp where the observed ADT is an estimate based
week of traffic counting.
on less than a full
29
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than the 2005 projections, typically ranging from a third ~o
two-thirds of the 2005 projections. Because of the 19-year
discrepancy between the counts and the forecast, this range of
observed traffic levels seems reasonable. For at least one of
the three parameters of ADT or a.m. or p.m. peak hour, traffic en
7 of the ramps in 1986 was higher than that predicted for 2005.
Another of the ramps had 1986 volumes that were as high as 94% of
the year 2005 predictions. These ramps are indicated in Table 2,
and are distributed across each of the three interchanges.
Caltrans seriously underestimated the future traffic volurr.es for
these ramps, since traffic modeling shows yearly increases in
traffic levels until the ramps or freeways are saturated, and
then constant levels.
In 1984, 12 miles of new-alignment freeway opened in Santa
Clara County from Cochrane Road in Morgan Hill to Route 82 in San
Jose. The new freeway, part of Route 101, replaced a length ^f
signalized highway known as Monterey Road and linked existing
freeway sections to the north and south. The 1978 FEIS predicted
1995 AADT and a.m. peak hour mainline traffic volumes at 2 points
along the new freeway. Two complete sets of these predictions
were made for two different population projections. The
"losouth" predictions assumed a moderate rate of growth in
southern Santa Clara county, while the "grosouth" predictions
assumed accelerated, substantial growth. Unfortunately, no
predictions were made for ramp or p.m. peak hour volumes, and the
AADT figures are 2-way volumes (lumping both travel directions
30
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into the given volume).
Both the north and southbound directions of the new freeway
between the Bernal and Cochrane Roads interchanges (the southern
half of the project) were counted for 6 1/2 days in August of
1985. For the northern half of the new freeway, only the
southbound direction was counted, in both April of 1985 and
October of 1984 for 7 days each time.
Table 3 lists the traffic forecasts and the actual counts.
Assuming that traffic volumes will not decline, Caltrans
substantially under-predicted both AADT and peak hour traffic on
this project. Virtually all the predictions for 1995 using
either growth alternative were exceeded a decade early.
Another project on Route 101 further north in Santa Clara
County widened the existing freeway from 6 to 8 lanes through the
towns of San Mateo, Mountain View, and Palo Alto. Completed in
December of 1988, this project had peak hour predictions for 1995
and 2010 for all ramps and sections of the mainline. These
predictions were made by DKS Associates'4. Unfortunately, only
one of the numerous interchanges along this section of freeway
had been counted since the project was completed, and none of the
freeway mainline had been counted since it was widened.
The interchange that had been counted, in April of 1989, is
the Lawrence Expressway/Route 101 interchange at the southern
terminus of the project. The ramp configuration and designations
14 (July 1987 Route 101 in Santa Clara County: Bernal Road to
the San Mateo County Line. Corridor Study and Operations Analysis.
Final Report. DKS Associates).
31
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Table 3: Predicted and Observed Traffic Volumes on Route 101
(new alignment freeway from Cochrane Road to Route 82)
Note: All predicted volumes are for 1995. North and southbound are abbreviated
NB and SB. "GroSouth" assumes high, accelerated population growth in southern
Santa Clara County; "LoSouth" assumes steady, continuing population growth.
Mainline south of Metcalf Rd. overcrossing (between Bernal and Cochrane
interchanges):
"LoSouth" traffic predictions:
Two-way ADT: NB a.m. peak hour: SB a.m. peak hour:
45,000 2,420 1.620
"GroSouth" traffic predictions:
Two-way ADT: NB a.m. peaK hour: S3 a.m. peak hour:
56,000 2,970 VJ80
Observed traffic volumes (based on a 6 1/2-day count 8/85):
Two-way ADT: NB a.m. peak hour: SB a.m. peak hour:
68,201 2,722 2,623
Mainline south of Blossom Hill Rd. (between Blossom Hill and Bernal
interchanges):
"LoSouth" traffic predictions:
Two-way ADT: SB a.m. peak hour:
54,200 1,950
"GroSouth" traffic predictions:
Two-way ADT: SB a.m. peak hour:
67,200 2,420
Observed traffic volumes (SB counts only; no NB counts):
(10/84) SB ADT: 44,142 SB a.m. peak: 2,980
(4/85) SB ADT: 36,576 SB a.m. peak: 3,034
SB average ADT: 40,359 average SB a.m. peak: 3,007
Two-way ADT:
80,718'
'(calculated assuming SB ADT=NB ADT; actual two-way ADT may be greater
since for mainline segment to the north, SB ADT was less than NB ADT)
32
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Figure 4: Lawrence Expressway/Route 101 Interchange
Ramp Configuration
Route 101
Off ramp from 101 SB
On loop to 101 SD
Lawrence
Expressway
On ramp to 101 S
Off loop from 101 S
On ramp to 101 NB
ff loop from 101 NB
loop to 101 NB
Off ramp from 101 NB
Southbound
(SB)
Northbound
(NB)
33
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of this full cloverleaf are shown in Figure 4.
Of the 8 ramps, 4 had 1989 a.m. peak hour volumes higher
than the 1995 predictions, and 2 of these were even higher than
the 2010 predictions. The comparison is shown in Table 4. While
it was only possible to judge the validity of the forecasts for
one of many intersections and nowhere on the mainline, and no
forecasts were made for ADT volumes, fully half of the
comparisons possible show substantial underprediction.
Table 4: Predicted and Observed Traffic Volumes for the Route
101/Lawrence Expressway Interchange
Note: Predicted volumes are for 1995 and 2010, and observed volumes are
from April 1989 counts. Ramp configuration is shown in Figure 4. North
and southbound are abbreviated NB and SB, respectively.
aun. peak hour:
Ramp: 1989 (Observed) 1995 Prediction 2010 Prediction
On loop to 101 SB from Xway 334 539 651
Off ramp from 101 SB to Xway1 701 693 771
Off loop from 101 SB to Xway1 344 328 371
On ramp to 101 SB from Xway 798 1,050 1,000
On ramp to 101 NB from Xway 392 590 619
Off loop from 101 NB to Xwa/ 1,025 842 1XX)
On loop to 101 NB from Xway 532 649 o91
Off ramp from 101 NB to Xway1 722 674 720
1 indicates a ramp where traffic was significantly underpredicted.
The fourth and final Bay Area project in this segment of the
study was the construction of a new freeway from Route 80 to the
Richmond/San Rafael bridge. The 6-lane freeway, with an HOV lane
in both directions for much of its length, replaced a road
network that consisted of both a signalized highway and a limited
34
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access 4-lane expressway (Hoffman Boulevard). Original plans
were for the freeway to be labelled Route 17 or 1-180, but today
it is designated 1-580, although it is not yet complete. The
road is open to traffic, but a few interchanges are nor yet -n
their final configuration or are still closed. Caltrans
officials believe that current traffic volumes are below the
volumes the road will carry when it is completed.
Detailed predictions for 1995 ramp and mainline ADT and a.ni.
and p.m. peak hour volumes were made in ~he August 1973 P.evisea
Traffic Projections for the 130 (17) Corridor... -n tne Ti~v ;r
Richmond. Caltrans counted traffic on most of the existing on
and off ramps in late April and May of 1990, but has not counted
mainline volumes on the freeway. Indeed, counting the mainline
will prove difficult, for in the rush to open the new lanes after
the Loma Prieta earthquake of October 1989, no loops were
installed.
However, because the bridge at the western end of the
project is a toll bridge, daily traffic volumes are always
recorded there. Thus ADT is readily calculable, but only in the
direction of the toll, which is westbound. Knowing the total
vehicles at the project's western terminus and adding and
subtracting all vehicles entering and leaving the mainline could
theoretically yield mainline ADT volumes at any point along the
project. This was not possible, however, since Caltrans had not
counted the exit immediately east of the bridge, among others.
Table 5 compares the 1995 predictions to the 1990 counts.
35
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Table 5: Predicted and Observed Traffic Volumes on 1-580 [the Hoffman Freeway]
Note: Predicted volumes are for 1995, and assume the freeway is completed. Observed volumes are
from counts in late April and early May of 1990, when the freeway was not yet completed. West ana
eastbound are abbreviated WB and EB, respectively.
ADT: ajn. peak hour: p.m. peak hour:
Ramp Observed Predicted Observed Predicted Observed Predicted
1990 1995 1990 1995 1990 1995
WB on ramp from Central Ave.1 4,458 2,940 378 260 511 140
EB off ramp to Central Ave. 2^80 2,625 193 210 236 345
WBofframptoBayviewAve.1 3,564 5,400 200 490 711 320
WB on ramp from Bayview Ave. 1,904 5,870 180 495 182- 370
EB on ramp from Bayview Ave.1 2,039 5,400 407 300 183 325
WB off ramp to Erlandson St. 2,288 7,000 187 400 235 600
EB on loop from Eriandson St. 1.801 7.000 123 500 222 360
WB off ramp to 23rd St.1 5.506 7,860 316 iSO 599 -30
EB on ramp from 23rii St.' 2J.22 3,950 372 100 226 ;1;>
EB off ramp to 23rd St. 1.649 4,670 i28 :?5 i','1 -7~>
EH on loop from 23rd St.1 3,937 4,320 884 3
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Caltrans District 10 traffic count staff to carry relatively
minor levels of traffic, and thus the ADT mainline predictions
just east of Western Drive can be used as roughly equivalent to
the ADT predictions at the toll plaza. Table 5 also compares the
toll plaza ADT count based on the late April and May traffic to
the mainline prediction east of Western Drive. While District 10
traffic count staff suspect that west and eastbound ADT volumes
are not equal on 1-580, since the toll is only collected in the
westbound direction, there is no measurement of eastbound
traffic. Thus I could only compare tne observed vestscund ADT
volume at this point to the westbound prediction to the east.
This prediction seems reasonable, for the 1990 traffic is
considerably below the level projected for 1995.
Of the 6 projects in the greater Sacramento area, it was
possible to include only one, the Roseville Bypass, in this
second part of the study. In September of 1987, a new-alignment,
/
4-lane limited access expressway opened from the existing Route
65 to 1-80, allowing through traffic to bypass the signalized
highway through downtown Roseville (see Figure 2). This bypass
is essentially a new-alignment freeway. Predictions of 2-way ADT
and peak hour volumes on the bypass were made in the 1984 FEIS
for traffic levels in the year 1987 and at 3-year intervals
thereafter. Traffic on the bypass is counted continuously, and
Table 6 compares the predictions to the counts.
The actual volumes are less than the predictions for this
project. Roseville was predicted to develop substantially as the
37
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Table 6: Predicted and Actual Traffic Volumes on
the Roseville Bypass (Route 65)
Note: Actual volumes are rounded to the nearest hundred. Actual ADT
volumes are AADT figures; predictions are not assumed to be AADT figures.
Actual volumes were obtained for a continuous count of the freeway for
the entire year specified.
Two-way mainline ADT volumes:
1988 Actual 1989 Actual 1987 Prediction 1990 Prediction
13,000 14,800 11,700 21,200
Two-way peak hour volumes:
1988 Actual 1989 Actual 1987 Prediction 1990 Prediction
1,300 1,500 1,200 2,200
computer and semiconductor industries moved to the area. One
factor that may explain the lower than expected volumes is that
as a result of changes in these industries much of the predicted
development has not occurred.
D. Discussion of Part II Findings
Despite the numerous problems and uncertainties discussed at
length earlier with the data this study uses, it is clear that
the planning for freeway capacity increases has frequently
underestimated the traffic that actually uses the new or improved
roads or interchanges. While the magnitude of the
underprediction has varied, in 5 of the 6 projects that were
analyzed, the forecasted traffic volumes or some portion thereof
were exceeded, as much as a decade ahead of schedule. Thus it
seems that there has been a consistent underprediction of traffic
use for a variety of projects, including those planned quite
recently as well as more than a decade ago.
38
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Looking in detail at the specific factors that could explain
where the forecast models erred is beyond the scope of this
study. Certainly one problem is the lengthy time between project
planning and construction. Because of the complex environmental
process, the vagaries of construction, political opposition, or
inertia, planning and constructing a major freeway project can
take up to a decade or more. This tends to decrease the validity
of the forecast models for several reasons.
First, given infrequent traffic counts, the counts on -he
existing road network, wnich are an essential input tc the models
predicting future traffic, often predate the final environmental
document by as much as 4 years. If traffic has increased during
this time, which almost invariably is the situation in
California, the models will tend to underpredict future traffic.
Second, lengthy time between planning and construction may mean
that the effects on traffic of significant increases or •
locational shifts in regional growth in the meantime are not
predicted.
An "explanation" by Caltrans for the observed
underpredictions might simply be that regional growth outstripped
the projections of the various local and regional planning
bodies, and blame for this is simply not attributable to the
transportation providers. However, increased regional growth is
often a function, at least in part, of freeway capacity
increases.
Ultimately the reason for underprediction is irrelevant when
39
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weighing the consequences of this trend on regional air quality.
Because congestion levels and tailpipe emissions are partially
determined by traffic volumes, underprediction of volumes means
that these projects' air quality analyses were inaccurate and
overly optimistic. No matter the cause, consistent
underprediction of future traffic means that the supposed air
quality benefits of freeway work: have been consistently
overstated.
CONCLUSION
This study found significant flaws in the air quality
analyses done for freeway capacity increases. The level of
detail of the analyses was often inadequate and the traffic
forecasts underlying the analyses showed a pattern of
underprediction of the improved roads' actual use. Freeway
projects that were allowed on the belief that they were going^to
help solve our pollution problems have instead probably made them
worse.
Checking on the accuracy of the traffic predictions is
essential to preventing further deterioration in air quality.
After years of federal and state reductions in highway project
funds, Proposition 111, in addition to county transportation tax
initiatives throughout the state, will provide a huge influx of
money into cash-starved construction programs. Many projects
which have been planned for years will now have their NEPA/CEQA
documents prepared, or will be put out for bids. If traffic
40
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predictions turn out to significantly understate the actual
traffic levels on these projects, Californians will suffer by
breathing air that will be more noxious than predicted in the
projects' air quality analyses.
Furthermore, given the drastically tighter standards of the
California Clean Air Act, as well as the forthcoming Clean Air
Act amendments, it is now more important than ever to scrutinize
these types of highway projects closely to see that they don't
pull our urban areas into a smog-choked future fron wnicn we
could only escape at enormous social cost.
To improve the planning process for these types of projects,
I suggest the following steps be undertaken. Most urgently,
Caltrans should improve its traffic counting program, especially
in the Bay Area and other areas of the state where this program
is weak. Spending over a billion dollars a year on construction
and so little on traffic counts is poor public policy, for the'
counts form the basis on which all highway planning rests.
The technology exists, and is employed in the Sacramento
area, to continuously count freeway traffic. For roughly $4,000
for each location, Sacramento has permanently installed the
hardware needed in conjunction with buried roadway loops to
continuously monitor freeway mainline and ramp volumes. Using
loops to monitor ramp traffic, as is done in Sacramento,
eliminates the inaccuracy of air hose counts caused by vehicles
with more than 2 axles. Also, new loops have become available
which are round in shape rather than square, and appear to be
41
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considerably more reliable and less prone to failure. Broken
loops should be replaced, and all new projects should have loops
installed as a matter of course.
Predictions for traffic use on capacity increasing projects
should be standardized to include estimates of AADT and a.m. and
p.m. peak hour volumes, for each roadway direction, rather than
minutes of delay, combined 2-way volumes, or other information.
Even more importantly, Caltrans should check the accuracy of
their traffic predictions by comparing them to actual rcadvay
counts to continually improve predictions on future projecrs.
The analysis of the effect of the project on emissions
should as a minimum quantify the emissions on CO (both in the
immediate project vicinity as well as regionally) , HC, NO., CO.,,
and PM-10. A practical monitoring and compliance plan should be
required to be a part of every project that alludes to mitigation
measures. Interchange projects should model not only the >
emissions of the cars actually on the ramps or in the
interchange, but also the emissions of the vehicles on the
mainline affected by the interchange traffic.
42
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Appendix A
There is a fairly large body of research that examines the effect
of highways on regional economies and land use. With the large
amounts of federal money provided for the interstate network in
the 1950's and early 1960's, there was an accompanying flurry of
academic research, as well as studies sponsored by the DOT and
FHWA, on the effects of these highways. Much of this work, falls
into one or more of the following categories:
-The effecr of a highway bypass on the economy of "he
bypassed town or village;
-The regional economic effects of urban beltways;
-Land use patterns at freeway interchanges in both rural and
suburban areas;
-Highway impacts on both actual and perceived property
values; ,
-Land use changes resulting from arterial and highway
improvements, for both rural and for urban areas;
-Demographic and community changes resulting from new
alignments and highway improvements.
These studies have used a very diverse assortment of data
sources, including aerial photography, number of and prices for
home sales, interviews with local officials and homeowners,
census tract information, gross sales and manufacturing data, and
county zoning maps.
Some of the more interesting or relevant studies are
43
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summarized below. The call number, in parentheses, is used by
the Institute of Transportation Studies Library, at UC Berkeley,
where most of these are available.
Griggs, A.0. Review of Some Effects of Manor Roads on Urban
Communities. '83. Chapter 3, "Land Use Changes".
Includes summary of various studies done on the effect of house
prices. Typically these show a slight decrease in value for
houses very close to the freeway (a result of increased noise)
and increases for those homes nearby that benefit from the
improved mobility. Range is -6 to +10%. (NS 83-531).
Kingham, I.R. "Suburban Hwys. & Roads as Instruments of Land Use
Change," Trans. Research Record 565, '76.
Highway engineers see their task as catching up on the provision
of road capacity to meet travel demand. "Suburban highways are a
result of land development and do not influence land use change."
All he did to conclude this, though, was interviews; a study with
limited use.
Buffington, J.L., et al. "Non-User Impacts of Different Hwy.
Designs as Measured by Land Use and Land Value Changes. Research
Report 225-2. Tx. Trans. Inst., Tx. A & M University. '78.
Found (for Texas) that urban areas were less affected by highway
improvements than suburban and rural areas, because of the lack
of undeveloped properties to develop.
Adkins, W.G. & A.W. Tieken. "Economic Impacts of Expressways in
San Antonio, Tx. Trans. Inst., Bull.#11, '58.
Because of the lack of undeveloped/vacant land in the region,
there were few land use changes when the new expressways were
built.
Adkins, W.G. "Effects of the Dallas Central Expressway on Land
Values and Land Use," Tx. Trans. Inst., Bull.#6, '57.
This freeway, built through a previous slum, created major land
use changes. Much new commercial, industrial, and residential
development occurred. Most of these changes occurred abutting
the highway or not far from it, though.
Duke, R. "The Effects of a Depressed Expressway— a Detroit Case
Study," The Appraisal Journal,'58.
Ford Expressway influences limited to roughly 300 metres on both
sides of it.
Palmquist,R.B. "The Impact of Hwy. Improvements on Property
Values in WA State," for WA DOT. '81.
Multiple regression study shows appreciation for areas with the
44
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new highway is 15-17% higher than for those without. Even within
600' of the road where noise is an issue, appreciation due to
accessibility is generally greater than the noise depreciation.
A sophisticated study: he looked at over 9000 sale prices, as
well as interviewing residents. However, the increases in
appreciation occurred only where the highway could be used for
commuting. (TA1001.5.P7).
Yu,J.C.& Allison,J.L. "A Methodology for forecasting Beltroute
Corridor Land Use Impacts and its Application to Utah 1-215. Dpt.
of Civil Eng., U. of Utah, '85.
Essentially the goal of this study is to allow towns to plan to
encourage "appropriate" (as defined by each community) growth
along the road corridor. The authors believe that beltways are
developed differently than regular limited-access expressways,
because they carry a different set of passengers. They establish
a complex predictive model to be used by town planners across the
country, who must input data specific to existing land uses in
the region of their proposed beltway. They test their model on
1-215 outside of Salt Lake. Conclusions: "[Beltroutes] are
particularly capable of altering, on a large scale, the attitude
potential land users have for land within the region through
which the route will be located as well as for land within
reasonable distance of the beltroute." "The perpendicular extent
of the [beltroute] corridor is a function of the homogeny of land
use as well as homogeny of characteristics of the land itself.
The extent [of] such a homogeny, both perpendicular and parallel
to the beltroute, yields an indication of the potential area that
a particular land use may eventually occupy." "A beltroute can
facilitate and even precipitate new land uses within the urban
area..." (TA1001.5.P7). •
Payne-Maxie Consultants, Blayney-Dyett Urban & Regional Planners.
"The Land Use and Development Impacts of Beltways: Case Studies,"
for DOT, '80.
A huge study trying to pin down the effects of urban
circumferential highways for 8 regions. Most of the roads
studied were built in the '60's or '70's. It lacks any
statistical techniques to attempt to accurately link changes to
the road, but rather tries to do so anecdotally/qualitatively.
200 pages later, the reader has a picture of how areas develop,
but not how the roads affected their development. (HE370.2.P2).
Barton-Aschman Assoc., for Illinois DOT. Highway and Land-use
Relationships in Interchange Areas. Springfield, VA. '68
A fairly typical example from numerous studies I saw on land use
at interchanges. (There is a related set of research on the
economics of interchange location, typically in terms of sales
volumes, based on such factors as ADT on the highway). This
study concludes "new hwy. facilities have a strong tendency to
generate new uses of land that are often, themselves, generators
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of large traffic volumes" [e.g., shopping malls]. (HE370.2.32).
Babcock,W.F.& Khasnabis,S. "An Analysis of the Impact of Freeways
on Urban Land Developments in NC...," NC State Raleigh, '74.
"Historically, the estimation of traffic for the freeway & the
intersecting roads has been accomplished by standard traffic
projection techniques. Generally, these have been based upon
existing land development plans and adopted transportation plans.
In many cases, such predictions have not been realistic, because
of unanticipated traffic that was generated by new land uses
brought about by the existence of the freeway." This study tried
to determine what development had occurred because of the freeway
by looking at aerial photographs over time and interviewing city
planners. (4505 Microfiche).
Burkhardt,J.S. Socio-economic Reactions to Hwy. Developr-.enx:.
'83. Anaiyz-es effects of freeways typically built througn urban,
and usually poor, areas in the 1960's & 1970's. He looked az
demographic, land use, housing market, etc. changes.
While such freeway building has essentially stopped roday because
such projects are no longer socially acceptable, he has some
interesting findings. Measurable impacts were limited to a 5 to
10 block swathe adjacent to highway, and the impacts were not
necessarily negative for the neighborhood. Big conclusion: the
general patterns of these freeways on the adjacent areas are
definitely secondary to site-by-site variations. (TA1001.5P7).
Cosby,P.J.& J.L.Buffington OR Herndon,C.W.& Buffington. "Land
Use Impacts of improving... Collins St. in a Developed Area of
Arlington, TX/ Gessner Rd. in a Developing Area of Houston/ etc.
Tx. Trans. Inst., Tx. A&M U., Ntl. Tech. Info. Service. '79 to
'80.
These are 6 very similar studies which use the same research
methodology. All look at improvements to arterial [non-
expressway] roads in different urban and suburban areas of Texas.
The studies set up 6 categories of land use, and guantify the
changes in land use occurring after the road upgrades. Typical
conclusions; "although the improvement of Collins St. helped
create an area more attractive for development, the impact on
land use [for this developed area] was not extensive. a). Most
of the development in this area occurred— before the road
improvement began and was most likely not influenced by the road
change....c) The road improvement is viewed as a positive
influence, because if the street had not been widened the
resulting congestion would: have been a deterrent to development.
OR: [for a developing area], 1)Commercial and multi-family
residential developments that were put on unimproved land were
located in the Gessner area partly because of the improved
access. 2). The improvement was also important in the changes
from single family to commercial and multi-family uses. General
criticisms; These studies are fairly simplistic. By lumping all
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land use into 6 categories, they do not distinguish between
density, quality, etc. of the areas before and after
improvements. Furthermore, they limited analysis to what struck
me as an overly-narrow band along the improved roadways. There
is no attempt to verify causality of changes, but only the
assumption that the changes are a direct result of the road.
Finally, none of the studies looked at limited-access highways.
(N.S.79-998,30-404/5/6.etc).
Rollins,J.B. et al. Effects of Roadway Improvements on Adjacent
Land Use; An Aggregative Analysis and the Feasibility of using
Urban Development Models. Tx. Trans. Inst. in coop, with FHWA.
Research Report 225-22. Study 2-8-77-225. '82
This study looked at 18 arterial improvements in non-rural Texas,
including the ones above. Typical improvements were arterial
lane increases, adding medians, turning lanes, etc., and most
were done in the '70's. This was easily the most statistically
sophisticated study I found. Techniques included ordinary least
squares multiple regression and a simultaneous equations ^cdel
with two-stage and three-stage least squares. The ir.odei allowed
the changes in the percent of each of the 6 land use categories
to be explained by numerous other independent variables besides
just the road improvements. Conclusions: net overall land
development is not significantly changed due to the roadway
improvements. But, roadway improvements do affect the
development rates of specific types of land uses. Residential
and public development are associated with ADT growth, and thus
road improvements. (N.S.82-116).
Economic and Social Effects of Highway Improvements, Section IV,
"Land & Prop. Values & Land Usage in relation to Dort Hwy. t
improvements. U.Mich., '61.
Older study, but some interesting findings. "The Dort Highway [a
Flint, MI bypass built in the late 1950's], like most other major
arteries, has been a powerful force molding & developing the area
which it serves." "The highway, by providing accessibility,
makes it possible to subdivide large tracts for the more
intensive uses demanded as a result of increasing economic
activity and growth..."
Mountain West, Socioeconoroic and Land Value Impact of Urban
Freeways in Arizona, for AZDOT in coop, with FHWA. (FHWA #AZ87-
282). '87.
Very thorough, careful study of the impact of freeway
construction on land use changes and property values in the
greater Phoenix region. To study land uses, aerial photography,
zoning changes, census data, and planning documents
were used. Property sales and valuation data and owner
interviews were also used. This study used control areas
(lacking the freeways but otherwise similar) to link observed
changes specifically to the freeways. Major findings: "The
strongest and most obvious conclusion about the historic
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socioeconomic impact of freeways in metro Phoenix is that
freeways are a necessary but not sufficient cause for development
to occur. Other factors are equally as important, including
municipal planning and zoning, land availability, existing
utilities and infrastructure, and other transportation modes—
railroads and arterials... (etc). Freeways merely create a
condition that improves the market opportunity for change....
Development around freeways can be controlled by strong urban
land use planning. However, it is clear that income-generating
properties— non-residential uses and apartments— have strong
locational preferences for freeway corridors... [The] intensity
of freeway corridor development depends on a combination of
macroeconomic demand conditions and the supply of developable
land... Beyond these broad statements, the specific kinds of land
uses and their locations are very much dependent on the
peculiarities of place— existing land uses, existing zoning,
etc... Land values in proposed freeway corridors have increased
due to road alignment announcements... It is clear that freeways
have stimulated non-residential growth.1'
This grossly oversimplifies very detailed findings.
(HE336.E3.T66).
Briggs,R. "The Impact of Interstate Hwy System on Non-metro.
Growth," DOT, Office of Univ. Research. Ntl. Tech. Info. Service,
•80.
Statistically sophisticated look at the big national picture;
included suburban, exurban, and rural growth across the country.
The county was the unit of analysis. Conclusions: "The results
of the research showed that, while counties with Interstates...
have higher average growth rates, even after confounding
factors... are controlled, the presence of a limited access
highway is far from an assurance of development for an individual
county... The Interstate system was less able to explain the
spatial pattern of development than non-transportation factors.
(PB81-212987 fiche).
Few studies investigate the effect of highway improvements
on induced trips/ADT/congestion, and thus air quality. All too
often this topic is discussed in general qualitative terms with
apparently very little quantitative work having been done to
demonstrate actual effects. The following studies touch on this
issue at least peripherally.
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John Paterson Urban Systems. Feasibility of Assessing Effects of
Road Improvements on Trip Making and Urban Public Transport, for
the [Australian] Commonwealth Bureau of Roads, '71.
Essentially, this whole document is an attempt by a consultant to
secure a contract to write a computer model to forecast the
effect of highway improvements on induced trips. He wanted about
Aust. $25,000 in 1973 money to do it, and predicted that it would
take 3 people most of a year to write the model. Apparently he
didn't get the contract. This document/proposal is very general
and of limited use. (HE370.2.J6).
Ziering,E. et al. "Energy Impacts of Transportation System
Improvements," Trans. Research Record 870.
This study basically applies modeling and work done by numerous
other researchers into a new model. "Unlike many earlier energy
impact estimation procedures, this methodology explicitly
considers induced and diverted travel resulting from a
transportation improvement and the effect of znis travel ^n ~ne
level of transportation services." Key to calculating rne
induced traffic levels are a set of travel-demand elasticities
developed by Charles River Associates for the CA Energy
Commission in 1982. "[The model] produced results that were
frequently counterintuitive... and contrary to commonly accepted
conclusions [ie, road improvements conserve fuel by reducing
congestion] concerning the energy [and air quality] impacts of
projects." Furthermore, "Highway widening or bypass projects can
either increase or decrease... consumption... Ramp-metering
projects yield energy savings when implemented under congested
conditions... In most cases, ramp delays reduce the amount of
induced new travel."
"The Vehicle-Miles of Travel-Urban Highway Supply Relationship,"
in Ntl. Coop. Hwy. Research Program's Research Results Digest
#127, 12/80.
Summary of NCHRP project 8-19 by Cambridge Systematics et al.
which generated a computer model that relates highway supply to,
among other things, air quality. This model, which apparently is
huge and consumes large amounts of computer time, was run on 2
Bay Area highways: lane additions to Rte.24 from the Caldecott
Tunnel east to Concord, and construction of Rte. 24 west from the
tunnel. The model says both these projects have been net air
quality improvements for all pollutants except for NOx.
(TA1001.5.N32).
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