how does the use of light rail park-and-ride facilities in charlotte influence vehicle emissions and...
DESCRIPTION
Park-and-ride lots are often promoted as an easy, cheap and equitable way of providing transit to a much broader population that increases transit ridership. The purpose of this thesis is to determine an estimate as to what extent VMT and vehicle emissions have increased or decreased as a result of light rail park-and-ride usage and, additionally, to find out if the literature discussed holds true in the Charlotte, NC example. For this study, two estimates will be created, one indicating VMT and emissions of park-and-ride users with existing conditions and another indicating VMT and emissions with conditions before the light rail was built, assuming that all park-and-ride users drove to their destination. Another component of this thesis was to observe and estimate to what extent the VMT savings would be if all park-and-ride lots were replaced with transit-oriented developments of varying densities.TRANSCRIPT
1
How does the Use of Light Rail Park-and-ride Facilities in Charlotte
Influence Vehicle Emissions and Create more Vehicle Miles
Traveled?
By
David Cook
A thesis submitted to the University of North Carolina at Charlotte
Graduate Department of Geography and Earth Sciences
Charlotte
Spring 2011
Professor Michael Duncan
2
Abstract
How does the Use of Light Rail Park-and-ride Facilities in Charlotte Influence Vehicle
Emissions and Create more Vehicle Miles Traveled?
Park-and-ride lots are often promoted as an easy, cheap and equitable way of providing
transit to a much broader population that increases transit ridership. The purpose of this thesis is
to determine an estimate as to what extent VMT and vehicle emissions have increased or
decreased as a result of light rail park-and-ride usage and, additionally, to find out if the literature
discussed holds true in the Charlotte, NC example. For this study, two estimates will be created,
one indicating VMT and emissions of park-and-ride users with existing conditions and another
indicating VMT and emissions with conditions before the light rail was built, assuming that all
park-and-ride users drove to their destination. Another component of this thesis was to observe
and estimate to what extent the VMT savings would be if all park-and-ride lots were replaced
with transit-oriented developments of varying densities.
The final analysis of the two estimates indicated a 50% drop in vehicle miles traveled
among park-and-ride users by traveling to park-and-ride lots instead of directly in the CBD.
Emission reductions varied by vehicle type and emission type but were 11 – 37 percent range for
each emission type. However, this impact is considered to be minimal in the overall reduction of
VMT and emissions, as the amount of people using park-and-ride and light rail as an option for a
trip is small compared to the amount of similar trips being made overall by all modes. Overall
regional VMT reduction is estimated to be about 0.2 percent as a result of park-and-ride users
using park-and-ride and light rail instead of driving the full distance.
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List of Figures
Figure 1: Study Area Locater Map Page 9
Figure 2: Average VMT by Station, All Stations and All Park-and-Ride
Stations Page 25
Figure 3: Average VMT by Station, All Stations and All Park-and-Ride
Stations Page 27
Figure 4: Average VMT by Station, All Stations and All Park-and-Ride
Stations (hypothetical) Page 30
Figure 5: Absolute Change in VMT between Scenario 1 (Home-Station) and
Scenario 2 (Home-Final Destination) among Survey Respondents Page 32
Figure 6: Average VMT by Station, All Stations and All Park-and-Ride
Stations (hypothetical) Page 34
Figure 7: Difference in VMT between Survey Sample all Users for
Hypothetical Scenario Page 35
Figure 8: Absolute Change in VMT between Scenario 1 (Home-Station)
and Scenario 2 (Home-Final Destination) for all estimated
Park-and-Ride Users in a given day Page 37
Figure 9: Total CO Emissions, CO Emissions per Mile, and CO Emissions
per User in grams for a 2001 average age vehicle for both LDV
and LDT Vehicle Types Page 40
Figure 10: Total HC Emissions, HC Emissions per Mile, and HC Emissions
per User in grams for a 2001 average age vehicle for both LDV
and LDT Vehicle Types Page 41
Figure 11: Total NOx Emissions, NOx Emissions per Mile, and NOx Emissions
per User in grams for a 2001 average age vehicle for both LDV and
LDT Vehicle Types Page 42
Figure 12: Total CO Emissions for Cars and Trucks for each Station Page 44
Figure 13: Average per User CO Emissions assuming Cars and Trucks
for Each Station Page 45
Figure 14: Total HC Emissions for Cars and Trucks for each Station Page 46
Figure 15: Average per User HC Emissions for Cars and Trucks for Each Station Page 47
Figure 16: Total NOx Emissions for Cars and Trucks for each Station Page 48
Figure 17: Average per User NOx Emissions for Cars and Trucks for Each Station Page 49
Figure 18: Total CO Emissions, CO Emissions per Mile, and CO Emissions
per User in grams for a 2001 average age vehicle for both LDV
and LDT Vehicle Types Page 52
Figure 19: Total HC Emissions, HC Emissions per Mile, and HC Emissions
per User in grams for a 2001 average age vehicle for both LDV
and LDT Vehicle Types Page 53
Figure 20: Total NOx Emissions, NOx Emissions per Mile, and NOx Emissions
per User in grams for a 2001 average age vehicle for both LDV and
LDT Vehicle Types Page 54
Figure 21: Total CO Emissions for Cars and Trucks for each Potential Station
(Home – Final Destination) Page 57
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Figure 22: Average Per User CO Emissions for Cars and Trucks for Each
Potential Station (Home – Final Destination) Page 58
Figure 23: Total HC Emissions for Cars and Trucks for each Potential Station
(Home – Final Destination) Page 59
Figure 24: Average Per User HC Emissions for Cars and Trucks for Each
Potential Station (Home – Final Destination) Page 60
Figure 25: Total NOx Emissions for Cars and Trucks for each Potential Station
(Home – Final Destination) Page 61
Figure 26: Average Per User NOx Emissions for Cars and Trucks for Each
Potential Station (Home – Final Destination) Page 62
Figure 27: Aggregate CO Emissions for Cars (LDV’s) for the Home – Station
Scenario and the Home – Final Destination Scenario Page 65
Figure 28: Average Per User CO Emissions for Cars (LDV’s) for the
Home – Station Scenario and the Home – Final Destination Scenario Page 65
Figure 29: Aggregate CO Emissions for Trucks (LDT’s) for the Home – Station
Scenario and the Home – Final Destination Scenario Page 66
Figure 30: Average Per User CO Emissions for Cars (LDV’s) for the
Home – Station Scenario and the Home – Final Destination Scenario Page 66
Figure 31: Total Hot Soak HC Emissions (in grams) by Station for all
Park-and-Ride Users assuming 100 percent ideal sunny and partly
cloudy weather Page 70
Figure 32: Total Running and HC Emissions in the Home – Station Scenario
for Cars (LDV’s) 100 percent ideal sunny and partly cloudy weather Page 71
Figure 33: Total Running and HC Emissions in the Home – Station Scenario
for Trucks (LDT’s) 100 percent ideal sunny and partly cloudy weather Page 71
Figure 34: Total Running and HC Emissions in the Home – Final Scenario
for Cars (LDV’s) 100 percent ideal sunny and partly cloudy weather Page 72
Figure 35: Total Running and HC Emissions in the Home – Final Scenario
for Cars (LDV’s) 100 percent ideal sunny and partly cloudy weather Page 72
Figure 36: Total Hot Soak HC Emissions (in grams) by Station for all
Park-and-Ride Users assuming 55.9 percent ideal sunny and partly
cloudy weather Page 74
Figure 37: Total Running and HC Emissions in the Home – Station Scenario
for Cars (LDV’s) 55.9 percent ideal sunny and partly cloudy weather Page 75
Figure 38: Total Running and HC Emissions in the Home – Station Scenario
for Trucks (LDT’s) 55.9 percent ideal sunny and partly cloudy weather Page 75
Figure 39: Total Running and HC Emissions in the Home – Final Scenario
for Cars (LDV’s) 55.9 percent ideal sunny and partly cloudy weather Page 76
Figure 40: Total Running and HC Emissions in the Home – Final Scenario
for Cars (LDV’s) 55.9 percent ideal sunny and partly cloudy weather Page 76
Figure 41: VMT Reduction Amounts by Scenario (500 People) Page 81
Figure 42: VMT Reduction Amounts by Scenario (1,000 People) Page 82
Figure 43: Differences in VMT reduction for the two density level scenarios Page 83
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List of Tables
Table 1: Estimated VMT for 2009 Park-and-Ride User Survey Respondents
from Home TAZ to nearest Park-and-Ride TAZ (existing conditions) Page 25
Table 2: Estimated VMT for All Park-and-Ride Users in a Given Day from
Home TAZ to nearest Park-and-Ride TAZ (existing conditions) Page 27
Table 3: Estimated VMT for 2009 Park-and-Ride User Survey Respondents
from Home TAZ to Final Destination TAZ (pre-existing conditions Page 30
Table 4: Absolute and Percent Changes in overall VMT among different Station
Categories (Survey Respondents) Page 33
Table 5: Estimated VMT for all potential 2009 Park-and-Ride Users from
Home TAZ to Final Destination TAZ (pre-existing conditions) Page 34
Table 6: Absolute and Percent Changes in overall VMT among different Station
Categories (All Estimated Users) Page 37
Table 7: Total, per user and per mile emissions by type of emission from home
to station using the 2001 model year as a base for start and running
emissions rate (all Park-and-ride users) Page 39
Table 8: Total and Average per User CO Emissions assuming Cars and Trucks
for each Park-and-Ride Station (Home – Station) Page 44
Table 9: Total and Average per User HC Emissions for Cars and Trucks for
each Park-and-Ride Station (Home – Station) Page 46
Table 10: Total and Average per User NOx Emissions for Cars and Trucks for
each Park-and-Ride Station (Home – Station) Page 48
Table 11: Total, per user and per mile emissions by type of emission from home
to final destination using the 2001 model year as a base for start and
running emissions rate (all Park-and-ride users Page 51
Table 12: Total and Average per User CO Emissions for Cars and Trucks for
each Home Park-and-Ride Station (Home – Final Destination) Page 57
Table 13: Total and Average per User HC Emissions for Cars and Trucks for
each Home Park-and-Ride Station (Home – Final Destination) Page 59
Table 14: Total and Average per User NOx Emissions for Cars and Trucks for
each Potential Park-and-Ride Station (Home – Final Destination) Page 61
Table 15: Total Hot Soak HC Emissions (in grams) by Station for all
Park-and-Ride User’s assuming 100 percent ideal sunny and partly
cloudy weather: Page 68
Table 16: Total Hot Soak HC Emissions (in grams) by Station for all
Park-and-Ride User’s assuming 55.9 percent ideal sunny and partly Page 74
cloudy weather:
Table 17: VMT reduction among TOD residents for five reduction rate scenarios
for 500 people (300 households) Page 81
Table 18: VMT reduction among TOD residents for five reduction rate scenarios
for 1,000 people (600 households) Page 82
Table 19: Average start and running emissions for cars and trucks by model year Page 90
Table 20: Survey results and data sheet (Home – Station Scenario) Page 91
Table 21: Survey results and data sheet (Home – Final Destination Scenario) Page 98
6
List of Abbreviations
ATAZ Attraction Transportation Analysis Zone
CATS Charlotte Area Transit System
CBD Central Business District
CDOT Charlotte Department of Transportation
CO Carbon Monoxide
CO2 Carbon Dioxide
CTPP Census Transportation Planning Products
DMV Department of Motor Vehicles
EPA Environmental Protection Agency
GIS Geographic Information System
HC Hydrocarbons
LDV Light Duty Vehicle
LDT Light Duty Truck
MUMPO Mecklenburg-Union Metropolitan Planning Organization
NOAA National Oceanic and Atmospheric Administration
NOx Mono-Nitrogen Oxides
PTAZ Production Transportation Analysis Zone
TAZ Traffic Analysis Zone
TOD Transit-Oriented Development
TransCAD Urban Transportation Modeling System
VHT Vehicle Hours Traveled
VMT Vehicle Miles Traveled
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Chapter 1: Introduction and Problem Statement
Park-and-ride commuter parking lots are important facilitators for the LYNX Light Rail
in Charlotte and encourage people not living in nearby Transit-Oriented Developments (mixed-
use developments centered around transit stations) to use their cars and to utilize free parking
adjacent to a transit station. Park-and-ride lots are a cheap, easy, and more equitable way of
providing transit access to a much broader population and thus increase transit ridership.
Increasing transit ridership is also a very important goal of transit agencies. Does park-and-ride
reduce VMT or does it create more VMT, thus generating more congestion and emissions and, if
so, to what extent?
The purpose of this research problem is to determine an estimate as to what extent
commuter VMT has changed (increased or decreased) as a result of having the light rail park-
and-ride. How has the aggregate commuter travel length (vehicle miles traveled) been affected
by having the light rail park-and-ride facilities? By estimating the impact of light rail park-and-
ride lots on VMT it is possible to estimate preliminary environmental effects such as cold start
(higher emissions per capita in shorter trips) and hot soak evaporative emissions using national
coefficients provided by the EPA. Using network data provided by the CDOT, it was possible to
estimate the amount of VMT change as a result of having light rail park-and-ride lots. The origin
of the park-and-ride user is important in understanding the spatial scope of park-and-ride
catchment areas and the travel behavior of park-and-ride users and will be a core part of the
proposed research question.
The following figure indicates a map of the study area, which includes every park-and-
ride station along the light rail in South Charlotte along South Boulevard. The map of the study
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area includes a general overview of the study area, location of the light rail in Charlotte, location
of light rail facilities, and the location of park-and-ride facilities, which are indicated by red
buffers. For this study, the study area will include the light rail line from Uptown to I-485 at
Pineville as well as the extended area in which park-and-ride users live around each park-and-
ride lot. The extended area is based on a 2009 on-board user survey in which the origin location
for all park-and-ride users has been recorded and grouped by Traffic Analysis Zone (TAZ).
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Figure 1: Study area locator map indicating all stations and stops along the light rail and
commuter park-and-ride lots circled in red
GIS Data and layers Source: Charlotte-Mecklenburg Planning Department
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Chapter 2: Literature Review
Rail and bus-based park-and-ride lots first appeared in the late 1960s and early 1970s in
the United Kingdom (Parkhurst 2000). Throughout the 1970s, park-and-ride lots became very
popular in the United Kingdom and eventually the concept spread into other Western European
countries and North America. Today park-and-ride lots are expanding rapidly across the world,
including Asia and South America. They have, in most cases, proven successful in attracting
auto commuters and increasing transit ridership. These lots are a more equitable (those with
access to an automobile) way of providing transit access to a much larger population than that of
transit-oriented developments and thus increase transit ridership (Burgess 2008, Parkhurst 1995
and 2000).
However, congestion remains persistent and continues to grow in cities that have park-
and-ride lots. There is a debate as to whether these facilities have actually led to an increase in
vehicle miles traveled rather than a decrease. There is a modest body of literature on the subject
of the direct and indirect effects of park-and-ride usage on increasing congestion and VMT
(vehicle miles traveled) in the UK experience but relatively little in the context of the US
experience (Parkhurst 1995 and 2000). This makes the research questions of how and to what
extent VMT has been affected in the Charlotte region an important contribution to the existing
literature. There is some evidence that park-and-ride facilities inadvertently increase congestion
and VMT through both direct and indirect effects such as induced demand (in which newly
freed-up sections of roadway created through the interception of automobiles by park-and-ride
lots are quickly filled up by new users and new types of trips) and traffic relocation (Parkhurst
1995 and 2000).
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Ideally, park-and-ride lots serve to intercept would-be trips into the center city by
capturing auto-based traffic along the way and enabling people to utilize transit for part of the
trip. In a perfect situation, every car parked at a park-and-ride lot would mean one less car
traveling into the center city. According to Parkhurst (1995), park-and-ride lots almost certainly
lead to an increase in congestion and auto traffic. Trips removed from the roadway network due
to park-and-ride auto-interception have been replaced by new trips encouraging new auto users
to quickly fill up the newly created open spaces on the road, many of which are going into the
center city (Parkhurst 1995). However, the induced demand effect can also occur if the park-and-
ride lots are replaced with transit-oriented development (TOD’s) since new TOD residents would
also be driving less. There has been modest body of articles published over the past 30 years
about the negative effects of park-and-ride lots and the indirect impacts they have on increasing
auto-based roadway congestion and traffic (Burgess 2008, Parkhurst 1995 and 2000). This
literature review will summarize scholarly papers that relate to the question of park-and-ride
impacts on VMT in Charlotte, North Carolina and draw conclusions as to why this study is
important in the broader context of the literature.
Parkhurst (1995) notes many drawbacks with regard to park-and-ride lots, including its
ineffectiveness in reducing traffic downstream of a parking site (induced demand effect). This
effect can also occur by building TOD’s. Another drawback includes abstraction of former
transit users to the automobile (former bus user’s now using park-and-ride lots). Other
drawbacks include the environmental impact of building large surface parking lots and decks on
sensitive land on the urban fringe, political inequity since it is not an open option to all even
though many times the entire population pays for its subsidies through taxes, and the increased
parking capacity which may create additional trip-end opportunities (Parkhurst 1995). After
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producing a survey for Oxford and York, Parkhurst (1995) concluded that there was a significant
amount of transit abstraction (i.e. former bus users who have switched to driving with the advent
of light rail park-and-ride lots) and that those who used park-and-ride lots were more likely to
make more discretionary trips than regular auto commuters (Parkhurst 1995). He also concluded
that there was no “decongestion dividend” in which VMT could be offset (Parkhurst 1995). He
recommended that in order for park-and-ride to be successful, it is important to consider the
region as a whole by investigating the impact of traffic growth, trip generation, and residential
self selection (Parkhurst 1995). The largest contribution of park-and-ride lots to congestion
growth was the induced demand effect in which park-and-ride creates more road space further
upstream of a station, encouraging new users and new trips for those not using the same network
beforehand (Parkhurst 1995). He also recommended policy packaging such as road pricing and
traffic calming coupled with park-and-ride lots as a means to reduce congestion and VMT
(Parkhurst 1995).
In a later article Parkhurst (2000) looks more in depth at the travel behavior of park-and-
ride users and the negative congestion/VMT-related effects of the lots. Parkhurst (2000) notes
that there is still a debate as to the true effectiveness of reducing congestion and VMT through
park-and-ride and that there is little evidence supporting the contention that it does indeed reduce
congestion (Parkhurst 2000). He also notes that in cases in which traffic-reducing policies have
been successfully implemented with park-and-ride lots the change in VMT has been slight if at
all (Parkhurst 2000). Parkhurst (2000) found that auto trips ranged from 1.5 to 12.7 kilometers
(0.9 to 7.9 miles) and that many park-and-ride users would have used transit anyway if park-and-
ride did not exist (Parkhurst 2000).
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Much of the research on park-and-ride lots comes from the United Kingdom since it has
the longest history of any country of using these lots. The spatial redistributing of traffic from a
regional scale to a more localized scale can create induced discretionary traffic (Meek, Ison, and
Enoch 2007). This induces access trips further upstream of park-and-ride lots and creates new
discretionary trips among park-and-ride users (Meek, Ison, and Enoch 2007). They also point out
that although those park-and-ride lots serve to increase auto-based traffic by themselves; they
may have an impact on reducing congestion and VMT if implemented as part of a package with
traffic-reducing policies such as road pricing, traffic calming, and parking control in the center
city, thus reducing the induced demand effect (Meek, Ison, and Enoch 2007). They also point out
that there is a dearth in the literature as to the origin (i.e. home addresses) of park-and-ride users
(Meek, Ison, and Enoch 2007). The origin is important in understanding the spatial scope of
park-and-ride catchment areas and the travel behavior of park-and-ride users and will be a core
part of the proposed research question.
The effectiveness of park-and-ride has been explored in many other works of literature.
Whitefield and Cooper (1998) indicated that the long-range effects of park-and-ride are more
complex than generally acknowledged and there is a lack of evidence showing that park-and-ride
lots reduce car-based trips (Whitefield & Cooper 1998). A research paper done by RPS (2009)
concluded that much of the benefit of park-and-ride is economic rather than sustainable in nature
(RPS 2009). In an article by Sherwin (1998), the author wrote of significant indications that
park-and-ride lots rely on auto ownership, which promotes car use and may increase journey
lengths or VMT through both direct and indirect effects (Sherwin 1998). In a more recent article
by Meek, Ison and Enoch (2009), the authors point out that in a survey of towns and cities with
park-and-ride lots 33 percent reported a VMT increase and 20 percent reported no increase or
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decline, with all other respondents indicating a slight decrease or no answer (Meek, Ison, &
Enoch 2009).
Park-and-ride lots generally do little to discourage auto ownership and many non-work
based trips will be made anyway and in greater frequency since park-and-ride rail lines often do
not accommodate efficient trip chaining. Dickins (1991) draws many of the same conclusions as
Parkhurst (1995 and 2000), Meek (2007 and 2009) and Burgess (2008), but also explains that
American cities are far more dependent on and susceptible to the negative effects of park-and-
ride lots than European cities due to the differences in urban structure between the two regions
(Dickins 1991).
One of the articles most relevant to the research question I have proposed was written by
Elizabeth Deakin and Manish Shirgaokar (2005) and investigates the travel behavior of park-
and-ride users in San Francisco and its impact on regional VMT. Deakin and Shirgaokar (2005)
provided detailed survey-based information on the origin and characteristics of park-and-ride
users in the US context (Deakin & Shirgaokar 2005). This information differs in many regards
compared to the UK examples explained before, but shares many of the same base assumptions
and results. Deakin and Shirgaokar (2005) found that nearly all of the park-and-ride users
commuted to the stations by automobile alone (Deakin & Shirgaokar 2005). Parking was
provided for free at nearly every station and the number of stations was growing rapidly (Deakin
& Shirgaokar 2005). The survey provided the first true look at the types of people using the park-
and-ride lots in the San Francisco Bay area and their travel behavior characteristics. Deakin and
Shirgaokar’s (2005) results showed that 93 to 100 percent of the users, depending on the station,
started their trips at home and 94 to 97 percent were using park-and-ride lots for work purposes
only, which differ from the examples in the Oxford/York studies (Deakin & Shirgaokar 2005).
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Those studies found that only 44 to 48 percent were using the park-and-ride lots for work only
(though even in the UK context this still represented the largest type of trip being made by park-
and-ride users) (Parkhurst 1995). Deakin and Shirgaokar (2005) also revealed that around 67 to
93 percent of all park-and-ride users in the San Francisco area were using park-and-ride lots four
or more days a week and 89 to 100 percent used it two to three days a week (Deakin &
Shirgaokar 2005). The average travel time to a station was found to be 16 minutes (Deakin &
Shirgaokar 2005). The key findings were that most persons were single person commuters who
worked full time and used the same park-and-ride lots for four or more days a week. When added
to the network, their contribution in decreasing VMT was almost negligible due to the high costs
associated with single person usage of park-and-ride lots and the induced demand effect (Deakin
& Shirgaokar 2005).
There is a modest amount of scholarly peer-reviewed research indicating that park-and-
ride lots do little to reduce VMT and are more likely than not to increase congestion due to many
indirect effects of park-and-ride usage. There was no literature found to support park-and-ride as
a tool to reduce congestion by itself. Parkhurst provides a context for the UK experience that is
also relevant to the US experience due to the similar types of people using park-and-ride lots and
similar indirect effects such as induced demand and redistribution of traffic. All of the papers
agreed that park-and-ride is appealing to auto users, increases economic activity in the center city
by reducing the need for central parking in prime land, and that it can serve as a politically sound
way of increasing ridership, but generally remains ineffective in reducing VMT. There also
appears to be a dearth in the research as to the environmental effects of park-and-ride lots,
including hot soak, in which evaporative emissions from cars parked on surface lots can create
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pollution, and the disproportionately high amount of emissions expelled per capita in a short
three-mile trip when compared to a longer 10-mile trip due to the effect of start emissions.
Emissions from park-and-ride users may be higher as a result of the very nature of the
type of trip being made, indicating that emissions per VMT have a high correlation with trip
distance. Shorter trips to a nearby park-and-ride lot have disproportionately larger amounts of
emissions per capita than cars traveling the entire length of the trip to a CBD or center city.
Related to this, Burgess (2008) indicates in his article that 84 percent of hydrocarbons and 54
percent of nitrogen oxide are burned in the first three miles of a 10-mile trip and claims that high
per capita emissions of park-and-ride users is just as important as other indirect effects of park-
and-ride such as induced demand (Burgess 2008). The EPA currently uses the MOBILE6 model
and MOVES Motor Vehicle Emissions Simulator model to calculate both start and running
emissions at the national level based on a number of variables. The MOBILE6 vehicle emissions
modeling software was developed by the EPA and has been used by EPA papers as well as
Houk’s paper “Making Use of MOBILE6’s Capabilities for Modeling Start Emissions” to model
running and start emissions (EPA website, EPA 2009, and Houk 2004).
These scholarly papers are important in the context of Charlotte as well since there have
been a limited number of studies in the US and none in Charlotte as to the direct and indirect
effects of park-and-ride and its impact on vehicle emissions and VMT. One of the main points
of this research was to determine if the Charlotte experience with park-and-ride matches the
general consensus of the literature. As there is relatively little literature regarding the US
experience, examining how park-and-ride has had an effect on emissions and VMT in the
Charlotte region is an important addition.
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Chapter 3: Data and Methodology
The main element being researched in this study is the connection/relationship between
vehicle miles traveled and the use of park-and-ride lots by automobile commuters. This study
aims to determine the estimated difference between vehicle miles travelled and emissions among
light rail park-and-ride trips versus the amount of vehicles miles travelled and emissions that
would have occurred had those trips continued to their final destination (typically in the CBD).
There are several methods by which could have been collected for this study, including on-site
license plate data collection (to determine origin location and vehicle type mix) and a survey. For
the purpose of this study, an on-board user survey provided by CDOT will be used since it has
the origin and destination already available for park-and-ride users and because it is financially
more feasible than on-site data collection. Many of the before-mentioned authors used surveys to
identify the travel behavior and characteristics of park-and-ride users, especially in the study
done by Deakin and Shirgaokar (2005) in the San Francisco Bay Area. This survey-based study
helped to identify the characteristics of park-and-ride users in the San Francisco Bay Area,
including how far they had traveled and from where the commuters were coming (Deakin and
Shirgaokar 2005). This thesis used TransCAD, which is traditionally used as an urban
transportation modeling system, as a simple database management system, to help organize the
data and answer this question.
Determining the origin for park-and-ride users is essential to determining the distance
they traveled to reach a station and the impact they have on regional vehicle miles traveled. The
spring 2009 on-board user survey compiled origin (home) and destination (Final non-station
destination) data grouped by TAZ (Traffic Analysis Zone) for 309 park-and-ride users. The
survey also provides the method of entry for each light rail station (e.g. park-and-ride, carpool,
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walk, kiss-and-ride, and other) as well as the direction of the light rail user and the final station
stop from station of entry. For the purpose of this study, only VMT and emissions for the 309
park-and-ride users will be calculated. The survey indicates the origin as production TAZ
(PTAZ) and the destination as attraction TAZ (ATAZ) between home and final-destination
locations. Using the PTAZ survey results it will be possible to geocode the origin for all 309
park-and-ride users for the purpose of estimating a network distance between home addresses
and their corresponding final-destination location and park-and-ride facility. For the purpose of
this study, an estimate was created to observe the effects of redistributing the traffic created by
park-and-ride users from trips made directly to Uptown Charlotte to trips being made to park-
and-ride lots. Once the VMT has been estimated for both scenarios, it will be possible to expand
the survey results to include all of the estimated daily park-and-ride users based on the
Combined ExpFactor Linked field in the survey. The Combined ExpFactor Linked field is a
weighted sum of all the estimated number of park-and-ride users represented by each of the park-
and-ride survey respondents. This will indicate an approximate VMT amount for all estimated
light rail park-and-ride users in a given day.
For this study, two transportation network estimates will be created based on the data
provided by CDOT. One will indicate the amount of VMT as a result of having select trips to
park-and-ride lots (existing conditions). The other model will indicate the amount of VMT if
those same trips were instead being made directly to their final destination (generally in the CBD
and surrounding areas), with a new assumption that all Uptown commuters are now going from
their home addresses directly to the Uptown area. The difference between the VMT results of
these two models will give some indication as to the extent of impact that park-and-ride lots are
having in the Charlotte area in reducing or increasing VMT. When calculating emissions
19
amounts, both estimates will also account for hot soak and cold start to estimate the difference in
total vehicle emissions between the two scenarios.
To determine the origin and destination of park-and-ride commuters in order to build a
network distance for these park-and-ride commuters, two variables must be used in the study,
including the home TAZ of park-and-ride users (origin) and the exact TAZ of the light rail park-
and-ride lots as well as work locations (destination). The origin-destination pair forms a matrix
by which a network distance between points can be estimated yielding the amount of additional
VMT being created by these trips. The network distance data provided by CDOT that are used to
estimate the distance between origin and destination pairs are based on numerous model
coefficients that were calculated by CDOT. These coefficients are in-vehicle travel time, out-of-
vehicle travel time, initial wait time, transfers for transit and drive access time, auto time, auto
costs (in cents), auto distance, income, and HOV savings for automobile. The data provided by
CDOT is an estimated TAZ Origin-Destination distance matrix for the Charlotte metropolitan
area. Light rail park-and-ride address locations will be collected from CATS and used to
determine the stations’ TAZ location for the first scenario.
Though this estimate is a simple and effective way of measuring the effects of light rail
park-and-ride facilities on VMT and emissions, it does have many problems and assumptions
affiliated with it. The study is expanded to capture all park-and-ride users by using the Combined
ExpFactor Linked field in the survey. This estimates how many people are actually using park-
and-ride lots for every one survey respondent. The estimates also assume their route is fixed
from origin to final destination with no intermediate stops. In addition, because the estimate uses
a national coefficient to estimate the amount of emissions from hot soak and cold start, it is also
20
an assumption that driving behavior and the types of automobile being used by park-and-ride
users are similar to the national average.
Coefficient national averages provided by the EPA are essential in measuring the amount
of vehicle emissions being given off by park-and-ride users for the purpose of this research.
There are two variables that will be used to measure the environmental impacts of park-and-ride
lots. The first is hot soak, which will measure the amount of evaporative emissions being given
off as cars sit idly in park-and-ride lots as well as cool down evaporative emissions. All stations
except the I-485 station, which is an enclosed parking deck, will measure the affects of hot soak
over a nine hour period. Since the I-485 station has an enclosed parking deck, cars parked here
will be excluded from the total nine hours and hot soak will only be measured for one hour, or
the amount of time it takes a car to cool down. It will be assumed that all of the persons using
park-and-ride lots from the survey are working a normal nine-hour day. It will also be assumed
that it is a non-cloudy day conducive for hot soak emissions which will give an overestimated
hot soak result for the average day in a year. Finally it is assumed that the amount of evaporative
emissions in Charlotte surface lots is similar to the national average since the estimate will be
using a national coefficient to help determine the amount of hot soak. In the case of cold start, it
will be possible to estimate vehicle emissions based on trip length using an EPA national cold
start coefficient as well as the national average age of a vehicle which is about nine years old.
Since the estimate will be using national coefficient averages and has several assumptions
attached to it, the results will not be exact but rather provide an idea as to the amount of
emissions being expelled as a result of cold start and hot soak evaporative emissions.
Additionally, the estimate assumes that cars and trucks in the Charlotte area are about the same
age as cars and trucks at the national level (i.e. nine years old).
21
As mentioned before, the EPA currently uses the MOBILE6 model and MOVES model
to calculate both start and running emissions at the national level. The MOVES model (Motor
Vehicle Emissions Simulator) was developed by the EPA office of Transportation and Air
Quality (OTAQ) and is used to estimate emissions (both start and running) for mobile sources
based on the mix of vehicles (type, year, etc.), the amount of time the vehicle has been parked,
ambient temperature of the vehicle, and the fuel the vehicle is using (EPA OTAQ website). This
model can be used at any scale (national, regional, local, etc) but is used by the EPA to
determine national emission averages for start and running emissions for each year (EPA 2009).
According to the EPA website, MOBILE6 is an emission factor model for predicting gram per
mile emissions of Hydrocarbons (HC), Carbon Monoxide (CO), Nitrogen Oxides (NOx), Carbon
Dioxide (CO2), Particulate Matter (PM), and toxics from on-road vehicles (EPA website). Both
of these models are used in calculating on-road vehicle start and running emissions and have
yielded interesting emission results (EPA website).
According to an article released by the EPA, cold start emissions occur within the first
505-860 seconds of driving or roughly a length of 3.59-3.9 vehicle miles before the normal
running emissions begin (EPA 2009 and Houk 2004). Cold start occurs when an automobile has
been sitting (generally overnight) for a period of 6 hours or more (EPA 2009). According to
Houk, start emissions in the summer (mainly cold start) accounts for 28% of the total on-road
volatile organic compound (VOC), 31% of carbon monoxide (CO), and 20% of nitrogen oxides
(NOx) emissions in 2001 (Houk 2004). In the winter, start emissions account for around 50% of
all CO emissions (Houk 2004). Start emissions (particularly cold start) will be major concerns in
this study since typical trips made by park-and-ride users are expected to be much shorter than if
those same users travelled directly into the CBD instead, especially in the wintertime. One major
22
assumption as expressed in the Houk article is that the MOBILE6 vehicle emissions modeler
assumes that all morning commute trips to work are calculated as a single start from the home
end and does not account for any stops a commuter may have on the way to work for breakfast
or coffee and does not account for multiple starts in the morning. According to the EPA, start
emissions and running emissions vary greatly from year to year for all on-road vehicles in the
US. In 2000, the average car in the US emitted 10.24 grams of CO, 1.294 grams of HC
(Hydrocarbons), and 0.983 grams of NOx during the start phase (cold start phase) for a total of
12.517 grams in emissions (EPA 2009). In 2010, the average car emitted only 3.65 grams of CO,
0.423 grams of HC, and 0.119 grams of NOx for a total of 4.192 grams in start emissions, a
reduction of 8.325 grams in emissions during the start phase or 66.5% (EPA 2009). However,
since the average age of a vehicle in the US is 9.4 years old, it is assumed that the current start
emissions for all vehicles on the road will be equivalent to the start and running emission rate of
a car produced in 2001 (RITA 2009).
According to the EPA, the average car built in 2001 emits 0.2196 grams of cumulative
evaporative HC emissions in a nine hour period in 2001 (EPA 2001). This rate will be applied to
all of the park-and-ride users except the I-485 station users where evaporative HC emissions
were calculated for a one hour cool down time. In 2001, the average start emissions for an LDV
(light duty vehicle or car) were 8.86 grams of CO, 0.932 grams of HC, and 0.672 grams NOx.
The average running emissions for an LDV in 2001 per mile was 0.579 grams of CO per mile,
0.016 grams of HC per mile, and 0.080 grams of NOx per mile. The amount of start and running
emissions for cars in this study represents a lower bound emissions estimate. The study is
repeated for all LDTs (light duty trucks) to show an upper end of emission results, as these
vehicles have much higher start and running emissions rates than LDVs. Among LDTs in 2001
23
the average start emissions were 14.15 grams of CO, 1.45 grams of HC, and 1.12 grams NOx.
The average running emissions for an LDT in 2001 were 0.848 grams of CO per mile, 0.0486
grams of HC per mile, and 0.144 grams of NOx per mile. The results below assume a total of
8.86 grams of CO, 0.932 grams of HC, and 0.672 grams of NOx for all car (LDV) trips (start
emissions) and 14.15 grams of CO, 1.45 grams of HC, and 1.12 grams of NOx for all truck
(LDT) trips. Following this, the running emissions rate is added on a per mile rate for all trips
over 3.90 miles (after the cold start period). The true amount of emissions for the Charlotte is
likely to be somewhere between the lower bound car (LDV) estimate and the upper bound truck
(LDT estimate).
24
Chapter 4: Model Analysis
4.1 Results of the Analysis (VMT)
The first step of the analysis was to determine an estimate VMT for two separate
scenarios. The estimates take into account the return trip for each park-and-ride user as a separate
trip from the origin – destination trip and assume a similar trip path on the return trip. One
scenario indicates the existing conditions whereby park-and-ride users drove from their origin
TAZ to the nearest light rail park-and-ride stations (park-and-ride TAZ). The other scenario
indicates pre-existing light rail conditions whereby all potential park-and-ride users drove all the
way to their final destination TAZ. There are two sections of estimated results including the
existing home-station VMT followed by the pre-existing home-final destination VMT. Each
section will have two subset tables of results, one of which will indicate the estimated VMT for
the 309 park-and-ride survey users, followed by the estimated VMT results for all park-and-ride
users based on the Combined ExpFactor Linked field from the 2009 On-board User Survey.
Indicated below in the first set of data results is the estimated VMT for the 304 park-and-
ride survey respondents for the home – station (existing conditions) scenario and 309 survey
respondents for the home – final destination (hypothetical) scenario for the current existing
home-light rail park-and-ride lot conditions. Since all interzonal (e.g. trips made from within the
same TAZ) are excluded and there were slightly more interzonal trips made in the home – station
scenario, there is a slight difference in the survey size. The estimated VMT results are broken up
by station and then indicated for all stations combined (one indicating all light rail stations
combined and one indicating all park-and-ride stations combined). Most of these trips were
headed to the CBD as well as some trips ending further along the light rail line but outside of the
25
CBD as final point of station departure. Also indicated is the estimated minimum to maximum
VMT for the 309 park-and-ride users for each park-and-ride station as well as all park-and-ride
stations and all the light rail stations combined. Finally, a figure indicating the average VMT for
each station, VMT for all park-and-ride stations, and VMT for all stations will be shown in the
table below.
Table 1: Estimated VMT for 2009 Park-and-Ride User Survey Respondents from Home TAZ to
nearest Park-and-Ride TAZ (existing conditions):
Home Station Records Mean VMT Min-Max VMT
I-485 Station 165 8.3445 0.58 – 25.46
Sharon Road West Station 30 5.6808 1.06 – 24.76
Arrowood Station 30 6.6307 0.74 – 24.63
Archdale Station 4 1.6240 1.27 – 2.57
Tyvola Station 22 4.3961 0.79 – 25.69
Woodlawn Station 14 3.7559 0.45 – 27.83
Scaleybark Station 29 6.9538 0.45 – 34.08
Non-Park-and-Ride Stations 10 6.7018 1.04 – 30.51
All Stations 304 7.1457 0.45 – 34.08
All Park-and-Ride Stations 294 7.1608 0.45 – 34.08
CDOT 2009 On-Board User Survey and Network OD Matrix
Figure 2: Average VMT by Station, All Stations and All Park-and-Ride Stations:
CDOT 2009 On-Board User Survey and Network OD Matrix
0123456789
26
The results in the table 1 and figure 2 above indicate the average and minimum–
maximum estimated VMT for the 304 survey respondents for each park-and-ride station, all
park-and-ride stations combined, and all stations combined (including all non-park-and-ride
stations). There were 10 survey respondents located at non-park-and-ride lots which are assumed
to be the remaining TOD stations further up the line. It is likely that these survey respondents
drove to a differenct parking facility near these TOD stations that were not official CATS park-
and-ride facilities. The overall average per person estimated VMT is approximately 7.15 miles
for all stations and 7.16 miles for all park-and-ride stations among the 304 park-and-ride survey
respondents. The minimum distance traveled was an estimated 0.45 miles located at Woodlawn
Station and Scaleybark and the longest was an estimated 34.08 miles located at Scaleybark
Station. The station with the highest average estimated VMT was the I-485 station at
approximately 8.34 miles and the lowest was Archdale station with an average estimated trip
being 1.62 miles from home to station. The I-485 station made up the largest share of users
among the survey respondents, accounting for 165 survey respondents or about 54 percent of the
survey sample.
After completing the analysis for the survey sample for all park-and-ride users going
from the home origin TAZ to the station destination TAZ (survey sample existing conditions),
the analysis was then expanded using the Combined ExpFactor Linked field in the survey which
aims to estimate VMT for all park-and-ride users by expanding each survey respondent to match
the actual number of park-and-ride users they represent. Indicated below is a table and figure
indicating the estimated average and minimum–maximum VMT for all estimated park-and-ride
users in a single day broken down by park-and-ride lot as well as all stations and all park-and-
ride stations combined. After using the Combined ExpFactor Linked field from the 2009 On-
27
Board User Survey, there are an estimated 4,642 park-and-ride users on an average given day
represented by the survey sample of 304 respondents. The results take into account the return trip
as a separate trip and assume a similar trip path was made on the return trip.
Table 2: Estimated VMT for All Park-and-Ride Users in a Given Day from Home TAZ to
nearest Park-and-Ride TAZ (existing conditions):
Home Station Records Mean VMT Min-Max VMT
I-485 Station 2260.13 8.2777 0.58 – 25.46
Sharon Road West Station 545.06 5.2129 1.06 – 24.76
Arrowood Station 437.60 5.6458 0.74 – 24.62
Archdale Station 72.41 1.9417 1.28 – 2.58
Tyvola Station 317.40 3.3745 0.79 – 25.69
Woodlawn Station 434.09 4.3746 0.45 – 27.83
Scaleybark Station 410.77 6.9014 0.45 – 34.08
Non-Park-and-ride Stations 164.03 6.1404 1.04 – 30.51
All Stations 4641.50 6.2678 0.45 – 34.08
All Park-and-ride Stations 4477.46 6.2722 0.45 – 34.08
CDOT 2009 On-Board User Survey and Network OD Matrix
Figure 3: Average VMT by Station, All Stations and All Park-and-Ride Stations:
CDOT 2009 On-Board User Survey and Network OD Matrix
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The results in the table 2 and figure 3 above indicate the average and minimum–
maximum estimated VMT for all the estimated 4,642 park-and-ride users for each park-and-ride
station, all park-and-ride stations combined, and all stations combined (including all non-park-
and-ride stations). The overall average per person estimated VMT is approximately 6.27 miles
for all stations and for all park-and-ride stations among the estimated 4,642 park-and-ride users.
This is slightly lower than the estimated 7.16 miles for the survey respondents indicating that the
average overall park-and-ride user is travelling less than the average survey user. The minimum
distance traveled was an estimated 0.45 miles located at Woodlawn Station and Scaleybark
Station and the longest was an estimated 34.08 miles located at Scaleybark Station. The station
with the highest average estimated VMT was the I-485 station at approximately 8.28 miles and
the lowest was Archdale station with an average estimated trip being 1.94 miles from home to
station. The I-485 station made up the largest share of users among all estimated park-and-ride
users accounting for 2,260 users or about 49 percent of all estimated users.
The estimated results from table 2 provide a much clearer picture of the true amount of
VMT incurred on an average day by the estimated daily number of light rail park-and-ride users.
The approximate total VMT calculated for the current existing conditions for all light rail park-
and-ride users is roughly 30,973 miles travelled out of approximately 15,962,423 (EPA 2003) for
Charlotte as a whole in a given day or about 0.2 percent of all VMT in a given day. According to
a CATS 2009 survey, approximately 56 percent of all trips made on the light rail are home-based
work trips (either traveling from home to work or work to home as trip type) (CATS 2009). If we
assume that 56 percent of park-and-ride users are also using light rail park-and-ride as a means of
transportation then an estimated 2,600 park-and-ride users are using park-and-ride as a mode of
commuting. In 2010, about 70,000 – 75,000 people worked in the Charlotte CBD (Charlotte
29
Center City Partners), so this makes up roughly 3.5 – 3.7 percent of all mode choice types for
CBD workers assuming that all people who commute by park-and-ride work in the CBD.
The second part of the analysis was to estimate the hypothetical pre-light rail conditions
in which VMT is estimated for all potential park-and-ride trips that are now redirected to their
final destination most typically in the CBD but also along the light rail line in neighborhoods
such as Southend. The amount of VMT was first estimated for the survey respondents and then
expanded to include the estimated total number of potential park-and-ride users using the
Combined ExpFactor Linked Field from the 2009 User Survey. Seen below are a table and figure
for all those survey respondents who would have used park-and-ride stations (existing) but
instead travelled directly to their final destination (hypothetical). The survey sample size is
slightly larger for the home – final destination scenario with 309 survey respondents than the
home – station scenario which included 304 survey respondents. The estimated results are
broken up in a fashion similar to the home-station results in which estimated results are indicated
for each park-and-ride station, all stations combined, and all park-and-ride stations combined.
The stations in this case are same affiliating stations as the survey users in the home – station
scenario but do not represent the final destination of the user. The final destination is most
typically found further along the line or in the CBD. Also shown below is a figure which shows
the average amount of VMT for this scenario for each category.
30
Table 3: Estimated VMT for 2009 Park-and-Ride User Survey Respondents from Home TAZ to
Final Destination TAZ (pre-existing conditions):
Home Station Records Mean VMT Min-Max VMT
I-485 Station 165 17.6185 0.35 – 35.79
Sharon Road West Station 30 13.4896 8.42 – 22.35
Arrowood Station 30 12.5320 0.42 – 22.67
Archdale Station 5 7.3353 3.70 – 9.80
Tyvola Station 23 10.0035 6.75 – 26.18
Woodlawn Station 15 7.5512 4.57 – 19.16
Scaleybark Station 31 8.2579 1.63 – 31.26
Non-Park-and-Ride Stations 10 7.7719 1.31 – 29.06
All Stations 309 14.2442 0.35 – 35.79
All Park-and-Ride Stations 299 14.4606 0.35 – 35.79
CDOT 2009 On-Board User Survey and Network OD Matrix
Figure 4: Average VMT by Station, All Stations and All Park-and-Ride Stations (hypothetical):
CDOT 2009 On-Board User Survey and Network OD Matrix
02468
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31
The results in the table 3 and figure 4 above indicate the average and minimum –
maximum estimated VMT for the 309 park-and-ride survey respondents for each park-and-ride
station, all park-and-ride stations combined, and all stations combined (including all non-park-
and-ride stations) for the hypothetical home – final destination scenario. The overall average per
person estimated VMT is approximately 14.24 miles for all stations and 14.46 for all park-and-
ride stations among the 309 potential park-and-ride users. This is an estimated 99 percent higher
than in the first scenario (existing conditions) for all stations combined and an estimated 102
percent higher than all park-and-ride stations combined. The minimum distance traveled was an
estimated 0.35 miles located at the I-485 station and the longest was an estimated 35.79 miles
located at I-485 Station as well. The short trip distance of 0.35 miles in the I-485 example
indicates that this park-and-ride user lived close to the center city (Origin TAZ of 10010) and
their final destination (destination TAZ of 10009) and chooses to drive to the I-485 station
instead of a closer station according to the survey results which are a very rare situation. This is
further substantiated in the survey as only about two additional people made a similar trip if you
expand the survey using the Combined ExpFactor Linked field. The station with the highest
average estimated VMT was the I-485 stations at approximately 17.62 miles and the lowest was
Archdale station with an average estimated trip being 7.34 miles from home to final non-station
destination.
Indicated in the figure below is the average estimated VMT for all station categories
(each individual station, all stations combined and all park-and-ride stations combined) between
the existing conditions scenario (home-station) and the second hypothetical scenario (home-final
destination) among survey respondents. Also seen is a table showing the percent increase in
VMT when switching trip type from scenario one to scenario two. The amount of VMT increase
32
ranged from 16 to 351 percent. The overall average increase in VMT when switching from the
home – park-and-ride scenario to the hypothetical home – final destination scenario for all
stations was an estimated 99 percent or double the amount of VMT. Average VMT tended to
steadily decrease from station to station in the home – final destination scenario starting with the
station with the highest estimated VMT (I-485) until reaching all non-park-and-ride lots which
had the second lowest average VMT.
Figure 5: Absolute Change in VMT between Scenario 1 (Home-Station) and Scenario 2 (Home-
Final Destination) among Survey Respondents:
CDOT 2009 On-Board User Survey and Network OD Matrix
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Scenario 1
Scenario 2
33
Table 4: Absolute and Percent Changes in overall VMT among different Station Categories
(Survey Respondents)*:
Station Absolute Percentage
I-485 Station +9.3 111.1 %
Sharon Road West Station +7.8 137.5 %
Arrowood Station +5.9 89.0 %
Archdale Station +5.7 351.7 %
Tyvola Station +5.6 127.6 %
Woodlawn Station +3.8 101.0 %
Scaleybark Station +1.3 18.8 % Non-Park-and-Ride Stations +1.2 16.0 %
All Stations +7.2 99.3 % All Park-and-Ride Stations +7.3 101.9 %
CDOT 2009 On-Board User Survey and Network OD Matrix
*This represents the percent and absolute per user VMT change in VMT by station for the survey
respondents when they travel to their final destination entirely by car instead of travelling part of
the way by light rail
The final part of the VMT section of the analysis estimates the VMT for all potential
park-and-ride users based on the survey sample as they travel in a hypothetical trip from home to
their final destination by using the Combined ExpFactor Linked field. The table and figure below
indicates the estimated average amount of VMT and minimum – maximum VMT categorized by
individual station, all stations combined, and all park-and-ride stations combined. After using the
Combined ExpFactor Linked Field, there was an estimated 4,767 potential park-and-ride users
(pre-existing conditions) represented by the sample size of 309 in an average day. Also
presented below is a figure showing the difference in overall estimated VMT between the survey
sample and the total estimated potential park-and-ride users in the hypothetical pre-light rail
scenario.
34
Table 5: Estimated VMT for all potential 2009 Park-and-Ride Users from Home TAZ to Final
Destination TAZ (pre-existing conditions):
Home Station Records Mean VMT Min-Max VMT
I-485 Station 2260.13 17.7195 0.35 – 35.79
Sharon Road West Station 545.06 13.0116 8.42 – 22.35
Arrowood Station 429.56 12.1475 0.42 – 22.67
Archdale Station 82.96 7.7155 3.70 – 9.80
Tyvola Station 357.77 8.8240 6.75 – 26.18
Woodlawn Station 475.23 6.6698 4.67 – 19.16
Scaleybark Station 452.62 7.7643 1.63 – 31.26
Non-Park-and-Ride Stations 164.03 7.1270 1.31 – 29.06
All Stations 4767.37 13.4264 0.35 – 35.79
All Park-and-Ride Stations 4603.34 13.6509 0.35 – 35.79
CDOT 2009 On-Board User Survey and Network OD Matrix
Figure 6: Average VMT by Station, All Stations and All Park-and-Ride Stations (hypothetical):
CDOT 2009 On-Board User Survey and Network OD Matrix
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35
Figure 7: Difference in VMT between Survey Sample all Users for Hypothetical Scenario:
CDOT 2009 On-Board User Survey and Network OD Matrix
The results in the table and figures above indicate the average and minimum – maximum
estimated VMT for all the estimated 4,767 potential park-and-ride users for each park-and-ride
station, all park-and-ride stations combined, and all stations combined (including all non-park-
and-ride stations) in the hypothetical home – final destination trip type scenario. The overall
average per person estimated VMT is approximately 13.43 miles for all stations and 13.65 miles
for all park-and-ride stations among the estimated 4,767 potential park-and-ride users. This is
slightly lower than the estimated 14.24 miles for all park-and-ride home stations and 14.46 miles
for all home stations for the survey respondents, indicating that the average overall potential
park-and-ride user is travelling less than the average survey user. The minimum distance traveled
was an estimated 0.35 miles located at I-485 Station and the longest was an estimated 35.79
miles located at the I-485 Station as well. The station with the highest average estimated VMT
was the I-485 station at approximately 17.72 miles and the lowest was Archdale station with an
0
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36
average estimated trip being 7.72 miles from home to station. The I-485 station made up the
largest share of users among all estimated park-and-ride users, accounting for 2,260 users or
about 47 percent of all estimated users.
The estimated results from table 5 provide a much clearer picture of the true amount of
VMT incurred in an average day by the estimated daily number of potential light rail park-and-
ride users. The approximate total VMT calculated for the hypothertical home – final destination
scenario for all light rail park-and-ride users is roughly 64,009 miles travelled (accounting for
round-trips) out of approximately 15,962,423 for Charlotte as a whole in a given day, or about
0.4 percent of all VMT in a given day, and twice the amount of VMT as the first home-station
scenario. This is a decrease of roughly 33,036 in VMT from the home – station scenario value,
which were 30,973 in VMT. Indicated in the figure below is the average estimated VMT for all
station categories between the existing conditions scenario (home-station) and the second
hypothetical scenario (home-final destination) among all estimated park-and-ride users after
using the Combined ExpFactor Linked field. Also included is a table showing the percent
increase in VMT when switching trip type from scenario one to scenario two. The amount of
VMT increase ranged from 12 to 297 percent. The overall average increase for all stations was
slightly sharper than the increase among survey respondents with a 114 percent increase (slightly
more than double). The absolute change decreases from roughly nine at I-485 to only one mile at
Scaleybark.
37
Figure 8: Absolute Change in VMT between Scenario 1 (Home-Station) and Scenario 2 (Home-
Final Destination) for all estimated Park-and-Ride Users in a given day:
CDOT 2009 On-Board User Survey and Network OD Matrix
Table 6: Absolute and Percent Changes in overall VMT among different Station Categories (All
Estimated Users):
Station Absolute Percentage
I-485 Station 9.4 114.1
Sharon Road West Station 7.8 149.6
Arrowood Station 6.5 115.2
Archdale Station 5.8 297.4
Tyvola Station 5.4 161.5
Woodlawn Station 2.3 52.5
Scaleybark Station 0.9 12.5
Non-Park-and-Ride Stations 1.0 16.1
All Stations 7.2 114.2
All Park-and-Ride Stations 7.4 117.6
CDOT 2009 On-Board User Survey and Network OD Matrix
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Scenario 1
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38
4.3 Results of the Analysis (Emissions)
As mentioned the metholodgy section, cold start, which is defined as higher emissions
per mile travelled in the first few miles of driving after a vehicle is initially started, is a major
concern for shorter trips. Therefore, the emissions emitted from a vehicle are highest in the first
few miles (or usually during the first 505 seconds) at the start of a trip than the rest of the trip.
The result is higher emissions per VMT in the second model as a result of driving shorter trips.
The EPA states the cold start emissions phase occurs in the first 3.9 miles of travel after initially
starting the car after a soak period of at least six-seven hours (EPA 2009). After traveling the
initial 3.9 miles, a vehicle switches from the start emissions phase to the running emissions
phase, which is generally much lower.
As mentioned in the methodology, a second measure that increases emissions is hot soak,
in which cars left sitting all day in an open parking space create evaporative emissions. Hot soak
will be measured and estimated at an hourly rate for a typical nine hour work day for all vehicles
parked in park-and-ride stations except the I-485 station which is a covered deck and not
exposed to the sun. Since hot soak does occur during vehicle cool down, the rate of hot soak
emissions will be applied for one hour (average vehicle cool down time) for all vehicles parked
at the I-485 station to estimate real life conditions as closely as possible. The following table and
figures indicate estimated total and average amount of emissions by emission type including CO
emissions, HC emissions, and NOx emissions using the Combined ExpFactor Linked field as a
weight in the home – station current conditions. This represents total and average per user
emission amount for all users by emission type on all trips as they go from the home TAZ to
their affiliating station TAZ. As mentioned in the methodology section, the 2001 model year was
39
used to estimate vehicle emissions since the average age of a vehicle in the US is approximately
nine years old. Two types of vehicles are represented including cars (LDV’s) and trucks (LDT’s)
representing lower and upper estimates for each emission type. The HC emission results below
do not include hot soak HC emissions. Those results are inidicated at the final part of the
emissions section.
Table 7: Total, per user and per mile emissions by type of emission from home to station using
the 2001 model year as a base for start and running emissions rate (all Park-and-ride users):
2001 CO Emissions 2001 HC Emissions 2001 NOx Emissions
TOTAL Home-Station Grams TOTAL Home-Station Grams TOTAL Home-Station Grams
Car (LDV) 45,374.639 Car 4,586.623 Car 4,422.832
Truck (LDT) 71,903.133 Truck 7,522.194 Truck 7,545.219
PER MILE* PER MILE PER MILE
Car 1.465 Car 0.148 Car 0.143
Truck 2.321 Truck 0.243 Truck 0.244
PER PandR USER PER PandR USER PER PandR USER
Car 9.776 Car 0.988 Car 0.953
Truck 15.491 Truck 1.621 Truck 1.626 Source: EPA 2009 and CDOT 2009
*Per Mile estimates of emissions are usefull since they can give some indication of emissions for
varying trip distances on average.
40
Figure 9: Total CO Emissions, CO Emissions per Mile, and CO Emissions per User in grams for
a 2001 average age vehicle for both LDV and LDT Vehicle Types:
Source: EPA 2009 and CDOT 2009
0.00
20,000.00
40,000.00
60,000.00
80,000.00
Car (LDV) Truck (LDT)
Total 2001 CO Emissions (grams)
Total 2001CO Emissions(grams)
0.00
0.50
1.00
1.50
2.00
2.50
Car (LDV) Truck (LDT)
2001 CO Emissions Per Mile (grams)
2001 COEmissions PerMile (grams)
0.00
5.00
10.00
15.00
20.00
Car (LDV) Truck (LDT)
2001 CO Emissions Per User (grams)
2001 COEmissions PerUser (grams)
41
Figure 10: Total HC Emissions, HC Emissions per Mile, and HC Emissions per User in grams
for a 2001 average age vehicle for both LDV and LDT Vehicle Types:
Source: EPA 2009 and CDOT 2009
0.00
2,000.00
4,000.00
6,000.00
8,000.00
Car (LDV) Truck (LDT)
Total 2001 HC Emissions (grams)
Total 2001 HCEmissions(grams)
0
0.05
0.1
0.15
0.2
0.25
0.3
Car (LDV) Truck (LDT)
2001 HC Emissions Per Mile (grams)
2001 HCEmissions PerMile (grams)
0
0.5
1
1.5
2
Car (LDV) Truck (LDT)
2001 HC Emissions Per User (grams)
2001 HCEmissions PerUser (grams)
42
Figure 11: Total NOx Emissions, NOx Emissions per Mile, and NOx Emissions per User in
grams for a 2001 average age vehicle for both LDV and LDT Vehicle Types:
Source: EPA 2009 and CDOT 2009
0.00
2,000.00
4,000.00
6,000.00
8,000.00
Car (LDV) Truck (LDT)
Total 2001 NOX Emissions (grams)
Total 2001 NOXEmissions(grams)
0
0.1
0.2
0.3
Car (LDV) Truck (LDT)
2001 NOX Emissions Per Mile (grams)
2001 NOXEmissions PerMile (grams)
0
0.5
1
1.5
2
Car (LDV) Truck (LDT)
2001 NOX Emissions Per User (grams)
2001 NOXEmissions PerUser (grams)
43
It is estimated that among cars (LDV’s) the total estimated CO emission amount was
45,375 grams (lower range) and for trucks (LDT’s) it is estimated to be 71,903 grams (upper
range) for all 4,642 park-and-ride users on an average trip from home to the nearest station. In
terms of per mile CO emissions, that translates to 1.465 grams of CO per mile for cars and 2.321
grams of CO per mile for trucks. In terms of per user CO emissions, the value is roughly 9.775
grams of CO per user for cars and 15.491 grams of CO per user for trucks. The total estimated
amount of HC emissions in the home-station (existing conditions) scenario is estimated to be
4,587 grams in the case of cars and 7,522 grams in the case of trucks. In terms of per mile HC
emissions, this translates to roughly 0.148 grams of HC for cars and 0.243 grams of HC for
trucks. In terms of per user HC emissions the value is estimated to be 0.988 grams for cars and
1.621 grams for trucks. Finally, the estimated total amount of NOx emissions for a vehicle with
an average age of nine years is estimated to be 4,423 grams of NOx for cars and 7,545 grams of
NOx for trucks. In terms of per mile, this is roughly 0.143 grams of NOx per mile for cars and
0.244 grams of NOx per mile for trucks. In terms of per user, the value is estimated to be 0.953
grams of NOx per user for cars and 1.626 grams of NOx per user for trucks.
The following table and figures indicate the total and average amount (per user) of
emissions for each emission type for each park-and-ride station and all non-park-and-ride
stations combined in the home – station scenario. This intends to show the variation in estimated
total emissions and emissions per user for each station. Once again, the amount of emissions will
be broken up by cars (LDV’s) and trucks (LDT’s) to indicate a lower and upper bound for the
emission estimate for each emission type. Total amount of users is indicated in parentheses.
44
Table 8: Total and Average per User CO Emissions assuming Cars and Trucks for each Park-
and-Ride Station (Home – Station):
Station (Total Users)
Total CO Emissions (Car)
CO Emissions Per User (Car)
Total CO Emissions (Truck)
CO Emissions Per User (Truck)
I-485 Station (2,260) 22,381.20 9.90 35,432.09 15.68
Sharon Road West Station (545) 5,110.34 9.38 8,124.31 14.91
Arrowood Station (438) 4,099.37 9.37 6,517.51 14.89
Archdale Station (72) 641.56 8.86 1,024.62 14.15
Tyvola Station (317) 2,862.17 9.02 4,564.45 14.38
Woodlawn Station (434) 4,323.09 9.96 6,841.05 15.76
Scaleybark Station (411) 4,336.08 10.56 6,832.72 16.63
Non-Park-and-Ride Stations (164) 1,620.84 9.88 2,566.39 15.65
Source: EPA 2009 and CDOT 2009
Figure 12: Total CO Emissions for Cars and Trucks for each Station:
Source: EPA 2009 and CDOT 2009
0.00
5,000.00
10,000.00
15,000.00
20,000.00
25,000.00
30,000.00
35,000.00
40,000.00
Total CO Emissions (Car)
Total CO Emissions (Truck)
45
Figure 13: Average per User CO Emissions assuming Cars and Trucks for Each Station:
Source: EPA 2009 and CDOT 2009
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
CO Emissions Per User (Car)
CO Emissions Per User (Truck)
46
Table 9: Total and Average per User HC Emissions for Cars and Trucks for each Park-and-Ride
Station (Home – Station):
Station (Total Users)
Total HC Emissions (Car)
HC Emissions Per User (Car)
Total HC Emissions (Truck)
HC Emissions Per User (Truck)
I-485 Station (2,260) 2,272.78 1.01 3,782.44 1.67
Sharon Road West Station (545) 527.51 0.97 849.60 1.56
Arrowood Station (438) 426.03 0.97 689.78 1.58
Archdale Station (72) 67.49 0.93 105.00 1.45
Tyvola Station (317) 301.31 0.95 476.92 1.50
Woodlawn Station (434) 420.32 0.97 677.27 1.56
Scaleybark Station (411) 410.30 1.00 679.03 1.65
Non-Park-and-Ride Stations (164) 160.88 0.98 262.17 1.60
Source: EPA 2009 and CDOT 2009
Figure 14: Total HC Emissions for Cars and Trucks for each Station:
Source: EPA 2009 and CDOT 2009
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
3,500.00
4,000.00
Total HC Emissions (Car)
Total HC Emissions (Truck)
47
Figure 15: Average per User HC Emissions for Cars and Trucks for Each Station:
Source: EPA 2009 and CDOT 2009
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
HC Emissions Per User (Car)
HC Emissions Per User (Truck)
48
Table 10: Total and Average per User NOx Emissions for Cars and Trucks for each Park-and-
Ride Station (Home – Station):
Station (Total Users)
Total NOx Emissions (Car)
NOx Emissions Per User (Car)
Total NOx Emissions (Truck)
NOx Emissions Per User (Truck)
I-485 Station (2,260) 2,350.49 1.04 4,028.38 1.78
Sharon Road West Station (545) 463.82 0.85 786.04 1.44
Arrowood Station (438) 385.03 0.88 653.84 1.49
Archdale Station (72) 48.66 0.67 81.10 1.12
Tyvola Station (317) 240.77 0.76 404.94 1.28
Woodlawn Station (434) 370.46 0.85 627.94 1.45
Scaleybark Station (411) 413.33 1.01 707.19 1.72
Non-Park-and-Ride Stations (164) 150.27 0.92 255.79 1.56
Source: EPA 2009 and CDOT 2009
Figure 16: Total NOx Emissions for Cars and Trucks for each Station:
Source: EPA 2009 and CDOT 2009
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
3,500.00
4,000.00
4,500.00
Total NOX Emissions (Car)
Total NOX Emissions (Truck)
49
Figure 17: Average per User NOx Emissions for Cars and Trucks for Each Station:
Source: EPA 2009 and CDOT 2009
According to the results above, the station reporting the highest amount of emissions for
each emission type was the I-485 station, which also had the highest amount of users and VMT.
Total CO emissions for cars (LDV’s), which represents a lower bound emission limit for this
study, ranged from an estimated 642 grams of CO emissions at the Archdale park-and-ride
station to 22,381 grams at the I-485 station. Total CO per user for cars ranged from 8.86 grams at
the Archdale station to 10.56 grams at the Scaleybark station. Interestingly, the stations with the
highest amount of CO emissions were those further along the light rail line located closer to the
CBD and stations on both ends of the line tended to be higher in terms of per user average CO
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
2.00
NOX Emissions Per User (Car)
NOX Emissions Per User (Truck)
50
emissions than the ones in the middle. In terms of HC emissions for cars, the absolute estimated
total HC emission value ranged from 68 grams at Archdale station to 2,273 grams at the I-485
station. In terms of per user HC emissions, the station with the lowest average per user HC
emission value was Archdale with 0.93 grams and the highest was the I-485 station with 1.01
grams. In terms of NOx emissions, the amount of total estimated NOx emissions for cars ranged
from 49 grams at Archdale to 2,351 grams at the I-485 station. The amount of total per user NOx
emissions for cars ranged from 0.67 grams at Archdale station to 1.04 grams at the I-485 station.
On the other end, total and average emissions of CO, HC, and NOx for trucks (LDT’s)
were substantially higher and represent an upper bound emission limit for this study. In terms of
total CO emissions, the station with the lowest overall CO emissions was Archdale station with
an estimated 1,025 grams of CO for all users while the highest overall CO emissions for any
station was the I-485 with 35,432 grams. Average per user CO emissions for trucks ranged from
14.15 grams at Archdale station to 16.63 grams at Scaleybark station. In terms of HC emissions
for trucks, the station with the lowest overall HC emission value for trucks was Archdale station
with 105 grams of HC emissions and the station with the highest was the I-485 station with an
aggregate 3,782 grams. The per user truck emission value for HC emissions ranged from 1.45
grams at Archdale station to 1.67 at the I-485 station. Finally, in terms of NOx emissions for
trucks, the total estimated emissions ranged from 81 grams at Archdale station to 4,028 grams at
the I-485 station. The per user NOx emission value for trucks ranged from 1.12 grams at
Archdale station to 1.78 grams at the I-485 station. In every emission type case, the I-485 station
accounted for about half of all user emissions as a total. In terms of per user emissions the top
three stations were Scaleybark, Woodlawn and I-485 for CO emissions and I-485, Scaleybark
and non-park-and-ride stations for HC and NOx emissions.
51
The second part of the emissions estimate analysis was to determine the
approximate amount of emissions under the pre-existing hypothetical home – final destination
trip type. The following table and figures indicate estimated total and average amount of
emissions by emission type, including CO emissions, HC emissions, and NOx emissions, using
the Combined ExpFactor Linked field as a weight in the home – station current conditions. This
represents total and average emissions for all users by emission type on all trips as they go from
the home TAZ to their nearest station TAZ. As mentioned in the methodology section, the 2001
model year was used to estimate vehicle emissions since the average age of a vehicle in the US is
approximately nine years old. Two types of vehicles are represented, including cars (LDV’s) and
trucks (LDT’s) representing lower and upper bound limit estimates for each emission type. The
HC emission results below do not include hot soak HC emissions. Those results are inidicated at
the final part of the emissions section.
Table 11: Total, per user and per mile emissions by type of emission from home to final
destination using the 2001 model year as a base for start and running emissions rate (all Park-
and-ride users):
2001 CO Emissions 2001 HC Emissions 2001 NOx Emissions
TOTAL Home-Final D. Grams TOTAL Home-Final D. Grams TOTAL Home-Final D. Grams
Car (LDV) 68,707.770 Car 5,174.624 Car 6,860.859
Truck (LDT) 106,224.436 Truck 9,134.424 Truck 11,922.390
PER MILE PER MILE PER MILE
Car 1.073 Car 0.081 Car 0.107
Truck 1.660 Truck 0.143 Truck 0.186
PER USER PER USER PER USER
Car 14.412 Car 1.085 Car 1.439
Truck 22.282 Truck 1.916 Truck 2.501
Source: EPA 2009 and CDOT 2009
52
Figure 18: Total CO Emissions, CO Emissions per Mile, and CO Emissions per User in grams
for a 2001 average age vehicle for both LDV and LDT Vehicle Types:
Source: EPA 2009 and CDOT 2009
0.000
20,000.000
40,000.000
60,000.000
80,000.000
100,000.000
120,000.000
Car (LDV) Truck(LDT)
Total 2001 CO Emissions (Grams)
Total 2001 COEmissions(Grams)
0.000
0.500
1.000
1.500
2.000
Car (LDV) Truck (LDT)
2001 CO Emissions Per Mile (Grams)
2001 COEmissions PerMile (Grams)
0.000
5.000
10.000
15.000
20.000
25.000
Car (LDV) Truck (LDT)
2001 CO Emissions Per User (Grams)
2001 COEmissions PerUser (Grams)
53
Figure 19: Total HC Emissions, HC Emissions per Mile, and HC Emissions per User in grams
for a 2001 average age vehicle for both LDV and LDT Vehicle Types:
Source: EPA 2009 and CDOT 2009
0.000
2,000.000
4,000.000
6,000.000
8,000.000
10,000.000
Car (LDV) Truck (LDT)
Total 2001 HC Emissions (Grams)
Total 2001 HCEmissions(Grams)
0.000
0.050
0.100
0.150
Car (LDV) Truck (LDT)
2001 HC Emissions Per Mile (Grams)
2001 HCEmissions PerMile (Grams)
0.000
0.500
1.000
1.500
2.000
2.500
Car (LDV) Truck (LDT)
2001 HC Emissions Per User (Grams)
2001 HCEmissions PerUser (Grams)
54
Figure 20: Total NOx Emissions, NOx Emissions per Mile, and NOx Emissions per User in
grams for a 2001 average age vehicle for both LDV and LDT Vehicle Types:
Source: EPA 2009 and CDOT 2009
0.000
5,000.000
10,000.000
15,000.000
Car (LDV) Truck(LDT)
Total 2001 NOX Emissions (Grams)
Total 2001 NOXEmissions(Grams)
0.000
0.050
0.100
0.150
0.200
Car (LDV) Truck (LDT)
2001 NOX Emissions Per Mile (Grams)
2001 NOXEmissions PerMile (Grams)
0.000
0.500
1.000
1.500
2.000
2.500
3.000
Car (LDV) Truck (LDT)
2001 NOX Emissions Per User (Grams)
2001 NOXEmissions PerUser (Grams)
55
It is estimated that among cars (LDV’s) the total estimated CO emission amount was
68,708 grams (lower range) and for trucks (LDT’s) it is estimated to be 106,224 grams (upper
range) for all 4,767 park-and-ride users on an average trip from home to final destination. In the
first home – station scenario, the aggregate CO emissions were 45,375 for cars and 71,903 grams
for trucks. In the home – final destination scenario (pre-light rail), the aggregate CO emission
amount was 34 percent higher for cars and 32 percent higher for trucks. In terms of per mile
traveled, the value is approximately 1.073 grams of CO per mile for cars and 1.660 grams of CO
per mile for trucks. This is roughly a 36 percent reduction for cars and a 40 percent reduction for
trucks in grams per mile from the first home – station scenario, indicating the strong per mile
impact of CO emissions for the shorter average trip length in the home – station scenario versus
the home – final destination scenario. In terms of per user from home – final destination, the
emissions value is roughly 14.412 grams of CO per user for cars and 22.282 grams of CO per
user for trucks, a 32 percent and 31 percent increase for cars and trucks, respectively, from the
first home – station estimate per user CO emission value.
The total estimated amount of HC emissions in the home-station (existing conditions) is
estimated to be 5,175 grams of CO in the case of cars and 9,134 grams of CO in the case of
trucks. This represents an 11 percent increase for cars and an 18 percent increase for trucks from
the home – station scenario. In terms of per mile HC emissions, the value is roughly 0.081 grams
of HC for cars and 0.143 grams of HC for trucks. This represents an 83 percent decrease in cars
and a 70 percent decrease in trucks for grams of HC per mile from the first home – station
scenario. In terms of per user HC emissions, the value is an estimated 1.085 grams of HC for
cars and 1.916 grams of HC for trucks. This is roughly a 9 percent increase for cars and a 15
percent increase for trucks from the first home – station scenario. Finally, the estimated total
56
amount of NOx emissions for a vehicle with an average age of nine years is estimated to be
6,861 grams of NOx for cars and 11,922 grams of NOx for trucks for all trips in their journey
from home to final destination. This represents an estimated 36 percent increase for cars and a 37
percent increase for trucks in total NOx emissions from the first home – station scenario. In
terms of per mile NOx emissions, the value is roughly 0.107 grams of NOx per mile for cars and
0.186 grams of NOx per mile for trucks, a 33 percent decrease for cars and a 31 percent decrease
for trucks from the first home – station scenario. In terms of per user NOx emissions, the value is
estimated to be 1.439 grams of NOx per user for cars 2.501 grams of NOx per user for trucks, a
34 percent increase for cars and a 35 percent increase for trucks from the first home – station
scenario.
The following table and figures indicate the total and average amount (per user) of
emissions for each emission type for each potential park-and-ride station and all potential non-
park-and-ride stations combined in the home – final destination scenario. This intends to show
the variation in estimated total emissions and emissions per user for each potential station. Once
again, the amount of emissions will be broken up by cars (LDV’s) and trucks (LDT’s) to indicate
a lower and upper bound for the emission estimate for each emission type. Total amount of
potential park-and-ride users is indicated in parentheses.
57
Table 12: Total and Average per User CO Emissions for Cars and Trucks for each Home Park-
and-Ride Station (Home – Final Destination):
Home Station (Total Users)
Total CO Emissions (Car)
CO Emissions Per User (Car)
Total CO Emissions (Truck)
CO Emissions Per User (Truck)
I-485 Station (2,260) 38,162.32 16.89 58,545.02 25.90
Sharon Road West Station (545) 7,704.81 14.14 11,924.16 21.88
Arrowood Station (438) 5,876.82 13.68 9,111.34 21.21
Archdale Station (72) 919.54 11.08 1,444.12 17.41
Tyvola Station (317) 4,189.86 11.71 6,556.36 18.33
Woodlawn Station (475) 4,972.66 10.46 7,840.70 16.50
Scaleybark Station (411) 5,086.66 11.24 7,981.13 17.63
Non-Park-and-Ride Stations (164) 1,795.10 10.94 2,281.61 17.20
Source: EPA 2009 and CDOT 2009
Figure 21: Total CO Emissions for Cars and Trucks for each Potential Station (Home – Final
Destination):
Source: EPA 2009 and CDOT 2009
0.00
10,000.00
20,000.00
30,000.00
40,000.00
50,000.00
60,000.00
70,000.00
Total CO Emissions (Car)
Total CO Emissions (Truck)
58
Figure 22: Average Per User CO Emissions for Cars and Trucks for Each Potential Station
(Home – Final Destination):
Source: EPA 2009 and CDOT 2009
0.00
5.00
10.00
15.00
20.00
25.00
30.00
CO Emissions Per User (Car)
CO Emissions Per User (Truck)
59
Table 13: Total and Average per User HC Emissions for Cars and Trucks for each Home Park-
and-Ride Station (Home – Final Destination):
Home Station (Total Users)
Total HC Emissions (Car)
HC Emissions Per User (Car)
Total HC Emissions (Truck)
HC Emissions Per User (Truck)
I-485 Station (2,260) 2,607.65 1.15 4,799.62 2.12
Sharon Road West Station (545) 587.46 1.08 1,031.71 1.89
Arrowood Station (438) 457.58 1.07 796.69 1.85
Archdale Station (72) 82.42 0.99 135.78 1.64
Tyvola Station (317) 361.63 1.01 604.39 1.69
Woodlawn Station (475) 463.97 0.98 753.05 1.58
Scaleybark Station (411) 451.59 1.00 746.65 1.65
Non-Park-and-Ride Stations (164) 162.32 0.99 266.53 1.62
Source: EPA 2009 and CDOT 2009
Figure 23: Total HC Emissions for Cars and Trucks for each Potential Station (Home – Final
Destination):
Source: EPA 2009 and CDOT 2009
0.00
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
6,000.00
Total HC Emissions (Car)
Total HC Emissions (Truck)
60
Figure 24: Average Per User HC Emissions for Cars and Trucks for Each Potential Station
(Home – Final Destination):
Source: EPA 2009 and CDOT 2009
0.00
0.50
1.00
1.50
2.00
2.50
HC Emissions Per User (Car)
HC Emissions Per User (Truck)
61
Table 14: Total and Average per User NOx Emissions for Cars and Trucks for each Potential
Park-and-Ride Station (Home – Final Destination):
Home Station (Total Users)
Total NOx Emissions (Car)
NOx Emissions Per User (Car)
Total NOx Emissions (Truck)
NOx Emissions Per User (Truck)
I-485 Station (2,260) 4,024.86 1.78 7,042.24 3.12
Sharon Road West Station (545) 763.59 1.40 1,325.63 2.43
Arrowood Station (438) 574.80 1.34 996.15 2.32
Archdale Station (72) 81.24 0.98 138.81 1.67
Tyvola Station (317) 381.36 1.07 645.38 1.83
Woodlawn Station (475) 424.66 0.89 721.80 1.52
Scaleybark Station (411) 452.89 1.00 774.65 1.71
Non-Park-and-Ride Stations (164) 157.45 0.96 268.72 1.64
Source: EPA 2009 and CDOT 2009
Figure 25: Total NOx Emissions for Cars and Trucks for each Potential Station (Home – Final
Destination):
Source: EPA 2009 and CDOT 2009
0.00
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
6,000.00
7,000.00
8,000.00
Total NOX Emissions (Car)
Total NOX Emissions (Truck)
62
Figure 26: Average Per User NOx Emissions for Cars and Trucks for Each Potential Station
(Home – Final Destination):
Source: EPA 2009 and CDOT 2009
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
NOX Emissions Per User (Car)
NOX Emissions Per User (Truck)
63
According to the results above, the station reporting the highest amount of emissions for
each emission type was once again the I-485 station which, as noted before, also had the highest
amount of users and VMT. Total CO emissions for cars (LDV’s), which represents a lower
bound emission limit for this study, ranged from an estimated 920 grams of CO emissions at the
Archdale park-and-ride station to 38,162 grams at the I-485 station. Total CO per user for cars
ranged from 10.46 grams at the Woodlawn station to 16.89 grams at the I-485 station. CO
emissions per user was the highest at the I-485 station and tended to decline at each ensuing
station further in toward the CBD. In terms of HC emissions for cars, the absolute estimated total
HC emission value ranged from 82 grams at Archdale station to 2,608 grams at the I-485 station.
In terms of per user HC emissions, the station with the lowest average per user HC emission
value was Woodlawn with 0.98 grams and the highest was the I-485 station with 1.15 grams. In
terms of NOx emissions, the amount of total estimated NOx emissions for cars ranged from 81
grams at Archdale to 4,025 grams at the I-485 station. The amount of total per user NOx
emissions for cars ranged from 0.96 grams at the non park-and-ride stations to 1.78 grams at the
I-485 station.
Total and average emissions of CO, HC, and NOx for trucks (LDT’s) were substantially
higher and represent an upper bound emission limit for this study. In terms of total CO emissions
for the home – final destination scenario, the station with the lowest overall CO emissions was
Archdale station with an estimated 1,444 grams of CO for all users, while the highest overall CO
emissions for any station was the I-485 station with 58,545 grams. Average per user CO
emissions for trucks ranged from 16.50 grams at Archdale station to 25.90 grams at Scaleybark
station. In terms of HC emissions for trucks, the station with the lowest overall HC emission
value for trucks was Archdale station with 136 grams of HC emissions and the station with the
64
highest was the I-485 station with an aggregate 4,900 grams. The estimated per user truck
emission value for HC emissions ranged from 1.58 grams at Woodlawn station to 2.12 grams at
the I-485 station. Finally, in terms of estimated NOx emissions for trucks, the total estimated
emissions ranged from 139 grams at Archdale station to 7,042 grams at the I-485 station. The per
user NOx emission value for trucks ranged from 1.52 grams at Woodlawn station to 3.12 grams
at the I-485 station. In terms of per user emissions, the top three stations were I-485, Sharon
Road West, and Arrowood for CO and NOx emissions and I-485, Sharon Road West, and
Woodlawn stations for HC emissions. The following figures indicate the difference between total
and average per user emissions for CO emissions for both cars (LDV’s) and trucks (LDT’s).
65
Figure 27: Aggregate CO Emissions for Cars (LDV’s) for the Home – Station Scenario and the
Home – Final Destination Scenario:
Source: EPA 2009 and CDOT 2009
Figure 28: Average Per User CO Emissions for Cars (LDV’s) for the Home – Station Scenario
and the Home – Final Destination Scenario:
Source: EPA 2009 and CDOT 2009
0.005,000.00
10,000.0015,000.0020,000.0025,000.0030,000.0035,000.0040,000.0045,000.00
Total CO Emissions Home -Station (Car)
Total CO Emissions Home - FinalDestination (Car)
0.002.004.006.008.00
10.0012.0014.0016.0018.00
Per User CO Emissions Home -Station (Car)
Per User CO Emissions Home -Final Destination (Car)
66
Figure 29: Aggregate CO Emissions for Trucks (LDT’s) for the Home – Station Scenario and the
Home – Final Destination Scenario:
Source: EPA 2009 and CDOT 2009
Figure 30: Average Per User CO Emissions for Cars (LDV’s) for the Home – Station Scenario
and the Home – Final Destination Scenario:
Source: EPA 2009 and CDOT 2009
0.00
10,000.00
20,000.00
30,000.00
40,000.00
50,000.00
60,000.00
70,000.00
Total CO Emissions Home -Station (Truck)
Total CO Emissions Home - FinalDestination (Truck)
0.00
5.00
10.00
15.00
20.00
25.00
30.00
Per User CO Emissions Home -Station (Truck)
Per User CO Emissions Home -Final Destination (Truck)
67
In the final part of the emissions analysis, hot soak was calculated for all survey users and
expanded users (using the Combined ExpFactor Linked field) of park-and-ride lots. The hot soak
time was calculated for nine hours for all surface parking lots (typical work day), and for one
hour at the I-485 parking deck, which approximates cool down time. Hot soak evaporative
emissions were calculated for Sharon Road West, Arrowood, Archdale, Tyvola, Woodlawn,
Scaleybark and non-park-and-ride (assumed to be open-air) stations for nine hours, accounting
for 144 of the 309 survey respondents or roughly 46.6 percent of all park-and-ride users in the
survey (CDOT) and one hour for the remaining 165 users of the I-485 station. Once again, cold
start emissions are evaporative emissions from cars left sitting in an open parking space during
the day (applies to all but I-485 station) as well as cool down time (applies to all stations). It is
important to note that hot soak assumes sunny conditions with no overcast, as evaporative
emissions are highest during these types of days. Based on this assumption, all cloudy days will
be excluded from the purpose of this study and an average percent based on the average number
of sunny days in a year will be used for the evaporative emissions section. According to the
NOAA National Data Center, there are an average of 152 cloudy days in Charlotte and 204 clear
or partly cloudy days (NOAA). This means that approximately 55.9 percent of all days are clear
or partly cloudy. The first part of the study will assume 100 percent sunny conditions as a base
estimate while the second part will assume that approximately 55.9 percent of hot soak emissions
are escaping into the atmposhere (based approximate existing conditions). For the purpose of this
study, the same assumption will be applied to the results calculated. According to the EPA, the
average car emitted 0.2196 grams of cumulative evaporative emissions in a nine-hour period in
2001 (EPA 2001). This rate will be applied to all of the park-and-ride users. It is also important
to note that hot soak emissions are a type of HC emissions.
68
The total amount of estimated hot soak evaporative emissions for all 144 survey users
parked in open decks is roughly 31.622 grams of HC emissions. The amount is 4.026 grams of
HC emissions for the 165 users at the I-485 station representing the cool down period only for
that station. The amount of hot soak emissions for all park-and-ride users (using the Combined
ExpFactor Linked field variable) is approximately 550.589 grams for all open air lots and 55.147
grams at the I-485 station for an estimated total of 605.736 grams of HC emissions. The total
amount of evaporative hot soak HC emissions is small when compared to the total HC cold start
and running emissions on a park-and-ride user’s trip. Based on 100 percent clear and partly
cloudy days, the total HC estimated emission value for all trips from home – station is 4,587
grams for cars and 7,522 for trucks. After including the HC emissions for hot soak, the new
estimated total is roughly 5,193 grams for cars and 8,128 grams for trucks. This means that hot
soak emissions accounted for an estimated 11.7 percent for cars (lower HC emission bound) and
7.5 percent for trucks (upper HC emission bound). Shown below is a table and figure indicating
estimated total hot soak HC emissions for each park-and-ride station and all non-park-and-ride
stations combined for 100 percent clear and partly cloudy days. The total number of users is
indicated in parentheses in figure 31.
Table 15: Total Hot Soak HC Emissions (in grams) by Station for all Park-and-Ride User’s
assuming 100 percent ideal sunny and partly cloudy weather:
Station (Users) HC Hot Soak Emissions
I-485 Station (2,260) 55.147
Sharon Road West Station (545) 119.696
Arrowood Station (430) 94.332
Archdale Station (83) 18.217
Tyvola Station (358) 78.567
Woodlawn Station (434) 104.36
Scaleybark Station (452) 99.395
Non-Park-and-Ride Stations (164) 36.021
Source: EPA 2009 and CDOT 2009
69
Figure 31: Total Hot Soak HC Emissions (in grams) by Station for all Park-and-Ride Users
assuming 100 percent ideal sunny and partly cloudy weather:
Source: EPA 2009 and CDOT 2009
The graphs below shows the share of estimated hot soak HC emissions among all HC
emissions for both the home – station scenario and the home – final destination scenario for both
cars (LDV’s) and trucks (LDT’s) based on 100 percent ideal sunny/partly cloudy conditions.
0
20
40
60
80
100
120
140
HC Hot Soak Emissions
HC Hot Soak Emissions
70
Figure 32: Total Running and HC Emissions in the Home – Station Scenario for Cars (LDV’s)
assuming 100 percent ideal sunny and partly cloudy weather:
Source: EPA 2009 and CDOT 2009
Figure 33: Total Running and HC Emissions in the Home – Station Scenario for Trucks (LDT’s)
assuming 100 percent ideal sunny and partly cloudy weather:
Source: EPA 2009 and CDOT 2009
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
HC hot soak
HC Runing Car
0.00500.00
1,000.001,500.002,000.002,500.003,000.003,500.004,000.004,500.00
HC hot soak
HC Running Truck
71
Figure 34: Total Running and HC Emissions in the Home – Final Destination Scenario for Cars
(LDV’s) assuming 100 percent ideal sunny and partly cloudy weather:
Source: EPA 2009 and CDOT 2009
Figure 35: Total Running and HC Emissions in the Home – Final Scenario for Cars (LDV’s)
assuming 100 percent ideal non-cloudy sunny and partly cloudy weather:
Source: EPA 2009 and CDOT 2009
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
HC hot soak
HC Running Car
0.00
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
6,000.00
HC hot soak
HC Running Truck
72
The second part of the estimated average amount of evaporative hot soak emissions will
assume thet 55.9 percent of the total evaporative emissions are escaping into the atmosphere in a
given day. This is based on the average number of sunny and partly cloudy days in a year in the
Charlotte region (NOAA). This is a more accurate look at the total estimated evaporative
emissions escaping into the atmosphere in a random day in Charlotte. Based on this new
estimate, the total amount of estimated hot soak evaporative emissions for all 144 survey users
parked in open decks is roughly 17.677 grams of HC emissions. The amount is 2.25 grams of HC
emissions for the 165 users at the I-485 station representing the cool down period only for that
station. The amount of hot soak emissions for all park-and-ride users (using the Combined
ExpFactor Linked field variable) is approximately 307.779 grams for all open air lots and 30.827
grams at the I-485 station for an estimated total of 338.606 grams of HC emissions. The total
amount of evaporative hot soak HC emissions is now even smaller when compared to the total
HC cold start and running emissions on a park-and-ride user’s trip. Based on 55.9 percent clear
and partly cloudy days, the total HC estimated emission value for all trips from home – station
was 4,587 grams for cars and 7,522 for trucks. After including the HC emissions for hot soak,
the new estimated total was roughly 4,926 grams for cars and 7,861 grams for trucks. This means
that hot soak emissions accounted for an estimated 6.9 percent for cars (lower HC emission
bound) and 4.3 percent for trucks (upper HC emission bound). Shown below is a table and figure
indicating estimated total hot soak HC emissions for each park-and-ride station and all non-park-
and-ride stations combined for 55.9 percent clear and partly cloudy days. The total number of
users is indicated in parentheses in figure 36.
73
Table 16: Total Hot Soak HC Emissions (in grams) by Station for all Park-and-Ride User’s
assuming 55.9 percent ideal non-cloudy weather:
Station (Users) HC Hot Soak Emissions
I-485 Station (2,260) 30.827
Sharon Road West Station (545) 66.910
Arrowood Station (430) 52.732
Archdale Station (83) 10.183
Tyvola Station (358) 43.919
Woodlawn Station (434) 58.337
Scaleybark Station (452) 55.562
Non-Park-and-Ride Stations (164) 20.136
Source: NOAA, EPA 2009 and CDOT 2009
Figure 36: Total Hot Soak HC Emissions (in grams) by Station for all Park-and-Ride Users
assuming 55.9 percent ideal non-cloudy weather:
Source: NOAA, EPA 2009 and CDOT 2009
The graphs below shows the share of estimated hot soak HC emissions among all HC
emissions for both the home – station scenario and the home – final destination scenario for both
cars (LDV’s) and trucks (LDT’s) based on 55.9 percent ideal sunny/partly-cloudy conditions.
This a better picture as to the impact hot soak HC emissions has on overall HC emissions.
01020304050607080
HC Hot Soak Emissions
HC Hot Soak Emissions
74
Figure 37: Total Running and HC Emissions in the Home – Station Scenario for Cars (LDV’s)
assuming 55.9 percent ideal sunny and partly cloudy weather:
Source: NOAA, EPA 2009 and CDOT 2009
Figure 38: Total Running and HC Emissions in the Home – Station Scenario for Trucks (LDT’s)
assuming 55.9 percent ideal sunny and partly cloudy weather:
Source: NOAA, EPA 2009 and CDOT 2009
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
HC hot soak
HC Runing Car
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
3,500.00
4,000.00
4,500.00
HC hot soak
HC Running Truck
75
Figure 39: Total Running and HC Emissions in the Home – Final Destination Scenario for Cars
(LDV’s) assuming 55.9 percent ideal sunny and partly cloudy weather:
Source: NOAA, EPA 2009 and CDOT 2009
Figure 40: Total Running and HC Emissions in the Home – Final Destination Scenario for
Trucks (LDT’s) assuming 55.9 percent ideal sunny and partly cloudy weather:
Source: NOAA, EPA 2009 and CDOT 2009
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
HC hot soak
HC Running Car
0.00
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
6,000.00
HC hot soak
HC Running Truck
76
Chapter 5: Concluding Proposals
The purpose of this thesis is to determine whether vehicle miles traveled and vehicle
emissions have increased or decreased in Charlotte as a result of light rail park-and-ride lot usage
among commuters and to what extent. The analysis of the estimates indicated an estimated 50%
drop in vehicle miles traveled among park-and-ride users by patronizing park-and-ride and light
rail for part of the trip instead of driving the entire trip. The final emissions result for the home –
final destination scenario had less of an impact per user mile due to the adverse affects of
running emissions on shorter home – station trips. Total CO emissions were reduced by an
estimated 34 percent for cars (LDV’s) and 32 percent for trucks (LDT’s) by driving to a park-
and-ride lot and using light rail instead of driving the entire trip. Aggregate NOx emissions were
reduced by 36 percent for cars and 37 percent for trucks among the estimated daily total park-
and-ride users by traveling part of the journey by light rail instead of driving directly to the final
destination. Finally, HC emissions had two factors, one accounting for HC running emissions
during the actual trip and the other accounting for hot soak emissions while the car is parked.
Accounting just for change in HC emissions for the trip alone, total HC emission was reduced by
an estimated 11 percent for cars and 18 percent for trucks among park-and-ride users by using
park-and-ride and light rail instead of driving the entire distance. However, when accounting for
hot soak and assuming park-and-ride users parked in open air parking locations at their final
destination, aggregate HC emissions decreased by 11 percent (relatively no difference between
the two estimates) for cars and decreased 20 percent for trucks among park-and-ride users by
using park-and-ride and light rail instead of driving to the final destination.
The greatest factor contributing to a higher emission rate among shorter home-station
trips was the impact of cold-start. The impact of hot soak was largely negligible, making up less
77
than about 12 percent of all car (LDV) HC emissions and 7 – 8 percent of all truck (LDT) HC
emissions. There are many assumptions equated with this study that detract from its overall
accuracy, including the use of national averages and coefficients to determine emissions and
vehicle age. In the case of emissions, the study provided emission estimates for both cars and
trucks to give a high and low range.
The true impact of reducing VMT and emissions among park-and-ride users is relatively
low due to the small amount of people using park-and-ride lots as a means of transportation into
the CBD or along the light rail line. It is estimated during the week of September 7th
through the
11th
, an average of 1,758 cars were parked at all park-and-ride stations, 960 of which were
located at the I-485/Pineville park-and-ride deck. All of the current light rail park-and-ride
facilities have a combined capacity of 3,191 parking spaces, which indicates that stations were
operating at approximately 55 percent capacity during the work week of September 7th
through
the 11th
in the middle of the day. If this sample represents the amount of people using the light
rail park-and-ride lots as a means of transportation to the final destination [incomplete sentence].
Indeed, the total VMT impact is estimated to be about 0.2 percent for the home – station
(existing conditions) scenario and 0.4 percent for the home – final destination (pre-existing
conditions) scenario of total VMT in Charlotte. This translates to roughly a 0.2 percent decrease
in aggregate VMT in Charlotte as a result of park-and-ride users choosing to patronize park-and-
ride and light rail instead of driving the entire trip. According to a CATS 2009 survey,
approximately 56 percent of all trips made on the light rail are home-based work trips (either
traveling from home to work or work to home as trip type). As a result, as suspected, the impact
would be a very slight decrease in VMT and emissions among all morning CBD commuters. The
recent on-board survey provided by the Charlotte Area Transit System and the CDOT estimated
78
how many people are actually boarding the light rail by station as of 2009 by using the
ExpFactor Linked field to expand the survey sample as well as what their average travel distance
is between origin TAZ and destination TAZ.
The final estimated VMT for the home – station scenario is about 30,973 miles and the
estimated VMT for the home – final destination scenario is roughly 64,009 miles. The absolute
VMT decrease is estimated to be about 33,036 miles travelled between both estimates and about
52 percent.
The final part of this study is intended to roughly estimate what the VMT change would
be if all park-and-ride lots were substituted with transit-oriented developments (TOD’s) for
varying scenarios. In 1995 the average VMT per person in Charlotte was roughly 21.7 miles
travelled (EPA 2003). However, it is likely that this level has increased on a per person average
basis and the overall VMT per person for Charlotte is estimated to be roughly 22.5 miles
travelled in 2010, which is similar to levels found in other southern cities including Atlanta,
Dallas, and Houston (Sorensen 2010). There are many different estimates for how much VMT
can be reduced among TOD dwellers by building a TOD around a light rail or commuter rail
stop but the averages seemed to range from 15 – 30 percent, according to the literature.
According to Ewing, doubling of densities can result in a 25 – 30 percent reduction in VMT
(Ewing 1997). Consistent with this, a report prepared by the Puget Sound Regional Council
found that by increasing densities at intersections by 10 percent resulted in a 0.5 percent decrease
in VMT (Litman 2011). According to Dill, TOD residents of Portland TOD’s saw an average
decrease of 19 – 30 percent in VMT versus the city as a whole (Dill 2004 and Dill 2006). In
another study by Ohland and Poticha, VMT was found to decrease by 43 percent among TOD
dwellers or a total of 9.80 VMT for TOD residents versus 17.34 VMT for the average resident in
79
the county as a whole. In a study by CCAP completed in 2003, it was found that the average
decline in VMT among Atlanta mixed-use projects ranged from 15 – 52 percent and that a mixed
use development located 0.1 miles away for a transit station saw an average 38 percent reduction
in VMT among residents (CCAP 2003). According to a report released by the TCRP, VMT
decreased by an average 15 – 25 percent for low density suburban areas in four case studies:
Washington DC, Philadelphia, Portland, and San Francisco (Arrington and Cervero 2008).
For the purpose of this study, ten different TOD scenarios are presented that estimate the
average VMT savings for all of the TOD residents if the seven park-and-ride facilities were
replaced with TOD’s based on average VMT reduction and housing density. The typical size of a
new TOD in Charlotte ranged from 269 units to 360 units tended to be about 300 units on
average or just over 500 residents. 300 housing units and 500 TOD residents will be used for a
lower bound density estimate with 600 units and 1,000 TOD residents being used as an upper
bound estimate. For each density level five different VMT reduction assumptions will be
estimated. The first scenario will assume a lower bound estimate shown in the literature (15
percent reduction), the second will indicate a middle-low bound estimate (20 percent reduction),
the third will show a middle-high bound (25 percent reduction), the fourth will indicate a upper
bound estimate (about 30 percent reduction), and the final will assume that the rate of VMT
reduction in Charlotte is similar to the rate of VMT reduction in Portland, Oregon among TOD
residents (around 43 percent). The following tables and figures indicate the results in estimated
VMT reductions for the ten scenarios and are based on an original non-TOD VMT per capita
estimate of 22.5 miles travelled for the average Charlotte resident.
80
Table 17: VMT reduction among TOD residents for five reduction rate scenarios for 500 people
(300 households):
VMT Reduction (%) VMT Reduction (ABS) TOD VMT Charlotte VMT
Low 15% 3.4 19.1 22.5
Middle-Low 20% 4.5 18.0 22.5
Middle-High 25% 5.6 16.9 22.5
High 30% 6.7 15.8 22.5
Portland 43% 9.8 12.7 22.5
Reduction Rate Households Population # Stations Total People
Charlotte VMT
TOD VMT
VMT Savings
Low (15%) 300 500 7 3,500 78,750 66,850 11,900
Middle-Low (20%) 300 500 7 3,500 78,750 63,000 15,750
Middle-High (25%) 300 500 7 3,500 78,750 59,150 19,600
High (30%) 300 500 7 3,500 78,750 55,300 23,450
Portland (43%) 300 500 7 3,500 78,750 44,450 34,300
Figure 41: VMT Reduction Amounts by Scenario (500 People):
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
VMT Savings (500 ppl)
VMT Savings (500 ppl)
81
Table 18: VMT reduction among TOD residents for five reduction rate scenarios for 1,000
people (600 households):
VMT Reduction (%) VMT Reduction (ABS) TOD VMT Charlotte VMT
Low 15% 3.4 19.1 22.5
Middle-Low 20% 4.5 18.0 22.5
Middle-High 25% 5.6 16.9 22.5
High 30% 6.7 15.8 22.5
Portland 43% 9.8 12.7 22.5
Reduction Rate Households Population # Stations Total People
Charlotte VMT
TOD VMT
VMT Savings
Low (15%) 600 1,000 7 7,000 157,500 133,700 23,800
Middle-Low (20%) 600 1,000 7 7,000 157,500 126,000 31,500 Middle-High (25%) 600 1,000 7 7,000 157,500 118,300 39,200
High (30%) 600 1,000 7 7,000 157,500 110,600 46,900
Portland (43%) 600 1,000 7 7,000 157,500 88,900 68,600
Figure 42: VMT Reduction Amounts by Scenario (500 People):
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
VMT Savings (1,000 ppl)
VMT Savings (1,000 ppl)
82
Figure 43: Differences in VMT reduction for the two density level scenarios:
According to the results above, a roughly estimated 11,900 VMT to 34,300 VMT would
be saved based on reduction rate for the 300 household scenario. A total estimate of 23,800 VMT
to 68,600 VMT would be saved based on the reduction rate for the higher density 600 household
scenario. It is likely that the average VMT decrease, based on findings in the literature, would be
roughly about 20 – 25 percent in the Charlotte context. Based on this assumption, the likely
VMT savings amount in the Charlotte area for TOD residents at the seven current park-and-ride
stations would be an estimated 15,750 – 19,600 miles traveled for the 500 resident scenario and
31,500 – 39,200 miles traveled in the 1,000 resident scenario. An even mix of 500 resident and
1,000 resident TOD’s would roughly result in a VMT savings of 23,525 miles traveled to 29,400
miles traveled based on a 20 – 25 percent reduction in VMT. However, the key findings of the
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
Low (15%) Middle-Low(20%)
Middle-High(25%)
High (30%) Portland(43%)
VMT Savings (500 ppl)
VMT Savings (1,000 ppl)
83
home – station versus home – final destination indicated a roughly higher VMT savings of an
estimated 33,036 miles traveled. In order to meet the estimated reduction in VMT of park-and-
ride, TOD savings for the 500 average TOD dwellers per station scenario would have to be 43
percent or greater (the very high Portland case study). Based on the estimate for VMT savings
for the average 1,000 (high density) average TOD dwellers per station scenario, the VMT
reduction amount would have to be roughly 20 percent or greater (middle-low VMT reduction
rate). Based on these findings, park-and-ride is more likely a better choice in the Charlotte
context for reducing VMT in more suburban parts of the city. If TOD’s in the city had a higher
density of 1,000 dwellers per TOD (twice the current average Charlotte TOD density) than the
VMT savings might be greater than the average savings created by park-and-ride.
84
Chapter 6: Future Research
This research has provided an indication as to the VMT and emission impact of park-and-
ride use in a rapidly growing US Sunbelt city. Very few studies have been done specifically
looking at the VMT costs of using park-and-ride lots and even fewer have been done in the US
context, with none observing the impact in Charlotte, NC. The minimal impact on VMT (about a
0.3 percent reduction) among park-and-ride users could challenge the park-and-ride role as a
congestion reducer and an effective way of getting people to use transit in Charlotte. Further
studies could explore the park-and-ride/Transit-Oriented Development tradeoff further to see
which is more effective in reducing VMT, emissions and congestion. Though TODs may not
necessarily increase ridership as much as park-and-ride, they have been shown to reduce
automobile congestion and emissions by reducing the need for development along the urban
fringe, preserving green fields, encouraging efficient trip chaining (combining all errands or trips
into one sensible trip), and boosting walking accessibility through the smart use of land around a
transit station. Additionally, another drawback to the study is that it fails to capture the true mix
of vehicles being used to reach Charlotte park-and-ride stations and uses only national
coefficients and averages to determine regional vehicle emissions. A future study that had a
better sample of the actual vehicle fleet in question would yield much more accurate results with
regard to vehicle age and emission rates. In this case, capturing license plate numbers and
collecting vehicle type and origin data would yield much more accurate results for estimating
regional emissions and determining better origin data for all park-and-ride users in a given day.
Future studies could also look into the impact of induced demand and transit abstraction,
which are talked about frequently in the literature review as major indirect effects of increasing
85
levels of congestion and VMT among park-and-ride users. Since there was no data in the 2009
on-board user survey to indicate how many people were using transit before switching to park-
and-ride, it is hard to tell the true effect of transit abstraction in the Charlotte case study. For
every park-and-ride user that was using bus transit before the advent of light rail in Charlotte, a
switch from only bus to park-and-ride (auto/light rail) usage would result in an even higher VMT
and emission rate among the park-and-ride users. The induced demand effect (trips removed
from the roadway network due to park-and-ride auto-interception are being replaced by new trips
encouraging new auto users to quickly fill up the newly created open spaces on the road, many of
which are going into the center city) is also an important indirect effect that could be modeled in
future research. The induced demand effect could also be modeled if all park-and-ride stations
were replaced with TOD and the two scenarios could be compared to see which has the greater
impact in reducing induced traffic and congestion. The impact of induced demand could be
modeled in the future by using a transportation modeling system that accounts for feedback loops
and latent demand (Litman 2010) as well as incorporating the interrelationships between land
use, density, and transport (Litman 2010). There are several modeling systems that could be
employed to help model the impact of induced demand including the FHWA SMITE
(Spreadsheet Model for Induced Travel Estimation), TRANUS and MEPLAN (Litman 2010).
According to Litman’s paper, the main elements and variables needed to estimate induced
demand are generated traffic growth rates (e.g. elasticity of traffic volume with respect to road
volume), discount rate, maximum peak vehicles per lane, before average speed limit, after
average speed limit, volume of peak-period travel time, vehicle operating costs, annual lane
hours at capacity in both directions, diverted trips external costs, and induced travel external
costs. There was some general consensus in the literature that these indirect effects can possibly
86
lead to more congestion and more VMT if not addressed in the planning stages of park-and-ride
development.
87
References
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Transport Geography 17 (6) (2009): 468-475.
14. National Oceanic and Atmospheric Administration. “Cloudiness – Mean Number of Days
(Clear, Partly Cloudy, Cloudy)” Data Table (1971 – 2000):
http://www1.ncdc.noaa.gov/pub/data/ccd-data/nrmavg.txt
15. RITA BTS. “National Transportation Statistics.” Published by Research and Innovative
Technology Administration Bureau of Transportation Statistics, Washington, D.C., 2009.
16. Parkhurst, Graham. “Park and Ride: Could it lead to an Increase in Car Traffic?”
Transport Policy 2(1) (1995): 15-23.
17. Parkhurst, Graham. “Influence of Bus-based Park and Ride facilities on Users’ Car
Traffic.” Transport Policy 7 (2000): 159-172.
18. RPS. “The effectiveness and Sustainability of Park and Ride.” Published by Historic
Towns Forum, Bristol, UK, June 12, 2009.
19. Semmens, John. “Does Light Rail Worsen Congestion and Air Quality?” Published by
Laissez Faire Institute, Chandler, Arizona, June 2005.
20. Sherwin, H. “Park and Ride – Its Role in Local Transport Policy.” Published by the
CPRE, London, UK (1998).
21. Sorensen, Paul. “Population Density versus Per-Capita VMT for the 14 Largest U.S.
Metropolitan Regions.” January 8, 2010:
http://www.newgeography.com/content/001317-population-density-vs-per-capita-vmt-
14-largest-us-metropolitan-regions
22. US Environmental Protection Agency. “Development of Emission Rates for Light-Duty
Vehicles in the Motor Vehicles Simulator (MOVES 2009).” Published by the US
Environmental Protection Agency, Washington, D.C., August, 2009.
23. US Environmental Protection Agency. “Development of Methodology for Estimating
VMT Weighting by Facility Type.” Published by the US Environmental Protection
Agency, Washington, D.C., April, 2001.
24. US Environmental Protection Agency. “User’s guide to Mobile 6.1 and Mobile 6.2
Mobile Source Emission Factor Model.” Published by the US Environmental Protection
Agency, Washington, D.C., August, 2003.
25. Whitefield, Steff and Bryan Cooper. “The Travel Effects of Park and Ride.” WS Atkins
Planning Consultants (1998).
89
Appendices
Table 19: Average start and running emissions for cars and trucks by model year:
90
Table 20: The following table indicates the number of survey users (indicated by #) for each
station, the origin and destination TAZ (PTAZ and ATAZ respectively) for each user, the
estimated number of additional people using the light rail and travelling on a similar path (the
Combined ExpFactor Linked field), and VMT per user (determined by the average trip length
from the PTAZ to ATAZ using the OD pair matrix provided by CDOT), and the VMT for all
estimated park-and-ride users (determined by multiplying the VMT survey result by the the
Combined ExpFactor Linked field) for the home – station scenario:
# FINAL_ON_Station PTAZ ATAZ Combined ExpFactor Linked
VMT Survey VMT All
1 Archdale Station 11029 11029 11.0 2.6 28.3
2 Archdale Station 11029 11029 19.7 2.3 46.2
3 Archdale Station 11029 11029 19.7 1.9 38.0
4 Archdale Station 11029 11029 22.0 1.3 28.1
5 Arrowood Station 11030 11030 0.6 24.6 14.9
6 Arrowood Station 11030 11030 8.0 19.8 159.3
7 Arrowood Station 11030 11030 16.1 13.3 213.1
8 Arrowood Station 11030 11030 13.1 10.8 141.4
9 Arrowood Station 11030 11030 18.1 10.5 190.5
10 Arrowood Station 11030 11030 9.7 10.5 102.0
11 Arrowood Station 11030 11030 9.7 10.1 98.3
12 Arrowood Station 11030 11030 3.9 9.4 36.2
13 Arrowood Station 11030 11030 16.1 9.3 149.3
14 Arrowood Station 11030 11030 16.1 8.4 135.5
15 Arrowood Station 11030 11030 16.1 8.4 135.5
16 Arrowood Station 11030 11030 16.1 7.9 126.7
17 Arrowood Station 11030 11030 36.5 7.3 265.2
18 Arrowood Station 11030 11030 16.1 6.6 105.3
19 Arrowood Station 11030 11030 9.7 5.2 50.8
20 Arrowood Station 11030 11030 9.7 4.8 46.8
21 Arrowood Station 11030 11030 9.7 4.5 44.0
22 Arrowood Station 11030 11030 18.1 3.9 70.8
23 Arrowood Station 11030 11030 16.1 3.9 62.7
24 Arrowood Station 11030 11030 14.6 3.0 43.6
25 Arrowood Station 11030 11030 16.1 2.8 45.3
26 Arrowood Station 11030 11030 16.1 2.5 40.1
27 Arrowood Station 11030 11030 16.1 2.5 40.1
28 Arrowood Station 11030 11030 16.1 2.5 40.1
29 Arrowood Station 11030 11030 36.5 1.3 49.0
30 Arrowood Station 11030 11030 18.1 1.3 23.3
31 Arrowood Station 11030 11030 18.1 1.0 18.8
32 Arrowood Station 11030 11030 2.3 0.9 2.2
91
33 Arrowood Station 11030 11030 8.2 0.9 7.8
34 Arrowood Station 11030 11030 16.1 0.7 11.9
35 I-485 Station 10522 10522 16.0 25.5 407.2
36 I-485 Station 10522 10522 16.0 21.7 347.0
37 I-485 Station 10522 10522 7.9 20.6 162.4
38 I-485 Station 10522 10522 16.0 19.9 318.8
39 I-485 Station 10522 10522 7.9 17.9 141.3
40 I-485 Station 10522 10522 16.0 17.6 281.3
41 I-485 Station 10522 10522 16.0 16.7 266.4
42 I-485 Station 10522 10522 16.0 15.9 254.0
43 I-485 Station 10522 10522 16.0 15.8 253.0
44 I-485 Station 10522 10522 29.7 15.7 466.3
45 I-485 Station 10522 10522 7.9 15.0 118.3
46 I-485 Station 10522 10522 16.0 15.0 239.6
47 I-485 Station 10522 10522 14.7 14.7 216.8
48 I-485 Station 10522 10522 16.0 14.3 228.6
49 I-485 Station 10522 10522 7.9 14.0 110.6
50 I-485 Station 10522 10522 0.7 13.8 9.2
51 I-485 Station 10522 10522 11.7 13.7 160.3
52 I-485 Station 10522 10522 7.9 13.7 107.6
53 I-485 Station 10522 10522 16.0 13.6 218.2
54 I-485 Station 10522 10522 14.7 13.3 195.8
55 I-485 Station 10522 10522 16.2 13.0 211.6
56 I-485 Station 10522 10522 14.7 12.8 188.3
57 I-485 Station 10522 10522 16.0 12.8 204.6
58 I-485 Station 10522 10522 16.0 12.8 204.6
59 I-485 Station 10522 10522 16.0 12.8 204.6
60 I-485 Station 10522 10522 7.9 12.5 98.8
61 I-485 Station 10522 10522 16.0 12.1 193.3
62 I-485 Station 10522 10522 16.0 12.0 191.5
63 I-485 Station 10522 10522 7.9 11.8 93.1
64 I-485 Station 10522 10522 14.7 11.7 172.5
65 I-485 Station 10522 10522 7.9 11.7 92.3
66 I-485 Station 10522 10522 16.0 11.7 186.6
67 I-485 Station 10522 10522 7.9 11.6 91.6
68 I-485 Station 10522 10522 16.0 11.6 186.0
69 I-485 Station 10522 10522 16.0 11.3 180.2
70 I-485 Station 10522 10522 7.9 11.1 87.1
71 I-485 Station 10522 10522 16.0 10.8 171.9
72 I-485 Station 10522 10522 16.0 10.7 171.1
73 I-485 Station 10522 10522 16.0 10.7 171.1
74 I-485 Station 10522 10522 7.9 10.5 82.9
75 I-485 Station 10522 10522 16.0 10.5 167.6
76 I-485 Station 10522 10522 7.9 10.3 81.3
77 I-485 Station 10522 10522 7.9 10.3 81.1
78 I-485 Station 10522 10522 7.9 10.3 81.1
79 I-485 Station 10522 10522 16.0 10.3 164.6
80 I-485 Station 10522 10522 14.7 10.2 149.9
92
81 I-485 Station 10522 10522 16.0 10.2 162.9
82 I-485 Station 10522 10522 14.7 10.0 146.8
83 I-485 Station 10522 10522 16.0 10.0 159.5
84 I-485 Station 10522 10522 14.7 9.9 145.9
85 I-485 Station 10522 10522 7.9 9.9 78.1
86 I-485 Station 10522 10522 7.9 9.9 78.1
87 I-485 Station 10522 10522 7.9 9.9 78.1
88 I-485 Station 10522 10522 16.0 9.9 158.5
89 I-485 Station 10522 10522 16.0 9.4 151.1
90 I-485 Station 10522 10522 1.9 9.4 18.1
91 I-485 Station 10522 10522 7.9 9.4 74.4
92 I-485 Station 10522 10522 7.9 9.4 74.4
93 I-485 Station 10522 10522 16.0 9.3 148.6
94 I-485 Station 10522 10522 7.9 8.9 70.2
95 I-485 Station 10522 10522 16.0 8.8 141.1
96 I-485 Station 10522 10522 16.0 8.8 141.1
97 I-485 Station 10522 10522 7.9 8.8 69.1
98 I-485 Station 10522 10522 7.9 8.8 69.1
99 I-485 Station 10522 10522 7.9 8.4 65.9
100 I-485 Station 10522 10522 14.7 8.2 121.1
101 I-485 Station 10522 10522 11.7 8.2 96.3
102 I-485 Station 10522 10522 11.7 8.2 96.3
103 I-485 Station 10522 10522 16.0 8.2 130.3
104 I-485 Station 10522 10522 14.7 8.1 119.5
105 I-485 Station 10522 10522 14.7 8.1 119.5
106 I-485 Station 10522 10522 7.9 8.1 63.9
107 I-485 Station 10522 10522 7.9 8.1 63.9
108 I-485 Station 10522 10522 16.0 8.1 129.2
109 I-485 Station 10522 10522 16.0 8.1 129.2
110 I-485 Station 10522 10522 16.0 8.1 129.2
111 I-485 Station 10522 10522 16.0 7.9 125.9
112 I-485 Station 10522 10522 16.0 7.9 125.9
113 I-485 Station 10522 10522 7.9 7.9 62.0
114 I-485 Station 10522 10522 16.0 7.9 125.9
115 I-485 Station 10522 10522 16.0 7.8 124.0
116 I-485 Station 10522 10522 16.0 7.8 124.0
117 I-485 Station 10522 10522 16.0 7.8 124.0
118 I-485 Station 10522 10522 16.0 7.8 124.0
119 I-485 Station 10522 10522 29.7 7.7 229.8
120 I-485 Station 10522 10522 16.0 7.7 123.9
121 I-485 Station 10522 10522 16.0 7.7 123.9
122 I-485 Station 10522 10522 7.9 7.7 61.0
123 I-485 Station 10522 10522 7.9 7.7 61.0
124 I-485 Station 10522 10522 14.7 7.7 112.7
125 I-485 Station 10522 10522 7.9 7.7 60.3
126 I-485 Station 10522 10522 16.0 7.7 122.4
127 I-485 Station 10522 10522 11.7 7.7 89.6
128 I-485 Station 10522 10522 29.7 7.5 221.1
93
129 I-485 Station 10522 10522 16.0 7.2 114.4
130 I-485 Station 10522 10522 29.7 6.9 205.7
131 I-485 Station 10522 10522 7.9 6.9 54.6
132 I-485 Station 10522 10522 7.9 6.9 54.6
133 I-485 Station 10522 10522 29.7 6.7 198.5
134 I-485 Station 10522 10522 16.0 6.7 107.0
135 I-485 Station 10522 10522 16.0 6.6 106.2
136 I-485 Station 10522 10522 14.7 6.6 97.7
137 I-485 Station 10522 10522 16.0 6.6 106.2
138 I-485 Station 10522 10522 7.9 6.6 52.3
139 I-485 Station 10522 10522 7.9 6.6 52.3
140 I-485 Station 10522 10522 7.9 6.6 52.3
141 I-485 Station 10522 10522 16.0 6.4 103.0
142 I-485 Station 10522 10522 14.7 6.3 93.1
143 I-485 Station 10522 10522 29.7 6.2 185.3
144 I-485 Station 10522 10522 7.9 6.2 49.2
145 I-485 Station 10522 10522 16.0 6.2 99.9
146 I-485 Station 10522 10522 7.9 6.2 49.2
147 I-485 Station 10522 10522 16.0 6.2 99.5
148 I-485 Station 10522 10522 29.7 6.1 180.9
149 I-485 Station 10522 10522 29.7 6.1 180.9
150 I-485 Station 10522 10522 14.7 6.1 89.8
151 I-485 Station 10522 10522 14.7 6.1 89.8
152 I-485 Station 10522 10522 14.7 6.1 89.8
153 I-485 Station 10522 10522 7.9 6.1 48.0
154 I-485 Station 10522 10522 7.9 6.1 48.0
155 I-485 Station 10522 10522 7.9 6.1 48.0
156 I-485 Station 10522 10522 16.0 6.1 97.5
157 I-485 Station 10522 10522 16.0 5.9 95.1
158 I-485 Station 10522 10522 16.0 5.9 95.1
159 I-485 Station 10522 10522 16.0 5.9 95.1
160 I-485 Station 10522 10522 16.0 5.9 95.1
161 I-485 Station 10522 10522 7.9 5.7 44.9
162 I-485 Station 10522 10522 7.9 5.7 44.9
163 I-485 Station 10522 10522 7.9 5.7 44.9
164 I-485 Station 10522 10522 16.0 5.7 91.2
165 I-485 Station 10522 10522 16.0 5.6 88.9
166 I-485 Station 10522 10522 14.7 5.6 81.9
167 I-485 Station 10522 10522 16.0 5.6 88.9
168 I-485 Station 10522 10522 16.0 5.6 88.9
169 I-485 Station 10522 10522 11.7 5.6 65.1
170 I-485 Station 10522 10522 7.9 5.4 42.8
171 I-485 Station 10522 10522 14.7 4.9 72.3
172 I-485 Station 10522 10522 7.9 4.9 38.7
173 I-485 Station 10522 10522 11.7 4.9 57.5
174 I-485 Station 10522 10522 14.7 4.6 68.3
175 I-485 Station 10522 10522 29.7 4.1 121.4
176 I-485 Station 10522 10522 14.7 4.1 60.2
94
177 I-485 Station 10522 10522 14.7 4.1 60.2
178 I-485 Station 10522 10522 7.9 4.1 32.2
179 I-485 Station 10522 10522 16.0 4.1 65.5
180 I-485 Station 10522 10522 16.0 3.9 62.5
181 I-485 Station 10522 10522 16.0 3.7 59.4
182 I-485 Station 10522 10522 7.9 3.7 29.2
183 I-485 Station 10522 10522 7.9 3.7 29.0
184 I-485 Station 10522 10522 7.9 3.6 28.4
185 I-485 Station 10522 10522 16.0 3.3 53.3
186 I-485 Station 10522 10522 14.7 3.2 46.8
187 I-485 Station 10522 10522 16.0 3.2 50.9
188 I-485 Station 10522 10522 7.9 2.6 20.8
189 I-485 Station 10522 10522 7.9 2.6 20.8
190 I-485 Station 10522 10522 16.0 2.4 38.5
191 I-485 Station 10522 10522 16.0 0.7 11.7
192 I-485 Station 10522 10522 16.0 0.7 11.7
193 I-485 Station 10522 10522 14.7 0.7 10.7
194 I-485 Station 10522 10522 16.0 0.7 11.7
195 I-485 Station 10522 10522 16.0 0.7 11.7
196 I-485 Station 10522 10522 16.0 0.7 11.7
197 I-485 Station 10522 10522 16.0 0.7 11.7
198 I-485 Station 10522 10522 4.7 0.7 3.4
199 I-485 Station 10522 10522 16.0 0.6 9.3
200 Non-Park and Ride Stations 10020 10020 12.7 30.5 388.7
201 Non-Park and Ride Stations 10149 10149 19.8 7.1 141.4
202 Non-Park and Ride Stations 11025 11025 12.7 6.5 83.2
203 Non-Park and Ride Stations 10149 10149 19.8 5.7 112.2
204 Non-Park and Ride Stations 11026 11026 19.8 5.4 105.9
205 Non-Park and Ride Stations 11025 11025 25.5 3.8 97.5
206 Non-Park and Ride Stations 10149 10149 1.4 3.4 4.7
207 Non-Park and Ride Stations 11026 11026 12.7 2.4 30.2
208 Non-Park and Ride Stations 11025 11025 19.8 1.2 22.9
209 Non-Park and Ride Stations 11026 11026 19.8 1.0 20.5
210 Scaleybark Station 11027 11027 8.5 34.1 288.3
211 Scaleybark Station 11027 11027 20.9 30.1 630.5
212 Scaleybark Station 11027 11027 8.5 23.4 197.9
213 Scaleybark Station 11027 11027 20.9 20.0 419.0
214 Scaleybark Station 11027 11027 8.5 11.7 99.0
215 Scaleybark Station 11027 11027 20.9 11.6 242.3
216 Scaleybark Station 11027 11027 8.5 9.4 79.7
217 Scaleybark Station 11027 11027 15.8 7.3 115.0
218 Scaleybark Station 11027 11027 15.8 7.0 111.1
219 Scaleybark Station 11027 11027 8.5 5.8 49.2
220 Scaleybark Station 11027 11027 20.9 4.7 98.8
221 Scaleybark Station 11027 11027 15.8 3.5 55.8
222 Scaleybark Station 11027 11027 8.5 3.4 28.7
223 Scaleybark Station 11027 11027 20.9 3.4 70.6
224 Scaleybark Station 11027 11027 8.5 3.2 26.7
95
225 Scaleybark Station 11027 11027 8.5 2.6 21.7
226 Scaleybark Station 11027 11027 8.5 2.6 21.7
227 Scaleybark Station 11027 11027 20.9 2.5 52.9
228 Scaleybark Station 11027 11027 15.8 2.3 35.6
229 Scaleybark Station 11027 11027 20.9 2.2 46.0
230 Scaleybark Station 11027 11027 15.8 1.4 22.6
231 Scaleybark Station 11027 11027 8.5 1.4 12.1
232 Scaleybark Station 11027 11027 8.5 1.4 12.1
233 Scaleybark Station 11027 11027 20.9 1.4 29.9
234 Scaleybark Station 11027 11027 12.6 1.4 18.0
235 Scaleybark Station 11027 11027 8.5 1.3 11.1
236 Scaleybark Station 11027 11027 20.9 1.0 20.8
237 Scaleybark Station 11027 11027 8.5 1.0 8.4
238 Scaleybark Station 11027 11027 20.9 0.5 9.5
239 Sharon Road West Station 10523 10523 21.1 24.8 521.6
240 Sharon Road West Station 10523 10523 0.7 19.6 13.1
241 Sharon Road West Station 10523 10523 39.4 9.4 370.4
242 Sharon Road West Station 10523 10523 1.6 8.8 14.4
243 Sharon Road West Station 10523 10523 18.3 8.8 161.0
244 Sharon Road West Station 10523 10523 18.3 8.8 161.0
245 Sharon Road West Station 10523 10523 39.4 8.3 326.3
246 Sharon Road West Station 10523 10523 21.1 7.6 159.9
247 Sharon Road West Station 10523 10523 2.1 7.4 15.3
248 Sharon Road West Station 10523 10523 0.8 6.6 5.2
249 Sharon Road West Station 10523 10523 18.3 5.7 104.6
250 Sharon Road West Station 10523 10523 18.3 5.6 101.9
251 Sharon Road West Station 10523 10523 18.3 5.2 95.6
252 Sharon Road West Station 10523 10523 18.3 4.9 89.3
253 Sharon Road West Station 10523 10523 0.7 3.5 2.3
254 Sharon Road West Station 10523 10523 0.6 3.5 2.1
255 Sharon Road West Station 10523 10523 21.1 3.5 73.8
256 Sharon Road West Station 10523 10523 18.3 3.5 64.2
257 Sharon Road West Station 10523 10523 18.3 3.5 64.2
258 Sharon Road West Station 10523 10523 39.4 2.9 115.1
259 Sharon Road West Station 10523 10523 21.1 2.9 61.6
260 Sharon Road West Station 10523 10523 18.3 2.9 53.6
261 Sharon Road West Station 10523 10523 18.3 2.7 49.5
262 Sharon Road West Station 10523 10523 21.1 2.7 56.9
263 Sharon Road West Station 10523 10523 18.3 1.7 30.3
264 Sharon Road West Station 10523 10523 19.1 1.3 24.3
265 Sharon Road West Station 10523 10523 18.3 1.3 23.2
266 Sharon Road West Station 10523 10523 18.3 1.1 19.4
267 Sharon Road West Station 10523 10523 18.3 1.1 19.4
268 Sharon Road West Station 10523 10523 39.4 1.1 41.7
269 Tyvola Station 11028 11028 1.5 25.7 37.6
270 Tyvola Station 11028 11028 10.7 9.4 100.6
271 Tyvola Station 11028 11028 16.7 9.4 156.7
272 Tyvola Station 11028 11028 10.7 9.4 100.3
96
273 Tyvola Station 11028 11028 16.7 6.5 109.0
274 Tyvola Station 11028 11028 16.7 6.1 101.7
275 Tyvola Station 11028 11028 16.7 5.1 84.7
276 Tyvola Station 11028 11028 16.7 4.1 67.7
277 Tyvola Station 11028 11028 0.8 2.5 2.0
278 Tyvola Station 11028 11028 16.7 2.3 39.1
279 Tyvola Station 11028 11028 40.4 1.8 74.2
280 Tyvola Station 11028 11028 16.7 1.8 30.7
281 Tyvola Station 11028 11028 10.7 1.8 19.7
282 Tyvola Station 11028 11028 8.3 1.6 13.7
283 Tyvola Station 11028 11028 10.7 1.4 14.7
284 Tyvola Station 11028 11028 10.7 1.4 14.7
285 Tyvola Station 11028 11028 16.7 1.4 22.9
286 Tyvola Station 11028 11028 20.0 1.3 26.0
287 Tyvola Station 11028 11028 15.9 1.1 17.9
288 Tyvola Station 11028 11028 10.7 1.1 11.5
289 Tyvola Station 11028 11028 15.9 0.8 12.6
290 Tyvola Station 11028 11028 16.7 0.8 13.2
291 Woodlawn Station 11068 11068 41.1 27.8 1144.9
292 Woodlawn Station 11068 11068 68.2 3.7 249.2
293 Woodlawn Station 11068 11068 1.6 3.5 5.5
294 Woodlawn Station 11068 11068 18.1 2.6 46.8
295 Woodlawn Station 11068 11068 20.6 2.2 45.8
296 Woodlawn Station 11068 11068 33.8 2.2 75.3
297 Woodlawn Station 11068 11068 41.1 1.9 78.7
298 Woodlawn Station 11068 11068 33.8 1.6 55.5
299 Woodlawn Station 11068 11068 33.8 1.6 54.3
300 Woodlawn Station 11068 11068 7.6 1.6 12.1
301 Woodlawn Station 11068 11068 41.1 1.2 51.0
302 Woodlawn Station 11068 11068 41.1 1.2 47.5
303 Woodlawn Station 11068 11068 18.1 0.9 17.0
304 Woodlawn Station 11068 11068 33.8 0.5 15.5
SUM 2172.3 30973.4
97
Table 21: The following table indicates the number of survey users (indicated by #) for each
station, the origin and destination TAZ (PTAZ and ATAZ respectively) for each user, the
estimated number of additional people using the light rail and travelling on a similar path (the
Combined ExpFactor Linked field), and VMT per user (determined by the average trip length
from the PTAZ to ATAZ using the OD pair matrix provided by CDOT), and the VMT for all
estimated park-and-ride users (determined by multiplying the VMT survey result by the the
Combined ExpFactor Linked field) for the home – final destination scenario:
# FINAL_ON_Station PTAZ ATAZ Combined ExpFactor Linked
VMT Survey VMT All
1 Archdale Station 10517 10011 19.7 9.8 193.1
2 Archdale Station 10506 10002 22.0 8.8 193.9
3 Archdale Station 11029 10009 10.5 7.7 81.4
4 Archdale Station 10502 10014 19.7 6.6 131.0
5 Archdale Station 10166 10482 11.0 3.7 40.7
6 Arrowood Station 10951 10272 3.9 22.7 87.5
7 Arrowood Station 3200 10010 16.1 21.0 336.8
8 Arrowood Station 11015 10013 0.6 17.0 10.3
9 Arrowood Station 10589 10010 16.1 17.0 273.1
10 Arrowood Station 10960 10009 13.1 16.8 220.0
11 Arrowood Station 10943 10010 36.5 15.0 546.9
12 Arrowood Station 10536 10001 14.6 14.5 212.3
13 Arrowood Station 10504 10737 2.3 14.2 32.9
14 Arrowood Station 10504 10737 8.2 14.2 116.9
15 Arrowood Station 10585 10001 16.1 14.1 227.1
16 Arrowood Station 10910 10020 9.7 14.1 136.7
17 Arrowood Station 10915 10009 9.7 13.6 131.9
18 Arrowood Station 10533 10020 9.7 13.4 129.8
19 Arrowood Station 10515 10010 16.1 12.9 207.4
20 Arrowood Station 10515 10010 16.1 12.9 207.4
21 Arrowood Station 10470 10010 9.7 12.1 116.9
22 Arrowood Station 10470 10012 18.1 11.9 216.6
23 Arrowood Station 10857 10011 8.0 11.8 94.8
24 Arrowood Station 10589 10012 16.1 11.6 186.2
25 Arrowood Station 10534 10009 16.1 11.5 185.2
26 Arrowood Station 10515 10009 16.1 11.2 179.9
27 Arrowood Station 10519 10010 16.1 11.2 179.2
28 Arrowood Station 10517 10016 36.5 10.9 398.3
29 Arrowood Station 10548 10014 18.1 9.7 174.9
30 Arrowood Station 11030 10020 8.0 9.1 72.7
98
31 Arrowood Station 10582 10009 16.1 9.0 144.0
32 Arrowood Station 10559 10014 18.1 7.9 143.0
33 Arrowood Station 10559 10009 16.1 7.3 117.8
34 Arrowood Station 10550 10149 18.1 7.0 127.7
35 Arrowood Station 10010 10011 9.7 0.4 4.0
36 I-485 Station 10929 10773 16.0 35.8 572.3
37 I-485 Station 3196 10773 16.0 33.7 538.7
38 I-485 Station 3295 10009 16.0 30.9 494.6
39 I-485 Station 9194 10010 16.0 29.1 464.6
40 I-485 Station 7006 10010 16.0 28.2 451.2
41 I-485 Station 3062 10011 16.0 27.4 438.7
42 I-485 Station 9283 10009 16.0 26.6 425.0
43 I-485 Station 3178 10011 7.9 26.4 207.6
44 I-485 Station 9202 10011 7.9 26.0 204.6
45 I-485 Station 3087 10009 16.0 25.4 406.3
46 I-485 Station 9204 10009 11.7 24.4 285.4
47 I-485 Station 9211 10010 14.7 24.1 355.0
48 I-485 Station 3038 10009 7.9 23.4 184.4
49 I-485 Station 10890 10010 16.0 23.2 370.2
50 I-485 Station 3190 10009 16.0 23.1 368.8
51 I-485 Station 9211 10011 7.9 22.7 178.6
52 I-485 Station 9282 10009 16.0 22.7 362.4
53 I-485 Station 10904 10009 7.9 22.5 177.4
54 I-485 Station 10893 10010 16.0 22.4 357.8
55 I-485 Station 9210 10009 7.9 22.3 175.8
56 I-485 Station 9210 10009 16.0 22.3 356.9
57 I-485 Station 9281 10010 7.9 22.3 175.7
58 I-485 Station 3199 10010 7.9 21.9 172.4
59 I-485 Station 10902 10010 7.9 21.8 172.1
60 I-485 Station 10927 10014 14.7 21.4 315.4
61 I-485 Station 10903 10010 16.0 21.3 340.3
62 I-485 Station 10963 10010 16.0 21.1 338.1
63 I-485 Station 10893 10011 14.7 20.9 308.1
64 I-485 Station 10927 10009 16.0 20.9 333.8
65 I-485 Station 9281 10011 7.9 20.9 164.4
66 I-485 Station 3204 10010 16.0 20.8 333.0
67 I-485 Station 3203 10012 14.7 20.8 305.7
68 I-485 Station 10902 10012 16.0 20.7 331.2
69 I-485 Station 10922 10010 14.7 20.6 303.5
70 I-485 Station 10294 10010 16.0 20.5 327.4
71 I-485 Station 10929 10010 16.0 20.3 324.2
72 I-485 Station 10929 10010 16.0 20.3 324.2
73 I-485 Station 10931 10010 14.7 20.3 298.3
74 I-485 Station 10931 10010 14.7 20.3 298.3
75 I-485 Station 10902 10002 1.9 20.2 38.7
76 I-485 Station 10905 10010 16.0 20.2 322.3
77 I-485 Station 10905 10010 16.0 20.2 322.3
78 I-485 Station 10906 10010 29.7 20.1 597.5
99
79 I-485 Station 10906 10010 16.0 20.1 322.1
80 I-485 Station 10906 10010 16.0 20.1 322.1
81 I-485 Station 10902 10009 7.9 20.1 158.6
82 I-485 Station 10932 10010 14.7 20.1 295.2
83 I-485 Station 3197 10010 14.7 20.0 293.9
84 I-485 Station 3197 10010 16.0 20.0 319.4
85 I-485 Station 10931 10016 29.7 19.9 591.3
86 I-485 Station 10930 10009 7.9 19.5 153.3
87 I-485 Station 10930 10009 7.9 19.5 153.3
88 I-485 Station 10933 10010 29.7 19.3 573.4
89 I-485 Station 10933 10010 7.9 19.3 152.3
90 I-485 Station 10931 10012 29.7 19.1 567.8
91 I-485 Station 10931 10012 14.7 19.1 281.7
92 I-485 Station 10921 10010 29.7 19.1 566.2
93 I-485 Station 10921 10010 16.0 19.1 305.2
94 I-485 Station 10919 10010 16.0 19.0 304.4
95 I-485 Station 10919 10010 14.7 19.0 280.2
96 I-485 Station 10919 10010 7.9 19.0 150.0
97 I-485 Station 10905 10014 16.0 19.0 303.8
98 I-485 Station 10928 10009 16.0 18.8 301.3
99 I-485 Station 10929 10011 7.9 18.8 148.3
100 I-485 Station 10931 10011 7.9 18.8 148.3
101 I-485 Station 10933 10117 7.9 18.8 148.1
102 I-485 Station 10294 10009 16.0 18.8 300.1
103 I-485 Station 10905 10011 16.0 18.7 299.2
104 I-485 Station 10906 10011 7.9 18.7 147.3
105 I-485 Station 10922 10019 11.7 18.7 218.5
106 I-485 Station 10922 10019 11.7 18.7 218.5
107 I-485 Station 10923 10010 29.7 18.6 553.1
108 I-485 Station 10924 10010 16.0 18.6 298.1
109 I-485 Station 10918 10010 16.0 18.6 297.7
110 I-485 Station 10932 10011 7.9 18.6 146.6
111 I-485 Station 10931 10020 7.9 18.6 146.6
112 I-485 Station 10931 10009 7.9 18.6 146.2
113 I-485 Station 3197 10011 16.0 18.5 296.3
114 I-485 Station 10906 10009 7.9 18.4 145.2
115 I-485 Station 10294 11025 16.0 18.4 293.7
116 I-485 Station 10932 10009 16.0 18.3 293.4
117 I-485 Station 10920 10010 16.0 18.3 293.3
118 I-485 Station 3197 10009 16.0 18.3 292.1
119 I-485 Station 10931 11025 16.0 18.2 290.4
120 I-485 Station 10932 10019 11.7 18.1 211.8
121 I-485 Station 10919 10014 7.9 17.9 140.9
122 I-485 Station 3196 10010 16.0 17.9 285.9
123 I-485 Station 10949 10010 16.0 17.7 282.4
124 I-485 Station 10926 10010 14.7 17.6 259.7
125 I-485 Station 10919 10011 16.0 17.6 281.4
126 I-485 Station 10919 10009 7.9 17.3 136.5
100
127 I-485 Station 10923 10011 7.9 17.2 135.5
128 I-485 Station 10911 10010 14.7 17.0 250.7
129 I-485 Station 10894 10149 29.7 17.0 504.1
130 I-485 Station 10924 10020 7.9 17.0 133.7
131 I-485 Station 10920 10011 16.0 16.9 270.3
132 I-485 Station 10917 10011 7.9 16.7 131.2
133 I-485 Station 10917 10011 7.9 16.7 131.2
134 I-485 Station 10917 10011 16.0 16.7 266.4
135 I-485 Station 10920 10009 16.0 16.6 266.0
136 I-485 Station 10913 10010 29.7 16.5 489.2
137 I-485 Station 10913 10010 14.7 16.5 242.7
138 I-485 Station 10532 10011 7.9 16.4 129.1
139 I-485 Station 10917 10009 7.9 16.4 129.1
140 I-485 Station 10920 11025 16.0 16.2 259.5
141 I-485 Station 10961 10009 7.9 16.2 127.6
142 I-485 Station 10531 10010 16.0 16.1 257.6
143 I-485 Station 3207 10011 7.9 16.0 126.3
144 I-485 Station 10926 10020 11.7 16.0 187.0
145 I-485 Station 10926 10009 7.9 15.9 125.5
146 I-485 Station 3207 10020 7.9 15.8 124.5
147 I-485 Station 3212 10010 16.0 15.6 249.2
148 I-485 Station 10951 10009 7.9 15.4 121.1
149 I-485 Station 10951 10009 16.0 15.4 245.9
150 I-485 Station 10913 10014 14.7 15.3 225.7
151 I-485 Station 10913 10011 16.0 15.1 240.7
152 I-485 Station 10943 10010 14.7 15.0 220.3
153 I-485 Station 10943 10010 14.7 15.0 220.3
154 I-485 Station 10912 10011 16.0 14.9 237.7
155 I-485 Station 10913 10009 7.9 14.8 116.4
156 I-485 Station 10938 10009 7.9 14.7 115.9
157 I-485 Station 10531 10011 7.9 14.7 115.6
158 I-485 Station 10909 10012 14.7 14.5 212.7
159 I-485 Station 10874 10011 7.9 14.4 113.6
160 I-485 Station 3209 10020 16.0 14.3 229.3
161 I-485 Station 10001 10536 7.9 14.3 112.7
162 I-485 Station 3209 10009 16.0 14.3 228.5
163 I-485 Station 10535 10024 16.0 14.2 226.9
164 I-485 Station 3212 10011 14.7 14.1 208.2
165 I-485 Station 3212 10011 16.0 14.1 226.2
166 I-485 Station 10909 10011 16.0 14.1 226.1
167 I-485 Station 10937 10009 16.0 14.1 225.6
168 I-485 Station 10588 10009 7.9 14.1 110.7
169 I-485 Station 3212 10009 16.0 13.9 221.9
170 I-485 Station 10537 10010 16.0 13.9 221.6
171 I-485 Station 10537 10010 16.0 13.9 221.6
172 I-485 Station 10537 10010 14.7 13.9 204.0
173 I-485 Station 10537 10010 16.0 13.9 221.6
174 I-485 Station 10537 10010 16.0 13.9 221.6
101
175 I-485 Station 10584 10011 7.9 13.8 108.5
176 I-485 Station 10943 10011 7.9 13.5 106.5
177 I-485 Station 10533 10020 7.9 13.4 105.4
178 I-485 Station 10533 10020 7.9 13.4 105.4
179 I-485 Station 10586 10010 16.0 13.3 212.5
180 I-485 Station 10943 10009 7.9 13.3 104.4
181 I-485 Station 3210 10012 16.0 13.2 211.0
182 I-485 Station 3212 10149 11.7 12.7 149.0
183 I-485 Station 10537 10012 16.0 12.7 203.5
184 I-485 Station 10011 10945 14.7 12.4 182.6
185 I-485 Station 10157 3211 16.2 12.4 201.4
186 I-485 Station 10419 10020 16.0 12.3 196.9
187 I-485 Station 11032 10011 16.0 12.3 196.3
188 I-485 Station 10537 10009 16.0 12.2 194.3
189 I-485 Station 10013 10279 0.7 11.8 7.8
190 I-485 Station 10897 10009 16.0 11.4 182.6
191 I-485 Station 10589 10009 16.0 11.0 176.2
192 I-485 Station 10469 10011 7.9 10.2 80.5
193 I-485 Station 10472 10020 16.0 9.7 155.1
194 I-485 Station 10529 10009 7.9 9.0 70.6
195 I-485 Station 10131 10002 14.7 6.6 96.7
196 I-485 Station 10537 10558 4.7 6.2 29.2
197 I-485 Station 10435 10014 14.7 5.9 87.0
198 I-485 Station 10043 10014 29.7 2.8 83.2
199 I-485 Station 10149 10009 16.0 1.9 30.9
200 I-485 Station 10010 10009 7.9 0.3 2.7
201 Non-Park and Ride Stations 5066 10012 12.7 29.1 370.2
202 Non-Park and Ride Stations 10576 10012 19.8 8.5 168.3
203 Non-Park and Ride Stations 10514 10009 19.8 8.5 167.3
204 Non-Park and Ride Stations 10510 10020 12.7 6.8 86.6
205 Non-Park and Ride Stations 10435 10011 19.8 6.1 121.1
206 Non-Park and Ride Stations 10195 10550 1.4 5.8 7.9
207 Non-Park and Ride Stations 10183 10014 12.7 4.1 52.4
208 Non-Park and Ride Stations 10156 10016 19.8 4.0 79.7
209 Non-Park and Ride Stations 10128 10011 25.5 3.5 89.6
210 Non-Park and Ride Stations 10143 10011 19.8 1.3 26.0
211 Scaleybark Station 277 10009 8.5 31.3 264.4
212 Scaleybark Station 3152 10020 8.5 26.8 226.9
213 Scaleybark Station 2176 10012 20.9 20.2 422.3
214 Scaleybark Station 10168 10773 12.6 18.7 235.2
215 Scaleybark Station 10169 11040 8.5 14.6 123.7
216 Scaleybark Station 10529 10010 15.8 13.8 218.3
217 Scaleybark Station 10838 10011 20.9 13.6 285.2
218 Scaleybark Station 10656 10012 20.9 11.7 245.6
219 Scaleybark Station 10247 10011 8.5 9.0 76.1
220 Scaleybark Station 10429 10010 15.8 8.8 138.4
221 Scaleybark Station 10498 10010 20.9 6.6 138.7
222 Scaleybark Station 10195 10010 15.8 6.6 103.7
102
223 Scaleybark Station 10694 10011 8.5 6.5 55.0
224 Scaleybark Station 10492 10001 15.8 5.3 83.2
225 Scaleybark Station 10011 10195 8.5 5.1 42.8
226 Scaleybark Station 10162 10011 8.5 4.3 36.3
227 Scaleybark Station 10167 10009 8.5 4.3 36.2
228 Scaleybark Station 10169 10010 20.9 4.3 89.2
229 Scaleybark Station 10135 10009 8.5 4.2 35.9
230 Scaleybark Station 10167 10011 8.5 4.2 35.5
231 Scaleybark Station 10170 10010 20.9 3.7 77.9
232 Scaleybark Station 10153 10011 20.9 3.7 76.6
233 Scaleybark Station 10160 10117 20.9 3.7 76.4
234 Scaleybark Station 10168 10009 15.8 3.6 57.7
235 Scaleybark Station 10168 10009 20.9 3.6 76.3
236 Scaleybark Station 10168 10011 8.5 3.6 30.1
237 Scaleybark Station 11027 10010 20.9 3.4 72.0
238 Scaleybark Station 11027 10012 20.9 3.4 71.8
239 Scaleybark Station 10168 10019 8.5 3.4 28.6
240 Scaleybark Station 10186 10009 8.5 2.4 20.2
241 Scaleybark Station 10143 10012 20.9 1.6 34.1
242 Sharon Road West Station 10529 10279 0.7 22.3 14.9
243 Sharon Road West Station 10529 10279 0.6 22.3 13.3
244 Sharon Road West Station 9062 10020 21.1 21.3 449.5
245 Sharon Road West Station 10919 10010 39.4 19.0 749.6
246 Sharon Road West Station 10951 10010 39.4 17.1 672.8
247 Sharon Road West Station 10920 10011 21.1 16.9 356.1
248 Sharon Road West Station 10146 10919 1.6 16.6 27.1
249 Sharon Road West Station 10917 10009 2.1 16.4 34.1
250 Sharon Road West Station 10947 10001 18.3 16.3 299.5
251 Sharon Road West Station 10531 10010 18.3 16.1 295.4
252 Sharon Road West Station 10947 10009 18.3 14.8 270.5
253 Sharon Road West Station 10536 10010 18.3 14.6 268.3
254 Sharon Road West Station 10536 10014 21.1 13.5 284.1
255 Sharon Road West Station 10911 10195 0.8 12.4 9.8
256 Sharon Road West Station 10534 10014 39.4 12.1 475.7
257 Sharon Road West Station 10279 10011 0.7 12.0 8.0
258 Sharon Road West Station 10534 10009 21.1 11.5 242.9
259 Sharon Road West Station 10534 10009 18.3 11.5 211.4
260 Sharon Road West Station 10517 10010 18.3 11.2 206.0
261 Sharon Road West Station 10517 10010 18.3 11.2 206.0
262 Sharon Road West Station 10518 10011 18.3 10.4 191.1
263 Sharon Road West Station 10517 10013 39.4 10.3 406.6
264 Sharon Road West Station 10474 10009 18.3 9.9 182.0
265 Sharon Road West Station 10530 10010 18.3 9.8 179.8
266 Sharon Road West Station 11031 10002 19.1 9.8 187.4
267 Sharon Road West Station 11031 10002 18.3 9.8 179.5
268 Sharon Road West Station 10529 10009 21.1 9.0 189.0
269 Sharon Road West Station 10529 10009 18.3 9.0 164.4
270 Sharon Road West Station 10529 10011 18.3 8.9 162.9
103
271 Sharon Road West Station 10478 10009 18.3 8.4 154.4
272 Tyvola Station 2030 10557 1.5 26.2 38.3
273 Tyvola Station 10551 10279 0.8 17.8 14.4
274 Tyvola Station 10531 11025 10.7 14.0 150.1
275 Tyvola Station 10586 10010 16.7 13.3 221.8
276 Tyvola Station 10589 10014 16.7 11.6 193.2
277 Tyvola Station 10589 10009 10.7 11.0 118.1
278 Tyvola Station 10475 10010 16.7 10.6 176.8
279 Tyvola Station 11029 10010 20.0 9.4 188.8
280 Tyvola Station 10506 10009 16.7 8.8 146.2
281 Tyvola Station 10514 10010 16.7 8.7 144.8
282 Tyvola Station 10562 10010 16.7 8.6 142.8
283 Tyvola Station 10558 10002 8.3 8.2 68.7
284 Tyvola Station 10562 10016 40.4 8.2 331.7
285 Tyvola Station 10507 10011 16.7 8.1 134.5
286 Tyvola Station 10516 10010 16.7 7.9 131.8
287 Tyvola Station 10507 10009 10.7 7.8 83.5
288 Tyvola Station 10507 10009 10.7 7.8 83.5
289 Tyvola Station 10494 10020 15.9 7.6 120.8
290 Tyvola Station 11028 10012 40.4 7.4 299.4
291 Tyvola Station 10562 10009 10.7 6.8 73.4
292 Tyvola Station 10509 11025 15.9 6.8 108.3
293 Tyvola Station 10509 11025 16.7 6.8 113.5
294 Tyvola Station 10557 10020 10.7 6.8 72.4
295 Woodlawn Station 10484 10279 1.6 19.2 29.9
296 Woodlawn Station 10807 10012 41.1 12.3 505.5
297 Woodlawn Station 10493 10010 18.1 8.0 145.7
298 Woodlawn Station 10496 10002 20.6 7.7 157.9
299 Woodlawn Station 11068 10010 41.1 7.5 306.8
300 Woodlawn Station 10171 10010 33.8 7.2 243.6
301 Woodlawn Station 10562 10009 18.1 6.8 124.0
302 Woodlawn Station 10564 10014 33.8 6.4 216.9
303 Woodlawn Station 10564 10014 7.6 6.4 48.4
304 Woodlawn Station 10573 10009 41.1 6.2 253.7
305 Woodlawn Station 10481 10010 68.2 5.8 398.0
306 Woodlawn Station 10494 10013 33.8 5.5 185.6
307 Woodlawn Station 10495 10009 41.1 4.9 201.0
308 Woodlawn Station 10496 10009 33.8 4.7 160.4
309 Woodlawn Station 10166 10010 41.1 4.7 192.2
SUM 4401.4 64008.7