United States
Environmental Protection
Agency
Air and Radiation
EPA420-R-98-002
March 1999
vvEPA
Benefits Estimates for
Selected TCM Programs
> Printed on Recycled Paper
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EPA420-R-98-002
March 1999
for
Regional and State Programs Division
Office of Mobile Sources
U.S. Environmental Protection Agency
Prepared for EPA by
ICF Incorporated
93 00 Lee Highway
Fairfax. VA
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TABLE OF CONTENTS
Page
INTRODUCTION -i-
I. ANALYSIS OF SINGLE TCMs
A. Example 1: Regional Public Transportation Authority
Telecommuting Program in Maricopa County, Arizona
1. General Description 1
2. Data Sources 1
3. Phase 1: Travel Activity Effects 1
4. Phase 2: Emission Effects 8
B. Example 2: Atlanta/De Kalb Greenway Trails
1. General Description 17
2. Data Sources 17
3. Phase 1: Travel Activity Effects 17
4. Phase 2: Emission Effects 22
C. Example 3: Cleveland Walkway to Gateway
1. General Description 30
2. Data Sources 30
3. Phase 1: Travel Activity Effects 30
4. Phase 2: Emission Effects 34
D. Example 4: Brevard County Vanpool Service
1. General Description 40
2. Data Sources 40
3. Phase 1: Travel Activity Effects 40
4. Phase 2: Emission Effects 45
E. Example 5: Boulder HOP Shuttle Service
1. General Description 54
2. Data Sources 54
3. Phase 1: Travel Activity Effects 54
4. Phase 2: Emission Effects 59
II. ANALYSIS OF TCM PACKAGES
A. Example 6: Cornell University
Transportation Demand Management Program
1. General Description 67
2. Data Sources 68
3. Phase 1: Modal Choice Analysis 69
4. Phase 2: Travel Activity Effects 81
5. Phase 3: Emission Effects 84
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BENEFITS ESTIMATES FOR
SELECTED TCM PROGRAMS
INTRODUCTION
This document presents applications of EPA's transportation control measure (TCM) analysis
guidance, entitled Methodologies for Estimating Emission and Travel Activity Effects ofTCMs, to six
actual TCM programs. The document is ^^^^^^^^^^^^_^^^^^^^^^^^^_
intended to assist government officials,
transportation planners/analysts, and other
interested parties in using EPA's TCM guidance
to analyze and evaluate TCM programs that have
been completed, are currently in progress, or are
proposed for future implementation.
The methodology outlined in EPA's
guidance for estimating the effects of TCM
programs consists of two phases, each of which
is composed of a number of smaller steps. The
first phases involves estimation of the travel
activity effects ofTCMs, including effects on
number of trips, vehicle miles traveled (VMT),
and vehicle speeds. In the second phase, the
effects on trips, VMT, and speeds are used to
determine effects on emissions of hydrocarbons
(HC), nitrogen oxides (NOx), and carbon
monoxide (CO). EPA's methodology also
presents a technique for analyzing the effects of
TCM packages, which involves using data on
current mode choices, travel costs by mode, and
travel times by mode to determine which TCMs
in a package of two or more will be chosen by
target populations. This type of analysis is
important given that TCM programs
implemented in the same area tend to interact
with one another.
As noted above, this document shows
how EPA's TCM methodology can be applied to
six TCM programs that have actually been
implemented in the U.S. These programs span a
number of the TCMs listed in the 1990 Clean Air
Act Amendments, including improved transit,
bicycle and walking paths, and ridesharing.
Using the methodology to analyze the travel
activity and emission effects of these and other
TCMs requires a large number of individual
parameters (presented in the equations in this
document) to be estimated or assumed by the
user. The methodology also requires obtaining a
Phase 1: Effects on Travel Activity
Step 1: Potential trip effects
Step 2: Direct work and non-work trip reductions
Step 3: Indirect work and non-work trip increases
Step 4: Peak and off-peak trip shifts
Step 5: Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Step 6: Peak and off-peak VMT changes due to
reduced number of trips
Step 7: VMT changes due to reduced trip lengths
Step 8: Net VMT changes
Step 9: Peak and off-peak speed changes
Phase 2: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
Step 4: Summation of emission effects
-i-
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substantial amount of program-specific and region-specific data. To the extent possible, the examples
below make use of such data, although in some cases reasonable assumptions or default data based on
national figures have been used. These cases are indicated where they occur. The implication of using
assumptions or default data is that the results of the analysis will tend to be less accurate than if actual
program or regional data were used. In analyzing their own TCM programs, government officials and
transportation planners/analysts will likely have ready access to most of the program-specific and region-
specific data required by EPA's methodology.
This document is divided into two sections. The first section presents example applications of
EPA's TCM guidance to programs involving only one TCM. The second section presents example
applications of the guidance to TCM packages.
-11-
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1. ANALYSIS OF SINGLE TCMs
This section uses the methodology described in Chapters 2 and 3 of EPA's TCM guidance
to estimate the travel activity effects and emissions effects of programs involving only one TCM.
The TCMs addressed in these examples include telecommuting programs, walking and biking trails,
transit improvements, and rideshare programs.
Example 1: Regional Public Transportation Authority Telecommuting Program in
Maricopa County, Arizona
General Description
The Regional Public Transportation Authority (RPTA) in Maricopa County, Arizona, has
implemented a program to promote telecommuting in the Maricopa County area. The program has
developed a telecommuting training curriculum and promotional materials to provide assistance to
employers interested in developing telecommuting programs. The program began with MPO approval
in September 1993. RPTA's goal for this program is to attain at least a 200 percent increase in the
number of businesses and other organizations with telecommuting programs in the region.
Data Sources
"Clean Air Campaign and Trip Reduction Survey," prepared by West Group Marketing Research
for the Regional Public Transportation Authority, Spring 1996. (hereafter, "TRP Survey")
"1996 Telecommuting Survey," prepared by West Group Marketing Research for RPTA/Valley
Metro, June 1996. (hereafter, "Telecommuting Survey")
Transportation Inventory & Analysis of Existing Conditions, 1996: Maricopa County.
1997 County and City Extra: Annual Metro, City, and County Data Book, Bernan Press, 1997.
1990 U.S. Census data.
1996 Statistical Abstract of the United
States.
Phase 1: Travel Activity Effects
Step 1 in the estimation of travel activity
effects for the RPTA program involves an
assessment of the potential trip effects from the
program. For telecommuting programs, these
potential effects are calculated using the
following formula:
PT = N * F / D * 2
In the formula, PT is the
number of trips
potentially affected, N is
Phase 1: Effects on Travel Activity
Step 1: Potential trip effects
Step 2: Direct work and non-work trip reductions
Step 3: Indirect work and non-work trip increases
Step 4: Peak and off-peak trip shifts
Step 5: Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Step 6: Peak and off-peak VMT changes due to
reduced number of trips
Step 7: VMT changes due to reduced trip lengths
Step 8: Net VMT changes
Step 9: Peak and off-peak speed changes
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the number of
participants in the
telecommuting program,
F is the frequency of
participation (in days per
week), and D is the
average number of
commute days per week.
The appropriate value for N is derived by first calculating the total number of telecommuters
in the program area, which is obtained by multiplying the total population of non-home-based employed
people in the region covered by the RPTA program (1,124,600) by the percentage of respondents in the
TRP Survey who telecommuted in 1996 (5 percent). The total number of telecommuters is then
multiplied by the percentage of telecommuting programs in the area that are attributable to the RPTA
program. Because the number of telecommuting programs in the area has increased from 57 to 260 since
the beginning of the RPTA program, and because the goal of the RPTA program is to increase the
number of telecommuting programs by 200 percent, it is reasonable to assume that 114 (or 57 times 200
percent) of the current 260 programs are attributable to the RPTA program. Thus, N = 1,124,600 * 0.05
* (114/260) = 24,655.
The value for F is derived from the Telecommuting Survey, which indicates that 27% of
respondents telecommute one to three days a week, 25% telecommute four or five days a week, and 16%
telecommute one to three days a month. Using average estimates for telecommute days (e.g., for
participants telecommuting four or five days a week, an average of 4.5 days is used) and assuming that
there are four five-day work weeks in a month, F = (0.27)(2) + (0.25)(4.5) + (0.16)(0.5) + (0.32)(0)
= 1.75.
The value for D is 5, based on the fact that there are five workdays per week.
Using the data above, PT = 24,655 * 1.75 / 5 * 2 = 17,259. Thus, the potential number of trips
reduced per day by the RPTA program is 17,259.
Step 2 in the travel activity methodology involves estimating the direct work and non-work trip
reductions from the RPTA program. Whereas the potential trip reductions calculated in Step 1 represent
the total number of trips that might be reduced by a TCM program, direct trip reductions measure the
number of trips that actually are reduced and, thus, can be less than potential trip reductions (e.g., if
a telecommuter was previously using transit to commute). Direct trip reductions are calculated using
the following formulas:
ATRIPSD = a * PT
ATRIPSDW= (o * ATRIPSD
ATRIPSDNW = (1 - co) * ATRIPSD
In the formulas, ATRIPSD is the total direct trip reduction, PT is (as above) the
potential trip reductions, ATRIPSD w is the direct work trip reduction,
ATRIPSDNW is the direct non-work trip reduction, a is the fraction of program
participants who make a direct trip change, and to is the fraction of trip effects
that are work-related.
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For telecommuting, a is defined
as -(1 - SAT) / AVO, where SAT is the
fraction of telecommuters who work in
satellite offices and AVO is average
vehicle occupancy. Because the
information on the RPTA program does
not indicate that satellite offices are used,
SAT is assumed to be 0%. The value
used for AVO is based on the following
information from the TRP Survey: 76%
of work trips are in single occupancy
vehicles (SOVs) (AVO = 1), 15% of work
trips are in carpools (AVO = 2.3), 5% of
work trips are on buses (AVO assumed to
be 15), 2% of work trips are on bicycles,
and 2% of work trips are walking. Thus,
AVO = (0.76 + 0.15 + 0.05 + 0.02 + 0.02)
/ [(0.76 / 1) + (0.15 / 2.3) + (0.05 / 15)]
= 1.21. Using the values for SAT and
AVO, a = -(1-0) /1.21 = -0.83.
Focus: FROM POTENTIAL TO ACTUAL TRIP CHANGES
The equations in Step 2 of the travel activity methodology
show how the potential trip effects ~ PT - break down
into actual reductions in work and non-work trips. The
rectangles below show how only a fraction (a) of potential
trip effects are realized, becoming ATPJPSD. Then, a
fraction (co) of these trip reductions are reductions in work
trips, while the rest (1 - co) are reductions in non-work
trips.
PT
(l-a) * PT
a*PT
ATRIPSD
ATRIPSD
o*ATRIPSD
Table 2-5 in EPA's TCM guidance document indicates that, for telecommuting, the parameter
(0 is equal to 1. This is because telecommuting directly affects work trips only.
Using the data above, ATPJPSD = -0.83 * 17,259 = -14,325, ATRIPSD w = 1 * -14,325 = -14,325,
and ATRIPSDNW = (1 - 1) * -14,325 = 0. Summarizing these results, the RPTA program is responsible
for directly reducing 14,325 trips per day, all of which are work-related.
Step 3 in the travel activity methodology
involves estimating the actual indirect trip
increases (for both work and non-work trips)
from the RPTA program. Indirect trip increases
are secondary effects that typically result when
vehicles normally used for commuting are left
at home. These increases are calculated using
the following formulas:
ATRIPSIW = INCWH * -ATRIPSD / 2
ATRIPSINW = INCNH * -ATRIPSD / 2
Focus: WHY ACTUAL TRIP CHANGES ARE LESS
THAN POTENTIAL CHANGES
In this example, the fraction of potential trip effects
that are realized (a) is defined as the fraction of
telecommuters who do not work in satellite offices,
divided by average vehicle occupancy. Telecommuters
who use satellite offices are excluded because they still
drive from home to the satellite offices. The remaining
fraction is divided by average vehicle occupancy
because some of the workers who become
telecommuters may have been sharing rides originally.
If, for example, two workers had been sharing one
vehicle for commuting, and each began telecommuting
(without using a satellite office), we would see a
reduction of only one trip to work. Here, AVO is 2,
and a would be (l-0)/2, or one-half. (Note: The
parameter a is actually expressed as a negative number
to reflect that TCMs are typically designed to reduce
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In the formulas, ATRIPS: w is the indirect work trip increase, ATRIPSINW is the
indirect non-work trip increase, and INCWH and INCNH are the rates of increased
SOV work and non-work trip making by household members of TCM
participants who leave their vehicles at home. The other parameter in the
formulas is defined in an earlier step of the methodology.
INCWH is defined as NV * SHR * (SIZE - 1) * EMP * TGW, where NV is the fraction of the
population that does not own a vehicle (Note: This analysis interprets this parameter to mean the
percentage of drivers without a vehicle, which is estimated as the percentage of vehicle-owning
households in the program area that have only one vehicle.), SHR is the fraction of shared mode trips,
SIZE is average household size, EMP is the fraction of the population that is employed, and TGw is the
work trip generation rate for SOV users. NV is
assumed to be 42%, based on U.S. Census data
for Maricopa County. The TRP Survey
indicates that 15% of work trips are in carpools
and 5% are on buses, resulting in an SHR
estimate of 20%. (Note: It may be appropriate to
use only the transit portion of shared mode trips
for the SHR parameter.) SIZE is assumed to be
2.59, based on information reported in the 7997
County and City Extra. The value for EMP is
55% and is taken from the TRP Survey, which
indicates that 47% of the population in the
program area is employed full-time and 8% of
the population is employed part-time. The TRP
Survey also reports 1,663,200 SOV work trips
and 971,700 SOV commuters, and thus TGW =
1,663,200/971,700 = 1.71. Based on these
numbers, INCWH = 0.42 * 0 .20 * (2.59 - 1) *
0.55* 1.71=0.'l3.
INCNH is defined as NV * SHR * (SIZE
- 1) * UNEMP * TGN, where NV, SHR, and
SIZE are as defined above, UNEMP is the
fraction of the population that is not employed,
and TGN is the non-work trip generation rate for
SOV users. UNEMP is simply (1 - EMP) and
thus equals 45%. TGN is assumed to be the same
as TGW (i.e., 1.71). Based on these numbers,
INCNH = 0.42 * 0.20 * (2.59 - 1) * 0.45 * 1.71 = 0.10.
Using the data above, ATRIPSIW = 0.13 * -(-14,325) / 2 = 1,862, and ATRIPSINW = 0.10
* -(-14,325) 12= 1,433. Summarizing these results, the RPTA program is indirectly responsible
for an increase of 1,862 work trips per day and 1,433 non-work trips per day.
Step 4 in EPA's methodology for estimating travel activity effects of TCMs, which involves
determining direct peak and off-peak period trip shifts, does not apply to telecommuting programs.
Thus, Step 4 is not relevant to the analysis of the RPTA program.
Focus: TRIPS REDUCED HERE CAN INCREASE
TRIPS ELSEWHERE
In Step 3 of the travel activity methodology, the
conceptbehindthe calculation of INCWH (the increased
fraction of work trips made by other household
members) is that the availability of another car when
one person starts participating in a TCM program (e.g.,
telecommuting) will prompt other workers in the
household who previously had to share rides to work to
begin driving. To estimate how frequently this would
happen, we multiply the number of other workers in a
typical household - (SIZE - 1) * BMP - by the
fraction of work trips made by shared modes (SHR)
and then by the fraction of households that might not
have enough cars for every worker. The factor (SIZE
- 1) is the typical number of persons in a household
minus one, to allow for the worker who is now
participating in the TCM program. BMP is the fraction
of people who are employed, and NV is the fraction of
households that have only one vehicle (and therefore
might be more likely to have more workers than cars)
. (Note: Similar logic underlies the calculation of
INCN H, which is the increased fraction of non-work
trips made by other household members. In this
fraction, the variable UNEMP is used to account for
unemployed drivers in the household.)
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Step 5 in the travel activity methodology involves estimating the net trip changes from the RPTA
program as distributed between work and non-work trips and peak and off-peak periods. These changes
are calculated using the following formulas:
ANETRPWP = (o * ATRIPSgp + PKW * (ATRIPSDW + ATRIPSIW)
ANETRPWOP = co * ATRIPSSOP + (1 - PKW) * (ATRIPSDW + ATRIPSIW)
ANETRP
^p = (!-«)* ATRIPSSP + PK
= (1 - G>) * ATRIPS^p + (1 -
* (ATRIPSDNW + ATRIPSINW)
^) * (ATRIPSUNW + ATRIPSINW)
In the formulas, ANETRPWP is the net work trip change in the peak period,
ANETRPWOP is net work trip change in the off-peak period, ANETRP^p is the
net non-work trip change in the peak period, and ANETRP^ OP is the net non-
work trip change in the off-peak period. ATRIPSSP is the change in peak period
trips, and ATRIPSSOP is the change in off-peak period trips. PKW is the observed
fraction of work trips during the peak period, and PK^ is the observed fraction
of non-work trips during the peak period. The other parameters in the formulas
are defined in earlier steps of the methodology.
Because there are no trip shifts associated with telecommuting (see Step 4), ATRIPSSP and
ATRIPSSOP are each equal to 0.
The value used for PKW is 0.7, based on
data for Phoenix, Arizona presented in Appendix
B of the TCM guidance document, and assuming
that peak travel hours are from 6 a.m. to 9 a.m.
and 4 p.m. to 7 p.m. PK^ is assumed to be 0.3,
based on an example presented in the TCM
guidance document.
Using the data above, ANETRPWP = 0
+ 0.7 * (-14,325 + 1,862) = -8,724, ANETRPWOP
= 0 + (1 - 0.7) * (-14,325 + 1,862) = -3,739,
ANETRPWP = 0 + 0.3 * (0 + 1,433) = 430,
and ANETRP^op = 0 * (1 - 0.3) * (0 + 1,433)
= 1,003. Summarizing these results, the RPTA
program results in net decreases in peak and
off-peak work trips of 8,724 per day and 3,739
per day, respectively. The program also results
in increases in peak and off-peak non-work trips
of 430 per day and 1,003 per day, respectively.
Step 6 in the travel activity methodology involves estimating the peak and off-peak VMT
changes due to the trip changes from the RPTA program. These changes are calculated using the
following formulas:
AVMTp = (ANETRPWP * DISTW) + (ANETRP^p * DIST^)
AVMTOP = (ANETRPWOP * DISTW) + (ANETRP^p * DIST^)
In the formulas, AVMTP is the change in peak-period VMT due to trip changes,
AVMTOP is the change in off-peak VMT due to trip changes, DISTW is the
average VMT per trip for work trips, and DIST^ is the average VMT per trip
Focus: DISTRIBUTING TRIP CHANGES BY
TIME-OF-DAY
Earlier steps in the travel activity methodology have
shown that trip changes resulting from TCM
programs can be broken down into work trip changes
and non-work trip changes. As shown in Step 5,
another key distinction is between peak-period trip
changes and off-peak trip changes. The parameter
PKW accounts for work trips occurring during peak
hours (i.e., 6:00 am to 9:00 am, and 4:00 pmto 7:00
pm). Similarly, the parameter PKNW accounts for
non-work trips occurring during peak hours.
Because most people tend to keep regular work
hours, we would generally expect PKW to be greater
than 0.5. In addition, because non-work trips are
more discretionary than work trips, we would expect
most of them to occur in off-peak periods (when
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for non-work trips. The other parameters in the formulas are defined in earlier
steps of the methodology.
DISTW is 13.9 miles per trip, as indicated by the TRP Survey. DIST^ is assumed to be 4.7
miles, based on the average passenger vehicle trip length for Maricopa County (7.1 miles, as reported
in Transportation Inventory & Analysis of Existing Conditions, 1996: Maricopa County) and the
percentages of total trips that are work and non-work related (as reported in the 1996 Statistical Abstract
of the United States).
Using the data above, AVMTP = (-8,724 * 13.9) + (430 * 4.7) = -119,243 and AVMTOP = (-3,739
* 13.9) + (1,003 * 4.7) = -47,258. Summarizing these results, the RPTA program reduces peak-period
VMT by 119,243 miles per day due to trip changes and reduces off-peak VMT by 47,258 miles per day
due to trip changes.
Step 7 in the travel activity methodology involves estimating the VMT changes due to trip length
changes resulting from the RPTA program. These changes are calculated using the following formulas:
AVMTLW = p * PT * -(DISTW - DISTnew)
AVMTLNW = p * PT * -(DIST^ - DISTnew)
In the formulas, AVMTL w is the change in VMT due to work trip length
changes, AVMTL ^ is the change in VMT due to non-work trip length changes,
P is fraction of program participants who change their trip length, and DISTnew is
the new work or non-work trip length. The other parameters in the formulas are
defined in earlier steps of the methodology.
For telecommuting, the guidance indicates that p is equal to SAT. As noted in Step 2, SAT = 0
and thus p = 0.
Because no participants in the RPTA
program are assumed to work at satellite work
centers, DISTnew = 0 for work trips (i.e., the new
work trip length is 0 because all participants work
at home). Because the RPTA program does not
directly affect non-work trips, DISTnew for non-
work trips is equal to
FOCUS: VMT IS REDUCED TWO WAYS
As shown in Step 7, in addition to reducing VMT
through trip reductions, TCM programs can also reduce
VMT by reducing the length of existing trips. For
example, telecommuters who work at satellite work
centers that are closer to home than their regular offices
(so that DISTnew < DISTW) must still drive to and from
Using the data above AVMTL w = 0 * workeachday. However, because these telecommuters
17259* -(13 9 - 0) = 0 and AVMT ' = 0 * have reduced the lenS^ of each *"?> VMT decreases-
17,259 * -(4.7 - 4.7) = 0. Summarizing these
results, the RPTA program does not reduce VMT
through changes in trip lengths.
Step 8 in the travel activity methodology involves estimating the total peak and off-peak VMT
changes resulting from the RPTA program. These changes are calculated using the following formulas:
ANETVMT = AVMTp + PKW * AVMT
ANETVMT0p = AVMT
LW
+
* AVMT
L,NW
0p
(1 - PKW) * AVMTL>W + (1 -
* AVMT
L,NW
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In the formulas, ANETVMTP is the total change in peak period VMT, and
ANETVMTOP is the total change in off-peak VMT. The other parameters in the
formulas are defined in earlier steps of the methodology.
Using the data above, ANETVMTP = -119,243 + 0.7*0 + 0.3*0 = -! 19,243 and ANETVMTOP
= -47,258 + (1 - 0.7) * 0 + (1 - 0.3) * 0 = -47,258. Summarizing these results, the RPTA program reduces
peak-period VMT by a total of 119,243 miles per day and off-peak VMT by a total of 47,258 miles per
day.
Step 9 in the travel activity methodology involves estimating peak and off-peak speed changes
resulting from the RPTA program. These changes are calculated using the following formulas:
ASPDp = (ANETVMTp / TOTVMTP) * ep
ASPDOP = (ANETVMT0p/ TOTVMT0p) * eop
In the formulas, ASPDP is the percentage change in peak-period speeds, ASPDOP
is the change in off-peak speeds, TOTVMTP is total peak-period VMT for the
program area, TOTVMTOP is total off-peak VMT for the program area, ep is the
elasticity of peak-period speed with respect to volume, and eop is the elasticity of
off-peak speed with respect to volume. The other parameters in the formulas are
defined in earlier steps of the methodology.
According to Transportation Inventory & Analysis of Existing Conditions, 1996: Maricopa
County, total VMT in Maricopa County is approximately 50 million miles per day. The TRP Survey
indicates that work-related (i.e., commuter) VMT in the program area is approximately 25 million miles
per day. Thus, VMT for non-work trips is approximately 25 million miles per day (i.e., 50 million total
minus 25 million work-related). Combining this information with the assumptions from Step 5 that 70%
of work-related trips occur in the peak period and 30% of non-work trips occur in the peak period yields
a value of 25 million miles per day for each of TOTVMTP and TOTVMTOP.
The parameter ep is assumed to be -0.75,
based on an example provided in the TCM
guidance document. The parameter eop is
assumed to be 0, because changes in off-peak
VMT are not likely to affect vehicle speeds
(i.e., due to a lack of congestion).
FOCUS: HOW REDUCING VMT AFFECTS
TRAVEL SPEED
When a TCM program reduces VMT during peak
periods, we would expect to see some increase (albeit
a small one) in overall fleet speeds given that fewer
vehicles on the road generally translates into less
Using the data above, ASPDP = -119,243 congestion^ m off-peak periods, however people are
/ 25,000,000 * -0.75 = 0.0036 and ASPDOP = ^^ aWe t0 tavel at ** SpeedS they Ch°°Se' and
-47,258 / 25,000,000 * 0 = 0. Summarizing these
results, the RPTA program increases peak-period
speeds by approximately 0.36% but has no effect
on off-peak speeds. (Note: Data for the
Maricopa County area indicate that ep could
potentially range from -0.5 to -1.94. Using these values for ep yields increases in peak-period speeds of
0.24% and 0.93%, respectively.)
have any noticeable effect on overall fleet speeds.
Based on these observations, it is reasonable to assume
that ep < 0 and enp = 0.
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Phase 2: Emission Effects STEP 1 (Trip
Changes')
Step 1 in the estimation of the emission
effects for the RPTA program involves
calculating the effect of trip changes on
emissions. This step is broken down into seven
smaller steps (la through Ig), which are outlined
below.
Step la in the emission methodology
involves estimating the distribution of trip
changes for the RPTA program. These changes
are calculated using the following formulas:
YTRTP.LDGV = TRIP
LDGV
(TRIP
LDGV
TRIP
LDGT1
)
YTRTP.LDGTI = 1 YTRIP.LDGV
In the formulas, YTRTP.LDGV is the
fraction of TCM-affected trips
taken by light-duty gasoline
vehicles (LDGVs), YTRIP.LDGTI
is the fraction of TCM-affected
trips taken by light-duty
gasoline trucks (LDGTls),
TRIP
LDGV
is the fraction of total
Phase 2: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
Step 4: Summation of emission effects
trips in the region taken by
LDGVs, and TRIPLDGT1 is the
fraction of total trips in the ^^^^^^^^^^^^^^^^^^^^^^^^^^^^_
region taken by LDGTls.
(Note: Most TCMs that can be analyzed using EPA's guidance document affect only
LDGVs or LDGTls.
Thus, the sum of YTRIP.LDGV and YTRTP.LDGTI is typically equal to one.)
TRIPLDGV and TRIPLDGT1 are derived from MOBILESa data for Maricopa County and are equal
to 0.619 and 0.173, respectively.
Using the data above, YTRTP.LDGV = 0-619 / (0.619 + 0.173) = 0.782 and YTRIP.LDGTI = 1 - 0-782
= 0.218. Summarizing these results, 78.2% of the trips affected by the RPTA program are taken by
LDGVs, and 21.8% are taken by LDGTls.
Step Ib in the emission methodology involves calculating cold-start and hot-start trip changes
for the RPTA program. These changes are calculated using the following formulas:
ATRIPSCST = YCSTW * (ANETRPWP + ANETRPWOP) + YCST NW * (ANETRP^p + ANETRP^p)
ATRIPSHST = (1 - YCSTW) * (ANETRPWP + ANETRPWOP) + (1 - YCSTNW) *
In the formulas, ATRIPSCST is the number of cold-start trip changes, ATRIPSHST
is the number of hot-start trip changes, YCST w is the fraction of work trips begun
in the cold-start mode, and YCST NW is the fraction of non-work trips begun in the
-------
cold-start mode. The other parameters in the formulas are defined in earlier
steps of the methodology.
Because work trips are mostly cold-start trips, the guidance calls for YCST w to be set equal to 1.
The guidance also suggests that YCST NW be set equal to 0.43, which is the default fraction of cold starts
used in the Federal Test Procedure (FTP).
Using the data above, ATRIPSCST
= 1 * (-8,724 + -3,739) + 0.43 * (430 + 1,003)
= -1 1,847 and ATRIPSHST = (1 - 1) * (-8,724
+ -3,739) + (1 - 0.43) * (430 + 1,003) = 817.
Summarizing these results, the RPTA program
results in a reduction of 1 1,847 cold-start trips
per day and an increase of 8 17 hot-start trips
per day.
Step Ic in the emission methodology
involves determining cold-start and hot-start
emission factors. These changes are calculated
for a given pollutant and vehicle class using the
following formulas:
Focus: EMISSION RATES BETWEEN WORK
TRIPS AND NON-WORK TRIPS CAN BE
DIFFERENT
Work trips tend to be mostly cold-start trips because
vehicles typically sit for several hours at a time before
morning and evening commutes (i.e., overnight, during
working hours). Many non-work trips, however, are
made during the day by unemployed individuals and
tend to be strung together over relatively short time
periods. Also, non-work trips are often made in the
evening by employed individuals shortly after their
evening commute trips.
= (EXH100o/oCST]26MPH " EXH10oo/oSTBj26MPIl) 3.59
HST = (-EXH100o/oHSTi26MEH " EXH10oo/oSTBj26MPIl) 3.59
In the formulas, CST is the cold-start emission factor in grams per trip, HST
is the hot-start emission factor in grams per trip, and EXH is the MOBILE
emission factor in grams per mile. The 3.59 factor is the FTP driving cycle
trip-start miles per trip, and 26 miles per hour is the speed for the start portion
of the FTP driving cycle. (Note: The subscripts on EXH refer to the operating
conditions and speed at which MOBILE evaluates EXH. For example,
"100%CST,26MPH" indicates 100% cold-start operating mode at 26 miles
per hour vehicle speed.)
Using national default data from MOBILE, CSTLDGVHC = (2.55 - 0.95) * 3.59 = 5.74 grams
per trip, CSTLDGT1HC = (3.59 - 1.34) * 3.59 = 8.08 grams per trip, HSTLDGVHC = (1.35 - 0.95) * 3.59 = 1.44
grams per trip, and HSTLDGT1 HC = (1.99 - 1.34) * 3.59 = 2.33 grams per trip. (Following the same
methodology, the cold-start and hot-start emission factors can also be determined for NOx and CO.)
Step Id in the emission methodology involves determining cold-start and hot-start emission
changes for the RPTA program. These changes are calculated using the following formulas:
AHCCST (AlKlrSCST YTRTP.LDGV
AHCHST = (ATRIPSHST YTRTP.LDGTI
(AlJvlrSCST YTRTP.LDGTI
(AIRIPSHST YTRTP.LDGTI
ANOxCST (ATRIPSCST YTRTP.LDGV CSILDGV)NOx) + (AIRIPSCST YTRIP.LDGTI CSILDGT1)NOx)
ANOxHST = (ATR1PSHST YTRTP.LDGTI HSI LDGV)NOx) + (A IRIPSHST YTRTP.LDGTI HSILDGT1)NOx)
ACOCST (AlKlrSCST YTRTP.LDGV CSlLDGVjCO) + (AlJvlrSCST YTRTP.LDGTI
IST = (ATRIPSHST YTRTP.LDGTI HSILDGVjCO) + (AIRIPSHST YTRIP.LDGTI
-------
In the formulas, AHCCST, ANOxCST, and ACOCST are the changes in cold-start
emissions for HC, NOx, and CO, respectively; and AHCHST, ANOxHST, and
ACOHST are the changes in hot-start emissions for HC, NOx, and CO,
respectively. The other parameters in the formulas are defined in earlier steps
of the methodology.
Using national default data from MOBILE, AHCCST = (-1 1,847 * 0.782 * 5.74) + (-1 1,847
* 0.218 * 8.08) = -74,045 and AHCHST = (817 * 0.782 * 1.44) + (817 * 0.218 * 2.33) = 1,335.
Summarizing these results, the RPTA program results in a reduction in cold-start HC emissions of 74,045
grams per day and an increase in hot-start HC emissions of 1,335 grams per day. (Following the same
methodology, the cold-start and hot-start emission changes can also be determined for NOx and CO.)
Step le in the emission methodology involves determining hot soak emission changes for the
RPTA program. These changes are calculated using the following formula:
AHCHSK = (ATRIPSTOTAL * YTRIP,LDGV * HSKLDGV) + (ATRIPSTOTAL * YTRIP,LDGTI * HSKLDGT1)
In the formula, AHCHSK is the change in hot soak emissions, ATRIPSTOTAL is the
total change in trips, and HSK is the hot soak emission factor in grams per trip.
(Note: Hot soak emissions are HC emissions only.)
ATRIPSTOTAL = ANETRPWP + ANETRPWOP
Thus, ATRIPSTOTAL = -8,724 + -3,739 + 430 + 1,003 = -1 1,030.
Using national default data from MOBILE, AHCHSK = (-1 1,030 * 0.782 * 3.06) + (-1 1,030
* 0.218 * 3.60) = -35,050. Summarizing this result, the RPTA program results in a reduction in hot soak
emissions of 35,050 grams per day.
Step If in the emission methodology involves determining diurnal emission changes for the
RPTA program. These changes are calculated^or a given vehicle class using the following formulas:
AHCDNL w = 0.676 * (ANETRPWP + ANETRPWOP) / TPDW * yim, * (WDI - MDI)
AHCDNL^ = 0.676 * (ANETRP^p + ANETRP^p) / TPD^ * YTRff * (WDI - MDI)
AHCDNL = AHCDNL)WjLDGV + AHCDNLjNW)LDGV + AHCDNLjW)LDGT1 + AHCDNL)NWiLDGT1
In the formulas, AHCDNL w is the change in diurnal emissions associated with
work trips, AHCDNLNW is the change in diurnal emissions associated with non-
work trips, and AHCDNL is the total change in diurnal emissions. TPDW is the
number of work trips per day per vehicle, and TPD^ is the number of non-work
trips per day per vehicle. WDI is the weighted diurnal emission factor in grams,
and MDI is the multi-day diurnal emission factor in grams. The other parameters
in the formulas are defined in earlier steps of the methodology. (Note: Diurnal
emissions are HC emissions only.)
The value used for TPDW is 2, since a commuter makes typically makes two work trips per day
(i.e., one trip from home to work, one trip from work to home). TPD^ is equal to TGN from Step 3 of
the "Travel Activity Effects" section above, and thus equals 1.71.
10
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Using national default data from
MOBILE, AHCDNLWLDGV = 0.676 * (-8,724
+ -3,739) / 2 * 0.782 * (3.30 - 6.04) = 9,026,
ARC
/ = 0.676* (430+ 1,003)71.71
DNL.NW.LDGV
* 0.782 * (3.30 - 6.04) = -1,214, AHCDNLWLDGT1
= 0.676 * (-8,724 + -3,739) / 2 * 0.218 * (5.11
- 15.33) = 9,385, AHCDNLNWLDGT1 = 0.676 * (430
+ 1,003)71.71 * 0.218* (5.11 - 15.33) =-1,262,
and AHCDNL = 9,026 + -1,214 + 9,385 + -1,262
= 15,935. Summarizing these results, the RPTA
program results in a net increase in diurnal
emissions of 15,935 grams per day.
Step lg in the emission methodology
involves calculating the total trip-related emission
changes for the RPTA program. These changes
are calculated using the following formulas:
Focus: A TCM CAN INCREASE DIURNAL
EMISSIONS FROM VEHICLES NOT IN USE
Diurnal emissions (i.e., emissions resulting from daily
temperature changes that occur while a vehicle is not in
use) occur regardless of whether a vehicle is driven.
Vehicles that are driven regularly emit more partial-day
and full-day diurnal emissions than vehicles that are
not driven regularly, which emit more multi-day diurnal
emissions. To account for this, Step If of the emission
methodology subtracts multi-day diurnal emissions
from weighted diurnal emissions (which account for
both partial-day and full-day diurnal emissions) in
order to obtain a "net" effect. It is interesting to note
that, although TCM programs that reduce vehicle trips
generally reduce total emissions on net, diurnal
emissions actually increase. This is because an
increase in the number of vehicles not in use leads to
an increase in multi-day diurnal emissions, which are
AHCTRff = AHCCST
AHCHST + AHCHSK
AHC
DNL
ANOxTRIP = ANOxCST + ANOx
ACOTRff = ACOCST + ACO
HST
HST
In the formulas, AHCTRIP, ANOxTRIP, and ACOTRIP are the total changes in HC, NOx,
and CO emissions, respectively, due to trip changes.
Using the data above, AHCTRIP = -74,045 + 1,335 + -35,050 + 15,935 = -91,825. Summarizing
this result, the RPTA program results in a net decrease in trip-related HC emissions of 91,825 grams per
day. (Following the same methodology, total trip-related emission changes can also be determined for
NOx and CO.)
11
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Emission Effects - STEP 2 (VMT Changes')
Step 2 in the estimation of the emission effects for the RPTA program involves calculating the
effect of VMT changes on emissions. This step is broken down into four smaller steps (2a through 2d),
which are outlined below.
Step 2a in the emission methodology involves estimating the distribution of VMT changes for
the RPTA program. These changes are calculated using the following formulas:
YVMT.LDGV = VMTLDGV / (VMTLDGV + VMTLDGT1)
YVMT.LDGTI = 1 " YVMT.LDGV
In the formulas, YVMT.LDGV is the fraction of TCM-affected VMT for light-duty
gasoline vehicles (LDGVs), YTRIPLDGTI is the fraction of TCM-affected VMT
for light-duty gasoline trucks (LDGTls), VMTLDGV is the fraction of total VMT
in the region for LDGVs, and VMTLDGT1 is the fraction of total VMT in the
region for LDGTls. (Note: Most TCMs that can be analyzed using EPA's
guidance document affect only LDGVs or LDGTls. Thus, the sum of YVMT.LDGV
and YVMT.LDGTI is typically equal to one.)
VMTLDGV and VMTLDGT1 are taken from MOBILESa data for Maricopa County and are equal
to 0.619 and 0.173, respectively. Using the data above, YVMT.LDGV = 0-619 / (0.619 + 0.173) = 0.782 and
YVMT.LDGTI = 1 - °-782 = °-218- Summarizing these results, 78.2% of the VMT affected by the RPTA
program is by LDGVs, and 21.8% is by LDGTls.
Step 2b in the emission methodology involves estimating hot-stabilized exhaust emission
changes for the RPTA program. These changes are calculated using the following formulas:
AHCsmP = (ANETVMTP * YVMT.LDGV * STBLDGV3QP) + (ANETVMTP * YVMT,LDGTI * STBLDGT13QP)
AHCsmoP = (ANETVMT0p * YVMT.LDGV * STBLDGVjHQOP) + (ANETVMTOP * YVMT.LDGTI * STBLDGTljHQOP)
ANOxSTBP = (ANETVMTP * YVMTLDGV * STBLDGVNOxP) + (ANETVMTP * YVMTLDGTI * STBLDGT1NOxP)
ANOxsmop = (ANETVMTOP * YVMT,LDGV * STBLDGV,NOx,OP) + (ANETVMTOP * YVMT.LDGTI *
SIBLDGT1)NOX]op)
ACOsmP = (ANETVMTP * YVMT.LDGV * STBLDGVmP) + (ANETVMTP * YVMT.LDGTI * STBLDGTUCOJ))
ACOSTB>OP = (ANETVMTOP * YVMT.LDGV * STBLDGViCO)OP) + (ANETVMTOP * YVMT.LDGTI * STBLDGTliCO)OP)
In the formulas, AHCSTB P, ANOxSTB P, and ACOSTB P are the peak-period changes
in hot-stabilized emissions for HC, NOx, and CO, respectively; and AHCSTB OP,
ANOxSTBOP, and ACOSTBOP are the off-peak changes in hot-stabilized emissions
for HC, NOx, and CO, respectively. STBP is the hot-stabilized emission factor
(in grams per mile) for each pollutant and vehicle class for the peak period
(during which average vehicle speed is assumed to be 20 miles per hour), and
STBOP is the hot-stabilized emission factor (in grams per mile) for each pollutant
and vehicle class for the off-peak period (during which average vehicle speed is
assumed to be 35 miles per hour). The other parameters in the formulas are
defined in earlier steps of the methodology.
Using national default data from MOBILE, AHCSTBP = (-119,243 * 0.782 * 1.23) + (-119,243
* 0.218 * 1.77) = -160,706 and AHCSTBOP = (-47,258 * 0.782 * 0.69) + (-47,258 * 0.218 * 0.94)
= -35,184. Summarizing these results, the RPTA program results in a reduction in peak-period hot-
12
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stabilized HC exhaust emissions of 160,706 grams per day and a reduction in off-peak hot-stabilized HC
exhaust emissions of 35,184 grams per day. (Following the same methodology, hot-stabilized exhaust
emission changes can also be determined for NOx and CO.)
Step 2c in the emission methodology involves estimating VMT-related evaporative emission
changes for the RPTA program. These changes are calculated using the following formulas:
vpp = (ANETVMTP * YVMT,LDGV * VEVPLDGV,P) + (ANETVMTP * YVMI,LDGTI * VEVPLDGT1,P)
-op = (ANETVMTOP * YVMT,LDGV * VEVPLDGV,OP) + (ANETVMTOP * YVMI,LDGTI * VEVPLDGT1,OP)
In the formulas, AHCygvp P is the change in peak-period evaporative emissions,
AHCvEvp OP is the change in off-peak evaporative emissions, and VEVP is the
VMT-related evaporative emission factor (in grams per mile) for each vehicle
class and time period (peak or off-peak). The other parameters in the formulas
are defined in earlier steps of the methodology. (Note: Evaporative emissions
are HC emissions only.)
Using national default data from
MOBILE, ARC
VEVP.P
= (-119,243* 0.782*0.44)
+ (-119,243 * 0.218 * 0.53) = -54,806 and
ARC
VEVP.OP
= (-47,258 * 0.782 * 0.34)
+ (-47,258 * 0.218 * 0.44) = -17,098.
Summarizing these results, the RPTA program
results in a reduction in peak-period evaporative
emissions of 54,806 grams per day and a
reduction in off-peak evaporative emissions
of 17,098 grams per day.
Focus: SUMMING EVAPORATIVE EMISSIONS
In Step 2c of the emission methodology, the
evaporative emission factor (VEVP) is calculated as
the sum of running loss emissions, crankcase
emissions, and refueling emissions. The peak-period
and off-peak evaporative emission factors differ only
in the running loss component, as this is the only type
of evaporative emissions that is influenced by vehicle
speeds.
Step 2d in the emission methodology involves calculating the total VMT-related emission
changes for the RPTA program. These changes are calculated using the following formulas:
= AHCSTBjP + AHCSTBjOP +
ANOXyMT = ANOxSTBP + ANOxSTB OP
= ACO
smP
ACO
smoP
In the formulas, AHCy^-, ANOxy^., and ACOyMj are the total changes in HC,
NOx, and CO emissions, respectively, due to VMT changes.
Using the data above, AHC^ = -160,706 + -35,184 + -54,806 + -17,098 = -267,794.
Summarizing this result, the RPTA program results in a net decrease in VMT-related HC emissions
of 267,794 grams per day. (Following the same methodology, total VMT-related emission changes
can also be determined for NOx and CO.)
13
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Emission Effects - STEP 3 (Speed Changes)
Step 3 in the estimation of the emission effects for the RPTA program involves calculating the
effect of speed changes on emissions. This step is broken down into four smaller steps (3a through 3d),
which are outlined below.
Step 3a in the emission methodology involves estimating the speeds associated with the RPTA
program. These speeds are calculated using the following formulas:
SPEEDPTCM = SPEEDPBASE * (1 + ASPDP)
SPEEDOPJCM = SPEEDOP3ASE * (1 + ASPDOP)
In the formulas, SPEEDPTCM is the peak-period speed after implementation of the
TCM, SPEED0pjcM is the off-peak speed after implementation of the TCM,
SPEEDPBASE is the peak-period speed prior to implementation of the TCM, and
SPEEDOP BASE is the off-peak speed prior to implementation of the TCM. The
other parameters in the formulas are defined in earlier steps of the methodology.
Based on data for the national default fleet, SPEEDPBASE is assumed to be 20 miles per hour,
and SPEEDOPBASE is assumed to be 35 miles per hour.
Using the data above, SPEEDPTCM = 20 * (1 + 0.0036) = 20.07 and SPEEDOPTCM = 35 * (1 + 0)
= 35. Summarizing these results, peak-period speeds have slightly increased from 20 miles per hour to
20.07 miles per hour due to the RPTA program. Off-peak speeds have not changed due to the program.
(Note: Using values of-0.5 and -1.94 for ep yields new peak-period speeds of 20.05 miles per hour and
20.19 miles per hour, respectively.)
Step 3b in the emission methodology involves estimating the total VMT for the program area
after implementation of the RPTA program. These VMT figures are calculated using the following
formulas:
VMTP TCM = TOTVMTp + ANETVMTP
VMTOPJCM = TOTVMTOP + ANETVMTOP
In the formulas, VMTP TCM is the total peak-period VMT in the program area
after implementation of the TCM, and VMTOPTCM is the total off-peak VMT in
the program area after implementation of the TCM. The other parameters in the
formulas are defined in earlier steps of the methodology.
Using data from Step 9 of the "Travel Activity Effects" section above, VMTPTCM = 25,000,000
+ -119,243 = 24,880,757 and VMTOPTCM = 25,000,000 + -47,258 = 24,952,742. Summarizing these
results, peak-period VMT has decreased from 25,000,000 miles per day to 24,880,757 miles per day due
to the RPTA program. Off-peak VMT has decreased from 25,000,000 miles per day to 24,952,742 miles
per day due to the program.
Step 3c in the emission methodology involves estimating peak-period and off-peak emission
changes due to changes in vehicle speeds. These changes are calculated using the following formulas:
AHCSPDjP = VMTPJCM * (STBFLT)HQPJCM + RNLFLTjPJCM) - VMTPJCM * (STBFLT)HQP3ASE + RNLFLTjP3ASE)
AHCSPDjOp ~~ »-M-J-OP.TCM (k-l-BFLTiHC)Opj.CM + FLT.OP.TCM) " * M1 OP)TCM (o-l-DFLT)HQOpjBASE
14
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ANOxSPD)p VMTPjCM (STBFLTjNOX)PjCM - STBFLTjNOX)P)BASE)
NOxSpD)Op = VMTOpjCM
ACOSPDjP = VMTPjCM (STBFLT)COjPjCM - STBFLT)CO)P)BASE)
ACOSPDjOp
In the formulas, AHCSPDP, ANOxSPDP, and ACOSPDP are the peak-period changes
in emissions for HC, NOx, and CO, respectively, due to a change in speeds; and
AHCSPD OP, ANOxSPD op, and ACOSPD OP are the off-peak changes in emissions for
HC, NOx, and CO, respectively, due to a change in speeds. STBFLT is the fleet-
wide hot-stabilized emission factor (in grams per mile) for each pollutant, time
period (i.e., peak or off-peak), and scenario (i.e., base or TCM). RNL^x is the
fleet-wide running loss emission factor (in grams per mile) for each time period
and scenario. The other parameters in the formulas are defined in earlier steps of
the methodology.
Based on data showing the relationship between vehicle speed and emissions, this analysis
assumes that the elasticity of STBFLT with respect to speed is -1 for HC, 0 for NOx, and -1 for CO.
Thus, a 1% increase in speed is assumed to result in a 1% decrease in HC and CO emissions (on a grams
per mile basis) and no change in NOx emissions. The elasticity of RNLFLT with respect to speed is also
assumed to be -1.
Using national default data from
MOBILE, AHCSPDP = 24,880,757 * (1.670
+ 0.211) - 24,880,757 * (1.676 + 0.212)
= -174,165 and AHCSPDOP = 24,952,742 * (1.938
+ 0.120) - 24,952,742 *'(1.938 + 0.120) = 0.
Summarizing these results, the RPTA program
u j j i * j TT/~> classes (e.g., LDGV, LDGT).
results in a decrease in speed-related HC \ B, , j
FOCUS:FLEET-WIDE EMISSIONS FACTORS IN
THIS STEP
It is important to note that the emission factors used in
Step 3c of the emission methodology are fleet-wide.
The emission factors used throughout the remainder of
the methodology are specific to individual vehicle
emissions of 174,165 grams per day for the peak
period but does not change speed-related HC emissions for the off-peak period. (Following the same
methodology, the peak-period and off-peak emission changes due to changes in speeds can also be
determined for NOx and CO.) (Note: Using values of -0.5 and -1.94 for ep yields decreases in speed-
related HC emissions of 124,404 grams per day and 447,854 grams per day, respectively.)
Step 3d in the emission methodology involves calculating the total speed-related emission
changes for the RPTA program. These changes are calculated using the following formulas:
ArlCSPD ArlCSPDiP + ArlCSPD)Op
ANOxSPD = ANOxSPD)P + ANOxSPE, OP
ACOSPD ACOSPDiP + ACOSPD)Op
In the formulas, AHCSPD, ANOxSPD, and ACOSPD are the total changes in HC,
NOx, and CO emissions, respectively, due to speed changes.
Using the data above, AHCSPD = -174,165 + 0 = -174,165. Summarizing this result, the RPTA
program results in a net decrease in speed-related HC emissions of 174,165 grams per day. (Following
the same methodology, total speed-related emission changes can also be determined for NOx and CO.)
(Note: Using values of-0.5 and -1.94 for ep yields net decreases in speed-related HC emissions of
124,404 grams per day and 447,854 grams per day, respectively.)
15
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Emission Effects - STEP 4 (Total)
Step 4 in the estimation of the emission effects for the RPTA program involves calculating the
total changes in HC, NOx, and CO emissions. These changes are calculated using the following
formulas:
ARC = AHCTRff + AHCvMT + AHCSPD
ANOx = ANOxTRIP + ANOxvMT + ANOxSPD
AGO = ACOTRff + ACOvMT + ACOSPD
In the formulas, ARC, ANOx, and AGO are the total changes in HC, NOx,
and CO emissions, respectively, due to the TCM program.
Using the data above, ARC = -91,825 + -267,794 + -174,165 = -533,784. Summarizing this
result, the RPTA program results in a net decrease in HC emissions of 533,784 grams per day,
or approximately 0.59 tons per day. (Following the same methodology, total emission changes
can also be determined for NOx and CO.) (Note: Using values of -0.5 and -1 .94 for ep yields
net decreases in HC emissions of 0.53 tons per day and 0.89 tons per day, respectively.)
16
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Example 2: Atlanta/DeKalb Greenway Trails
General Description
In 1994, the PATH Foundation funded the construction of 20 miles of trails built adjacent
to highways servicing downtown Atlanta. The main objective of the project was to reduce traffic
congestion by encouraging commuters to bike or walk to work rather than drive. The project also
attempted to capture trips to schools and shops. The following analysis extrapolates data available
for the 2.5-mile Westside Trail to estimate total reductions in trips, VMT, and emissions for the 20-mile
trail network. Ultimately, the PATH Foundation expects to construct over 110 miles of trails by the year
2000. Thus, the impact the trails have on travel activity and emissions will probably be much greater in
the future than this analysis indicates.
Data Sources
Conversations with Edwin McBrayer, Executive Director, PATH Foundation,
March 9 and 13, 1997.
1990 U.S. Census data.
1996 Statistical Abstract of the United States.
Texas Transportation Institute web page.
Phase 1: Travel Activity Effects
Step 1 in the estimation of travel activity
effects for the PATH project involves an
assessment of the potential trip effects from the
project. For this TCM, these potential effects
are calculated using the following user-defined
formula:
PT = N
In the formula, PT is the
potential effect on trips,
and N is the total number
of vehicles traveling on
roadways adjacent to
trails.
The appropriate value for N is derived using information from the Atlanta Regional Commission
(ARC) indicating that approximately 18,000 vehicles use roadways adjacent to the 2.5-mile Westside
Trail on a given day. Assuming that the remaining trails comprising the 20-mile network are built along
roads that experience similar usage, the number of vehicles using roadways adjacent to trails is 144,000.
Thus, the potential number of trips reduced per day by the PATH project is 144,000.
Step 2 in the travel activity methodology involves estimating the direct work and non-work trip
reductions from the PATH project. Whereas the potential trip reductions calculated in Step 1 represent
the total number of trips that might be reduced by a TCM program, direct trip reductions measure the
Phase 1: Effects on Travel Activity
Step 1: Potential trip effects
Step 2: Direct work and non-work trip reductions
Step 3: Indirect work and non-work trip increases
Step 4: Peak and off-peak trip shifts
Step 5: Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Step 6: Peak and off-peak VMT changes due to
reduced number of trips
Step 7: VMT changes due to reduced trip lengths
Step 8: Net VMT changes
Step 9: Peak and off-peak speed changes
17
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number of trips that actually are reduced and, thus, can be less than potential trip reductions (i.e., not all
vehicle passengers will switch to biking or walking ). Direct trip reductions are calculated using the
following formulas:
ATRIPSD = a * PT
ATRIPSDW= (o * ATRIPSD
ATRIPSDNW = (1 - G>) * ATRIPSD
In the formulas, ATRIPSD is the change in total direct trips, PT is (as above) the
potential trip reductions, ATRIPSD w is the change in direct work trips,
ATRIPSDNW is the change in direct non-work trips, a is the fraction of program
participants who make a direct trip change, and co is the fraction of trip effects
that are work-related.
The parameter a is assumed to be -0.04, based on information provided by ARC officials.
For TCM projects that influence work and non-work travel equally (such as the PATH project),
the TCM guidance calls for the parameter co to be set equal to the fraction of travel that is work-related.
Thus, (0 is assumed to be 0.3, based on information provided in the 1996 Statistical Abstract of the
United States.
Using the data above, ATRIPSD = -0.04 * 144,000 = -5,760, ATRIPSD w = 0.3 * -5,760 =
-1,728, and ATRIPSDNW = (1 - 0.3) * -5,760 = -4,032. Summarizing these results, the PATH project
is responsible for directly reducing 1,728 work trips per day and 4,032 non-work trips per day.
Step 3 in the travel activity methodology involves estimating the actual indirect trip increases
(for both work and non-work trips) from the PATH project. Indirect trip increases are secondary effects
that typically result when vehicles normally used for commuting or other trips are left at home. These
increases are calculated using the following formulas:
ATRIPSIW = INCWH * -ATRIPSD / 2
ATRIPSINW = INCNH * -ATRIPSD / 2
In the formulas, ATRIPS: w is the indirect work trip increase, ATRIPSINW is the
indirect non-work trip increase, and INCWH and INCNH are the rates of increased
SOV work and non-work trip making by household members of TCM
participants who leave their vehicles at home. The other parameter in the
formulas is defined in an earlier step of the methodology.
INCWH is defined as NV * SHR * (SIZE - 1) * BMP * TGW, where NV is the fraction of the
population that does not own a vehicle (Note: This analysis interprets this parameter to mean the
percentage of drivers without a vehicle, which is estimated as the percentage of vehicle-owning
households in the program area that have only one vehicle.), SHR is the fraction of shared mode trips,
SIZE is average household size, BMP is the fraction of the population that is employed, and TGw is the
work trip generation rate for SOV users. Based on 1990 U.S. Census data for DeKalb County, NV is
assumed to be 38%, SHR is assumed to be 19%, SIZE is assumed to be 2.56, and BMP is assumed to be
70%. TGW is assumed to equal 2. Based on these numbers, INCWH = 0.38 * 0.19 * (2.56 - 1) * 0.7 * 2 =
0.16.
INCNH = NV * SHR * (SIZE - 1) * UNEMP * TGN, where NV, SHR, and SIZE are as defined
above, UNEMP is the fraction of the population that is not employed, and TGN is the non-work trip
generation rate for SOV users. UNEMP is simply (1 - EMP) and thus equals 30%. TGN is assumed to be
the same as TGW (i.e., 2). Based on these numbers, INCNH = 0.38 * 0.19 * (2.56 - 1) * 0.3 * 2 = 0.07.
18
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Using the data above, ATRIPSIW = 0.16* -(-5,760) / 2 = 461, and ATRIPSINW = 0.07 * -(-5,760)
12 = 202. Summarizing these results, the PATH project is indirectly responsible for an increase of 461
work trips per day and 202 non-work trips per day. Summarizing these results, the PATH project is
indirectly responsible for an increase of 461 work trips per day and 202 non work trips per day.
Step 4 in EPA's methodology for estimating travel activity effects of TCMs, which involves
determining direct peak and off-peak period trip shifts, does not apply to walking and biking trails.
Thus, Step 4 is not relevant to the analysis of the PATH project.
Step 5 in the travel activity methodology involves estimating the net trip changes from the PATH
project as distributed between work and non-work trips and peak and off-peak periods. These changes
are calculated using the following formulas:
ANETRPWP = (o * ATRIPSSp + PKW * (ATRIPSDW + ATRIPSIW)
ANETRPWOP = (o * ATRIPSSOP + (1 - PKW) * (ATRIPSDW + ATRIPSIW)
ANETRP^p = (!-«)* ATRIPSSP + PK^ * (ATRIPSDNW + ATRIPSINW)
= (!-«)* ATRIPSSOP + (1 - PK^) * (ATRIPSUNW + ATRIPSINW)
In the formulas, ANETRPWP is the net work trip change in the peak period,
ANETRPW op is net work trip change in the off-peak period, ANETRP^p is the
net non-work trip change in the peak period, and ANETRP^ jOP is the net non-
work trip change in the off-peak period. ATRIPSSP is the change in peak period
trips, and ATRIPSSOP is the change in off-peak period trips. PKW is the observed
fraction of work trips during the peak period, and PK^ is the observed fraction
of non-work trips during the peak period. The other parameters in the formulas
are defined in earlier steps of the methodology.
Because there are no trip shifts associated with walking and biking trails (see Step 4), ATRIPSSP
and ATRIPSSOP are each equal to 0.
The values used for PKW and PK^ are 0.6 and 0.3, respectively, based on an example shown
in the TCM guidance document.
Using the data above, ANETRPWP = 0 + 0.6 * (-1,728 + 461) = -760, ANETRPWOP = 0 + (1 - 0.6)
* (-1,728 + 461) = -507, ANETRP^p = 0 + 0.3 * (-4,032 + 202) = -1,149, and ANETRP^op
= 0 + (1 - 0.3) * (-4,032 + 202) = -2,681. Summarizing these results, the PATH project results in net
decreases in peak and off-peak work trips of 760 per day and 507 per day, respectively. The project also
results in decreases in peak and off-peak non-work trips of 1,149 per day and 2,681 per day, respectively.
Step 6 in the travel activity methodology involves estimating the peak and off-peak VMT
changes due to the trip changes from the PATH project. These changes are calculated using the
following formulas:
AVMTp = (ANETRPWP * DISTW) + (ANETRP^p * DIST^)
AVMTOP = (ANETRPWOP * DISTW) + (ANETRP^p * DIST^)
In the formulas, AVMTP is the change in peak-period VMT due to trip changes,
AVMTOP is the change in off-peak VMT due to trip changes, DISTW is the
average VMT per trip for work trips, and DIST^ is the average VMT per trip
for non-work trips. The other parameters in the formulas are defined in earlier
steps of the methodology.
19
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DISTW is 13 miles per trip, as estimated by ARC. DIST^ is assumed to be 8.1 miles, based on
data from the 1996 Statistical Abstract of the United States.
Using the data above, AVMTP = (-760 * 13) + (-1,149 * 8.1) = -19,187 and AVMTOP = (-507 *
13) + (-2,681 * 8.1) = -28,307. Summarizing these results, the PATH project reduces peak-period VMT
by 19,187 miles per day due to trip changes and reduces off-peak VMT by 28,307 miles per day due to
trip changes.
Step 7 in the travel activity methodology involves estimating the VMT changes due to trip length
changes resulting from the PATH project. These changes are calculated using the following formulas:
AVMTLW = p * PT * -(DISTW - DISTnew)
AVMTLNW = p * PT * -(DIST^ - DISTnew)
In the formulas, AVMTL w is the change in VMT due to work trip length
changes, AVMTL ^ is the change in VMT due to non-work trip length changes,
P is fraction of program participants who change their trip length, and DISTnew is
the new work or non-work trip length. The other parameters in the formulas are
defined in earlier steps of the methodology.
Although it is conceivable that trail users may drive to a trail and walk or bicycle the rest of the
way, this analysis assumes that no trail users do so. Thus, both p and DISTnew are set equal to 0.
Using the data above, AVMTL w = 0 * 144,000 * -(13 - 0) = 0, and AVMTLNW = 0 * 144,000
* -(8.1 - 0) = 0. Summarizing these results, the PATH project does not reduce VMT through changes
in trip lengths.
Step 8 in the travel activity methodology involves estimating the total peak and off-peak VMT
changes resulting from the PATH project. These changes are calculated using the following formulas:
ANETVMTp = AVMTp + PKW * AVMTLW + PK^ * AVMTLNW
ANETVMT0p = AVMTOP + (1 - PKW) * AVMTL>W + (1 - PK^) * AVMTL>NW
In the formulas, ANETVMTp is the total change in peak period VMT, and
ANETVMTOP is the total change in off-peak VMT. The other parameters in the
formulas are defined in earlier steps of the methodology.
20
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Using the data above, ANETVMTP = -19,187 + 0.6 * 0 + 0.3 * 0 = -19,187 and ANETVMTOP
= -28,307 + (1 - 0.6) * 0 + (1 - 0.3) * 0 = -28,307. Summarizing these results, the PATH project reduces
peak-period VMT by atotal of 19,187 miles per day and off-peak VMT by atotal of 28,307 miles per
day.
Step 9 in the travel activity methodology involves estimating peak and off-peak speed changes
resulting from the PATH project. These changes are calculated using the following formulas:
ASPDp = (ANETVMTp / TOTVMTP) * ep
ASPDOP = (ANETVMT0p/ TOTVMT0p) * eop
In the formulas, ASPDP is the percentage change in peak-period speeds, ASPDOP is the
change in off-peak speeds, TOTVMTP is total peak-period VMT for the program area,
TOTVMTOP is total off-peak VMT for the program area, ep is the elasticity of peak-
period speed with respect to volume, and eop is the elasticity of off-peak speed with
respect to volume. The other parameters in the formulas are defined in earlier steps
of the methodology.
According to data from the Texas Transportation Institute, total VMT in metropolitan Atlanta
is approximately 80 million miles per day. Based on information from a local transportation agency
indicating that 40 percent of travel occurs during peak periods and 60 percent occurs during off-peak
periods, TOTVMTp is approximately 32 million miles per day and TOTVMTOP is approximately 48
million miles per day.
The parameter ep is assumed to be -0.75, based on an example provided in the TCM guidance
document. The parameter eop is assumed to be 0, because changes in off-peak VMT are not likely to
affect vehicle speeds (i.e., due to a lack of congestion).
Using the data above, ASPDP = -19,187 / 32,000,000 * -0.75 = 0.0004 and ASPDOP = -28,307 /
48,000,000 * 0 = 0. Summarizing these results, the PATH project increases peak-period speeds by
approximately 0.04% but has no effect on off-peak speeds.
21
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Phase 2: Emission Effects - STEP 1 (Trip Changes')
Step 1 in the estimation of the emission
effects for the PATH project involves calculating
the effect of trip changes on emissions. This step
is broken down into seven smaller steps
(la through Ig), which are outlined below.
Step la in the emission methodology
involves estimating the distribution of trip
changes for the PATH project. These changes
are calculated using the following formulas:
Phase 2: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3 a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
YTRTP.LDGV = TR!PLDGV '
YTRTP.LDGTI ~~ 1 " YTRTP.LDGV
In the formulas, YTRIPLDGV is the
fraction of TCM-affected trips
taken by light-duty gasoline
vehicles (LDGVs), YTRTP.LDGTI
is the fraction of TCM-affected
trips taken by light-duty gasoline
trucks (LDGTls), TRIPLDGV
is the fraction of total trips in the
region taken by LDGVs, and
TRIPLDGT1 is the fraction of total
trips in the region taken by
LDGTls. (Note: Most TCMs
that can be analyzed using EPA' s
guidance document affect only
LDGVs or LDGTls. Thus, the
sum of YTRIP.LDGV and YTRIP.LDGTI
is typically equal to one.)
TRIPLDGV and TRIPLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values are
based on the national average default values used in MOBILE.
Using the data above, YTRTP.LDGV = °-626 / (0.626 + 0.171) = 0.785 and YTRIP.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the trips affected by the PATH project are taken by
LDGVs, and 21.5% are taken by LDGTls.
Step Ib in the emission methodology involves calculating cold-start and hot-start trip changes
for the PATH project. These changes are calculated using the following formulas:
ATRIPSCST = YCST,W * (ANETRPW,P + ANETRPW,OP) + YCST,NW *
+ ANETRP^p)
ATRIPSHST = (1 - YCST,W) * (ANETRPWP + ANETRPW,OP) + (1 - YCST,NW)
ANETRP
NW.OP7
In the formulas, ATRIPSCST is the number of cold-start trip changes, ATRIPSHST
is the number of hot-start trip changes, YCST w is the fraction of work trips begun
in the cold-start mode, and YCST NW is the fraction of non-work trips begun in the
22
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cold-start mode. The other parameters in the formulas are defined in earlier
steps of the methodology.
Because work trips are mostly cold-start trips, the guidance calls for YCST.W to be set equal to 1 .
The guidance also suggests that YCST.NW be set equal to 0.43, which is the default fraction of cold starts
used in the Federal Test Procedure (FTP).
Using the data above, ATRIPSCST = 1 * (-760 + -507) + 0.43 * (-1,149 + -2,681) = -2,914 and
ATRIPSHST = (1 - 1) * (-760 + -507) + (1 - 0.43) * (-1,149 + -2,681) = -2,183. Summarizing these results,
the PATH project results in a reduction of 2,914 cold-start trips per day and a reduction of 2183 hot-start
trips per day.
Step Ic in the emission methodology involves determining cold-start and hot-start emission
factors. These changes are calculatedyfor a given pollutant and vehicle class using the following
formulas:
Cb 1 (EXH100o/oCSTj26MPH " kXH10oo/oSTB]26MPIl) 3.59
HSI (-bAHo " kXHo) 3.59
In the formulas, CST is the cold-start emission factor in grams per trip, HST
is the hot-start emission factor in grams per trip, and EXH is the MOBILE
emission factor in grams per mile. The 3.59 factor is the FTP driving cycle
trip-start miles per trip, and 26 miles per hour is the speed for the start portion
of the FTP driving cycle. (Note: The subscripts on EXH refer to the operating
conditions and speed at which MOBILE evaluates EXH. For example,
"100%CST,26MPH" indicates 100% cold-start operating mode at 26 miles
per hour vehicle speed.)
Using national default data from MOBILE, CSTLDGVHC = (2.55 - 0.95) * 3.59 = 5.74 grams per
trip, CSTLDGT1HC = (3.59 - 1.34) * 3.59 = 8.08 grams per trip, HSTLDGVHC = (1.35 - 0.95) * 3.59 = 1.44
grams per trip, and HSTLDGT1 HC = (1.99 - 1.34) * 3.59 = 2.33 grams per trip. (Following the same
methodology, the cold-start and hot-start emission factors can also be determined for NOx and CO.)
Step Id in the emission methodology involves determining cold-start and hot-start emission
changes for the PATH project. These changes are calculated using the following formulas:
AHCCST (ATRIPSCST YTRTP.LDGV ^TLDGVjHC) + (ATRIPSCST YTRTP.LDGTI
AHCHST = (ATRIPSHST * YTRTP.LDGTI * HSTLDGVHC) + (ATRIPSHST * YTRIRLDGTI * IIJILDGTI,HC;
ANOxCST = (ATRIPSCST * YTRTP,LDGV * CSTLDGV,NOx) + (ATRIPSCST * YTRIP.LDGTI :
ANOxHST = (ATRIPSHST * YTRTRLDGTI * HSTLDGvNOx) + (ATRIPSHST * YTRTPLDGTI
ACOCST = (ATRIPSCST * YTRTP.LDGV * CST^v^) + (ATRIPSCST * YTRTP.LDGTI *
ACOHST = (ATRIPSHST * YTRTPLDGTI * HSTLDGvCO) + (ATRIPSHST * YTRIRLDGTI *
In the formulas, AHCCST, ANOxCST, and ACOCST are the changes in cold-start
emissions for HC, NOx, and CO, respectively; and AHCHST, ANOxHST, and
ACOHST are the changes in hot-start emissions for HC, NOx, and CO,
respectively. The other parameters in the formulas are defined in earlier steps
of the methodology.
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Using national default data from MOBILE, AHCCST = (-2,914 * 0.785 * 5.74) + (-2,914 * 0.215
* 8.08) = -18,192 and AHCHST = (-2,183 * 0.785 * 1.44) + (-2,183 * 0.215 * 2.33) = -3,561.
Summarizing these results, the PATH project results in a reduction in cold-start HC emissions of 18,192
grams per day and a reduction in hot-start HC emissions of 3,561 grams per day. (Following the same
methodology, the cold-start and hot-start emission changes can also be determined for NOx and CO.)
Step le in the emission methodology involves determining hot soak emission changes for the
PATH project. These changes are calculated using the following formula:
AHCHSK = (ATRIPSTOTAL * YTRIP,LDGV * HSKLDGV) + (ATRIPSTOTAL * YTRIP,LDGTI * HSKLDGT1)
In the formula, AHCHSK is the change in hot soak emissions, ATRIPSTOTAL is the
total change in trips, and HSK is the hot soak emission factor in grams per trip.
(Note: Hot soak emissions are HC emissions only.)
ATRIPSTOTAL = ANETRPWP + ANETRPWOP + ANETRP^p + ANETRP^op. Thus,
ATRIPSTOTAL =-760 +-507 +-1,149 +-2,681 =-5,097.
Using national default data from MOBILE, AHCHSK = (-5,097 * 0.785 * 3.06) + (-5,097 * 0.215
* 3.60) = -16,189. Summarizing this result, the PATH project results in a reduction in hot soak emissions
of 16,189 grams per day.
Step If in the emission methodology involves determining diurnal emission changes for the
PATH project. These changes are calculatedyfor a given vehicle class using the following formulas:
AHCDNL w = 0.676 * (ANETRPWP + ANETRPWOP) / TPDW * yim, * (WDI - MDI)
AHCDNL^ = 0.676 * (ANETRP^p + ANETRP^p) / TPD^ * YTRff * (WDI - MDI)
AHCDNL = AHCDNL)WjLDGV + AHCDNLjNW)LDGV + AHCDNLjW)LDGT1 + AHCDNL)NWjLDGT1
In the formulas, AHCDNL w is the change in diurnal emissions associated with
work trips, AHCDNLNW is the change in diurnal emissions associated with non-
work trips, and AHCDNL is the total change in diurnal emissions. TPDW is the
number of work trips per day per vehicle, and TPD^ is the number of non-work
trips per day per vehicle. WDI is the weighted diurnal emission factor in grams,
and MDI is the multi-day diurnal emission factor in grams. The other parameters
in the formulas are defined in earlier steps of the methodology. (Note: Diurnal
emissions are HC emissions only.)
The value used for TPDW is 2, since a commuter makes typically makes two work trips per day
(i.e., one trip from home to work, one trip from work to home). TPD^ is equal to TGN from Step 3
of the "Travel Activity Effects" section above, and thus equals 2.
Using national default data from MOBILE, AHCDNL WLDGV = 0.676 * (-760 + -507) / 2 * 0.785
* (3.30 - 6.04) = 921, AHCDNLNWLDGV = 0.676 * (-1,149 + -2,681) /2 * 0.785 * (3.30 - 6.04) = 2,784,
AHCDNLWLDGT1 = 0.676 * (-760 + -507) / 2 * 0.215 * (5.11 - 15.33) = 941, AHCDNLNWLDGT1 = 0.676
* (-1,149+ -2,681)/2* 0.215 * (5.11 - 15.33) = 2,844, and AHCDNL = 921 + 2,784 + 941 + 2,844
= 7,490. Summarizing these results, the PATH project results in an increase in diurnal emissions
of 7,490 grams per day.
Step lg in the emission methodology involves calculating the total trip-related emission changes
for the PATH project. These changes are calculated using the following formulas:
24
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AHCTRff = AHCCST + AHCHST + AHCHSK + AHCDNL
ANOxTRIP = ANOxCST + ANOxHST
ACOTRff = ACOCST + ACOHST
In the formulas, AHCTRIP, ANOxTRIP, and ACOTRIP are the total changes in HC,
NOx, and CO emissions, respectively, due to trip changes.
Using the data above, AHCTRIP = -18,192 + -3,561 + -16,189 + 7,490 = -30,452. Summarizing
this result, the PATH project results in a net decrease in trip-related HC emissions of 30,452 grams per
day. (Following the same methodology, total trip-related emission changes can also be determined for
NOx and CO.)
Emission Effects - STEP 2 (VMT Changes')
Step 2 in the estimation of the emission effects for the PATH project involves calculating the
effect of VMT changes on emissions. This step is broken down into four smaller steps (2a through 2d),
which are outlined below.
Step 2a in the emission methodology involves estimating the distribution of VMT changes for
the PATH project. These changes are calculated using the following formulas:
YVMT,LDGV = VMTLDGV / (VMTLDGV + VMTLDGT1)
YvMI.LDGTl = 1 " YvMI.LDGV
In the formulas, YVMT.LDGV is th£ fraction of TCM-affected VMT for light-duty
gasoline vehicles (LDGVs), YTRIPLDGTI is th£ fraction of TCM-affected VMT for
light-duty gasoline trucks (LDGTls), VMTLDGV is the fraction of total VMT in
the region for LDGVs, and VMTLDGT1 is the fraction of total VMT in the region
for LDGTls. (Note: Most TCMs that can be analyzed using EPA's guidance
document affect only LDGVs or LDGTls. Thus, the sum of YVMT.LDGV and
YVMT.LDGTI is typically equal to one.)
VMTLDGV and VMTLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are the national average default values used in MOBILE for VMT mix.
Using the data above, YVMT.LDGV = °-626 / (°-626 + °-171) = °-785 and YVMT.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the VMT affected by the PATH project is by LDGVs,
and 21.5% is by LDGTls.
Step 2b in the emission methodology involves estimating hot-stabilized exhaust emission
changes for the PATH project. These changes are calculated using the following formulas:
25
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AHCsmP = (ANETVMTP * YVMT,LDGV * STBLDGV3QP) + (ANETVMTP * YVMT,LDGTI * STBLDGT13QP)
AHCsmoP = (ANETVMTOP * YVMT,LDGV * STBLDGV3QOP) + (ANETVMTOP * YVMT,LDGTI * STBLDGT13QOP)
ANOxsmP = (ANETVMTp * YVMI,LDGV * STBLDGV,NOx,P) + (ANETVMTP * YVMT,LDGTI * STBLDGTUNOx,P)
ANOxsmoP = (ANETVMTOP * YVMI,LDGV * STBLDGV,NOx,OP) + (ANETVMTOP * YVMT,LDGTI *
STBLDGT j jNOx,op)
ACOsmP = (ANETVMTP * YVMT,LDGV * STBLDGVmP) + (ANETVMTp * YVMT,LDGTI * STBLDGTUCO,P)
ACOsmoP = (ANETVMT0p * YVMT,LDGV * STBLDGVmoP) + (ANETVMTOP * YVMT,LDGTI * STBLDGTUCO,0p)
In the formulas, AHCSTB P, ANOxSTB P, and ACOSTB P are the peak-period changes
in hot-stabilized emissions for HC, NOx, and CO, respectively; and AHCSTB OP,
ANOxSTB op, and ACOSTB OP are the off-peak changes in hot-stabilized emissions
for HC, NOx, and CO, respectively. STBP is the hot-stabilized emission factor
(in grams per mile) for each pollutant and vehicle class for the peak period
(during which average vehicle speed is assumed to be 20 miles per hour), and
STBOP is the hot-stabilized emission factor (in grams per mile) for each pollutant
and vehicle class for the off-peak period (during which average vehicle speed is
assumed to be 35 miles per hour). The other parameters in the formulas are
defined in earlier steps of the methodology.
Using national default data from MOBILE, AHCSTBP = (-19,187 * 0.785 * 1.23) + (-19,187
* 0.215 * 1.77) = -25,828 and AHCSTBOP = (-28,307 * 0.785'* 0.69) + (-28,307 * 0.215 * 0.94) = -21,053.
Summarizing these results, the PATH project results in a reduction in peak-period hot-stabilized HC
exhaust emissions of 25,828 grams per day and a reduction in off-peak hot-stabilized HC exhaust
emissions of 21,053 grams per day. (Following the same methodology, hot-stabilized exhaust emission
changes can also be determined for NOx and CO.)
Step 2c in the emission methodology involves estimating VMT-related evaporative emission
changes for the PATH project. These changes are calculated using the following formulas:
= (ANETVMTp * YVMTLDGV * VEVPLDGVP) + (ANETVMTp * YVMILDGTI * VEVPLDGT1P)
= (ANETVMT0p * YVMT,LDGV * VEVPLDGV,OP) + (ANETVMTOP * YVMI,LDGTI * VEVPLDGTUOP)
In the formulas, AHCyEyp P is the change in peak-period evaporative emissions,
AHCyEvp OP is the change in off-peak evaporative emissions, and VEVP is the
VMT-related evaporative emission factor (in grams per mile) for each vehicle
class and time period (peak or off-peak). The other parameters in the formulas
are defined in earlier steps of the methodology. (Note: Evaporative emissions
are HC emissions only.)
Using national default data from MOBILE, AHC^p = (-19,187 * 0.785 * 0.44) + (-19,187
* 0.215 * 0.53) = -8,814 and AHC^y^ = (-28,307 * 0.785 * 0.34) + (-28,307 * 0.215 * 0.44) = -10,233.
Summarizing these results, the PATH project results in a reduction in peak-period evaporative emissions
of 8,814 grams per day and a reduction in off-peak evaporative emissions of 10,233 grams per day.
Step 2d in the emission methodology involves calculating the total VMT-related emission
changes for the PATH project. These changes are calculated using the following formulas:
AHCSTBjOp
= ANOxSTB)P + ANOxSTB)OP
26
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= ACOsP + ACO
smP smoP
In the formulas, AHCy^., ANOxy^., and AGOy^ are the total changes in HC,
NOx, and CO emissions, respectively, due to VMT changes.
Using the data above, AHC^ = -25,828 + -21,053 + -8,814 + -10,233 = -65,928. Summarizing
this result, the PATH project results in a net decrease in VMT-related HC emissions of 65,928 grams per
day. (Following the same methodology, total VMT-related emission changes can also be determined for
NOx and CO.)
Emission Effects - STEP 3 (Speed Changes)
Step 3 in the estimation of the emission effects for the PATH project involves calculating the
effect of speed changes on emissions. This step is broken down into four smaller steps (3a through 3d),
which are outlined below.
Step 3a in the emission methodology involves estimating the speeds associated with the PATH
project. These speeds are calculated using the following formulas:
SPEEDPTCM = SPEEDPBASE * (1 + ASPDP)
SPEEDOPJCM = SPEEDOP3ASE * (1 + ASPDOP)
In the formulas, SPEEDPTCM is the peak-period speed after implementation of the
TCM, SPEED0pjcM is the off-peak speed after implementation of the TCM,
SPEEDPBASE is the peak-period speed prior to implementation of the TCM, and
SPEEDOP BASE is the off-peak speed prior to implementation of the TCM. The
other parameters in the formulas are defined in earlier steps of the methodology.
Based on data for the national default fleet, SPEEDPBASE is assumed to be 20 miles per hour,
and SPEEDOPBASE is assumed to be 35 miles per hour.
Using the data above, SPEEDPTCM = 20 * (1 + 0.0004) = 20.01 and SPEEDOPTCM = 35 * (1 + 0)
= 35. Summarizing these results, peak-period speeds have slightly increased from 20 miles per hour
to 20.01 miles per hour due to the PATH project. Off-peak speeds have not changed due to the project.
Step 3b in the emission methodology involves estimating the total VMT for the program area
after implementation of the PATH project. These VMT figures are calculated using the following
formulas:
VMTP TCM = TOTVMTP + ANETVMTP
VMTOPJCM = TOTVMTOP + ANETVMTOP
In the formulas, VMTP TCM is the total peak-period VMT in the program area
after implementation of the TCM, and VMTOPTCM is the total off-peak VMT in
the program area after implementation of the TCM. The other parameters in the
formulas are defined in earlier steps of the methodology.
Using data from Step 9 of the "Travel Activity Effects" section above, VMTPTCM = 32,000,000
+ -19,187 = 31,980,813 and VMTOPTCM = 48,000,000 + -28,307 = 47,971,693. Summarizing these
results, peak-period VMT has decreased from 32,000,000 miles per day to 3 1,980,8 13 miles per day due
27
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to the PATH project. Off-peak VMT has decreased from 48,000,000 miles per day to 47,971,693 miles
per day due to the project.
Step 3c in the emission methodology involves estimating peak-period and off-peak emission
changes due to changes in vehicle speeds. These changes are calculated using the following formulas:
AHCSPD)P VM 1 PJCM (S 1 -t>FLT,HC,P,TCM + -"^ -^FLT.PJCM) " * M 1 PJCM (S 1 -°FLT,HC,P,BASE + -
AHCSPD)Op ~~ V MTOpjTcM (STBFLT)HCjOP)TCM + RNLFLTjOPjTCM) - VMT0pjTCM (STBFLTjHC)OP)BASE + RNLFLTjOPjBASE)
ANOxSPD)P = VMTPjCM (STBFLTjNOX)PjCM - STBFLTjNOX)P)BASE
ANOxSPD)Op = V M.TOPJCM
ACOSPDjP = VMTPjCM (STBFLT)COjPjCM - STBFLT)CO)P)BASE)
ACOSPDjOp = V JVlTOpjCM (STBFLT)COjOpjCM
In the formulas, AHCSPDP, ANOxSPDP, and ACOSPDP are the peak-period changes
in emissions for HC, NOx, and CO, respectively, due to a change in speeds; and
AHCSPD OP, ANOxSPD op, and ACOSPD OP are the off-peak changes in emissions for
HC, NOx, and CO, respectively, due to a change in speeds. STBFLT is the fleet-
wide hot-stabilized emission factor (in grams per mile) for each pollutant, time
period (i.e., peak or off-peak), and scenario (i.e., base or TCM). RNLp.^ is the
fleet-wide running loss emission factor (in grams per mile) for each time period
and scenario. The other parameters in the formulas are defined in earlier steps
of the methodology.
Based on data showing the relationship between vehicle speed and emissions, this analysis
assumes that the elasticity of STBFLT with respect to speed is -1 for HC, 0 for NOx, and -1 for CO.
Thus, a 1% increase in speed is assumed to result in a 1% decrease in HC and CO emissions (on a grams
per mile basis) and no change in NOx emissions. The elasticity of RNLFLT with respect to speed is also
assumed to be -1.
Using national default data from MOBILE, AHCSPDP = 31,980,813 * (1.675 + 0.212)
- 31,980,813 * (1.676 + 0.212) = -31,981 and AHCSPDOP = 47,971,693 * (1.938 + 0.120) - 47,971,693
* (1.938 + 0.120) = 0. Summarizing these results, the PATH project results in a decrease in speed-
related HC emissions of 3 1,98 1 grams per day for the peak period but does not change speed-related HC
emissions for the off-peak period. (Following the same methodology, the peak-period and off-peak
emission changes due to changes in speeds can also be determined for NOx and CO.)
Step 3d in the emission methodology involves calculating the total speed-related emission
changes for the PATH project. These changes are calculated using the following formulas:
AHCSPD ArlCSPDjP + ArlCSPD)Op
ANOxSPD = ANOxSPD)P + ANOxSPE, op
ACOSPD
In the formulas, AHCSPD, ANOxSPD, and ACOSPD are the total changes in HC,
NOx, and CO emissions, respectively, due to speed changes.
Using the data above, AHCSPD = -3 1,98 1 + 0 = -3 1,98 1 . Summarizing this result, the PATH
project results in a net decrease in speed-related HC emissions of 3 1 ,98 1 grams per day. (Following the
same methodology, total speed-related emission changes can also be determined for NOx and CO.)
28
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Emission Effects - STEP 4 (Total)
Step 4 in the estimation of the emission effects for the PATH project involves calculating the
total changes in HC, NOx, and CO emissions. These changes are calculated using the following
formulas:
ARC = AHCTRff + AHCvMT + AHCSPD
ANOx = ANOxTRIP + ANOxvMT + ANOxSPD
AGO = ACOTRff + ACOvMT + ACOSPD
In the formulas, AHC, ANOx, and ACO are the total changes in HC, NOx, and
CO emissions, respectively, due to the TCM program.
Using the data above, AHC = -30,452 + -65,928 + -31,981 = -128,361. Summarizing this result,
O 55555 O 5
the PATH project results in a net decrease in HC emissions of 128,361 grams per day, or approximately
0.14 tons per day. (Following the same methodology, total emission changes can also be determined for
NOx and CO.)
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Example 3: Cleveland Walkway to Gateway
General Description
The Cleveland Walkway to Gateway provides a link for transit riders arriving at Tower City
Center, the main shopping and entertainment area of downtown Cleveland, to the Gateway Sports and
Entertainment Complex. The climate-controlled walkway, which is about a quarter mile long, was
designed in part to stimulate transit ridership in the metro area and relieve traffic congestion, especially
during sporting events. The Greater Cleveland Regional Transport Authority determined that about
940,000 transit riders used the walkway during the 16-month period between April 1994 and August
1995.
(Note: Because the Walkway to Gateway is intended to link downtown shopping and entertainment areas
with the Gateway complexes, which are primarily used for recreational activities (e.g., sporting events),
this analysis assumes that the walkway has no effect (either directly or indirectly) on work-related trips,
VMT, speeds, or emissions (commutes by Stadium/Arena employees are considered non-work trips for
the purpose of this analysis). In addition, because events at the Gateway complex tend to occur during
off-peak hours, the analysis assumes that the walkway has no effect on peak period trips, VMT, speeds,
or emissions. Given these assumptions, this analysis excludes several of the formulas shown in EPA's
TCM guidance and in some cases modifies formulas to reflect the nature of the travel activity and
emissions effects from the Walkway to Gateway.)
Data Sources
Interview with Joel Freilich, Director, Strategic Planning and Research, Greater Cleveland
Regional Transit Authority, March 6, 1997.
1990 U.S. Census data.
1996 Statistical Abstract of the United States.
Texas Transportation Institute web page.
Phase 1: Travel Activity Effects
Step 1 in the estimation of travel activity
effects for the Walkway to Gateway involves an
assessment of the potential trip effects from the
program. For this TCM, these potential effects
are calculated using the following user-defined
formula:
PT = (N) / 487
Phase 1: Effects on Travel Activity
Step 1: Potential trip effects
Step 2: Direct work and non-work trip reductions
Step 3: Indirect work and non-work trip increases
Step 4: Peak and off-peak trip shifts
Step 5: Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Step 6: Peak and off-peak VMT changes due to
reduced number of trips
Step 7: VMT changes due to reduced trip lengths
Step 8: Net VMT changes
Step 9: Peak and off-peak speed changes
30
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In the formula, PT is the potential effect on trips, and N is the number of transit
riders who used the walkway between April 1994 and August 1995 (a period
of 487 days) who would not have taken transit in the absence of the walkway.
The appropriate value for N is derived by "adjusting" the number of transit riders who used the
walkway between April 1994 and August 1995 (i.e., 940,000) by the percentage of those riders who
would not have taken transit in the absence of the walkway. Assuming that 70 percent of walkway users
would not have taken transit, N = 0.70 * 940,000 = 658,000. (Note: The "70 percent" assumption for
transit use is for illustrative purposes only. A more realistic assumption could be developed using
surveys or expert judgment.) It should be noted that the Walkway is only open during events at Gateway.
Therefore, actual emission reductions on a given day are more than the average derived here.
Using the data above, PT = (658,000) / 487 = 1,351. Thus, the potential number of trips reduced
per day by the Walkway to Gateway is 1,351.
Step 2 in the travel activity methodology involves estimating the direct work and non-work trip
reductions from the Walkway to Gateway. Whereas the potential trip reductions calculated in Step 1
represent the total number of trips that might be reduced by a TCM program, direct trip reductions
measure the number of trips that actually are reduced and, thus, can be less than potential trip reductions
(e.g., if not all walkway users formerly drove alone to the Gateway complex). Direct trip reductions for
the Walkway to Gateway are calculated using the following formulas:
ATRIPSD = a * PT
ATRIPSDNW = (!-«)* ATRIPSD
In the formulas, ATRIPSD is the total direct trip reduction, PT is (as above) the
potential trip reductions, ATRIPSDNW is the direct non-work trip reduction, a is
the fraction of program participants who make a direct trip change, and co is the
fraction of trip effects that are work-related.
Because all trip reductions from the walkway are assumed to be non-work related, the TCM
guidance call for the parameter co to be set equal to 0.
For the Walkway to Gateway, a is defined as -(1 - DRIVTRAN) / AVO, where DRIVTRAN
is the fraction of people who drive to public transit stations and AVO is average vehicle occupancy.
This analysis assumes that 50 percent of transit riders using the walkway drive to public transit stations,
and thus DRIVTRAN = 0.5. Average vehicle occupancy for trips to Gateway is estimated to be 1.5.
Using these values for DRIVTRAN and AVO, a = -(1 - 0.5) /1.5 = -0.33.
Using the data above, ATRIPSD = -0.33 * 1,351 = -446 and ATRIPSDNW = (1 - 0) * -446 = -446.
Summarizing these results, the Walkway to Gateway is responsible for directly reducing 446 trips per
day, all of which are non-work related.
Step 3 in the travel activity methodology involves estimating the actual indirect trip increases
from the Walkway to Gateway. Indirect trip increases are secondary effects that typically result when
vehicles normally used for other trips are left at home. For the Walkway to Gateway, these increases
are calculated using the following formula:
ATRIPSINW = INCNH * -ATRIPSD / 2
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In the formula, ATRIPSINW is the indirect non-work trip increase, and INCNH
is the rate of increased SOV non-work trip making by household members of
TCM participants who leave their vehicles at home. The other parameter in
the formula is defined in an earlier step of the methodology.
INCNH is defined as NV * SHR * (SIZE - 1) * UNEMP * TGN, where NV is the fraction of the
population that does not own a vehicle (Note: This analysis interprets this parameter to mean the
percentage of drivers without a vehicle, which is estimated as the percentage of vehicle-owning
households in the program area that have only one vehicle.), SHR is the fraction of shared mode trips,
SIZE is average household size, UNEMP is the fraction of the population that is not employed, and TGN
is the non-work trip generation rate for SOV users. Based on 1990 U.S. Census data for Cuyahoga
County, NV is assumed to be 45%, SHR is assumed to be 19%, and SIZE is assumed to be 2.39.
Because the walkway is used almost entirely during evening hours, indirect trip increases do not depend
on employment status, and thus UNEMP is set equal to 1. Finally, TGN is estimated to be 1.0, based
on national default data indicating that the average person takes approximately 3 non-work trips per day
and assuming that 1/3 of these trips are taken during the evening hours. Based on these numbers, INCNH
= 0.45 * 0.19 * (2.39 - 1) * 1 * 1 = 0.12.
Using the data above, ATRIPSINW = 0.12* -(-446) 12 = 21. Thus, the Walkway to Gateway
is indirectly responsible for an increase of 27 non-work trips per day.
Step 4 in EPA's methodology for estimating travel activity effects of TCMs, which involves
determining direct peak and off-peak period trip shifts, does not apply to projects such as the Walkway
to Gateway.
Step 5 in the travel activity methodology involves estimating the net trip changes from the
Walkway to Gateway. These changes are calculated using the following formula:
ANETRP^op = (!-«)* ATRIPSSOP + (1 - PK^) * (ATRIPSDNW + ATRIPSINW)
In the formula, ANETRP^>OP is the net non-work trip change in the off-peak
period, ATRIPSS OP is the change in off-peak period trips, and PK^ is the
observed fraction of non-work trips during the peak period. The other
parameters in the formula are defined in earlier steps of the methodology.
Because there are no trip shifts associated with transit improvements (see Step 4), ATRIPSS OP
is equal to 0. Also, because direct and indirect trip effects from the Walkway to Gateway occur only
at off-peak periods, EPA's TCM guidance calls for PK^ to be set equal to 0.
Using the data above, ANETRP^op = (1 - 0) * 0 + (1 - 0) * (-446 + 27) = -419. Thus, the
Walkway to Gateway results in a net decrease of 419 off-peak non-work trips per day.
Step 6 in the travel activity methodology involves estimating the off-peak VMT changes due
to the trip changes from the Walkway to Gateway. These changes are calculated using the following
formula:
AVMTOP = (ANETRPWOP * DISTW) + (ANETRP^p * DIST^)
In the formula, AVMTOP is the change in off-peak VMT due to trip changes,
DISTW is the average VMT per trip for work trips, and DIST^ is the average
32
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VMT per trip for non-work trips. The other parameters in the formula are
defined in earlier steps of the methodology.
Because the Walkway to Gateway does not affect work trips, ANETRPWOP is equal to 0.
is assumed to be 8 miles per trip for trips to the Gateway complex (based on information about transit trip
lengths provided by the Greater Cleveland Regional Transit Authority) and 8.1 miles per trip for all other
non-work trips (based on data from the 1996 Statistical Abstract of the United States}.
Using the data above, AVMTOP = 0 + [(-446 * 8) + (27 * 8. 1)] = -3,349. Thus, the Walkway
to Gateway reduces off-peak VMT by 3,349 miles per day due to trip changes.
Step 7 in the travel activity methodology involves estimating the VMT changes due to trip length
changes resulting from the Walkway to Gateway. These changes are calculated using the following
formula:
AVMTLNW = p * PT * -(DIST^ - DISTnew)
In the formula, AVMTLNW is the change in VMT due to trip length changes, p is
the fraction of program participants who change their trip length, DIST^ is the
average length of a trip to the Gateway complex, and DISTnew is the new trip
length. The other parameters in the formula are defined in earlier steps of the
methodology.
Based on information in Table 2-10 of the TCM guidance, p is set equal to DRJVTRAN.
As noted in Step 2 above, DRTVTRAN = 0.5, and thus p = 0.5.
As noted in Step 6 above, DIST^ for transit trips to Gateway is 8 miles. That is, transit reduces
VMT by 8 miles per trip because transit stations tend to be located along the route from homes to
downtown Cleveland. Therefore, regardless of the driving distance to transit stops, DIST^ - DISTnew
= 8 miles.
Using the data above, AVMTLNW = 0.5 * 1,35 1 * -(8) = -5,404. Thus, the Walkway to Gateway
reduces VMT by 5,404 miles per day due to trip length changes.
Step 8 in the travel activity methodology involves estimating the total off-peak VMT changes
resulting from the Walkway to Gateway. These changes are calculated using the following formula:
ANETVMT0p = AVMTOP + (1 - PK^) * AVMTL>NW
In the formula, ANETVMTOP is the total change in off-peak VMT. The other
parameters in the formula are defined in earlier steps of the methodology.
Using the data above, ANETVMTOP = -3,349 + (1 - 0) * -5,404 = -8,753. Thus, the Walkway
to Gateway reduces off-peak VMT by a total of 8,753 miles per day.
Step 9 in the travel activity methodology involves estimating off-peak speed changes resulting
from the Walkway to Gateway. These changes are calculated using the following formula:
ASPDOP = (ANETVMT0p / TOTVMTOP) * eop
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In the formula, ASPDOP is the change in off-peak speeds, TOTVMTOP is total
off-peak VMT for the program area, and eop is the elasticity of off-peak speed
with respect to volume. The other parameter in the formula is defined in an
earlier step of the methodology.
According to data from the Texas Transportation Institute, total VMT in metropolitan Cleveland
is approximately 36 million miles per day. Assuming that 50 percent of travel activity occurs during
off-peak periods, TOTVMTOP is approximately 18 million miles per day.
Post-event traffic is less congested as a result of increased tranit use. However, sufficient data
is not available. Therefore, the parameter eop is assumed to be 0, because changes in off-peak VMT
do not usually affect vehicle speeds (i.e., due to a lack of congestion).
Using the data above, ASPDOP = (-8,753 /18,000,000) * 0 = 0. Summarizing this result, the
Walkway to Gateway has no effect on off-peak period speeds.
Phase 2: Emission Effects STEP 1 (Trip
Changes)
Step 1 in the estimation of the emission
effects for the Walkway to Gateway involves
calculating the effect of trip changes on
emissions. This step is broken down into seven
smaller steps (la through Ig), which are outlined
below.
Step la in the emission methodology
involves estimating the distribution of trip
changes for the Walkway to Gateway. These
changes are calculated using the following
formulas:
YTMP.LDGV = TRIPLDGV / (TRIPLDGV + TRIPLDGT1)
YTRIRLDGTI = 1 YTRIRLDGV
Phase 2: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3 a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
Step 4: Summation of emission effects
34
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In the formulas, YTRIP.LDGV is the fraction of TCM-affected trips taken by light-
duty gasoline vehicles (LDGVs), YTRTP.LDGTI is the fraction of TCM-affected trips
taken by light-duty gasoline trucks (LDGTls), TRIPLDGV is the fraction of total
trips in the region taken by LDGVs, and TRIPLDGT1 is the fraction of total trips
in the region taken by LDGTls. (Note: Most TCMs that can be analyzed using
EPA's guidance document affect only LDGVs or LDGTls. Thus, the sum of
YTRTP.LDGV and YTRTP.LDGTI is typically equal to one.)
TRIPLDGV and TRIPLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are based on the national average default values used in MOBILE.
Using the data above, YTRTP.LDGV = °-626 / (°-626 + °-171) = °-785 and YTRIP.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the trips affected by the Walkway to Gateway are taken
by LDGVs, and 21.5% are taken by LDGTls.
Step Ib in the emission methodology involves calculating cold-start and hot-start trip changes
for the Walkway to Gateway. These changes are calculated using the following formulas:
ATRIPSCST = YCSTW * (ANETRPWP + ANETRPWOP) + YCST NW * (ANETRP^p + ANETRP^p)
ATRIPSHST = (1 - YCSTW) * (ANETRPWP + ANETRPWOP) + (1 - YCSTNW) *
In the formulas, ATRIPSCST is the number of cold-start trip changes, ATRIPSHST
is the number of hot-start trip changes, YCST w is the fraction of work trips begun
in the cold-start mode, and YCST NW is the fraction of non-work trips begun in the
cold-start mode. The other parameters in the formulas are defined in earlier
steps of the methodology.
Because work trips are mostly cold-start trips, the guidance calls for YCST w to be set equal to 1 .
The guidance also suggests that YCSTNW be set equal to 0.43, which is the default fraction of cold starts
used in the Federal Test Procedure (FTP).
Using the data above, ATRIPSCST = 1 * (0 + 0) + 0.43 * (0 + -419) = -180 and ATRIPSHST
= (1 - 1) * (0 + 0) + (1 - 0.43) * (0 + -419) = -239. Summarizing these results, the Walkway to Gateway
results in a reduction of 180 cold-start trips per day and a reduction of 239 hot-start trips per day.
Step Ic in the emission methodology involves determining cold-start and hot-start emission
factors. These changes are calculated^or a given pollutant and vehicle class using the following
formulas:
= (EXH10oo/oCST,26MPH " EXHlclQo/oSTB)26MPH) 3.59
HST = (EXH10oo/oHST)26MPH " EXHlclQo/oSTB)26MPH) 3.59
In the formulas, CST is the cold-start emission factor in grams per trip, HST
is the hot-start emission factor in grams per trip, and EXH is the MOBILE
emission factor in grams per mile. The 3.59 factor is the FTP driving cycle
trip-start miles per trip, and 26 miles per hour is the speed for the start portion
of the FTP driving cycle. (Note: The subscripts on EXH refer to the operating
conditions and speed at which MOBILE evaluates EXH. For example,
"100%CST,26MPH" indicates 100% cold-start operating mode at 26 miles
per hour vehicle speed.)
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Using national default data from MOBILE, CSTLDGVHC = (2.55 - 0.95) * 3.59 = 5.74 grams per
trip, CSTLDGT1HC = (3.59 - 1.34) * 3.59 = 8.08 grams per trip,' HSTLDGVHC = (1.35 - 0.95) * 3.59 = 1.44
grams per trip, and HSTLDGT1 HC = (1.99 - 1.34) * 3.59 = 2.33 grams per trip. (Following the same
methodology, the cold-start and hot-start emission factors can also be determined for NOx and CO.)
Step Id in the emission methodology involves determining cold-start and hot-start emission
changes for the Walkway to Gateway. These changes are calculated using the following formulas:
AriCCST (AlKlrSCST YTRTP.LDGV CS1LDGV)HC) + (AlKlrSCST YTRTP.LDGTI
AHCHST (A 1 R1PSHST YTRIP.LDGTI "-^ J- LDGV.HC) + (A1R1PSHST YTRIP.LDGTI
AJNOxCST (AlKlrSCST YTRTPLDGV CSlLDGVNOx) + (A 1 Kir SCST YTRIPLDGTI CSlLDGT1NOx)
ANOxHST = (ATRIPSHST * YTRTP.LDGTI * HSTLDGV,NOx) + (ATRIPSHST * YTRTP.LDGTI * HSTLDGTUNOx)
ACOCST (AlKlrSCST YTRTP.LDGV CS1LDGV)CO) + (AlKlrSCST YTRTP.LDGTI
ACOHST (A 1 K1PSHST YTRTP.LDGTI "-^ J- LDGV.CO) + (A1R1PSHST YTRIP.LDGTI
In the formulas, AHCCST, ANOxCST, and ACOCST are the changes in cold-start
emissions for HC, NOx, and CO, respectively; and AHCHST, ANOxHST, and
ACOHST are the changes in hot-start emissions for HC, NOx, and CO,
respectively. The other parameters in the formulas are defined in earlier steps
of the methodology.
Using national default data from MOBILE, AHCCST = (-180 * 0.785 * 5.74) + (-180 * 0.215
* 8.08) = -1,124 and AHCHST = (-239 * 0.785 * 1.44) + (-239 * 0.215 * 2.33) = -390. Summarizing these
results, the Walkway to Gateway results in a reduction in cold-start HC emissions of 1,124 grams per day
and a reduction in hot-start HC emissions of 390 grams per day. (Following the same methodology,
the cold-start and hot-start emission changes can also be determined for NOx and CO.)
Step le in the emission methodology involves determining hot soak emission changes for the
Walkway to Gateway. These changes are calculated using the following formula:
AHCHSK = (ATRIPSTOTAL * YTRIP.LDGV * HSKLDGV) + (ATRIPSTOTAL * YTRIP.LDGTI * HSKLDGT1)
In the formula, AHCHSK is the change in hot soak emissions, ATRIPSTOTAL is the
total change in trips, and HSK is the hot soak emission factor in grams per trip.
(Note: Hot soak emissions are HC emissions only.)
ATRIPSTOTAL = ANETRPWP + ANETRPWOP + ANETRP^p + ANETRP^p.
Thus, ATRIPSTOTAL = 0 + 0 + 0 + -419 = -419.
Using national default data from MOBILE, AHCHSK = (-419 * 0.785 * 3.06) + (-419 * 0.215
* 3.60) = -1,331. Summarizing this result, the Walkway to Gateway results in a reduction in hot soak
emissions of 1,33 1 grams per day.
Step If in the emission methodology involves determining diurnal emission changes for the
Walkway to Gateway. These changes are calculatedyfor a given vehicle class using the following
formulas:
AHCDNL^ = 0.676 * (ANETRP^p + ANETRP^p) / TPD^ * YTRTP * (WDI - MDI)
36
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AHCDNL AHCDNL)WjLDGV + AHCDNLjNW)LDGV + AHCDNLjW)LDGT1 + AHCDNL)NWjLDGT1
In the formulas, AHCDNL>NW is the change in diurnal emissions associated with
non-work trips, and AHCDNL is the total change in diurnal emissions. TPD^
is the number of non-work trips per day per vehicle. WDI is the weighted
diurnal emission factor in grams, and MDI is the multi-day diurnal emission
factor in grams. The other parameters in the formulas are defined in earlier steps
of the methodology. (Note: Diurnal emissions are HC emissions only.)
is assumed to equal to TGN from Step 3 of the "Travel Activity Effects" section above,
and thus equals 1.0.
Using national default data from MOBILE, AHCDNLNWLDGV = 0.676 * (0 + -419) / 1 * 0.785
* (3.30 - 6.04) = 609, AHCDNLNWLDGT1 = 0.676 * (0 + -419) / 1 * 0.215 * (5.11 - 15.33) = 622, and
AHCDNL = 0 + 609 + 0 + 622 = 1,231. Summarizing these results, the Walkway to Gateway results in
a net increase in diurnal emissions of 1,231 grams per day.
Step lg in the emission methodology involves calculating the total trip-related emission changes
for the Walkway to Gateway. These changes are calculated using the following formulas:
AHCTRrP = AHCCST + AHCHST + AHCHSK + AHCDNL
ANOxTRIP = ANOxCST + ANOxffi
-HST
ACOTRrP = ACOCST + ACOHST
In the formulas, AHCTRIP, ANOxTRIP, and ACOTRIP are the total changes in HC,
NOx, and CO emissions, respectively, due to trip changes.
Using the data above, AHCTRIP = -1,124 + -390 + -1,331 + 1,231 = -1,614. Summarizing this
result, the Walkway to Gateway results in a net decrease in trip-related HC emissions of 1,614 grams per
day. (Following the same methodology, total trip-related emission changes can also be determined for
NOx and CO.)
Emission Effects STEP 2 (VMT Changes)
Step 2 in the estimation of the emission effects for the Walkway to Gateway involves calculating
the effect of VMT changes on emissions. This step is broken down into four smaller steps (2a through
2d), which are outlined below.
Step 2a in the emission methodology involves estimating the distribution of VMT changes for
the Walkway to Gateway. These changes are calculated using the following formulas:
YVMT.LDGV = VMTLDGV / (VMTLDGV + VMTLDGT1)
YVMT.LDGTI 1 ~ YVMT.LDGV
In the formulas, YVMT LDGV is the fraction of TCM-affected VMT for light-duty
gasoline vehicles (LDGVs), YTRTPLDGTI is the fraction of TCM-affected VMT
for light-duty gasoline trucks (LDGTls), VMTLDGV is the fraction of total VMT
in the region for LDGVs, and VMTLDGT1 is the fraction of total VMT in the
region for LDGTls. (Note: Most TCMs that can be analyzed using EPA's
guidance document affect only LDGVs or LDGTls. Thus, the sum of YVMT LDGV
and YVMTLDGTI is typically equal to one.)
37
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VMTLDGV and VMTLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are the national average default values used in MOBILE for VMT mix.
Using the data above, YVMT.LDGV = °-626 / (°-626 + °-171) = °-785 and YVMT.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the VMT affected by the Walkway to Gateway
is by LDGVs, and 21.5% is by LDGTls.
Step 2b in the emission methodology involves estimating hot-stabilized exhaust emission
changes for the Walkway to Gateway. These changes are calculated using the following formulas:
AHCSTBOP = (ANETVMT0p * YVMTLDGV * STBLDGVHCOP) + (ANETVMTOP * YVMTLDGTI * STBLDGT1HCOP)
ANOxsmop = (ANETVMTOP * YVMI,LDGV * STBLDGV,NOx,OP) + (ANETVMTOP * YVMT.LDGTI *
ACOSTB>OP = (ANETVMTOP * YVMT.LDGV * STBLDGViCO)OP) + (ANETVMTOP * YVMT.LDGTI * STBLDGTliCO)OP)
In the formulas, AHCSTB OP, ANOxSTB OP, and ACOSTB OP are the off-peak changes
in hot-stabilized emissions for HC, NOx, and CO, respectively. STBOP is the
hot-stabilized emission factor (in grams per mile) for each pollutant and vehicle
class for the off-peak period (during which average vehicle speed is assumed to
be 35 miles per hour). The other parameters in the formulas are defined in
earlier steps of the methodology.
Using national default data from MOBILE, AHCSTBOP = (-8,753 * 0.785 * 0.69) + (-8,753
* 0.215 * 0.94) = -6,510. Summarizing this result, the Walkway to Gateway results in a reduction
in off-peak hot-stabilized HC exhaust emissions of 6,510 grams per day. (Following the same
methodology, hot-stabilized exhaust emission changes can also be determined for NOx and CO.)
Step 2c in the emission methodology involves estimating VMT-related evaporative emission
changes for the Walkway to Gateway. These changes are calculated using the following formula:
= (ANETVMTOP * YVMT.LDGV * VEVPLDGVoP) + (ANETVMTOP * YVMT.LDGTI * VEVP
In the formula, AHCy^ jOP is the change in off-peak evaporative emissions, and
VEVP is the VMT-related evaporative emission factor (in grams per mile) for
each vehicle class. The other parameters in the formula are defined in earlier
steps of the methodology. (Note: Evaporative emissions are HC emissions only.)
Using national default data from MOBILE, AHC^^ = (-8,753 * 0.785 * 0.34) + (-8,753
* 0.215 * 0.44) = -3,164. Summarizing this result, the Walkway to Gateway results in a reduction
in off-peak evaporative emissions of 3,164 grams per day.
Step 2d in the emission methodology involves calculating the total VMT-related emission
changes for the Walkway to Gateway. These changes are calculated using the following formulas:
= AHCSTB)P + AHCSTB)OP + AHCyEvp^
ANOXvMT = ANOxSTBP + ANOxSTB OP
T = ACOsmP + ACOsmoP
In the formulas, AHCy^-, ANOxy^., and AGOy^- are the total changes in HC,
NOx, and CO emissions, respectively, due to VMT changes.
38
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Using the data above, AHC^ = 0 + -6,5 10 + 0 + -3, 164 = -9,674. Summarizing this result,
the Walkway to Gateway results in a net decrease in VMT-related HC emissions of 9,674 grams per day.
(Following the same methodology, total VMT-related emission changes can also be determined for NOx
and CO.)
Emission Effects - STEP 3 (Speed Changes)
Step 3 in the estimation of the emission effects for the Walkway to Gateway involves calculating
the effect of speed changes on emissions. This step is not necessary because, as estimated in Step 9
above, the Walkway to Gateway has no effect on vehicle speeds.
Emission Effects - STEP 4 (Total)
Step 4 in the estimation of the emission effects for the Walkway to Gateway involves calculating
the total changes in HC, NOx, and CO emissions. These changes are calculated using the following
formulas:
ARC = AHCTRff + AHCvMT + AHCSPD
ANOx = ANOxTRIP + ANOxvMT + ANOxSPD
AGO = ACOTRff + ACOvMT + ACOSPD
In the formulas, ARC, ANOx, and AGO are the total changes in HC, NOx,
and CO emissions, respectively, due to the TCM program.
Using the data above, ARC = -1,614 + -9,674 + 0 = -1 1,288. Summarizing this result,
the Walkway to Gateway results in a net decrease in HC emissions of 1 1,288 grams per day,
or approximately 0.011 tons per day. (Following the same methodology, total emission changes
can also be determined for NOx and CO.)
39
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Example 4: Brevard County Vanpool Service
General Description
Brevard County, located along the eastern Florida coastline, has been operating an innovative
vanpool program for more than 14 years. The vanpool program, which provides commuter services
and social service agency transportation needs to area residents, began in 1983 with six vans and by 1996
had grown to a total of 95 vans (44 of which are used for commuting). The program is administered by
Space Coast Area Transit (SCAT), in conjunction with a private, for-profit company called VPSI, Inc.
Data Sources
Interview with Jim Leisenfelt, Program Director, SCAT, February 20, 1997.
Interview with George Gaudy, VPSI, Inc., Brevard County, February 21, 1997.
1990 U.S. Census data.
1996 Statistical Abstract of the United States.
Texas Transportation Institute web page.
Phase 1: Travel Activity Effects
Phase 1:
Step 1:
Step 2:
Step 3:
Step 4:
Step 5:
Step 6:
Step 7:
Step 8:
Step 9:
Effects on Travel Activity
Potential trip effects
Direct work and non-work trip reductions
Indirect work and non-work trip increases
Peak and off-peak trip shifts
Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Peak and off-peak VMT changes due to
reduced number of trips
VMT changes due to reduced trip lengths
Net VMT changes
Peak and off-peak speed changes
Step 1 in the estimation of travel activity
effects for the Brevard County Vanpool Service
involves an assessment of the potential trip
effects from the program. For ridesharing
programs, these potential effects are calculated
using the following formula:
PT = N * F / D * 2
In the formula, PT is the
potential effect on trips,
N is the number of
participants in the
ridesharing program, ^^^^^^^^^^^^^^^^^^^^^^^^^^
F is the frequency of
participation (in days per
week), and D is the
average number of
commute days per week.
The appropriate value for N is determined from data obtained from interviews with program
officials. A total of 44 vans are leased to commuters, and each van seats 11 people (1 driver and 10
passengers). Thus, the greatest number of participants in the program at any one time is equal to 484
(i.e., 44* 11).
This analysis assumes that participants use the vanpools for transportation to work every day.
Thus, the value of F is assumed to be 5.
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The value for D is 5, based on the fact that there are five workdays per week.
Using the data above, PT = 484 * 5 / 5 * 2 = 968. Thus, the potential number of trips reduced
per day by the Brevard County Vanpool Service is 968.
Step 2 in the travel activity methodology involves estimating the direct work and non-work trip
reductions from the Brevard County Vanpool Service. Whereas the potential trip reductions calculated
in Step 1 represent the total number of trips that might be reduced by a TCM program, direct trip
reductions measure the number of trips that actually are reduced and, thus, can be less than potential trip
reductions (e.g., if a participant in the program was previously part of a carpool). Direct trip reductions
are calculated using the following formulas:
ATRIPSD = a * PT
ATRIPSDW= (o * ATRIPSD
ATRIPSDNW = (1 - co) * ATRIPSD
In the formulas, ATRIPSD is the total direct trip reduction, PT is (as above) the
potential trip reductions, ATRIPSD w is the direct work trip reduction,
ATRIPSDNW is the direct non-work trip reduction, a is the fraction of program
participants who make a direct trip change, and to is the fraction of trip effects
that are work-related.
For ridesharing, a is defined as -[NOLD + NEW * (NCAR - 1) / NCAR] / AVO, where NOLD
is the fraction of vanpoolers who join an existing vanpool and do not drive to a park and ride lot, NEW
is the fraction of vanpoolers who form new vanpools and do not drive to a park and ride lot, NCAR is the
average number of people in a vanpool, and AVO is average vehicle occupancy. Assuming that each
vanpool is started by one person, all vans are full, and 5% of vanpoolers drive to park and ride lots,
NOLD and NEW values are 0.864 and 0.086, respectively. NCAR is 11, which includes 1 driver and
10 passengers.
The value used for AVO is based on the following information from 1990 U.S. Census data for
Brevard County: approximately 83% of work trips are in single occupancy vehicles (SOVs) (AVO = 1),
approximately 13% of work trips are in carpools (AVO = 2.28), 2% of work trips are walking, 0.1% use
buses (AVO assumed to be 15), and less than 2% of work trips are made using motorcycles, bicycles, and
taxicabs combined. Thus, AVO = (0.83 + 0.13 + 0.02 + 0.001 + 0.02 ) / [(0.83 / 1) + (0.13 / 2.28)
+ (0.001 /15)] = 1.13. Using the values for NOLD, NEW, NCAR, and AVO, a = -[0.864 + 0.086
* (11 -I)/11]/1.13 = -0.83.
Table 2-5 in EPA's TCM guidance document indicates that, for ridesharing, the parameter to
is equal to 1. This is because ridesharing directly affects work trips only.
Using the data above, ATRIPSD = -0.83 * 968 = -803, ATRIPSD w = 1 * -803 = -803 and
ATRIPSDNW = (1 - 1) * -803 = 0. Summarizing these results, the Brevard County Vanpool Service
is responsible for directly reducing 803 trips per day, all of which are work-related.
Step 3 in the travel activity methodology involves estimating the actual indirect trip increases
(for both work and non-work trips) from the Brevard County Vanpool Service. Indirect trip increases
are secondary effects that typically result when vehicles normally used for commuting are left at home.
These increases are calculated using the following formulas:
ATRIPS:w = INCWH * -ATRIPSD / 2
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ATRIPSINW = INCNH * -ATRIPSD / 2
In the formulas, ATRIPS: w is the indirect work trip increase, ATRIPSINW is the
indirect non-work trip increase, and INCWH and INCNH are the rates of increased
SOV work and non-work trip making by household members of TCM
participants who leave their vehicles at home. The other parameter in the
formulas is defined in an earlier step of the methodology.
INCWH is defined as NV * SHR * (SIZE - 1) * BMP * TGW, where NV is the fraction of the
population that does not own a vehicle (Note: This analysis interprets this parameter to mean the
percentage of drivers without a vehicle, which is estimated as the percentage of vehicle-owning
households in the program area that have only one vehicle.), SHR is the fraction of shared mode trips,
SIZE is average household size, BMP is the fraction of the population that is employed, and TGw is the
work trip generation rate for SOV users. Based on 1990 U.S. Census data for Brevard County, NV
is assumed to be 41%, SHR is assumed to be 14%, SIZE is assumed to be 2.43, and BMP is assumed
to be 58%. TGW is assumed to equal 2. Based on these numbers, INCWH = 0.41 * 0.14 * (2.43 - 1) * 0.58
* 2 = 0.10.
INCNH = NV * SHR * (SIZE - 1) * UNEMP * TGN, where NV, SHR, and SIZE are as defined
above, UNEMP is the fraction of the population that is not employed, and TGN is the non-work trip
generation rate for SOV users. UNEMP is simply (1 - EMP) and thus equals 42%. TGN is assumed to
be the same as TGW (i.e., 2). Based on these numbers, INCNH = 0.41 * 0.14 * (2.43 - 1) * 0.42 * 2 = 0.07.
Using the data above, ATRIPS: w = 0.10* -(-803) / 2 = 40, and ATRIPSINW = 0.07 * -(-803) / 2
= 28. Summarizing these results, the Brevard County Vanpool Service is indirectly responsible for an
increase of 40 work trips per day and 28 non-work trips per day.
Step 4 in EPA's methodology for estimating travel activity effects of TCMs, which involves
determining direct peak and off-peak period trip shifts, does not apply to ridesharing programs.
Thus, Step 4 is not relevant to the analysis of the Brevard County Vanpool Service.
Step 5 in the travel activity methodology involves estimating the net trip changes from the
Brevard County Vanpool Service as distributed between work and non-work trips and peak and off-peak
periods. These changes are calculated using the following formulas:
ANETRPWP = w * ATRIPSD + PKW * (ATRIPSDW + ATRIPSIW)
ANETRPWOP = w * ATRIPSSOP + (1 - PKW) * (ATRIPSDW + ATRIPSIW)
ANETRP^p = (!-«)* ATRIPSSP + PK^ * (ATRIPSDNW + ATRIPSINW)
= (!-«)* ATRIPSSOP + (1 - PK^) * (ATRIPSUNW + ATRIPSINW)
In the formulas, ANETRPWP is the net work trip change in the peak period,
ANETRPW op is net work trip change in the off-peak period, ANETRP^p is the
net non-work trip change in the peak period, and ANETRP^ jOP is the net non-
work trip change in the off-peak period. ATRIPSSP is the change in peak period
trips, and ATRIPSSOP is the change in off-peak period trips. PKW is the observed
fraction of work trips during the peak period, and PK^ is the observed fraction
of non-work trips during the peak period. The other parameters in the formulas
are defined in earlier steps of the methodology.
Because there are no trip shifts associated with ridesharing (see Step 4), ATRIPSSP and
ATRIPSSOp are each equal to 0.
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The values used for PKW and PK^ are 0.6 and 0.3, respectively, based on an example shown
in the TCM guidance document.
Using the data above, ANETRPWP = 0 + 0.6 * (-803 + 40) = -458, ANETRPWOP = 0 + (1 - 0.6)
* (-803 + 40) = -305, ANETRPWP = 0 + 0.3 * (0 + 28) = 8, and ANETRP^op = 0 * (1 - 0.3) * (0 + 28)
= 20. Summarizing these results, the Brevard County Vanpool Service results in net decreases in peak
and off-peak work trips of 458 per day and 305 per day, respectively. The program also results in
increases in peak and off-peak non-work trips of 8 per day and 20 per day, respectively.
Step 6 in the travel activity methodology involves estimating the peak and off-peak VMT
changes due to the trip changes from the Brevard County Vanpool Service. These changes are calculated
using the following formulas:
AVMTp = (ANETRPWP * DISTW) + (ANETRP^p * DIST^)
AVMTOP = (ANETRPWOP * DISTW) + (ANETRP^p * DIST^)
In the formulas, AVMTP is the change in peak-period VMT due to trip changes,
AVMTOP is the change in off-peak VMT due to trip changes, DISTW is the
average VMT per trip for work trips, and DIST^ is the average VMT per trip
for non-work trips. The other parameters in the formulas are defined in earlier
steps of the methodology.
DISTW is 50 miles per trip, as estimated by a vanpool service official. DIST^ is assumed
to be 8.1 miles, based on data from the 1996 Statistical Abstract of the United States.
Using the data above, AVMTP = (-458 * 50) + (8*8.1) = -22,835 and AVMTOP = (-305 * 50)
+ (20 * 8.1) = -15,088. Summarizing these results, the Brevard County Vanpool Service reduces peak-
period VMT by 22,835 miles per day due to trip changes and reduces off-peak VMT by 15,088 miles per
day due to trip changes.
Step 7 in the travel activity methodology involves estimating the VMT changes due to trip length
changes resulting from the Brevard County Vanpool Service. These changes are calculated using the
following formula:
AVMTLW = p * PT * -(DISTW - DISTnew)
AVMTUNW = p * PT * -(DIST^ - DISTnew)
In the formulas, AVMTL w is the change in VMT due to work trip length
changes, AVMTLjNW is the change in VMT due to non-work trip length changes,
P is fraction of program participants who change their trip length, and DISTnew
is the new work or non-work trip length. The other parameters in the formulas
are defined in earlier steps of the methodology.
For ridesharing, the TCM guidance indicates that p is equal to 1 - NOLD - NEW. As noted
in Step 2 above, NOLD and NEW are 0.864 and 0.086, respectively. Thus, p = 1 - 0.864 - 0.086 = 0.05.
DISTnew for work trips is assumed to be 5 miles. Because the Brevard County Vanpool Service
does not directly affect non-work trips, DISTnew for non-work trips is equal to DIST^.
Using the data above, AVMTL w = 0.05 * 968 * -(50 - 5) = -2,178, and AVMTLNW = 0.05 * 968
43
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* -(8.1 - 8.1) = 0. Summarizing these results, the Brevard County Vanpool Service reduces work-related
VMT by 2,178 miles per day due to trip length changes but does not reduce non-work VMT due to trip
length changes.
Step 8 in the travel activity methodology involves estimating the total peak and off-peak VMT
changes resulting from the Brevard County Vanpool Service. These changes are calculated using the
following formulas:
ANETVMTp = AVMTp + PKW * AVMTLW + PK^ * AVMTLNW
ANETVMTOP = AVMTOP + (1 - PKW) * AVMTL,W + (1 - PK^) * AVMTUNW
In the formulas, ANETVMTp is the total change in peak period VMT, and
ANETVMTOP is the total change in off-peak VMT. The other parameters in the
formulas are defined in earlier steps of the methodology.
Using the data above, ANETVMTp = -22,835 + 0.6 * -2,178 + 0.3 * 0 = -24,142 and
ANETVMTOP = -15,088 + (1 - 0.6) * -2,178 + (1 - 0.3) * 0 = -15,959. Summarizing these results,
the Brevard County Vanpool Service reduces peak-period VMT by a total of 24,142 miles per day
and off-peak VMT by a total of 15,959 miles per day.
Step 9 in the travel activity methodology involves estimating peak and off-peak speed changes
resulting from the Brevard County Vanpool Service. These changes are calculated using the following
formulas:
ASPDp = (ANETVMTp / TOTVMTP) * ep
ASPDOP = (ANETVMT0p/ TOTVMT0p) * eop
In the formulas, ASPDP is the percentage change in peak-period speeds, ASPDOP
is the change in off-peak speeds, TOTVMTP is total peak-period VMT for the
program area, TOTVMTOP is total off-peak VMT for the program area, ep is the
elasticity of peak-period speed with respect to volume, and eop is the elasticity
of off-peak speed with respect to volume. The other parameters in the formulas
are defined in earlier steps of the methodology.
Total VMT for Brevard County is assumed to be approximately 12 million miles per day.
This assumption is derived using data from the Texas Transportation Institute on VMT in the
nearby Orlando area. Assuming that 50 percent of travel activity occurs during peak periods and 50
percent occurs during off-peak periods, TOTVMTP and TOTVMTOP are each approximately 6 million
miles per day.
The parameter ep is assumed to be -0.75, based on an example provided in the TCM guidance
document. The parameter eop is assumed to be 0, because changes in off-peak VMT are not likely
to affect vehicle speeds (i.e., due to a lack of congestion).
Using the data above, ASPDP = -24,142 / 6,000,000 * -0.75 = 0.003 and ASPDOP = -15,959
/ 6,000,000 * 0 = 0. Summarizing these results, the Brevard County Vanpool Service increases
peak-period speeds by approximately 0.3% but has no effect on off-peak speeds.
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Phase 2: Emission Effects - STEP 1 (Trip
Changes)
Step 1 in the estimation of the emission
effects for the Brevard County Vanpool Service
involves calculating the effect of trip changes on
emissions. This step is broken down into seven
smaller steps (la through Ig), which are outlined
below.
Step la in the emission methodology
involves estimating the distribution of trip
changes for the Brevard County Vanpool
Service. These changes are calculated using the
following formulas:
YTRTP.LDGV = TRIPLDGV / (TRIP
LDGV
TRIP
LDGT1
)
YTRIP.LDGTI ~~ 1 " YTRTP.LDGV
In the formulas, YTRTP.LDGV
is the fraction of TCM-affected
trips taken by light-duty gasoline
vehicles (LDGVs), YTMP.LDGTI
is the fraction of TCM-affected
trips taken by light-duty gasoline
trucks (LDGTls), TRIPLDGV
is the fraction of total trips in
the region taken by LDGVs,
and TRIPLDGT1 is the fraction
of total trips in the region taken
by LDGTls. (Note: Most TCMs
affect only LDGVs or LDGTls.
equal to one.)
Phase 2: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
Step 4: Summation of emission effects
that can be analyzed using EPA's guidance document
Thus, the sum of YTRIP LDGV and YTRIPLDGTI is typically
TRIPLDGV and TRIPLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are based on the national average default values used in MOBILE.
Using the data above, YTRTP.LDGV = °-626 / (0.626 + 0.171) = 0.785 and YTRIP.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the trips affected by the Brevard County Vanpool Service
are taken by LDGVs, and 21.5% are taken by LDGTls.
Step Ib in the emission methodology involves calculating cold-start and hot-start trip changes
for the Brevard County Vanpool Service. These changes are calculated using the following formulas:
ATRIPSCST = YCST,W * (ANETRPW,P + ANETRPW,OP) + YCST,NW *
+ ANETRP^p)
ATRIPSHST = (1 - YCST,W) * (ANETRPWP + ANETRPW,OP) + (1 - YCST,NW)
ANETRP
NW.OP7
In the formulas, ATRIPSCST is the number of cold-start trip changes, ATRIPSHST
is the number of hot-start trip changes, YCST w is the fraction of work trips begun
in the cold-start mode, and YCST NW is the fraction of non-work trips begun in the
45
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cold-start mode. The other parameters in the formulas are defined in earlier
steps of the methodology.
Because work trips are mostly cold-start trips, the guidance calls for YCST.W to be set equal to 1 .
The guidance also suggests that YCST.NW be set equal to 0.43, which is the default fraction of cold starts
used in the Federal Test Procedure (FTP).
Using the data above, ATRIPSCST = 1 * (-458 + -305) + 0.43 * (8 + 20) = -751 and ATRIPSHST
= (1 - 1) * (-458 + -305) + (1 - 0.43) * (8 + 20) = 16. Summarizing these results, the Brevard County
Vanpool Service results in a reduction of 75 1 cold-start trips per day and an increase of 16 hot-start trips
per day.
Step Ic in the emission methodology involves determining cold-start and hot-start emission
factors. These changes are calculatedyfor a given pollutant and vehicle class using the following
formulas:
CS 1 (EXH100o/oCSTj26MPH
HS1
" kXH10oo/oSTB]26MPIl) 3.59
3.59
In the formulas, CST is the cold-start emission factor in grams per trip, HST
is the hot-start emission factor in grams per trip, and EXH is the MOBILE
emission factor in grams per mile. The 3.59 factor is the FTP driving cycle
trip-start miles per trip, and 26 miles per hour is the speed for the start portion
of the FTP driving cycle. (Note: The subscripts on EXH refer to the operating
conditions and speed at which MOBILE evaluates EXH. For example,
"100%CST,26MPH" indicates 100% cold-start operating mode at 26 miles
per hour vehicle speed.)
Using national default data from MOBILE, CSTLDGVHC = (2.55 - 0.95) * 3.59 = 5.74 grams per
trip, CSTLDGT1HC = (3.59 - 1.34) * 3.59 = 8.08 grams per trip, HSTLDGVHC = (1.35 - 0.95) * 3.59 = 1.44
grams per trip, and HSTLDGT1 HC = (1.99 - 1.34) * 3.59 = 2.33 grams per trip. (Following the same
methodology, the cold-start and hot-start emission factors can also be determined for NOx and CO.)
Step Id in the emission methodology involves determining cold-start and hot-start emission
changes for the Brevard County Vanpool Service. These changes are calculated using the following
formulas:
AHCCST = (ATRIPSCST * YTRTP,LDGV *
AHCHST = (ATRIPSHST * YTRTRLDGTI *
(ATRIPSCST YTRTP.LDGTI
(ATRIPSHST YTRIRLDGTI
ANOxCST = (ATRIPSCST * YTRTP,LDGV * CSTLDGV,NOx) + (ATRIPSCST * YTRIP.LDGTI :
ANOxHST = (ATRIPSHST * YTRTRLDGTI * HSTLDGvNOx) + (ATRIPSHST * YTRTRLDGTI
HC
NOx
ACOCST = (ATRIPSCST * YTRTP,LDGV *
ACOHST = (ATRIPSHST * YTRTRLDGTI *
(ATRIPSCST YTRTP.LDGTI
(ATRIPSHST YTRIRLDGTI
co
)
In the formulas, AHCCST, ANOxCST, and ACOCST are the changes in cold-start
emissions for HC, NOx, and CO, respectively; and AHCHST, ANOxHST, and
ACOHST are the changes in hot-start emissions for HC, NOx, and CO,
respectively. The other parameters in the formulas are defined in earlier steps of
the methodology.
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Using national default data from MOBILE, AHCCST = (-751 * 0.785 * 5.74) + (-751 * 0.215
* 8.08) = -4,689 and AHCHST = (16 * 0.785 * 1.44) + (16 * 0.215 * 2.33) = 26. Summarizing these
results, the Brevard County Vanpool Service results in a reduction in cold-start HC emissions of 4,689
grams per day and an increase in hot-start HC emissions of 26 grams per day. (Following the same
methodology, the cold-start and hot-start emission changes can also be determined for NOx and CO.)
Step le in the emission methodology involves determining hot soak emission changes for the
Brevard County Vanpool Service. These changes are calculated using the following formula:
AHCHSK = (ATRIPSTOTAL * YTRIP,LDGV * HSKLDGV) + (ATRIPSTOTAL * YTRIP,LDGTI * HSKLDGT1)
In the formula, AHCHSK is the change in hot soak emissions, ATRIPSTOTAL is the
total change in trips, and HSK is the hot soak emission factor in grams per trip.
(Note: Hot soak emissions are HC emissions only.)
ATRIPSTOTAL = ANETRPWP + ANETRPW)OP + ANETRP^p + ANETRP^p.
Thus, ATRIPSTOTAL = -458 + -305 + 8 + 20 = -735.
Using national default data from MOBILE, AHCHSK = (-735 * 0.785 * 3.06) + (-735 * 0.215
* 3.60) = -2,334. Summarizing this result, the Brevard County Vanpool Service results in a reduction
in hot soak emissions of 2,334 grams per day.
Step If in the emission methodology involves determining diurnal emission changes for the
Brevard County Vanpool Service. These changes are calculatedyfor a given vehicle class using the
following formulas:
AHCDNL w = 0.676 * (ANETRPWP + ANETRPWOP) / TPDW * yim, * (WDI - MDI)
AHCDNL^ = 0.676 * (ANETRP^p + ANETRP^p) / TPD^ * YTRff * (WDI - MDI)
AHCDNL = AHCDNL)WjLDGV + AHCDNLjNW)LDGV + AHCDNLjW)LDGT1 + AHCDNL)NWjLDGT1
In the formulas, AHCDNL w is the change in diurnal emissions associated with
work trips, AHCDNLNW is the change in diurnal emissions associated with non-
work trips, and AHCDNL is the total change in diurnal emissions. TPDW is the
number of work trips per day per vehicle, and TPD^ is the number of non-work
trips per day per vehicle. WDI is the weighted diurnal emission factor in grams,
and MDI is the multi-day diurnal emission factor in grams. The other parameters
in the formulas are defined in earlier steps of the methodology. (Note: Diurnal
emissions are HC emissions only.)
The value used for TPDW is 2, since a commuter makes typically makes two work trips per day
(i.e., one trip from home to work, one trip from work to home). TPD^ is equal to TGN from Step 3
of the "Travel Activity Effects" section above, and thus equals 2.
Using national default data from MOBILE, AHCDNL WLDGV = 0.676 * (-458 + -305) / 2 * 0.785
* (3.30 - 6.04) = 555, AHCDNLNWLDGV = 0.676 * (8 + 20) / 2 * 0.785 * (3.30 - 6.04) = -20, AHCDNL WLDGT1
= 0.676* (-458+ -305)72*0.215 *(5.11 - 15.33) = 567, AHCDNLNWLDGT1 = 0.676 * (8 + 20) / 2 * 0.215
* (5.11 - 15.33) = -21, and AHCDNL = 555 + -20 + 567 + -21 = 1,081. Summarizing these results, the
Brevard County Vanpool Service results in an increase in diurnal emissions of 1,081 grams per day.
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Step Ig in the emission methodology involves calculating the total trip-related emission changes
for the Brevard County Vanpool Service. These changes are calculated using the following formulas:
AHCTRff = AHCCST + AHCHST + AHCHSK + AHCDNL
ANOxTRIP = ANOxCST + ANOxHST
ACOTRff = ACOCST + ACOHST
In the formulas, AHCTRIP, ANOxTRIP, and ACOTRIP are the total changes in HC,
NOx, and CO emissions, respectively, due to trip changes.
Using the data above, AHCTRIP = -4,689 + 26 + -2,334 + 1,081 = -5,916. Summarizing this result,
the Brevard County Vanpool Service results in a net decrease in trip-related HC emissions of 5,916
grams per day. (Following the same methodology, total trip-related emission changes can also be
determined for NOx and CO.)
Emission Effects - STEP 2 (VMT Changes')
Step 2 in the estimation of the emission effects for the Brevard County Vanpool Service involves
calculating the effect of VMT changes on emissions. This step is broken down into four smaller steps
(2a through 2d), which are outlined below.
Step 2a in the emission methodology involves estimating the distribution of VMT changes for
the Brevard County Vanpool Service. These changes are calculated using the following formulas:
YVMT,LDGV = VMTLDGV / (VMTLDGV + VMTLDGT1)
YvMT.LDGTl = 1 " YvMT.LDGV
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In the formulas, YVMT.LDGV is the fraction of TCM-affected VMT for light-duty
gasoline vehicles (LDGVs), YTRIPLDGTI is the fraction of TCM-affected VMT
for light-duty gasoline trucks (LDGTls), VMTLDGV is the fraction of total VMT
in the region for LDGVs, and VMTLDGT1 is the fraction of total VMT in the
region for LDGTls. (Note: Most TCMs that can be analyzed using EPA's
guidance document affect only LDGVs or LDGTls. Thus, the sum of YVMT.LDGV
and YVMT.LDGTI is typically equal to one.)
VMTLDGV and VMTLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are the national average default values used in MOBILE for VMT mix.
Using the data above, YVMT.LDGV = °-626 / (°-626 + °-171) = °-785 and YVMT.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the VMT affected by the Brevard County Vanpool Service
is by LDGVs, and 21.5% is by LDGTls.
Step 2b in the emission methodology involves estimating hot-stabilized exhaust emission
changes for the Brevard County Vanpool Service. These changes are calculated using the following
formulas:
, = (ANETVMTP * YVMT,LDGV * STBLDGV3QP) + (ANETVMTP * YVMT.LDGTI * STBLDGT13QP)
AHCsmoP = (ANETVMTOP * YVMT,LDGV * STBLDGV3QOP) + (ANETVMTOP * YVMT.LDGTI * STBLDGT13QOP)
ANOxsmP = (ANETVMTP * YVMT,LDGV * STBLDGV,NOx,P) + (ANETVMTP * YVMT,LDGTI * STBLDGT1,NOx,P)
ANOxsmop = (ANETVMTOP * YVMT,LDGV * STBLDGV,NOx,OP) + (ANETVMTOP * YVMT.LDGTI *
x,op)
ACOSTBJ, = (ANETVMTP * YVMT,LDGV * STBLDGVmP) + (ANETVMTP * YVMT,LDGTI * STBLDGTUCOJ))
ACOSTBiOP = (ANETVMTOP * YVMT.LDGV * STBLDGVjCO)OP) + (ANETVMTOP * YVMT.LDGTI * STBLDGT1]CO)OP)
In the formulas, AHCSTB P, ANOxSTB P, and ACOSTB P are the peak-period changes
in hot-stabilized emissions for HC, NOx, and CO, respectively; and AHCSTB OP,
ANOxSTBOP, and ACOSTBOP are the off-peak changes in hot-stabilized emissions
for HC, NOx, and CO, respectively. STBP is the hot-stabilized emission factor
(in grams per mile) for each pollutant and vehicle class for the peak period
(during which average vehicle speed is assumed to be 20 miles per hour),
and STBOP is the hot-stabilized emission factor (in grams per mile) for each
pollutant and vehicle class for the off-peak period (during which average vehicle
speed is assumed to be 35 miles per hour). The other parameters in the formulas
are defined in earlier steps of the methodology.
Using national default data from MOBILE, AHCSTBP = (-24,142 * 0.785 * 1.23) + (-24,142
* 0.215 * 1. 77) = -32,498 and AHCSTB op = (-15,959* 0.785'* 0.69) + (-15,959 * 0.215 * 0.94) = -11,870.
Summarizing these results, the Brevard County Vanpool Service results in a reduction in peak-period
hot-stabilized HC exhaust emissions of 32,498 grams per day and a reduction in off-peak hot-stabilized
HC exhaust emissions of 1 1,870 grams per day. (Following the same methodology, hot-stabilized
exhaust emission changes can also be determined for NOx and CO.)
Step 2c in the emission methodology involves estimating VMT-related evaporative emission
changes for the Brevard County Vanpool Service. These changes are calculated using the following
formulas:
= (ANETVMTp * YVMT,LDGV * VEVPLDGV,P) + (ANETVMTp * YVMT.LDGTI * VEVPLDGT1,P)
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AHCVEVP.OP = (ANETVMTOP * YVMT,LDGV * VEVPLDGV,OP) + (ANETVMTOP * YVMI,LDGTI * VEVPLDGT1,OP)
In the formulas, AHCygypj is the change in peak-period evaporative emissions,
AHCvEvp OP is the change in off-peak evaporative emissions, and VEVP is the
VMT-related evaporative emission factor (in grams per mile) for each vehicle
class and time period (peak or off-peak). The other parameters in the formulas
are defined in earlier steps of the methodology. (Note: Evaporative emissions
are HC emissions only.)
Using national default data from MOBILE, AHC^p = (-24,142 * 0.785 * 0.44) + (-24,142
* 0.215 * 0.53) = -1 1,090 and AHC^y^ = (-15,959 * 0.785'* 0.34) + (-15,959 * 0.215 * 0.44) = -5,769.
Summarizing these results, the Brevard County Vanpool Service results in a reduction in peak-period
evaporative emissions of 1 1,090 grams per day and a reduction in off-peak evaporative emissions of
5,769 grams per day.
Step 2d in the emission methodology involves calculating the total VMT-related emission
changes for the Brevard County Vanpool Service. These changes are calculated using the following
formulas:
AHCSTBjP + AHCSTBjOp
= ANOxSTB)P + ANOxSTB)OP
= ACOSTB)P + ACOSTB)OP
In the formulas, AHCy^, ANOxy^, and ACOy^ are the total changes in HC,
NOx, and CO emissions, respectively, due to VMT changes.
Using the data above, AHC^ = -32,498 + -1 1,870 + -1 1,090 + -5,769 = -61,227. Summarizing
this result, the Brevard County Vanpool Service results in a net decrease in VMT-related HC emissions
of 61,227 grams per day. (Following the same methodology, total VMT-related emission changes can
also be determined for NOx and CO.)
Emission Effects - STEP 3 (Speed Changes)
Step 3 in the estimation of the emission effects for the Brevard County Vanpool Service involves
calculating the effect of speed changes on emissions. This step is broken down into four smaller steps
(3a through 3d), which are outlined below.
Step 3a in the emission methodology involves estimating the speeds associated with the Brevard
County Vanpool Service. These speeds are calculated using the following formulas:
SPEEDPTCM = SPEEDPBASE * (1 + ASPDP)
SPEEDOPJCM = SPEEDOP3ASE * (1 + ASPDOP)
In the formulas, SPEEDPTCM is the peak-period speed after implementation of the
TCM, SPEEDOPTCM is the off-peak speed after implementation of the TCM,
SPEEDPBASE is the peak-period speed prior to implementation of the TCM, and
SPEEDOPBASE is the off-peak speed prior to implementation of the TCM. The
other parameters in the formulas are defined in earlier steps of the methodology.
Based on data for the national default fleet, SPEEDPBASE is assumed to be 20 miles per hour,
and SPEEDOPBASE is assumed to be 35 miles per hour. (Note: These default assumptions for speeds
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are likely to be unrealistic for Brevard County. The analysis might be similar, however, if more realistic
values were used.)
Using the data above, SPEEDPTCM = 20 * (1 + 0.003) = 20.06 and SPEEDOPTCM = 35 * (1 + 0)
= 35. Summarizing these results, peak-period speeds have slightly increased from 20 miles per hour
to 20.06 miles per hour due to the Brevard County Vanpool Service. Off-peak speeds have not changed
due to the service.
Step 3b in the emission methodology involves estimating the total VMT for the program area
after implementation of the Brevard County Vanpool Service. These VMT figures are calculated using
the following formulas:
VMTp TCM = TOTVMTp + ANETVMTP
VMTOPJCM = TOTVMT0p + ANETVMTOP
In the formulas, VMTP TCM is the total peak-period VMT in the program area
after implementation of the TCM, and VMTOPTCM is the total off-peak VMT
in the program area after implementation of the TCM. The other parameters
in the formulas are defined in earlier steps of the methodology.
Using data from Step 9 of the "Travel Activity Effects" section above, VMTPTCM = 6,000,000
+ -24,142 = 5,975,858 and VMTOPTCM = 6,000,000 + -15,959 = 5,984,041. Summarizing these results,
peak-period VMT has decreased from 6,000,000 miles per day to 5,975,858 miles per day due
to the Brevard County Vanpool Service. Off-peak VMT has decreased from 6,000,000 miles per day
to 5,984,041 miles per day due to the service.
Step 3c in the emission methodology involves estimating peak-period and off-peak emission
changes due to changes in vehicle speeds. These changes are calculated using the following formulas:
AHCSPDjP = VMTPJCM * (STBFLT)HQPJCM + RNLFLTjPJCM) - VMTPJCM * (STBFLT)HQP3ASE + RNLFLTjP3ASE)
AHCSPD)Op ~~ V MTOpjTcM (STBFLTjHCjOPjTCM + RNLFLT)0pjTCM) " MTOPjTCM (STBFLTjHC)OP)BASE
FLTjNOX)P)BASE)
ANOxSPD)p = VMTPjCM (STBFLTjNOX)PjCM - STB
ACOSPDjP = VMTPjTCM (STBFLT)COjPjCM - STBFLT)CO)P)BASE)
ACOSPD op = VMTOPTcM (kTBp-LT co OPJCM - STBFLT co OPBASE)
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In the formulas, AHCSPDP, ANOxSPDP, and ACOSPDP are the peak-period changes
in emissions for HC, NOx, and CO, respectively, due to a change in speeds; and
AHCSPD op, ANOxSEDj0p, and ACOSPDj0p are the off-peak changes in emissions for
HC, NOx, and CO, respectively, due to a change in speeds. STBFLT is the fleet-
wide hot-stabilized emission factor (in grams per mile) for each pollutant, time
period (i.e., peak or off-peak), and scenario (i.e., base or TCM). RNLpLT is the
fleet-wide running loss emission factor (in grams per mile) for each time period
and scenario. The other parameters in the formulas are defined in earlier steps
of the methodology.
Based on data showing the relationship between vehicle speed and emissions, this analysis
assumes that the elasticity of STBFLT with respect to speed is -1 for HC, 0 for NOx, and -1 for CO.
Thus, a 1% increase in speed is assumed to result in a 1% decrease in HC and CO emissions (on a grams
per mile basis) and no change in NOx emissions. The elasticity of RNLFLT with respect to speed is also
assumed to be -1.
Using national default data from MOBILE, AHCSPDP = 5,975,858 * (1.671 + 0.21 1) - 5,975,858
* (1.676 + 0.212) = -35,855 and AHCSPDOP = 5,984,041 * (L938 + 0.120) -5,984,041 * (1.938 + 0.120)
= 0. Summarizing these results, the Brevard County Vanpool Service results in a decrease in speed-
related HC emissions of 35,855 grams per day for the peak period but does not change speed-related HC
emissions for the off-peak period. (Following the same methodology, the peak-period and off-peak
emission changes due to changes in speeds can also be determined for NOx and CO.)
Step 3d in the emission methodology involves calculating the total speed-related emission
changes for the Brevard County Vanpool Service. These changes are calculated using the following
formulas:
AriCSPD AriCSPDjP + AriCSPD)OP
ANOxSPD = ANOxSPD)P + ANOxSPD)OP
ACOSPD ACOSPDjP + ACOSPD)OP
In the formulas, AHCSPD, ANOxSPD, and ACOSPD are the total changes in HC,
NOx, and CO emissions, respectively, due to speed changes.
Using the data above, AHCSPD = -35,855 + 0 = -35,855. Summarizing this result, the Brevard
County Vanpool Service results in a net decrease in speed-related HC emissions of 35,855 grams per day.
(Following the same methodology, total speed-related emission changes can also be determined for NOx
and CO.)
Emission Effects - STEP 4 (Total)
Step 4 in the estimation of the emission effects for the Brevard County Vanpool Service involves
calculating the total changes in HC, NOx, and CO emissions. These changes are calculated using the
following formulas:
AHC = AHCTRff + AHCvMT + AHCSPD
ANOx = ANOxTRIP + ANOxvMj + ANOxSPD
AGO = ACOTRff + ACOvMT + ACOSPD
In the formulas, AHC, ANOx, and AGO are the total changes in HC, NOx, and
CO emissions, respectively, due to the TCM program.
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Using the data above, ARC = -5,916 + -61,227 + -35,855 = -102,998. Summarizing this result,
the Brevard County Vanpool Service results in a net decrease in HC emissions of 102,998 grams per day,
or approximately 0.11 tons per day. (Following the same methodology, total emission changes can also
be determined for NOx and CO.)
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Example 5: Boulder HOP Shuttle Service
General Description
In 1989, transportation planners in Boulder, Colorado designed the HOP shuttle service in
response to commercial growth and the influx of traffic associated with the expansion. The goal of the
program was to provide an alternative to SOV driving, and therefore preserve the quality of the air and
prevent the construction of new roadways. The service was called the "HOP" because the name indicates
the ease with which a passenger may "hop" around Boulder to meetings, school, shopping centers, etc.
The service consists of six medium-size buses that circulate in two directions on a loop connecting the
University of Colorado campus and retail district with downtown employment and retail areas and the
Crossroads Mall area.
(Note: This analysis excludes the extra trips caused by the HOP shuttle buses themselves. Thus, the net
effects on trips, VMT, speeds, and emissions will be smaller than shown here.)
Data Sources
Interview with Penny Puskarich, Program Administrator, City of Boulder/Go Boulder, March 8,
1997.
"HOP Shuttle Service Profile," prepared by City of Boulder, Colorado, June 25, 1996.
1990 U.S. Census data.
1996 Statistical Abstract of the United States.
Phase 1: Travel Activity Effects
Step 1 in the estimation of travel activity
effects for the HOP service involves an
assessment of the potential trip effects from the
program. For this TCM, these potential effects
are calculated using the following user-defined
formula:
PT = N
In the formula,
PT is the potential effect
on trips per day,
and N is the number
of TCM participants.
Phase 1: Effects on Travel Activity
Step 1: Potential trip effects
Step 2: Direct work and non-work trip reductions
Step 3: Indirect work and non-work trip increases
Step 4: Peak and off-peak trip shifts
Step 5: Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Step 6: Peak and off-peak VMT changes due to
reduced number of trips
Step 7: VMT changes due to reduced trip lengths
Step 8: Net VMT changes
Step 9: Peak and off-peak speed changes
The appropriate value of N is derived by dividing the number of people who use the HOP shuttle
service each year by 307, the number of days per year the HOP Shuttle Service operates (it does not
operate on Sundays and holidays). According to the "HOP Shuttle Service Profile," approximately
1.1 million riders used the service in 1996. Thus,PT = N= 1,100,000/307 = 3,583. Summarizing
this result, the potential number of trips reduced per day by the HOP service is 3,583.
Step 2 in the travel activity methodology involves estimating the direct work and non-work trip
reductions from the HOP service. Whereas the potential trip reductions calculated in Step 1 represent
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the total number of trips that might be reduced by a TCM program, direct trip reductions measure the
number of trips that actually are reduced and, thus, can be less than potential trip reductions (e.g., if
a HOP rider was previously walking to his or her HOP destination). Direct trip reductions are calculated
using the following formulas:
ATRIPSD = a * PT
ATRIPSDW= (o * ATRIPSD
ATRIPSDNW = (1 - w) * ATRIPSD
In the formulas, ATRIPSD is the total direct trip reduction, PT is (as above)
the potential trip reductions, ATRIPSD w is the direct work trip reduction,
ATRIPSDNW is the direct non-work trip reduction, a is the fraction of program
participants who make a direct trip change, and co is the fraction of trip effects
that are work-related.
For transit improvements, a is defined as -1 / AVO, where AVO is average vehicle occupancy.
Assuming average vehicle occupancy for non-work trips is the same as work trips, the value used for
AVO is based on the following information from 1990 U.S. Census data for the City of Boulder:
approximately 65% of work trips are in single occupancy vehicles (SOVs) (AVO = 1), approximately
10% of work trips are in carpools (AVO = 2.3), 11% of work trips are walking, 6% use buses (AVO
assumed to be 15), and less than 8% of work trips are made using other means. Thus, AVO = (0.65
+ 0.1 + 0.11 + 0.06 + 0.08 ) / [(0.65 / 1) + (0.1 / 2.3) + (0.06 / 15)] = 1.43. Using this value for AVO,
a = -1/1.43 = -0.7.
Based on survey results from the "HOP Shuttle Service Profile," approximately 20% of HOP
riders use the service for work travel. Thus, the parameter co is equal to 0.2.
Using the data above, ATRIPSD = -0.7 * 3,583 = -2,508, ATRIPSD w = 0.2 * -2,508 = -502,
and ATRIPSDNW = (1 - 0.2) * -2,508 = -2,006. Summarizing these results, the HOP service is responsible
for directly reducing 502 work trips per day and 2,006 non-work trips per day.
Step 3 in the travel activity methodology involves estimating the actual indirect trip increases
(for both work and non-work trips) from the HOP service. Indirect trip increases are secondary effects
that typically result when vehicles normally used for commuting are left at home. These increases are
calculated using the following formulas:
ATRIPSIW = INCWH * -ATRIPSD / 2
ATRIPSINW = INCNH * -ATRIPSD / 2
In the formulas, ATRIPS: w is the indirect work trip increase, ATRIPSINW is the
indirect non-work trip increase, and INCWH and INCNH are the rates of increased
SOV work and non-work trip making by household members of TCM
participants who leave their vehicles at home. The other parameter in the
formulas is defined in an earlier step of the methodology.
INCWH is defined as NV * SHR * (SIZE - 1) * BMP * TGW, where NV is the fraction of the
population that does not own a vehicle (Note: This analysis interprets this parameter to mean the
percentage of drivers without a vehicle, which is estimated as the percentage of vehicle-owning
households in the program area that have only one vehicle.), SHR is the fraction of shared mode trips,
SIZE is average household size, BMP is the fraction of the population that is employed, and TGw is the
work trip generation rate for SOV users. Based on 1990 U.S. Census data for the City of Boulder, NV
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is assumed to be 34%, SHR is assumed to be 16%, SIZE is assumed to be 2.45, and BMP is assumed to
be 70%. TGW is assumed to equal 2. Based on these numbers, INCWH = 0.34 * 0 .16 * (2.45 - 1) * 0.7
*2 = 0.11.
INCNH = NV * SHR * (SIZE - 1) * UNEMP * TGN, where NV, SHR, and SIZE are as defined
above, UNEMP is the fraction of the population that is not employed, and TGN is the non-work trip
generation rate for SOV users. UNEMP is simply (1 - EMP) and thus equals 30%. TGN is assumed to
be the same as TGW (i.e., 2). Based on these numbers, INCNH = 0.34 * 0.16 * (2.45 - 1) * 0.3 * 2 = 0.05.
Using the data above, ATRIPSIW = 0.11* -(-2,508) / 2 = 138, and ATRIPSINW = 0.05 * -(-2,508)
/ 2 = 63. Summarizing these results, the HOP service is indirectly responsible for an increase of 138
work trips per day and 63 non-work trips per day.
Step 4 in EPA's methodology for estimating travel activity effects of TCMs, which involves
determining direct peak and off-peak period trip shifts, does not apply to transit improvements.
Thus, Step 4 is not relevant to the analysis of the HOP service.
Step 5 in the travel activity methodology involves estimating the net trip changes from the HOP
service as distributed between work and non-work trips and peak and off-peak periods. These changes
are calculated using the following formulas:
ANETRPWP = (o * ATRIPSSp + PKW * (ATRIPSDW + ATRIPSIW)
ANETRPWOP = (o * ATRIPSSOP + (1 - PKW) * (ATRIPSDW + ATRIPSIW)
ANETRP^p = (!-«)* ATRIPSSP + PK^ * (ATRIPSDNW + ATRIPSINW)
= (!-«)* ATRIPSSOP + (1 - PK^) * (ATRIPSUNW + ATRIPSINW)
In the formulas, ANETRPWP is the net work trip change in the peak period,
ANETRPW op is net work trip change in the off-peak period, ANETRP^p
is the net non-work trip change in the peak period, and ANETRP^ >OP is the net
non-work trip change in the off-peak period. ATRIPSSP is the change in peak
period trips, and ATRIPSS OP is the change in off-peak period trips. PKW is the
observed fraction of work trips during the peak period, and PK^ is the observed
fraction of non-work trips during the peak period. The other parameters in the
formulas are defined in earlier steps of the methodology.
Because there are no trip shifts associated with transit improvements (see Step 4), ATRIPSSP
and ATRIPSSOp are each equal to 0.
The values used for PKW and PK^ are 0.6 and 0.3, respectively, based on an example shown
in the TCM guidance document.
Using the data above, ANETRPWP = 0 + 0.6 * (-502 + 138) = -218, ANETRPWOP = 0 + (1 - 0.6)
* (-502 + 138) = -146, ANETRPWP = 0 + 0.3 * (-2,006 + 63) = -583, and ANETIUV.op = 0 * (1 - 0.3)
* (-2,006 + 63) = -1,360. Summarizing these results, the HOP service results in net decreases in peak
and off-peak work trips of 218 per day and 146 per day, respectively. The service also results
in decreases in peak and off-peak non-work trips of 583 per day and 1,360 per day, respectively.
Step 6 in the travel activity methodology involves estimating the peak and off-peak VMT
changes due to the trip changes from the HOP service. These changes are calculated using the following
formulas:
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AVMTp = (ANETRPWP * DISTW) + (ANETPJVp
AVMTOP = (ANETRPWOP * DISTW) + (ANETPJVOP * DIST^)
In the formulas, AVMTP is the change in peak-period VMT due to trip changes,
AVMTOP is the change in off-peak VMT due to trip changes, DISTW is the
average VMT per trip for work trips, and DIST^ is the average VMT per trip
for non-work trips. The other parameters in the formulas are defined in earlier
steps of the methodology.
The total length of the Hop Shuttle Service route is six miles. The average trip, according
to Go Boulder officials is two miles. Hence, both DISTW and DIST^ are assumed to be 2 miles.
Using the data above, AVMTP = (-218 * 2) + (-583 * 2) = -1,602 and AVMTOP = (-146 * 2)
+ (-1,360 * 2) = -3,012. Summarizing these results, the HOP service reduces peak-period VMT by 1,602
miles per day due to trip changes and reduces off-peak VMT by 3,012 miles per day due to trip changes.
Step 7 in the travel activity methodology involves estimating the VMT changes due to trip length
changes resulting from the HOP service. These changes are calculated using the following formulas:
AVMTLW = p * PT * -(DISTW - DISTnew)
AVMTUNW = p * PT * -(DIST^ - DISTnew)
In the formulas, AVMTL w is the change in VMT due to work trip length
changes, AVMTLjNW is the change in VMT due to non-work trip length changes,
P is fraction of program participants who change their trip length, and DISTnew
is the new work or non-work trip length. The other parameters in the formulas
are defined in earlier steps of the methodology.
Although it is conceivable that people may drive to a HOP stop to access the shuttle, this analysis
assumes that no HOP users do so. Thus, both p and DISTnew are set equal to 0.
Using the data above, AVMTL w = 0 * 3,583 * -(2 - 0) = 0, and AVMTLNW = 0 * 3,583 * -(2 - 0)
= 0. Summarizing these results, the HOP service does not reduce VMT through changes in trip lengths.
Step 8 in the travel activity methodology involves estimating the total peak and off-peak VMT
changes resulting from the HOP service. These changes are calculated using the following formulas:
ANETVMTp = AVMTp + PKW * AVMTLW + PK^ * AVMTLNW
ANETVMT0p = AVMTOP + (1 - PKW) * AVMTL>W + (1 - PK^) * AVMTL>NW
In the formulas, ANETVMTp is the total change in peak period VMT, and
ANETVMTOP is the total change in off-peak VMT. The other parameters in the
formulas are defined in earlier steps of the methodology.
Using the data above, ANETVMTp = -1,602 + 0.6*0 + 0.3*0 = -1,602 and ANETVMTOP
= -3,012 + (1 - 0.6) * 0 + (1 - 0.3) * 0 = -3,012. Summarizing these results, the HOP service reduces
peak-period VMT by atotal of 1,602 miles per day and off-peak VMT by atotal of 3,012 miles per day.
Step 9 in the travel activity methodology involves estimating peak and off-peak speed changes
resulting from the HOP service. These changes are calculated using the following formulas:
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ASPDp = (ANETVMTp / TOTVMTP) * ep
ASPDOP = (ANETVMT0p/ TOTVMTop) * eop
In the formulas, ASPDP is the percentage change in peak-period speeds, ASPDOP
is the change in off-peak speeds, TOTVMTP is total peak-period VMT for the
program area, TOTVMTOP is total off-peak VMT for the program area, ep is the
elasticity of peak-period speed with respect to volume, and eop is the elasticity of
off-peak speed with respect to volume. The other parameters in the formulas are
defined in earlier steps of the methodology.
Total VMT for the City of Boulder is assumed to be approximately 2 million miles per day.
This assumption is derived using data from the Texas Transportation Institute on VMT in the nearby
Denver area. Assuming that 50 percent of travel activity occurs during peak periods and 50 percent
occurs during off-peak periods, TOTVMTP and TOTVMTOP are each approximately 1 million miles
per day.
The parameter ep is assumed to be -0.75, based on an example provided in the TCM guidance
document. The parameter eop is assumed to be 0, because changes in off-peak VMT are not likely
to affect vehicle speeds (i.e., due to a lack of congestion).
Using the data above, ASPDP = -1,602 /1,000,000 * -0.75 = 0.001 and ASPDOP = -3,012
71,000,000 * 0 = 0. Summarizing these results, the HOP service increases peak-period speeds
by approximately 0.1% but has no effect on off-peak speeds.
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Phase 2: Emission Effects - STEP 1 (Trip Changes')
Step 1 in the estimation of the emission
effects for the HOP service involves calculating
the effect of trip changes on emissions. This step
is broken down into seven smaller steps
(la through Ig), which are outlined below.
Step la in the emission methodology
involves estimating the distribution of trip
changes for the HOP service. These changes
are calculated using the following formulas:
YTRTP.LDGV =
' (TRIP
LDGV
TR1P
LDGT1
YTRTP.LDGTI ~~ 1 " YTRIP.LDGV
Phase 2: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
Step 4: Summation of emission effects
In the formulas, YTRIP.LDGV
is the fraction of TCM-affected
trips taken by light-duty gasoline
vehicles (LDGVs), YTMP.LDGTI
is the fraction of TCM-affected
trips taken by light-duty gasoline
trucks (LDGTls), TRIPLDGV
is the fraction of total trips in
the region taken by LDGVs,
and TRIPLDGT1 is the fraction
of total trips in the region taken
by LDGTls. (Note: Most TCMs
that can be analyzed using EPA's
guidance document affect only
LDGVs or LDGTls. Thus, the ^^^^^^^^^^^^^^^^^^^^^
sum of YTRIP.LDGV and YTRTP.LDGTI
is typically equal to one.)
TRIPLDGV and TRIPLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are based on the national average default values used in MOBILE.
Using the data above, YTRTP.LDGV = °-626 / (0.626 + 0.171) = 0.785 and YTRIP.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the trips affected by the HOP service are taken by LDGVs,
and 21.5% are taken by LDGTls.
Step Ib in the emission methodology involves calculating cold-start and hot-start trip changes
for the HOP service. These changes are calculated using the following formulas:
ATRIPSCST = YCST,W * (ANETRPW,P + ANETRPW,OP) + YCST,NW *
+ ANETRP^p)
ATRIPSHST = (1 - YCST,W) * (ANETRPWP + ANETRPW,OP) + (1 - YCST,NW)
ANETRP
NW.OP7
In the formulas, ATRIPSCST is the number of cold-start trip changes, ATRIPSHST
is the number of hot-start trip changes, YCST w is the fraction of work trips begun
in the cold-start mode, and YCST NW is the fraction of non-work trips begun in the
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cold-start mode. The other parameters in the formulas are defined in earlier
steps of the methodology.
Because work trips are mostly cold-start trips, the guidance calls for YCST.W to be set equal to 1.
The guidance also suggests that YCST.NW be set equal to 0.43, which is the default fraction of cold starts
used in the Federal Test Procedure (FTP).
Using the data above, ATRIPSCST = 1 * (-218 + -146) + 0.43 * (-583 + -1,360) = -1,200 and
ATRIPSHST = (1 - 1) * (-218 + -146) + (1 - 0.43) * (-583 + -1,360) = -1,108. Summarizing these results,
the HOP service results in a reduction of 1,200 cold-start trips per day and a reduction of 1,108 hot-start
trips per day.
Step Ic in the emission methodology involves determining cold-start and hot-start emission
factors. These changes are calculatedyfor a given pollutant and vehicle class using the following
formulas:
CSI (EXH100o/oCSTj26MPH " kXH10oo/oSTB]26MPIl) 3.59
HSI (-bAHo " kXHo) 3.59
In the formulas, CST is the cold-start emission factor in grams per trip, HST
is the hot-start emission factor in grams per trip, and EXH is the MOBILE
emission factor in grams per mile. The 3.59 factor is the FTP driving cycle
trip-start miles per trip, and 26 miles per hour is the speed for the start portion
of the FTP driving cycle. (Note: The subscripts on EXH refer to the operating
conditions and speed at which MOBILE evaluates EXH. For example,
"100%CST,26MPH" indicates 100% cold-start operating mode at 26 miles
per hour vehicle speed. While "100%STB,26MPH" indicates 100% hot- or
cold-stabilized operating mode at 26 mph vehicle speed.)
Using national default data from MOBILE, CSTLDGVHC = (2.55 - 0.95) * 3.59 = 5.74 grams per
trip, CSTLDGT1HC = (3.59 - 1.34) * 3.59 = 8.08 grams per trip, HSTLDGVHC = (1.35 - 0.95) * 3.59 = 1.44
grams per trip, and HSTLDGT1 HC = (1.99 - 1.34) * 3.59 = 2.33 grams per trip. (Following the same
methodology, the cold-start and hot-start emission factors can also be determined for NOx and CO.)
Step Id in the emission methodology involves determining cold-start and hot-start emission
changes for the HOP service. These changes are calculated using the following formulas:
AHCCST (AlJvlPbCST YTRTP.LDGV CblLDGVjHC) ~*~ (AllvLPbCST YTRTP.LDGTI
AHCHST = (ATRIPSHST * YTRTP.LDGTI * HSTLDGVHC) + (ATRIPSHST * YTRIRLDGTI * IIJILDGTI,HC;
ANOxCST = (ATRIPSCST * YTRTP,LDGV * CSTLDGV,NOx) + (ATRIPSCST * YTRIP.LDGTI :
ANOxHST = (ATRIPSHST * YTRTP.LDGTI * HSTLDGVNOx) + (ATRIPSHST * YTRTP.LDGTI " IIJILDGTI,NOX;
ACOCST = (ATRIPSCST * YTRTP,LDGV * CSTLDGV,CO) + (ATRIPSCST * YTRTP,LDGTI *
ACOHST = (ATRIPSHST * YTRTP.LDGTI * HSTLDGVCO) + (ATRIPSHST * YTRIRLDGTI * IIJILDGTI,CO;
In the formulas, AHCCST, ANOxCST, and ACOCST are the changes in cold-start
emissions for HC, NOx, and CO, respectively; and AHCHST, ANOxHST,
and ACOHST are the changes in hot-start emissions for HC, NOx, and CO,
respectively. The other parameters in the formulas are defined in earlier steps
of the methodology.
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Using national default data from MOBILE, AHCCST = (-1,200 * 0.785 * 5.74) + (-1,200 * 0.215
* 8.08) = -7,492 and AHCHST = (-1,108 * 0.785 * 1.44) + (-1,108 * 0.215 * 2.33) = -1,808. Summarizing
these results, the HOP service results in a reduction in cold-start HC emissions of 7,492 grams per day
and a reduction in hot-start HC emissions of 1,808 grams per day. (Following the same methodology,
the cold-start and hot-start emission changes can also be determined for NOx and CO.)
Step le in the emission methodology involves determining hot soak emission changes for the
HOP service. These changes are calculated using the following formula:
AHCHSK = (ATRIPSTOTAL * YTRIP,LDGV * HSKLDGV) + (ATRIPSTOTAL * YTRIP,LDGTI * HSKLDGT1)
In the formula, AHCHSK is the change in hot soak emissions, ATRIPSTOTAL is the
total change in trips, and HSK is the hot soak emission factor in grams per trip.
(Note: Hot soak emissions are HC emissions only.)
ATRIPSTOTAL = ANETRPWP + ANETRPWOP + ANETRP^p + ANETRP^p.
Thus, ATRIPSTOTAL = -218 + -146 + -583 + -1,360 = -2,307.
Using national default data from MOBILE, AHCHSK = (-2,307 * 0.785 * 3.06) + (-2,307 * 0.215
* 3.60) = -7,327. Summarizing this result, the HOP service results in a reduction in hot soak emissions
of 7,327 grams per day.
Step If in the emission methodology involves determining diurnal emission changes for the HOP
service. These changes are calculatedyfor a given vehicle class using the following formulas:
AHCDNL w = 0.676 * (ANETRPWP + ANETRPWOP) / TPDW * yim, * (WDI - MDI)
AHCDNL^ = 0.676 * (ANETRP^p + ANETRP^p) / TPD^ * YTRff * (WDI - MDI)
AHCDNL = AHCDNL)WjLDGV + AHCDNLjNW)LDGV + AHCDNL>W)LDGT1 + AHCDNL)NWjLDGT1
In the formulas, AHCDNL w is the change in diurnal emissions associated with
work trips, AHCDNLNW is the change in diurnal emissions associated with
non-work trips, and AHCDNL is the total change in diurnal emissions. TPDW
is the number of work trips per day per vehicle, and TPD^ is the number of
non-work trips per day per vehicle. WDI is the weighted diurnal emission factor
in grams, and MDI is the multi-day diurnal emission factor in grams. The other
parameters in the formulas are defined in earlier steps of the methodology.
(Note: Diurnal emissions are HC emissions only.)
The value used for TPDW is 2, since a commuter typically makes two work trips per day
(i.e., one trip from home to work, one trip from work to home). TPD^ is equal to TGN from Step 3
of the "Travel Activity Effects" section above, and thus equals 2.
Using national default data from MOBILE, AHCDNL WLDGV = 0.676 * (-218 + -146) / 2 * 0.785
* (3.30 - 6.04) = 265, AHCDNLNWLDGV = 0.676 * (-583 + -1,360) / 2 * 0.785 * (3.30 - 6.04) = 1,413,
AHCDNLWLDGT1 = 0.676 * (-218 + -146) / 2 * 0.215 * (5.11 - 15.33) = 270, AHCDNLNWLDGT1 = 0.676
* (-583+ -1,360) 72*0.215* (5.11 -15.33)= 1,443, and AHCDNL = 265 + 1,413+270 + 1,443 = 3,391.
Summarizing these results, the HOP service results in an increase in diurnal emissions of 3,391 grams
per day.
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Step Ig in the emission methodology involves calculating the total trip-related emission changes
for the HOP service. These changes are calculated using the following formulas:
AHCTRrP = AHCCST + AHCHST + AHCHSK + AHCDNL
ANOxTRIP = ANOxCST + ANOxHST
ACOTRrP = ACOCST + ACOHST
In the formulas, AHCTRIP, ANOxTRIP, and ACOTRIP are the total changes in HC,
NOx, and CO emissions, respectively, due to trip changes.
Using the data above, AHCTRIP = -7,492 + -1,808 + -7,327 + 3,390 = -13,237. Summarizing this
result, the HOP service results in a net decrease in trip-related HC emissions of 13,237 grams per day.
(Following the same methodology, total trip-related emission changes can also be determined for NOx
and CO.)
Emission Effects STEP 2 (VMT Changes)
Step 2 in the estimation of the emission effects for the HOP service involves calculating the
effect of VMT changes on emissions. This step is broken down into four smaller steps (2a through 2d),
which are outlined below.
Step 2a in the emission methodology involves estimating the distribution of VMT changes
for the HOP service. These changes are calculated using the following formulas:
YVMT.LDGV = VMTLDGV / (VMTLDGV + VMTLDGT1)
YVMT.LDGTI i - YVMT.LDGV
In the formulas, YVMT LDGV is the fraction of TCM-affected VMT for light-duty
gasoline vehicles (LDGVs), YTRTPLDGTI is the fraction of TCM-affected VMT
for light-duty gasoline trucks (LDGTls), VMTLDGV is the fraction of total VMT
in the region for LDGVs, and VMTLDGT1 is the fraction of total VMT in the
region for LDGTls. (Note: Most TCMs that can be analyzed using EPA's
guidance document affect only LDGVs or LDGTls. Thus, the sum of YVMT LDGV
and YVMTLDGTI is typically equal to one.)
VMTLDGV and VMTLDGT1 are assumed to equal 0.626 and 0.171, respectively. These values
are the national average default values used in MOBILE for VMT mix.
Using the data above, YVMT.LDGV = °-626 / (0.626 + 0.171) = 0.785 and YVMT.LDGTI = 1 - °-785
= 0.215. Summarizing these results, 78.5% of the VMT affected by the HOP service is by LDGVs,
and 21.5% is by LDGTls.
Step 2b in the emission methodology involves estimating hot-stabilized exhaust emission
changes for the HOP service. These changes are calculated using the following formulas:
AHCsmP = (ANETVMTP * YVMT.LDGV * STBLDGV3QP) + (ANETVMTP * YVMT.LDGTI * STBLDGT13QP)
AHCsmoP = (ANETVMTOP * YVMT.LDGV * STBLDGV3QOP) + (ANETVMTOP * YVMT.LDGTI * STBLDGT13QOP)
ANOxSTBP = (ANETVMTP * YVMT.LDGV * STBLDGvNOxP) + (ANETVMTP * YVMT.LDGTI * §TBLDGT, NOxP)
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ANOxsmop = (ANETVMTop * YVMI,LDGV * STBLDGV,NOx,OP) + (ANETVMTOP * YVMT,LDGTI *
STBLDGT j jNOx,op)
ACOsmP = (ANETVMTP * YVMT,LDGV * STBLDGV,CO,P) + (ANETVMTP * YVMT,LDGTI * STBLDGTUCO,P)
ACOsmoP = (ANETVMTOP * YVMT,LDGV * STBLDGVmoP) + (ANETVMTOP * YVMT,LDGTI * STBLDGTUCO,OP)
In the formulas, AHCSTB P, ANOxSTB P, and ACOSTB P are the peak-period changes
in hot-stabilized emissions for HC, NOx, and CO, respectively; and AHCSTB OP,
ANOxSTB op, and ACOSTB OP are the off-peak changes in hot-stabilized emissions
for HC, NOx, and CO, respectively. STBP is the hot-stabilized emission factor
(in grams per mile) for each pollutant and vehicle class for the peak period
(during which average vehicle speed is assumed to be 20 miles per hour),
and STBOP is the hot-stabilized emission factor (in grams per mile) for each
pollutant and vehicle class for the off-peak period (during which average vehicle
speed is assumed to be 35 miles per hour). The other parameters in the formulas
are defined in earlier steps of the methodology.
Using national default data from MOBILE, AHCSTBP = (-1,602 * 0.785 * 1.23) + (-1,602 * 0.215
* 1.77) = -2,156 and AHCSTBOP = (-3,012 * 0.785 * 0.69) + (-3,012 * 0.215 * 0.94) = -2,240.
Summarizing these results, the HOP service results in a reduction in peak-period hot-stabilized HC
exhaust emissions of 2,156 grams per day and a reduction in off-peak hot-stabilized HC exhaust
emissions of 2,240 grams per day. (Following the same methodology, hot-stabilized exhaust emission
changes can also be determined for NOx and CO.)
Step 2c in the emission methodology involves estimating VMT-related evaporative emission
changes for the HOP service. These changes are calculated using the following formulas:
= (ANETVMTP * YVMTLDGV * VEVPLDGVP) + (ANETVMTp * YVMILDGTI * VEVPLDGT1P)
AHCVBVP.OP = (ANETVMTop * YVMT,LDGV * VEVPLDGV,OP) + (ANETVMTOP * YVMI,LDGTI * VEVPLDGTUOP)
In the formulas, AHCyEyp P is the change in peak-period evaporative emissions,
AHCyEvp OP is the change in off-peak evaporative emissions, and VEVP is the
VMT-related evaporative emission factor (in grams per mile) for each vehicle
class and time period (peak or off-peak). The other parameters in the formulas
are defined in earlier steps of the methodology. (Note: Evaporative emissions
are HC emissions only.)
Using national default data from MOBILE, AHCvEypp = (-1,602 * 0.785 * 0.44) + (-1,602
* 0.215 * 0.53) = -736 and AHC^y^ = (-3,012 * 0.785 * 0.34) + (-3,012 * 0.215 * 0.44) = -1,089.
Summarizing these results, the HOP service results in a reduction in peak-period evaporative emissions
of -736 grams per day and a reduction in off-peak evaporative emissions of 1,089 grams per day.
Step 2d in the emission methodology involves calculating the total VMT-related emission
changes for the HOP service. These changes are calculated using the following formulas:
~~ AHCSTBjP + AHCSTBjOP
= ANOxSTBP + ANOxSTB OP
= ACOsmP + ACOsmoP
In the formulas, AHCy^, ANOxy^., and AGOy^ are the total changes in HC,
NOx, and CO emissions, respectively, due to VMT changes.
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Using the data above, AHC^ = -2,156 + -2,240 + -736 + -1,089 = -6,221. Summarizing this
result, the HOP service results in a net decrease in VMT-related HC emissions of 6,221 grams per day.
(Following the same methodology, total VMT-related emission changes can also be determined for NOx
and CO.)
Emission Effects - STEP 3 (Speed Changes)
Step 3 in the estimation of the emission effects for the HOP service involves calculating the
effect of speed changes on emissions. This step is broken down into four smaller steps (3a through 3d),
which are outlined below.
Step 3a in the emission methodology involves estimating the speeds associated with the HOP
service. These speeds are calculated using the following formulas:
SPEEDPTCM = SPEEDPBASE * (1 + ASPDP)
SPEEDOPJCM = SPEEDOP3ASE * (1 + ASPDOP)
In the formulas, SPEEDPTCM is the peak-period speed after implementation of the
TCM, SPEED0pjcM is the off-peak speed after implementation of the TCM,
SPEEDPBASE is the peak-period speed prior to implementation of the TCM,
and SPEEDOP BASE is the off-peak speed prior to implementation of the TCM.
The other parameters in the formulas are defined in earlier steps of the
methodology.
Based on data for the national default fleet, SPEEDPBASE is assumed to be 20 miles per hour,
and SPEEDOPBASE is assumed to be 35 miles per hour.
Using the data above, SPEEDPTCM = 20 * (1 + 0.004) = 20.08 and SPEEDOPTCM = 35 * (1 + 0)
= 35. Summarizing these results, peak-period speeds have slightly increased from 20 miles per hour
to 20.08 miles per hour due to the HOP service. Off-peak speeds have not changed due to the service.
Step 3b in the emission methodology involves estimating the total VMT for the program area
after implementation of the HOP service. These VMT figures are calculated using the following
formulas:
VMTP TCM = TOTVMTP + ANETVMTP
VMTOPJCM = TOTVMTOP + ANETVMTOP
In the formulas, VMTP TCM is the total peak-period VMT in the program area
after implementation of the TCM, and VMTOPTCM is the total off-peak VMT
in the program area after implementation of the TCM. The other parameters
in the formulas are defined in earlier steps of the methodology.
Using data from Step 9 of the "Travel Activity Effects" section above, VMTPTCM = 1,000,000
+ -1,602 = 998,398 and VMTOPTCM = 1,000,000 + -3,012 = 996,988. Summarizing these results,
peak-period VMT has decreased from 1,000,000 miles per day to 998,398 miles per day due to the HOP
service. Off-peak VMT has decreased from 1,000,000 miles per day to 996,988 miles per day due to the
service.
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Step 3c in the emission methodology involves estimating peak-period and off-peak emission
changes due to changes in vehicle speeds. These changes are calculated using the following formulas:
AHCSPD)P VM 1 PJCM (S 1 -t>FLT,HC,P,TCM + -"^ -^FLT.PJCM) " * M 1 PJCM (S 1 -°FLT,HC,P,BASE + -
AHCSPD)Op ~~ V MTOpjTcM (STBFLT)HCjOp)TCM + R-NLFLT)0pjTCM) " M.TOPjTCM (STBFLTjHC)OP)BASE + RNLFLTjOPjBASE)
ANOxSPD)P = VMTPjCM (STBFLTjNOX)PjCM - STBFLTjNOX)P)BASE)
ANOxSPD)OP = V JVlTOpjCM (STBFLTjNOX)OpjCM STBFLTjNOX)0p)BASE)
ACOSPDjP = VMTPjCM (STBFLT)COjPjCM - STBFLT)CO)P)BASE)
ACOSPDjOp = V JVlTOpjCM (STBFLT)COjOpjCM
In the formulas, AHCSPDP, ANOxSPDP, and ACOSPDP are the peak-period changes
in emissions for HC, NOx, and CO, respectively, due to a change in speeds;
and AHCSPD OP, ANOxSPD OP, and ACOSPD OP are the off-peak changes in emissions
for HC, NOx, and CO, respectively, due to a change in speeds. STBFLT is the
fleet-wide hot-stabilized emission factor (in grams per mile) for each pollutant,
time period (i.e., peak or off-peak), and scenario (i.e., base or TCM). RNLFLT
is the fleet-wide running loss emission factor (in grams per mile) for each time
period and scenario. The other parameters in the formulas are defined in earlier
steps of the methodology.
Based on data showing the relationship between vehicle speed and emissions, this analysis
assumes that the elasticity of STBFLT with respect to speed is -1 for HC, 0 for NOx, and -1 for CO.
Thus, a 1% increase in speed is assumed to result in a 1% decrease in HC and CO emissions (on a grams
per mile basis) and no change in NOx emissions. The elasticity of RNLFLT with respect to speed is also
assumed to be -1.
Using national default data from MOBILE, AHCSPDP = 998,398 * (1.669 + 0.21 1) - 998,398
* (1.676 + 0.212) = -0 and AHCSPDOP = 996,988 * (1.938 + 0.120) - 996,988 * (1.938 + 0.120) = 0.
Summarizing these results, the HOP service changes neither speed-related HC emissions per day for the
peak period nor speed-related HC emissions for the off-peak period. (Following the same methodology,
the peak-period and off-peak emission changes due to changes in speeds can also be determined for NOx
and CO.)
Step 3d in the emission methodology involves calculating the total speed-related emission
changes for the HOP service. These changes are calculated using the following formulas:
AHCSPD
ANOxSPD = ANOxSPD)P + ANOxSPE, op
ACOSPD
In the formulas, AHCSPD, ANOxSPD, and ACOSPD are the total changes in HC,
NOx, and CO emissions, respectively, due to speed changes.
Using the data above, AHCSPD = 0 + 0 = 0. Summarizing this result, the HOP service results
in no net change in speed-related HC emissions per day. (Following the same methodology, total
speed-related emission changes can also be determined for NOx and CO.)
Emission Effects - STEP 4 (Total)
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Step 4 in the estimation of the emission effects for the HOP service involves calculating the total
changes in HC, NOx, and CO emissions. These changes are calculated using the following formulas:
ARC = AHCTRIP + AHCvMT + AHCSPD
ANOx = ANOxTRIP + ANOxvMT + ANOxSPD
AGO = ACOTRIP + ACOvMT + ACOSPD
In the formulas, ARC, ANOx, and AGO are the total changes in HC, NOx,
and CO emissions, respectively, due to the TCM program.
Using the data above, ARC = -13,236 + -6,221 + 0 = -19,457. Summarizing this result, the HOP
service results in a net decrease in HC emissions of 19,457 grams per day, or approximately 0.019 tons
per day. (Following the same methodology, total emission changes can also be determined for NOx
and CO.)
66
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2. ANALYSIS OF TCM PACKAGES
This section uses the methodology outlined in Chapters 2, 3, and 4 of EPA's TCM guidance
to estimate the travel activity effects and emissions effects of programs involving TCM packages.
The key distinction between the analysis presented in this section and the analysis in Section 1
is the need to first consider modal choice.
People tend to base their travel mode decisions on the attributes of each travel mode. The time
it takes to get to a destination by a certain mode, the cost of a mode, the convenience of a particular
mode, and mode reliability are the four characteristics people primarily consider when deciding on travel
methods. EPA's methodology for TCM packages uses these attribute characteristics in a particular study
area to determine the probability that a representative person in the affected community will choose
a particular mode. These probabilities for a representative individual are then extrapolated to the whole
study area population. When the characteristics of travel modes suddenly change (i.e. after TCM
implementation), travel attributes change, and therefore mode choice probabilities for the representative
individual and the entire study area also change. The TCM modeler can now compare the "pre-TCM"
mode splits with the "post-TCM" splits to determine mode choice change due to the introduction of the
TCM package.
Two analyses need to be conducted under the TCM package methodology before travel activity
and emission changes can be determined. The first involves establishing the travel attribute
characteristics and travel mode profiles that existed before introduction of the TCM package
(i.e., a "base case"). The second analysis predicts travel choices after TCM implementation by plugging
the new travel conditions into the base case framework. In other words, by multiplying the new travel
attributes by preferences established in the base case, a new travel mode profile can be obtained.
Example 6: Cornell University Transportation Demand Management Program
General Description
The Cornell University Transportation Demand Management Program (TDMP) was instituted
by the University in the early 1990s to combat significant traffic congestion near and on the Ithaca
campus. Realizing that a parking pricing scheme alone would not be sufficient to alter faculty and staff
work travel habits, the University's Office of Transportation Services (OTS) developed a transportation
management package that, along with parking fees, included subsidized transit and rideshare measures.
The TDMP introduced several measures to encourage transit and carpooling. First, all but one
campus parking lot began to charge single occupancy vehicles (SOVs). Second, a program called
RideShare was established with a number of features, some key ones are a rideshare parking fee schedule
that includes rebates in particular instances, a listing of people looking for others with whom to rideshare
to help match people interested in carpooling, and emergency ride services to staff members who become
stranded on campus due to missing their carpool rides. Finally, a program called OmniRide was
developed. This program provides Cornell employees who do not participate in the RideShare program
with free transit passes that can be used for work as well as leisure.
The Cornell TDMP has been quite successful, not only at reducing vehicle emissions as shown
in the analysis below, but at saving large amounts of money for the university by enabling it to forgo
large expenses for additional parking facilities that would have been needed otherwise. The university
estimates that, without TDMP, construction of additional parking structures offering atotal of 3,100
67
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parking spaces would have been needed since 1991, when the program started. With TDMP the
university has added a total of 350 parking spaces in that time period. Total cost savings to date from
the forgone construction are estimated at $13 million.
A key factor in the success of the program has been the measures taken to provide backups,
when needed, for commuters participating in the RideShare and OmniRide programs. Guaranteed rides
home are available when program participants need them due to unforeseen circumstances. Participants
also each receive a book often 1-day parking permits enabling them to drive alone on the occassional
days when circumstances require them to have their cars at work. In special circumstances, such as the
need to provide care to a family member for an extended period of time, participants may obtain
additional books of permits.
Program officials also point to their outreach efforts as a key to their success. One tangible result
is that they have gotten agreements from churches, town halls, grocery stores, and other facilites with
parking lots that are not heavily used during weekday working hours, to allow RideShare participants
to use their lots as park-and-ride lots.
Data Sources
"Commuting Solutions Summary of Transportation Demand Management Program (TDMP),"
Office of Transportation Services, June 1996.
Cornell Commuter Report, Spring 1996.
"Patterns and Trends: New York State Energy Profiles, 1981-1995," prepared by the New York
State Energy Research and Development Authority.
Personal Interview with David Lieb, Communications Manager, Office of Transportation and
Mail Services, March 12, 1997, March 13, 1997, and March 17, 1997.
Personal Interview with Lois Chaplin, University Bike Safety Specialist, March 12, 1997.
Personal Interview with Nate Earlbomb,
New York Department of Transportation,
Decembers, 1997.
"Report on Reducing Oregon's
Greenhouse Gas Emissions," prepared by
the Oregon Office of Energy.
"TCAT Service and Fare Consolidation
Project: Tompkins Consolidated Area
Transit, Ithaca, New York."
Texas Transportation Institute web page.
1990 U.S. Census data.
1996 Statistical Abstract of the United
States.
Phase 1: Modal Choice Analysis
Phase 1: Mode Choice Analysis
Step 1: Base case (before TCM implementation)
cost, time, convenience and reliability for
each mode
Step 2: Highest and lowest possible values for time
and cost among all modes
Step 3: Scale base-case cost, time, convenience,
and reliability values for each mode on a
"best-to-worst" scale
Step 4: Weight factors for cost, time, convenience
and reliability
Step 5: Base case utilities for each travel mode
(scale values times weight factors)
Step 6: Percentage of time in the base case a person
will travel by each mode
Step 7: Percentage of time after TCM
implementation a person will travel by each
mode. This involves redoing steps 1
through 6 with values reflecting the TCM.
68
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Step 1 of the modal choice analysis for the TDMP involves determining the base case (i.e., prior
to implementation of the TCM package) cost, time, convenience, and reliability for each mode of travel.
Cost
Relevant costs include parking fees, tolls, gasoline, and transit fees, although not every travel
mode incurs all four costs. (For example, SOV travelers do not incur transit fees. Transit users,
however, could face all four costs if they drive via a toll road to a transit station that charges for park-
and-ride services.) Data needed to determine travel mode costs in the study area include the average
distance to work for each mode, the fuel economy of passenger vehicles, gasoline prices, toll prices,
parking prices, and transit prices.
Data on the average round-trip work travel distance for each travel mode in Tompkins County
were not available from any consulted data sources. However, by cross-referencing the average trip
length and time for all American
workers (obtained from the 1996
Statistical Abstract of the United States)
with average work trip time information
for Tompkins County (obtained from
1990 U.S. Census data), the average
one-way trip length in Tompkins
County is determined to be 8.83 miles.
Because the majority of trips to the
Cornell campus before TCM
implementation were made by SOVs
(75%), this one-way trip length is
assigned to the SOV mode.
This analysis also assumes that carpool
vehicles would need to travel an extra
2 miles on a one-way work trip to pick
up passengers. Average transit distances
Focus: COMPONENTS OF TRAVEL COST BY MODE
Relevant costs for each travel mode are listed in the boxes
below. While an SOV and a carpool vehicle encounter similar
costs, total carpool costs need to be divided by average carpool
vehicle occupancy (CVO) in order to determine cost per
carpooler. (Note: This analysis is conducted from the
perspective of an individual making a commuting decision,
and thus costs need to be calculated on an individual basis.)
Transit costs must include the costs incurred by the fraction
of commuters who drive or get a ride to a transit stop.
Finally, this analysis assumes that the walk/bike travel mode
poses no cost to a commuter.
Fuel
Prices
Fuel
Efficiency
Parking
Fees
Tolls
Fuel Prices
Fuel Efficiency
Parkins Fees
Tolls
Note: Total cost
needs to be divided
by CVO to obtain
cost faced by each
individual.
Transit Fees
Note: Mode cost
must incorporate
the costs to transit
riders who drive
to a transit stop,
including fuel
prices, fuel
efficiency, parking
fees, and tolls.
and walk/bile distances in this particular
case are relatively small.
Fuel economy for the Tompkins
County area was derived using data from
an Oregon Greenhouse Gas study, which
reported that the average fuel economy
for a passenger vehicle in 1991 (the year
of TDMP implementation) was 20.1
miles per gallon (mpg). SOV fuel
economy is increased to 20.3 mpg to
account for the fact that most SOVs are
passenger cars. Also, fuel economy for
carpool vehicles
is lowered to 19.9 to account for the greater use of larger vehicles (e.g., mini-vans) and slower speeds.
Due to the lack of parking fees on the Cornell campus prior to TCM implementation and the
non-existence of toll roads in Tompkins County, costs for SOV and carpool use are simply the price of
gasoline consumed. (According to the NYSERDA, the average gasoline price in New York in 1991 was
$1.33 per gallon.) This analysis assumes that the cost of gasoline is distributed evenly among all carpool
SOV
Carpool
Transit
69
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passengers (including the driver). Therefore, the cost of gasoline consumed for an individual in a carpool
is determined by dividing the cost of gasoline by the average number of passengers in a carpool (2.18 in
Tompkins County, as reported in 1990 U.S. Census data).
Based on the data above,
the cost of SOV travel is calculated
as follows: 17.67 miles (round trip)
* $1.33 per gallon / 20.3 mpg = $1.16. The cost of carpool travel is calculated as follows: 22 miles
(round trip)
* $1.33 per gallon/19.9 mpg/2.18
= $0.67.
Total transit costs are the sum of two components. The first component, the price of using
transit,
is assumed to be $0.50, based on fee information found on the TCAT web site. The second component
accounts for transit users who drive to a transit stop. Assuming that 30% of transit users drive to their
stop, the average one-way distance to
the park-and-ride stop is 1.5 miles, and
average vehicle occupancy reflects
county averages (1.21 according to
1990 U.S. Census data), the average
one-way transit cost is calculated as
follows: $0.50 + 0.3
* (1.5 miles* $1.33 per gallon/20.1
mpg / 1.21) = $0.525. Multiplying this
figure by 2 yields a round-trip cost
of$1.05.
Time
For SOVs and carpools, round
trip travel time is determined by
dividing round trip travel distance by
average speed. Speed data for SOVs
and carpools is based on the national
average for travel on principle arterial
streets during peak hours. (Note: This
analysis assumes most work trips take
place during peak periods.) Because
Tompkins County is largely rural and
is not located near any major highway
infrastructure, this analysis assumes
that most travel is done on arterial
roads. Carpool vehicles travel
at slightly lower speeds due to the slow
speeds involved when traveling in
residential areas to pick up passengers.
For walkers and bikers, the analysis
assumes that the average speed is 5
miles per hour.
Focus: COMPONENTS OF TRAVEL TIME BY MODE
The factors that determine travel time for each mode are listed
in the boxes below. SOV travel time is calculated by dividing
travel distance by average vehicle speed. Carpool travel time
is calculated in the same manner. However, it is important
to note that carpool vehicles generally go slower and travel
longer distances than SOVs due to passenger pick-up stops.
In the TDMP base case, carpool vehicles are assumed to travel
four miles more than SOVs and travel at a speed 3 miles per
hour slower than SOVs. In addition to travel distance and
vehicle speed, transit commute time is augmented by time spent
waiting for transportation and time spent reaching the transit
stop. Walk/bike commute time is calculated in the same manner
as the SOV and carpool modes.
Travel
Distance
Vehicle
Speed
Travel
Distance
Vehicle
Speed
Note: Travel
distance will be
affected by the
number of
carpool
participants,
and vehicle
speed will be
less than SOV
speed due to
multiple stops
for passenger
pickup.
Travel
Distance
Vehicle
Speed
Time Spent
Waiting at
Transit Stop
Time Spent
Traveling to
and from
Transit Stop
Travel
Distance
Mode
Speed
SOV
Carpool
Transit
Walk/Bike
70
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To calculate travel time for transit, this analysis assumes that the average speed of a transit
vehicle is 20 miles per hour. With a round trip of 13 miles, travel time is calculated to be 0.65 hours.
EPA's TCM guidance suggests that walking and waiting time for transit amounts to approximately 8.76
minutes. This is multiplied by 2 to generate round-trip walking and waiting time for transit. Finally,
there is additional driving time for the fraction of individuals who drive to park-and-ride lots. This is
calculated by dividing the average round-trip distance for park-and-ride users by vehicle speed (assumed
to be 30 miles per hour) and multiplying by the fraction of transit riders who use park-and-ride lots (0.3).
Based on the information above, the travel time for SOVs is 17.67 miles (round trip) / 30 miles
per hour = 0.59 hours. The travel time for carpools is 22 miles (round trip) / 27 miles per hour = 0.81
hours. The travel time for transit is 13 miles (round trip) / 20 miles per hour + ((8.76 / 60) * 2) + (0.3
* (3 miles / 30 miles per hour)) = 0.97 hours. The travel time for walkers/bikers is 4.5 miles (round trip)
/ 5 miles per hour = 0.90 hours.
The costs and travel times associated with SOV travel, carpool travel, transit, and walking/biking
for the base case are summarized below in Table 1.
Table 1: Average Travel Cost and Time for the Base Case
Travel Mode
Walk/Bike
Transit
Carpool
SOV
Total
Daily
Work
Trip
Length
4.5
13
22
17.67
Average
Peak
Period
Speed
5
20
27
30
Hours of
Daily Work
Travel
Time
0.9
0.97
0.81
0.59
Fuel
Economy
N/A
20.1
19.9
20.3
Dollars per
Gallon
N/A
$1.33
$1.33
$1.33
Parking Fee
N/A
N/A
N/A
N/A
Transit Cost
(one way)
N/A
$0.52
N/A
N/A
Total Cost
-
$1.05
$0.67
$1.16
Note: This methodology does not include the costs of wear-and-tear on privately-owned vehicles and thus may undervalue the true costs faced
by SOV and carpool users. Nevertheless, wear-and-tear is an indirect cost that vehicle owners rarely account for in their work travel choices.
Convenience
Determining the convenience value for each travel mode primarily involves a qualitative
analysis. Due to a lack of information on Tompkins County and the area around Cornell's campus, the
convenience factors used on this analysis are based on factors shown in the TCM guidance for the San
Francisco area, with a few minor adjustments. (Note: A convenience value of 0 indicates that an option
is totally inconvenient, and a convenience value of 1 indicates that an option is totally convenient.)
The convenience of SOV travel in Tompkins County is given a value 0.9. While
the guidance gives SOVs a value of 0.8, the lack of a transit system in Tompkins
County similar to BART and the relative spread of development in Tompkins
County when compared to the density of San Francisco would seem to encourage
SOV use in Tompkins County to a greater extent.
The convenience of transit in Tompkins County is given a value of 0.2.
The TCM guidance gives transit a value of 0.4 for San Francisco. However,
the Bay Area's extensive transit system is much more comprehensive than the
system serving Tompkins County.
71
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The convenience of carpool travel in Tompkins County is given a value of 0.2.
While ridesharing in San Francisco is given a convenience value of 0.3, the lack
of congestion and spread of development in Tompkins County makes ridesharing
less convenient than it is in San Francisco.
The convenience of walking/biking in Tompkins County is given a value of 0.1.
While walking and biking can be very convenient for some people, for many
it is not a viable option.
Focus: ASSESSING CONVENIENCE OF EACH MODE
The convenience of a particular mode is largely determined by three factors - comfort, safety, and
flexibility. If a mode provides physical comfort, is relatively non-stressful, and does not prevent
commuters from indulging in their favorite travel habits, such as listening to the radio or drinking coffee,
its convenience value will be fairly high. Convenience value will also be enhanced by feelings of safety.
(For example, many observers partially attribute the recent popularity of sport utility vehicles to the feeling
of safety these vehicles provide.) If a transportation choice allows the commuter to complete errands
before and after work and provides flexibility in departure time, convenience value for that particular mode
will be relatively high. Conversely, a transportation choice that makes commuting taxing and stressful,
provides little transportation flexibility, and is prone more than any other mode to cause physical injury will
be relatively inconvenient and an unpopular modal choice.
Comfort
Safety
Aesthetic value is low, difficult and
time-consuming to access
transportation
Risk of personal
injury is high
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Flexibility
Can complete other trips, range
of start-end times, immediate
access to transportation
Cannot complete other trips, no range
of start-end times, difficult to
access transportation immediately
Reliability
Like convenience value, reliability can only be determined by a qualitative assessment.
(Note: A reliability value of 0 indicates that an option is totally unreliable, and a reliability value
of 1 indicates that an option is totally reliable.)
The reliability of SOV travel is given a value of 0.9. This is based on the fact
that (1) the vehicle is immediately available, (2) travel does not depend on
anyone else, and (3) there is a slight chance that a vehicle will experience
mechanical failure.
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The reliability of walking/biking is given a value of 0.4. This is based on that
fact that (1) travel does not depend on anyone else, (2) immobility is generally
not a problem, and (3) inclement weather can make this option intolerable.
The reliability of carpool travel is given a value of 0.2. This is based on that fact
that ridesharers depend on the cooperation of others.
The reliability of transit is given a value of 0.2. This is based on that fact that
(1) transit riders often experience delays, and (2) transit systems sometimes
experience mechanical failures.
Focus: ASSESSING RELIABILITY OF EACH MODE
The reliability of a particular mode is largely determined by two factors ~ availability and
predictability. If a particular transportation mode is immediately available and can deliver the user
to his/her destination of choice in a timely manner, reliability will be high. The reliability attribute of
a particular mode will be strengthened if the mode is also predictable. For example, if a car has just
been serviced, it is very likely to run with few problems, and performance predictability will be high.
Conversely, if a bus route is scheduled to run infrequently or is always late, predictability will be low.
Availability
Transportation is always
Transportation is rarely
immediately available
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Predictability
It is very difficult to
determine when transportation
will be needed and if it
will be available when wanted
Step 2 of the modal choice analysis for the TDMP involves determining the best and worst limits
of the cost and travel time profiles for the base case.
The best cost is the lowest cost among the four modes. Based on an example shown in the TCM
guidance document, the worst cost limit is derived by multiplying the highest cost among the four modes
by a factor of approximately 1.8. Therefore, the best cost is $0, and the worst cost is $2.08 (i.e., 1.8
* $1.16).
The best travel time involves no travel at all. For example, a faculty member who lives
in a dormitory experiences virtually no travel time. On the other hand, for people who commute over
long distances, travel time can easily extend over an hour. Therefore, the best travel time is assumed
to be 0, and the worst travel time is assumed to be 1.5 hours.
73
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Focus: COMPARING TIME ACROSS MODES
To normalize the range of travel times on a scale of 0 to 1 (longest commute time to shortest commute time),
the longest and shortest possible travel times a commuter could encounter need to be determined. In the TDMP
base case, the shortest possible commute time is 0 hours (for people who live next to their offices) and the
longest possible commute time is 1.5 hours (for SOV users who have a particularly long commute).
Normalized travel times in the TDMP base case are 0.607 for an SOV commute, 0.352 for a transit commute,
0.457 for a carpool commute, and 0.400 for a walk/bike commute.
0 (Longest) 0.5 (Shortest) 1
Transit Walk/Bike Carpool SOV
Step 3 of the modal choice analysis for the TDMP involves scaling the base case cost, time,
convenience, and reliability of each travel mode on a "best-to-worst" scale. To scale the cost and time
of each mode on a best-to-worst scale (1 representing the best value and 0 the worst value), the following
formulas are used:
COSTVALk = (worst cost - COST,,) / (worst cost - best cost)
TIMEVALk = (worst time - TIMEjJ / (worst time - best time)
In the formulas, COSTVALk is the cost value for travel mode k, TIMEVALk
is the time value of travel mode k, COSTk is the cost of mode k, and TIMEk
is the travel time of mode k.
Focus: COMPARING COST ACROSS MODES
To normalize the range of mode costs on a scale of 0 to 1 (highest commute cost to lowest commute cost),
the highest and lowest possible costs a commuter could encounter need to be determined. In the TDMP base
case, the lowest possible cost is $0 (for walkers and bikers) and the highest possible cost $2.08 (for SOV users
who have a particularly long commute or face an extra toll). Normalized costs in the TDMP base case are
0.444 for an SOV commute, 0.497 for a transit commute, 0.676 for a carpool commute, and 1.000 for
a walk/bike commute.
0 (Highest) 0.5 (Lowest) 1
SOV Transit Carpool
Based on the analysis above, COSTVALWalk/Blke = (2.08 - 0) / (2.08 - 0) = 1, COSTVALTn
74
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= (2.08 - 1.05) / (2.08 - 0) = 0.497, COSTVALCarpool = (2.08 - 0.67) / (2.08 - 0) = 0.676,
and COSTVALSOV = (2.08 - 1.16) / (2.08 - 0) = 0.444. Also, TIMEVALWalk/Blke = (1.5 - 0.9) / (1.5 - 0)
= 0.400, TIMEVALTransit = (1.5 - 0.97) / (1.5 - 0) = 0.352, TIMEVALCaipool = (1.5 - 0.81) / (1.5 - 0)
= 0.457, and TIMEVALSOV = (1.5 - 0.59) / (1.5 - 0) = 0.607. (Note: The values for convenience and
reliability are assumed to be the same as those calculated in Step 1 above.)
Focus: COMPARING RELIABILITY ACROSS MODES
although congestion can serve to reduce the
m^m\^^m^^m&^&a^£^§^^^
^e^jpj£foMfig^*&ViM
a reliability value of 0.4.
Comfort
0.5
(Best) 1
0 (Worst)
Carpool
Safety
Transit
Transit
Pnrnnnl
\%flc/
Walk/
Bike*
(Best) 1
0.5
(Best) 1
0 (Worst)
Transit
Flexibility
snv
Carpool
Pnrnnnl Trnncit
Walk/
Bike*
(Best) 1
*Thes.ejy
' apply to commuters who live close enougrra) their work sites to make this mode a viabl
Transit
Carpool
' These scores only apply to commuters who live close enough to tl
ir work sites to make this mode a viable option.
Focus: SOME FACTORS MATTER MORE
Step 4 of the modal choice analysis for the
TDMP involves determining a base case weight
profile for the population of the program area. This
step involves assigning the relative importance of each
attribute from the perspective of the average member
of the study population. The "weight profile" must
sum to one (i.e., 100% of the travel decision process is
affected by these four attributes). The TCM guidance
suggests initial relative weights of 0.3 for cost, 0.3 for
travel time, 0.2 for convenience, and 0.2 for reliability.
Based on survey data for the TDMP and calculations
performed under Steps 5 and 6 below, the relative
weights ultimately used in this analysis for cost, time,
convenience, and reliability are 0.3, 0.19, 0.3, and
0.21, respectively.
THAN OTHERS
How much does the average member of the
TCM program area value cost in comparison
with convenience? What weight should be
attached to reliability? The answers to these
questions will help determine the relative
importance of the four travel attributes for the
region being studied. This relative importance
is reflected in the "weight profile." For
example, if cost is valued more than time in a
particular community, any TCM that decreases
cost will have a greater chance of affecting
behavior than a TCM that modifies travel time.
The TCM guidance suggests an initial weight
profile. However, analysts will need to make
appropriate judgements to determine the weight
profile of the particular area being studied.
75
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Step 5 of the modal choice analysis for the TDMP involves calculating the total utilities of each
mode of travel for the base case. These utilities are determined for each travel mode using the following
formula:
TUk = COSTVALk * A! + CONVVALk * A2 + TIMVALk * X3 + RELVALk * X4
In the formula, TUk is the total utility of travel mode k, COSTVALk is the cost
value of mode k, CONVVALk is the convenience value of mode k, TIMVALk
is the time value of mode k, and RELVALk is the reliability value of mode k.
1] is the relative weight on cost, A,2 is the relative weight on convenience,
A,3 is the relative weight on time, and A,4 is the relative weight on reliability.
Based on the analysis above, TUWaMBlke = 1 * 0.3 + 0.1 * 0.3 + 0.4 * 0.19 + 0.4 * 0.21 = 0.49,
TUTransit = 0.497 * 0.3 + 0.2 * 0.3 + 0.352 * 0.19 + 0.2 * 0.21 = 0.32, TUCarpool = 0.676 * 0.3 + 0.2 * 0.3 +
0.457 * 0.19 + 0.2 * 0.21 = 0.39, and TUSOV = 0.444 * 0.3 + 0.9 * 0.3 + 0.607 * 0.19 + 0.9 * 0.21 = 0.71.
Step 6 of the modal choice analysis for the TDMP involves estimating the percentage of time
(i.e., probability) that a person from the program area will travel via a given mode of travel in the base
case. This percentage is calculated for each travel mode using the following formula:
_ 6.5TU
k ~ e k '
,=i e
In the formula, Pk is the probability that a person from the program area will
travel via mode k relative to the N modes examined.
Table 2 below presents the results of Step 6 for the base case. As can be seen from the table, the
estimated probabilities correspond closely to actual mode splits.
Table 2: Travel Mode Choice for the Base Case
Mode Split
Actual
Projected
SOV
74.9
68.9
Carpool
4.4
8.8
Transit
4.4
5.5
Walk/Bike
16.4
16.8
Step 7 of the modal choice analysis for the TDMP involves estimating the percentage of time
(i.e., probability) that a person from the program area will travel via a given mode of travel after
implementation of the TCM package. This requires repeating Steps 1 through 6 above using data and
assumptions applicable to the TCM package (see Steps 7a through 7f below).
Step 7a of the modal choice analysis for the TDMP involves determining the TCM-adjusted cost,
time, convenience, and reliability for each mode of travel.
Cost
For SOVs, the weighted average price for parking due to the TCM is calculated to be $0.83.
The parking fee for carpools is calculated to be $0.12 and includes both fees and rebates. Rebates are
offered to cars with three or more people that park in specific lots. Based on 1990 U.S. Census data
76
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for Tompkins County, this analysis assumes that 86.4% of carpools contain 2 people, 10.6% contain 3
people, and 3% have 4 or more people. The analysis also assumes that an even distribution of carpool
vehicles use the four campus carpool lots. Both carpools and SOVs incur gasoline costs, which are
added to the parking fees. Based on this information, the total costs for SOVs and carpools are estimated
to be $1.99 and $0.79, respectively.
The only cost for transit is the gasoline used by park-and-ride participants. As in Step 1 above,
this step assumes that 30% of the people who use transit drive to the transit station and that these vehicles
on average contain 1.21 people. The cost of using transit is estimated to be $0.05 after implmentation
of the TCM.
Time
The time attributes for each travel mode do not change due to the TCM package, given no
significant change in average speeds. In addition, congestion would be reduced equally for every mode
of travel (except for walking and biking).
The costs and travel times associated with SOV travel, carpool travel, transit, and walking/biking
for the TCM case are summarized below in Table 3.
Table 3: Average Travel Cost and Time After Implementation of the TCM
Total
Travel Mode
Walk/Bike
Transit
Carpool
SOV
Daily
Work
Trip
Length
4.5
13
22
17.67
Average
Peak
Period
Speed
5
20
27
30
Hours of
Daily Work
Travel
Time
0.9
0.97
0.81
0.59
Fuel
Economy
N/A
20.1
19.9
20.3
Dollars per
Gallon
N/A
$1.33
$1.33
$1.33
Parking Fee
N/A
N/A
$0.12
$0.83
Transit Cost
(one way)
N/A
$0.02
N/A
N/A
Total Cost
-
$0.05
$0.79
$1.99
Note: This methodology does not include the costs of wear-and-tear on privately-owned vehicles and thus may undervalue the true costs faced
by SOV and carpool users. Nevertheless, wear-and-tear is an indirect cost that vehicle owners rarely account for in their work travel choices.
Convenience
After implementation of the TCM, the convenience of SOV travel does not change, as nothing
is done to make SOV use more or less convenient. Due to the improvements resulting from the TCM,
however, the convenience of transit use is assumed to increase from 0.2 to 0.25. Similarly, the
convenience of carpooling is assumed to increase from 0.2 to 0.35, and the convenience of walking/
biking is assumed to increase from 0.1 to 0.2.
Reliability
After implementation of the TCM, the reliability of SOV travel does not change, as nothing
is done to make SOV use more or less reliable. Due to the improvements resulting from the TCM,
however, the reliability of transit use is assumed to increase from 0.2 to 0.25. Similarly, the reliability
of carpooling is assumed to increase from 0.2 to 0.3, and the reliability of walking/biking is assumed
to increase from 0.4 to 0.45.
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Step 7b of the modal choice analysis for the TDMP involves determining the best and worst
limits of the cost and travel time profiles for the TCM case.
The best cost is the lowest cost among the four modes. Based on an example shown in the
guidance document, the worst cost limit is derived by multiplying the highest cost among the four modes
by a factor of approximately 1.8. Therefore, the best cost is $0, and the worst cost is $3.58 (i.e., 1.8
* $1.99).
The best and worst travel times for the TCM case are assumed to be the same as in the base case.
Thus, the best travel time is 0, and the worst travel time is 1.5 hours.
Step 7c of the modal choice analysis for the TDMP involves scaling the TCM-adjusted cost,
time, convenience, and reliability of each travel mode on a "best-to-worst" scale using the formulas
shown in Step 3 above. Based on the analysis above, COSTVALWalk/Blke = (3.58 - 0) / (3.58 - 0) = 1,
COSTVALTransit = (3.58 - 0.05) / (3.58 - 0) = 0.986, COSTVALCaipool = (3.58 - 0.79) / (3.58 - 0) = 0.779,
and COSTVALSOV = (3.58 - 1.99) / (3.58 - 0) = 0.444. Also, TIMEVALWalk/Blke = (1.5 - 0.9) / (1.5 - 0)
= 0.400, TIMEVALTransit = (1.5 - 0.97) / (1.5 - 0) = 0.352, TIMEVALCaipool = (1.5 - 0.81) / (1.5 - 0)
= 0.457, and TIMEVALSOV = (1.5 - 0.59) / (1.5 - 0) = 0.607. (Note: The values for convenience and
reliability are assumed to be the same as those calculated in Step 7a above.)
Step 7d of the modal choice analysis for the TDMP involves determining a weight profile for
the population of the program area after implementation of the TCM. The TCM guidance calls for this
profile to be the same as the profile determined in the base case. Thus, the relative weights for cost, time,
convenience, and reliability are 0.3, 0.19, 0.3, and 0.21, respectively.
Step 7e of the modal choice analysis for the TDMP involves calculating the total utilities of each
mode of travel for the TCM case. These utilities are determined for each travel mode using the formula
shown in Step 5 above. Based on the analysis above, TUWaMBlke = 1 * 0.3 + 0.2 * 0.3 + 0.4 * 0.19 + 0.45
* 0.21=0.53, TUTransit = 0.986* 0.3+ 0.3 * 0.3 + 0.352 * 0.19 + 0.25* 0.21 = 0.51, TUCarpool = 0.779
* 0.3 + 0.35 * 0.3 + 0.457 * 0.19 + 0.3 * 0.21 = 0.49, and TUSOV = 0.444 * 0.3 + 0.9 * 0.3 + 0.607 * 0.19
+ 0.9*0.21 = 0.71.
Step 7f of the modal choice analysis for the TDMP involves estimating the percentage of time
(i.e., probability) that a person from the program area will travel via a given mode of travel after
implementation of the TCM. This percentage is calculated for each travel mode using the formula shown
in Step 6 above. Table 4 below presents the mode splits estimated under the TCM case, along with the
mode splits estimated for the base case.
Table 4: Travel Mode Choice Before and After Implementation of the TCM
Mode Split SOV Carpool Transit Walk/Bike
Base Case 68.9 8.8 5.5
TCM Case 54.8 13.2 14.7
Step 8 of the modal choice analysis for the TDMP involves estimating the daily changes in the
number of work trips made using each mode of travel. These changes are derived using the changes in
the number of Cornell faculty and staff who use each mode, as shown in Table 5 below.
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Table 5: Change in Number of People Using Each Mode Per Day (N = 11,481)
Projected Before TCM Implementation
Projected After TCM Implementation
Change in Mode Choice (Number of People)
SOV
7,916
6,293
-1,623
Carpool
1,015
1,512
497
Transit
628
1,688
1,060
Walk/Bike
1,923
1,989
66
The changes shown in Table 5 are converted into work trip changes as follows:
For the SOV mode, 1,623 cars are now left at home. This number is multiplied by 2 to reflect
that work trips involve a return trip, thus yielding a total of 3,246 trips reduced per day.
After TCM implementation, there are 497 additional carpoolers. An example in the TCM
guidance indicates that 33% of new carpoolers join existing carpools, 62% of new carpoolers
form new carpools that do not drive to park-and-ride lots, and 5% of new carpoolers form new
carpools that drive to park-and-ride lots. Based on these percentages, the total trip increase
by new carpools is estimated to be 285.
Of the 1,060 new transit users, this analysis assumes that 30%, or 318, drive to park-and-ride
lots. This number is divided by average vehicle occupancy for Tompkins County, yielding an
additional 263 vehicles (not including carpool park-and-ride vehicles) making trips to park-and-
ride lots. Multiplying this figure by 2 (to account for return trips) yields 526 additional trips.
As shown in Table 6 below, summing the change in trips for each category (SOV, carpool,
and transit) yields a net reduction of 2,435 trips per day for the TDMP.
Table 6: Work Trip Changes Per Day
Transit 526
New Carpools 282
New Carpools with Park-and-Ride 3 (equivalent carpool trips)
Total Trip Change -2,435
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Phase 2: Travel Activity Effects
Step 1 in the estimation of travel activity
effects, which involves an assessment of the
potential trip effects from the TCM program,
is not applicable in this case.
Step 2 in the travel activity methodology
involves estimating the direct work and non-work
trip reductions from the TDMP. Direct trip
reductions are calculated using the following
formulas:
ATRIPSDW= (o * ATRIPSD
ATRIPSDNW = (1 - co) * ATRIPSD
Phase 2: Effects on Travel Activity
Step 1: Potential trip effects
Step 2: Direct work and non-work trip reductions
Step 3: Indirect work and non-work trip increases
Step 4: Peak and off-peak trip shifts
Step 5: Summation of distribution of trip effects
among work peak, work off-peak, non-
work peak, and non-work off-peak trips
Step 6: Peak and off-peak VMT changes due to
reduced number of trips
Step 7: VMT changes due to reduced trip lengths
Step 8: Net VMT changes
Step 9: Peak and off-peak speed changes
In the formulas, ATRIPSD is the total direct trip reduction, ATRIPSD w is the
direct work trip reduction, ATRIPSDNW is the direct non-work trip reduction,
and to is the fraction of trip effects that are work-related.
ATRIPSD is calculated in Table 6 above to be -2,435 trips per day.
Due to the fact that TDMP is assumed to affect only work-related trips, the parameter to is set
equal to 1.
Using the data above, ATRIPSDW = 1 * -2,435 = -2,435, and ATRIPSDNW = (1 - 1) * -2,435 = 0.
Summarizing these results, the TDMP is responsible for directly reducing 2,435 trips per day, all of
which are work-related.
Step 3 in the travel activity methodology involves estimating the actual indirect trip increases
(for both work and non-work trips) from the TDMP. Indirect trip increases are secondary effects that
typically result when vehicles normally used for commuting are left at home. These increases are
calculated using the following formulas:
ATRIPSIW = INCWH * -ATRIPSD / 2
ATRIPSINW = INCNH * -ATRIPSD / 2
In the formulas, ATRIPS: w is the indirect work trip increase, ATRIPSINW is the
indirect non-work trip increase, and INCWH and INCNH are the rates of increased
SOV work and non-work trip making by household members of TCM
participants who leave their vehicles at home. The other parameter in the
formulas is defined in an earlier step of the methodology.
INCWH is defined as NV * SHR * (SIZE - 1) * EMP * TGW, where NV is the fraction of the
population that does not own a vehicle (Note: This analysis interprets this parameter to mean the
percentage of drivers without a vehicle, which is estimated as the percentage of vehicle-owning
households in the program area that have only one vehicle.), SHR is the fraction of shared mode trips,
SIZE is average household size, EMP is the fraction of the population that is employed, and TGw is the
work trip generation rate for SOV users. NV is assumed to be 44%, based on U.S. Census data for
Tompkins County. The TDMP data indicate that 13.2% of work trips are in carpools and 14.7% are on
buses, resulting in an SHR estimate of 27.9%. (Note: This variable uses estimates generated after TCM
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introduction.) SIZE is assumed to be 2.46, based on 1990 U.S. Census data. The value for BMP is 59%
and is taken from 1990 U.S. Census data. Based on an example in the TCM guidance, TGW is assumed
to equal 1.71. Based on these numbers, INCWH = 0.44 * 0.279* (2.46 - 1) * 0.59 * 1.71=0.18.
INCNH is defined as NV * SHR * (SIZE - 1) * UNEMP * TGN, where NV, SHR, and SIZE are as
defined above, UNEMP is the fraction of the population that is not employed, and TGN is the non-work
trip generation rate for SOV users. UNEMP is simply (1 - EMP) and thus equals 41%. TGN is assumed
to be the same as TGW (i.e., 1.71). Based on these numbers, INCNH = 0.44 * 0.279 * (2.46 - 1) * 0.41
* 1.71 =0.13.
Using the data above, ATRIPSIW = 0.18* -(-2,435) / 2 = 219, and ATRIPSINW = 0.13* -(-2,435)
12= 158. Summarizing these results, the TDMP is indirectly responsible for an increase of 219 work
trips per day and 158 non-work trips per day.
Step 4 in EPA's methodology for estimating travel activity effects of TCMs, which involves
determining direct peak and off-peak period trip shifts, is not relevant to the analysis of the TDMP.
Step 5 in the travel activity methodology involves estimating the net trip changes from the
TDMP as distributed between work and non-work trips and peak and off-peak periods. These changes
are calculated using the following formulas:
ANETRPWP = (o * ATRIPSSp + PKW * (ATRIPSDW + ATRIPSIW)
ANETRPWOP = (o * ATRIPSSOP + (1 - PKW) * (ATRIPSDW + ATRIPSIW)
ANETRP^p = (!-«)* ATRIPSSP + PK^ * (ATRIPSDNW + ATRIPSINW)
= (!-«)* ATRIPSSOP + (1 - PK^) * (ATRIPSDNW + ATRIPSINW)
In the formulas, ANETRPWP is the net work trip change in the peak period,
ANETRPW op is net work trip change in the off-peak period, ANETRP^p is the
net non-work trip change in the peak period, and ANETRP^ jOP is the net
non-work trip change in the off-peak period. ATRIPSSP is the change in peak
period trips, and ATRIPSS OP is the change in off-peak period trips. PKW is the
observed fraction of work trips during the peak period, and PK^ is the observed
fraction of non-work trips during the peak period. The other parameters in the
formulas are defined in earlier steps of the methodology.
Because there are no trip shifts associated with the TDMP (see Step 4), ATRIPSSP and
ATRIPSSOP are each equal to 0.
The values used for PKW and PK^ are 0.7 and 0.3, respectively, based on an example in the
TCM guidance and assuming that peak travel hours are from 6 a.m. to 9 a.m. and 4 p.m. to 7 p.m.
Using the data above, ANETRPWP = 0 + 0.7 * (-2,435 + 219) = -1,551, ANETRPWOP = 0 + (1 -
0.7) * (-2,435 + 219) = -665, ANETRP^'p = 0 + 0.3 * (0 + 158) = 47, and ANETRP^op = 0 * (1 - 0.3)
* (0 + 158) = 107. Summarizing these results, the TDMP results in net decreases in peak and off-peak
work trips of 1,55 1 per day and 665 per day, respectively. The program also results in increases in peak
and off-peak non-work trips of 47 per day and 107 per day, respectively.
Step 6 in the travel activity methodology involves estimating the peak and off-peak VMT
changes due to the trip changes from the TDMP. These changes are calculated using the following
formulas:
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AVMTp = (ANETRPWP * DISTW) + (ANETRP^p
AVMTOP = (ANETRPWOP * DISTW) + (ANETRP^op * DIST^)
In the formulas, AVMTP is the change in peak-period VMT due to trip changes,
AVMTOP is the change in off-peak VMT due to trip changes, DISTW is the
average VMT per trip for work trips, and DIST^ is the average VMT per trip
for non-work trips. The other parameters in the formulas are defined in earlier
steps of the methodology.
DISTW is derived to be 8.5 1 miles per trip based on the analysis of modal choice. DIST^ is
assumed to be 6.3 miles, based on work trip data for Tompkins County and data on work and non-work
trip distances reported in the 1996 Statistical Abstract of the United States .
Using the data above, AVMTP = (-1,551 * 8.51) + (47 * 6.3) = -12,903 and AVMTOP = (-665 *
8.51) + (107 * 6.3) = -4,978. Summarizing these results, the TDMP reduces peak-period VMT by 12,903
miles per day due to trip changes and reduces off-peak VMT by 4,978 miles per day due to trip changes.
Step 7 in the travel activity methodology involves estimating the VMT changes due to trip length
changes resulting from the TDMP. This step is not necessary, as it has been accounted for in the
estimation of ATRIP SD.
Step 8 in the travel activity methodology involves estimating the total peak and off-peak VMT
changes resulting from the TDMP. These changes are calculated using the following formulas:
ANETVMTp = AVMTp + PKW * AVMTLW + PK^ * AVMTLNW
ANETVMT0p = AVMTOP + (1 - PKW) * AVMTL>W + (1 - PK^) * AVMTL>NW
In the formulas, ANETVMTp is the total change in peak period VMT, and
ANETVMTOP is the total change in off-peak VMT. The other parameters in the
formulas are defined in earlier steps of the methodology.
Because VMT changes due to trip length changes have already been accounted for in the
analysis, AVMTL w and AVMTLNW are each set equal to 0.
Using the data above, ANETVMTp = -12,903 + 0.7*0 + 0.3*0 = -12,903 and ANETVMTOP
= -4,978 + (1 - 0.7) * 0 + (1 - 0.3) * 0 = -4,978. Summarizing these results, the TDMP reduces peak-
period VMT by a total of 12,903 miles per day and off-peak VMT by a total of 4,978 miles per day.
Step 9 in the travel activity methodology involves estimating peak and off-peak speed changes
resulting from the TDMP. These changes are calculated using the following formulas:
ASPDp = (ANETVMTp / TOTVMTP) * ep
ASPDOP = (ANETVMT0p/ TOTVMT0p) * eop
In the formulas, ASPDP is the percentage change in peak-period speeds, ASPDOP
is the change in off-peak speeds, TOTVMTP is total peak-period VMT for the
program area, TOTVMTOP is total off-peak VMT for the program area, ep is the
elasticity of peak-period speed with respect to volume, and eop is the elasticity
of off-peak speed with respect to volume. The other parameters in the formulas
are defined in earlier steps of the methodology.
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Total VMT in Tompkins County is approximately 1,662,000 miles per day. This analysis
assumes that half of this VMT is work-related. Combining this information with the assumptions from
Step 5 that 70% of work-related trips occur in the peak period and 30% of non-work trips occur in the
peak period yields a value of 831,000 miles per day for each of TOTVMTP and TOTVMTOP.
The parameter ep is assumed to be -0.75, based on an example provided in the TCM guidance
document. The parameter eop is assumed to be 0, because changes in off-peak VMT are not likely to
affect vehicle speeds (i.e., due to a lack of congestion).
Using the data above, ASPDP = -12,903
/ 831,000 * -0.75 = 0.0116 and ASPDOP = -4,978
/ 831,000 * 0 = 0. Summarizing these results,
the TDMP increases peak-period speeds by approximately 1.16% but has no effect on
off-peak speeds.
Phase 3: Emission Effects STEP 1 (Trip Changes)
Step 1 in the estimation of the emission
effects for the TDMP involves calculating the
effect of trip changes on emissions. This step
is broken down into seven smaller steps
(la through Ig), which are outlined below.
Step la in the emission methodology
involves estimating the distribution of trip
changes for the TDMP. These changes are
calculated using the following formulas:
YTMP.LDGV ~ TRIPLDGV / (TRIPLDGV + TRIPLDGT1)
YTRIRLDGTI = 1 YTRIRLDGV
Phase 3: Effects on Emissions
Step 1: Effect of trip changes on emissions
la: Distribution of trip changes among vehicle
types
Ib: Changes in cold-start and hot-start trips
Ic: Cold-start and hot-start emission factors by
pollutant and vehicle type
Id: Cold-start and hot-start emission changes
for the project
le: Hot-soak emission changes
If: Diurnal changes by vehicle type
Ig: Summation of trip related emission changes
Step 2: Effect of VMT changes on emissions
2a: Distribution of VMT changes among
vehicle types
2b: Hot-stabilized exhaust emission changes by
vehicle type
2c: VMT-related evaporative emission changes
2d: Summation of VMT-related emission
changes
Step 3: Emission effects due to speed changes
3 a: Peak and off-peak speed after
implementation
3b: Peak and off-peak VMT after
implementation
3c: Peak and off-peak emissions changes due
to changes in speeds
3d: Summation of speed related changes
Step 4: Summation of emission effects
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In the formulas, YTRIP.LDGV is the fraction of TCM-affected trips taken by light-
duty gasoline vehicles (LDGVs), YTRTP.LDGTI is the fraction of TCM-affected trips
taken by light-duty gasoline trucks (LDGTls), TRIPLDGV is the fraction of total
trips in the region taken by LDGVs, and TRIPLDGT1 is the fraction of total trips in
the region taken by LDGTls. (Note: Most TCMs that can be analyzed using
EPA's guidance document affect only LDGVs or LDGTls. Thus, the sum of
YTRTP.LDGV and YTRTP.LDGTI is typically equal to one.)
According to a study on the TDMP, TRIPLDGV and TRIPLDGTli/or the program area are equal
to 0.86 and 0.14, respectively.
Using the data above, YTRTP.LDGV = °-86 / (°-86 + °-14) = °-86 and YTRIP.LDGTI = 1 - °-86 = °-14-
Summarizing these results, 86% of the trips affected by the TDMP are taken by LDGVs, and 14% are
taken by LDGTls.
Step Ib in the emission methodology involves calculating cold-start and hot-start trip changes
for the TDMP. These changes are calculated using the following formulas:
ATRIPSCST = YCSTW * (ANETRPWP + ANETRPWOP) + YCST NW * (ANETRP^p + ANETRP^p)
ATRIPSHST = (1 - YCSTW) * (ANETRPWP + ANETRPWOP) + (1 - YCSTNW) *
In the formulas, ATRIPSCST is the number of cold-start trip changes, ATRIPSHST
is the number of hot-start trip changes, YCST w is the fraction of work trips begun
in the cold-start mode, and YCST NW is the fraction of non-work trips begun in the
cold-start mode. The other parameters in the formulas are defined in earlier
steps of the methodology.
Because work trips are mostly cold-start trips, the guidance calls for YCST w to be set equal to 1 .
The guidance also suggests that YCSTNW be set equal to 0.43, which is the default fraction of cold starts
used in the Federal Test Procedure (FTP).
Using the data above, ATRIPSCST = 1 * (-1,551 + -665) + 0.43 * (47 + 107) = -2,150 and
ATRIPSHST = (1 - 1) * (-1,551 + -665) + (1 - 0.43) * (47 + 107) = 88. Summarizing these results, the
TDMP results in a reduction of 2,150 cold-start trips per day and an increase of 88 hot-start trips per day.
Step Ic in the emission methodology involves determining cold-start and hot-start emission
factors. These changes are calculated^or a given pollutant and vehicle class using the following
formulas:
= (EXH10oo/oCST,26MPH " EXHlclQo/oSTB)26MPH) 3.59
HST = (EXH10oo/oHST)26MPH " EXHlclQo/oSTB)26MPH) 3.59
In the formulas, CST is the cold-start emission factor in grams per trip, HST
is the hot-start emission factor in grams per trip, and EXH is the MOBILE
emission factor in grams per mile. The 3.59 factor is the FTP driving cycle
trip-start miles per trip, and 26 miles per hour is the speed for the start portion
of the FTP driving cycle. (Note: The subscripts on EXH refer to the operating
conditions and speed at which MOBILE evaluates EXH. For example,
"100%CST,26MPH" indicates 100% cold-start operating mode at 26 miles per
hour vehicle speed.)
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Using national default data from MOBILE, CSTLDGVHC = (2.55 - 0.95) * 3.59 = 5.74 grams per
trip, CSTLDGT1HC = (3.59 - 1.34) * 3.59 = 8.08 grams per trip,' HSTLDGVHC = (1.35 - 0.95) * 3.59 = 1.44
grams per trip, and HSTLDGT1 HC = (1.99 - 1.34) * 3.59 = 2.33 grams per trip. (Following the same
methodology, the cold-start and hot-start emission factors can also be determined for NOx and CO.)
Step Id in the emission methodology involves determining cold-start and hot-start emission
changes for the TDMP. These changes are calculated using the following formulas:
AriCCST (AlKlrSCST YTRTP.LDGV CS1LDGV)HC) + (AlKlrSCST YTRTP.LDGTI
AHCHST (A 1 R1PSHST YTRIP.LDGTI "-^ J- LDGV.HC) + (A1R1PSHST YTRIP.LDGTI
AJNOxCST (AlKlrSCST YTRTPLDGV CSlLDGVNOx) + (A 1 Kir SCST YTRIPLDGTI CSlLDGT1NOx)
ANOxHST = (ATRIPSHST * YTRTP.LDGTI * HSTLDGV,NOx) + (ATRIPSHST * YTRTP.LDGTI * HSTLDGTUNOx)
ACOCST (AlKlrSCST YTRTP.LDGV CS1LDGV)CO) + (AlKlrSCST YTRTP.LDGTI
ACOHST (A 1 K1PSHST YTRTP.LDGTI -n-blLDGV)CO) + (A1R1PSHST YTRIP.LDGTI
In the formulas, AHCCST, ANOxCST, and ACOCST are the changes in cold-start
emissions for HC, NOx, and CO, respectively; and AHCHST, ANOxHST, and
ACOHST are the changes in hot-start emissions for HC, NOx, and CO,
respectively. The other parameters in the formulas are defined in earlier steps
of the methodology.
Using national default data from MOBILE, AHCCST = (-2,150 * 0.86 * 5.74) + (-2,150 * 0.14
* 8.08) = -13,045 and AHCHST = (88 * 0.86 * 1.44) + (88 * 0.14 * 2.33) = 138. Summarizing these
results, the TDMP results in a reduction in cold-start HC emissions of 13,045 grams per day and an
increase in hot-start HC emissions of 138 grams per day. (Following the same methodology, the cold-
start and hot-start emission changes can also be determined for NOx and CO.)
Step le in the emission methodology involves determining hot soak emission changes for the
TDMP. These changes are calculated using the following formula:
AHCHSK = (ATRIPSTOTAL * YTRIP.LDGV * HSKLDGV) + (ATRIPSTOTAL * YTRIP.LDGTI * HSKLDGT1)
In the formula, AHCHSK is the change in hot soak emissions, ATRIPSTOTAL is the
total change in trips, and HSK is the hot soak emission factor in grams per trip.
(Note: Hot soak emissions are HC emissions only.)
ATRIPSTOTAL = ANETRPWP + ANETRPWOP + ANETRP^p + ANETRP^p.
Thus, ATRIPSTOTAL = -1,551 + -665 + 47 + 107 = -2,062.
Using national default data from MOBILE, AHCHSK = (-2,062 * 0.86 * 3.06) + (-2,062 * 0.14
* 3.60) = -6,466. Summarizing this result, the TDMP results in a reduction in hot soak emissions of
6,466 grams per day.
Step If in the emission methodology involves determining diurnal emission changes for
the TDMP. These changes are calculatedyfor a given vehicle class using the following formulas:
AHCDNL w = 0.676 * (ANETRPWP + ANETRPWOP) / TPDW * YTRTP * (WDI - MDI)
AHCDNL^ = 0.676 * (ANETRP^p + ANETRP^p) / TPD^ * YTRTP * (WDI - MDI)
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AHCDNL AHCDNL)WjLDGV + AHCDNLjNW)LDGV + AHCDNLjW)LDGT1 + AHCDNL)NWjLDGT1
In the formulas, AHCDNL w is the change in diurnal emissions associated with
work trips, AHCDNLNW is the change in diurnal emissions associated with non-
work trips, and AHCDNL is the total change in diurnal emissions. TPDW is the
number of work trips per day per vehicle, and TPD^ is the number of non-work
trips per day per vehicle. WDI is the weighted diurnal emission factor in grams,
and MDI is the multi-day diurnal emission factor in grams. The other parameters
in the formulas are defined in earlier steps of the methodology. (Note: Diurnal
emissions are HC emissions only.)
The value used for TPDW is 2, since a commuter makes typically makes two work trips per day
(i.e., one trip from home to work, one trip from work to home). TPD^ is equal to TGN from Step 3 of
the "Travel Activity Effects" section above, and thus equals 1.71.
Using national default data from MOBILE, AHCDNLWLDGV = 0.676 * (-1,551 + -665) / 2 * 0.86
* (3.30 - 6.04) = 1,765, AHCDNLNWLDGV = 0.676 * (47 + 107) / 1.71 * 0.86 * (3.30 - 6.04) = -143,
AHCDNLWLDGT1 = 0.676 * (-1,551 + -665) / 2 * 0.14 * (5.11 - 15.33) = 1,072, AHCDNLNWLDGT1 = 0.676
* (47 + 107)71.71 *0.14* (5.11 - 15.33) =-87, and AHCDNL = 1,765 +-143 + 1,072 +-87 = 2607.
Summarizing these results, the TDMP results in a net increase in diurnal emissions of 2,607 grams
per day.
Step lg in the emission methodology involves calculating the total trip-related emission changes
for the TDMP. These changes are calculated using the following formulas:
AHCTRff = AHCCST + AHCHST + AHCHSK + AHCDNL
ANOxTRIP = ANOxCST + ANOxHST
ACOTRff = ACOCST + ACOHST
In the formulas, AHCTRIP, ANOxTRIP, and ACOTRIP are the total changes in HC,
NOx, and CO emissions, respectively, due to trip changes.
Using the data above, AHCTRIP = -13,045 + 138 + -6,466 + 2,607 = -16,766. Summarizing this
result, the TDMP results in a net decrease in trip-related HC emissions of 16,766 grams per day.
(Following the same methodology, total trip-related emission changes can also be determined for NOx
and CO.)
Emission Effects STEP 2 (VMT Changes)
Step 2 in the estimation of the emission effects for the TDMP involves calculating the effect
of VMT changes on emissions. This step is broken down into four smaller steps (2a through 2d), which
are outlined below.
Step 2a in the emission methodology involves estimating the distribution of VMT changes for
the TDMP. These changes are calculated using the following formulas:
YVMT.LDGV = VMTLDGV / (VMTLDGV + VMTLDGT1)
YVMI.LDGTI 1 ~ YVMT.LDGV
In the formulas, YVMT LDGV is th£ fraction of TCM-affected VMT for light-duty
gasoline vehicles (LDGVs), YTRTPLDGTI is th£ fraction of TCM-affected VMT
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for light-duty gasoline trucks (LDGTls), VMTLDGV is the fraction of total VMT
in the region for LDGVs, and VMTLDGT1 is the fraction of total VMT in the
region for LDGTls. (Note: Most TCMs that can be analyzed using EPA's
guidance document affect only LDGVs or LDGTls. Thus, the sum of YVMT.LDGV
and YVMT.LDGTI is typically equal to one.)
According to a study on the TDMP, VMTLDGV and VMTLDGTli/or the program area are equal
to 0.86 and 0.14, respectively.
Using the data above, YVMT.LDGV = °-86 / (°-86 + °-14) = °-86 and YVMT.LDGTI = 1 - °-86 = °-14-
Summarizing these results, 86% of the VMT affected by the TDMP is by LDGVs, and 14% is by
LDGTls.
Step 2b in the emission methodology involves estimating hot-stabilized exhaust emission
changes for the TDMP. These changes are calculated using the following formulas:
AHCsmP = (ANETVMTP * YVMT.LDGV * STBLDGV3QP) + (ANETVMTP * YVMT,LDGTI * STBLDGT13QP)
AHCsmoP = (ANETVMT0p * YVMT.LDGV * STBLDGVjHQOP) + (ANETVMTOP * YVMT.LDGTI * STBLDGT1]HQOP)
ANOxSTBP = (ANETVMTP * YVMTLDGV * STBLDGVNOxP) + (ANETVMTP * YVMTLDGTI * STBLDGT1NOxP)
ANOxsmop = (ANETVMTOP * YVMT,LDGV * STBLDGV,NOx,OP) + (ANETVMTOP * YVMT.LDGTI *
ACOsmP = (ANETVMTP * YVMT.LDGV * STBLDGVmP) + (ANETVMTP * YVMT.LDGTI * STBLDGTUCOJ))
ACOSTB>OP = (ANETVMTOP * YVMT.LDGV * STBLDGViCO)OP) + (ANETVMTOP * YVMT.LDGTI * STBLDGTliCO)OP)
In the formulas, AHCSTB P, ANOxSTB P, and ACOSTB P are the peak-period changes
in hot-stabilized emissions for HC, NOx, and CO, respectively; and AHCSTB OP,
ANOxSTBOP, and ACOSTBOP are the off-peak changes in hot-stabilized emissions
for HC, NOx, and CO, respectively. STBP is the hot-stabilized emission factor
(in grams per mile) for each pollutant and vehicle class for the peak period
(during which average vehicle speed is assumed to be 20 miles per hour),
and STBOP is the hot-stabilized emission factor (in grams per mile) for each
pollutant and vehicle class for the off-peak period (during which average vehicle
speed is assumed to be 35 miles per hour). The other parameters in the formulas
are defined in earlier steps of the methodology.
Using national default data from MOBILE, AHCSTBP = (-12,903 * 0.86 * 1.23) + (-12,903 * 0.14
* 1.77) = -16,846 and AHCSTBOP = (-4,978 * 0.86 * 0.69) + (-4,978 * 0.14 * 0.94) = -3,609. Summarizing
these results, the TDMP results in a reduction in peak-period hot-stabilized HC exhaust emissions
of 16,846 grams per day and a reduction in off-peak hot-stabilized HC exhaust emissions of 3,609 grams
per day. (Following the same methodology, hot-stabilized exhaust emission changes can also be
determined for NOx and CO.)
Step 2c in the emission methodology involves estimating VMT-related evaporative emission
changes for the TDMP. These changes are calculated using the following formulas:
= (ANETVMTP * YVMT.LDGV * VEVPLDGV,P) + (ANETVMTP * YVMT.LDGTI * VEVPLDGT,P)
= (ANETVMTOP * YVMT.LDGV * VEVPLDGvOP) + (ANETVMTOP * YVMT.LDGTI * VEVPLDGT1 ,OP)
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In the formulas, AHC^y^ is the change in peak-period evaporative emissions,
AHCvEvp OP is the change in off-peak evaporative emissions, and VEVP is the
VMT-related evaporative emission factor (in grams per mile) for each vehicle
class and time period (peak or off-peak). The other parameters in the formulas
are defined in earlier steps of the methodology. (Note: Evaporative emissions
are HC emissions only.)
Using national default data from MOBILE, AHC^p = (-12,903 * 0.86 * 0.44) + (-12,903
* 0.14 * 0.53) = -5,840 and AHC^y^ = (-4,978 * 0.86 * 0.34) + (-4,978 * 0.14 * 0.44) = -1,762.
Summarizing these results, the TDMP results in a reduction in peak-period evaporative emissions
of 5,840 grams per day and a reduction in off-peak evaporative emissions of 1,762 grams per day.
Step 2d in the emission methodology involves calculating the total VMT-related emission
changes for the TDMP. These changes are calculated using the following formulas:
= AHCSTB)P + AHCSTB)OP + AHC^^f
ANOXvMT = ANOxSTBP + ANOxSTB OP
T = ACOsmP + ACOsmoP
In the formulas, AHCy^-, ANOxy^., and ACOyMj are the total changes in HC,
NOx, and CO emissions, respectively, due to VMT changes.
Using the data above, AHC^ = -16,846 + -3,609 + -5,840 + -1,762 = -28,057. Summarizing
this result, the TDMP results in a net decrease in VMT-related HC emissions of 28,057 grams per day.
(Following the same methodology, total VMT-related emission changes can also be determined for NOx
and CO.)
Emission Effects STEP 3 (Speed Changes)
Step 3 in the estimation of the emission effects for the TDMP involves calculating the effect
of speed changes on emissions. This step is broken down into four smaller steps (3a through 3d), which
are outlined below.
Step 3a in the emission methodology involves estimating the speeds associated with the TDMP.
These speeds are calculated using the following formulas:
SPEEDPTCM = SPEEDPBASE * (1 + ASPDP)
SPEEDOPJCM = SPEEDOP3ASE * (1 + ASPDOP)
In the formulas, SPEEDPTCM is the peak-period speed after implementation of the
TCM, SPEEDOPTCM is the off-peak speed after implementation of the TCM,
SPEEDPBASE is the peak-period speed prior to implementation of the TCM,
and SPEEDOPBASE is the off-peak speed prior to implementation of the TCM.
The other parameters in the formulas are defined in earlier steps of the
methodology.
For this analysis, SPEEDPBASE is assumed to be 30 miles per hour, and SPEEDOPBASE is assumed
to be 35 miles per hour.
Using the data above, SPEEDPTCM = 30*(l+0.0116) = 30.35and SPEEDOPTCM = 35 * (1 + 0)
= 35. Summarizing these results, peak-period speeds have slightly increased from 30 miles per hour
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to 30.35 miles per hour due to the TDMP. Off-peak speeds have not changed due to the program.
Step 3b in the emission methodology involves estimating the total VMT for the program area
after implementation of the TDMP. These VMT figures are calculated using the following formulas:
VMTp TCM = TOTVMTp + ANETVMTP
VMTOPJCM = TOTVMT0p + ANETVMTOP
In the formulas, VMTP TCM is the total peak-period VMT in the program area
after implementation of the TCM, and VMTOPTCM is the total off-peak VMT
in the program area after implementation of the TCM. The other parameters
in the formulas are defined in earlier steps of the methodology.
Using data from Step 9 of the "Travel Activity Effects" section above, VMTPTCM = 831,000
+ -12,903 = 818,097 and VMTOPTCM = 831,000 + -4,978 = 826,022. Summarizing these results,
peak-period VMT has decreased from 83 1 ,000 miles per day to 8 1 8,097 miles per day due to the TDMP.
Off-peak VMT has decreased from 83 1,000 miles per day to 826,022 miles per day due to the program.
Step 3c in the emission methodology involves estimating peak-period and off-peak emission
changes due to changes in vehicle speeds. These changes are calculated using the following formulas:
AHCSPDjP = VMTPJCM * (STBFLT)HQPJCM + RNLFLTjPJCM) - VMTPJCM * (STBFLT)HQP3ASE + RNLFLTjP3ASE)
AHCSPDjOp ~~ V M 1 OP)TCM (k-l-BFLTiHC)Opj.CM + FLT.OP.TCM) " * M 1 OP)TCM (o-l-DFLT)HQOpjBASE
ANOxSPDiP VM 1 PjCM (S 1 -t>FLT,NOx,P,TCM " S I i>FLT,NOx,P,BASE)
ANOxSPDjOp VM 1 OPJCM (S I -t>FLT,NOx,OP,TCM "SI -t>FLT,NOx,OP,BASE)
ACOSPD)P VM 1 PJCM (S 1 -t>FLTiCO)PjcM "SI BFLTiCOjPiBASE)
ACOSPD)Op VM 1 OPJCM (S I -t>FLT,co,op,TCM -SI -DFLT,CO,OP,BASE)
In the formulas, AHCSPDP, ANOxSPDP, and ACOSPDP are the peak-period changes
in emissions for HC, NOx, and CO, respectively, due to a change in speeds;
and AHCSPD OP, ANOxSPD OP, and ACOSPD OP are the off-peak changes in emissions
for HC, NOx, and CO, respectively, due to a change in speeds. STBFLT is the
fleet-wide hot-stabilized emission factor (in grams per mile) for each pollutant,
time period (i.e., peak or off-peak), and scenario (i.e., base or TCM). RNLFLT
is the fleet-wide running loss emission factor (in grams per mile) for each time
period and scenario. The other parameters in the formulas are defined in earlier
steps of the methodology.
Based on data showing the relationship between vehicle speed and emissions, this analysis
assumes that the elasticity of STBFLT with respect to speed is -1 for HC, 0 for NOx, and -1 for CO.
Thus, a 1% increase in speed is assumed to result in a 1% decrease in HC and CO emissions (on a grams
per mile basis) and no change in NOx emissions. The elasticity of RNLFLT with respect to speed is also
assumed to be -1.
Using national default data from MOBILE, AHCSPDP = 818,097 * (1.916 + 0.1 19) - 818,097
* (1.938 + 0.120) = -18,816 and AHCSPDOP = 826,022 * (1.938 + 0.120) - 826,022 * (1.938 + 0.120) = 0.
Summarizing these results, the TDMP results in a decrease in speed-related HC emissions of 18,816
grams per day for the peak period but does not change speed-related HC emissions for the off-peak
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period. (Following the same methodology, the peak-period and off-peak emission changes due to
changes in speeds can also be determined for NOx and CO.)
Step 3d in the emission methodology involves calculating the total speed-related emission
changes for the TDMP. These changes are calculated using the following formulas:
AriCSPD AriCSPDiP + AriCSPD)OP
ANOxSPD = ANOxSPD)P + ANOxSPD)OP
ACOSPD
In the formulas, AHCSPD, ANOxSPD, and ACOSPD are the total changes in HC,
NOx, and CO emissions, respectively, due to speed changes.
Using the data above, AHCSPD = -18,816 + 0 = -18,816. Summarizing this result, the TDMP
results in a net decrease in speed-related HC emissions of 18,816 grams per day. (Following the same
methodology, total speed-related emission changes can also be determined for NOx and CO.)
Emission Effects - STEP 4 (Total)
Step 4 in the estimation of the emission effects for the TDMP involves calculating the total
changes in HC, NOx, and CO emissions. These changes are calculated using the following formulas:
AHC = AHCTRff + AHCvMT + AHCSPD
ANOx = ANOxTRIP + ANOxvMT + ANOxSPD
AGO = ACOTRff + ACOvMT + ACOSPD
In the formulas, AHC, ANOx, and AGO are the total changes in HC, NOx,
and CO emissions, respectively, due to the TCM program.
Using the data above, AHC = -16,766 + -28,057 + -18,816 = -63,639. Summarizing this result,
the TDMP results in a net decrease in HC emissions of 63,639 grams per day, or approximately 0.07 tons
per day. (Following the same methodology, total emission changes can also be determined for NOx
and CO.)
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