Transportation demand management (TDM) strategies focus on changing travel behavior - trip rates, trip length, travel mode, time-of-day, etc. - generally in order to reduce traffic during congested (peak) periods. TDM projects/programs generally reduce emissions of all pollutants by reducing vehicle trips and/or vehicle miles traveled (VMT) by personal motor vehicles, or by shifting trips from peak periods to less congested periods.
TDM strategies generally focus on reducing travel in light-duty vehicles (automobiles and light-duty trucks), which are large contributors to CO, VOC, and NOx emissions; consequently, these strategies may be most effective at targeting one or more of these pollutants.
Methodologies for analyzing the impacts of TDM strategies generally involve the following steps:
These strategies, and associated methodologies, are presented below. Some of the strategies covered in this section are addressed by EPA's "Best Workplaces for Commuters" program, and estimates of emissions impacts for these strategies can be derived from the COMMUTER Model, http://www.epa.gov/OMS/stateresources/policy/pag_transp.htm#cp and the accompanying guidance document, http://www.epa.gov/otaq/stateresources/policy/transp/commuter/420b14004.pdf.
Note: For most of the TDM strategies, the methodologies used in the sample calculations do not incorporate secondary or indirect emissions impacts from speed and volume changes or from increases in transit service that may be needed in response to a demand management program. These effects are not significant in most cases, but should be considered on a case-by-case basis.
Park-and-ride facilities include the construction or expansion of parking lots where people can park their vehicles and then join a carpool, vanpool or transit service. Typically, park-and-ride facilities are used in suburban areas. This strategy reduces emissions by decreasing the number of single-occupancy vehicles on the road.
By encouraging drivers to reduce VMT by sharing car trips or taking transit, park-and-ride lots reduce emissions of all pollutants associated with driving, as shown in the table below. However, the emissions benefits will not be proportional for all pollutants, since the use of a park-and-ride facility requires individuals to drive to the facility. As a result, this strategy does not reduce the number of vehicle cold starts that are taken, during which time the highest emissions output of CO, NOX, and VOCs are produced (in fact, it is possible that park-and-ride lots could lead to increased vehicle trip starts if people who used to pick each other up at individual homes now each drive to the park-and-ride lot).
Since park-and-ride facilities reduce VMT but not cold starts, they generally are less effective at reducing CO, NOX, and VOCs than other demand management strategies that reduce vehicle trip-making entirely. They can be effective, however, in reducing localized CO; for instance, by reducing vehicle trips into a central business district.
Table 3-1. Park-and-Ride Strategy-Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
 |
|
|
|
|
|
|
Factors affecting the level of emissions impacts include:
Park-and-ride facility impacts are typically analyzed using sketch planning methods. The calculation of emissions impacts should ideally account for any changes in trip lengths associated with driving to the park-and-ride lot (e.g., for instance, if someone drives one mile out of the way to access the park-and-ride) and any potential increase in trip starts associated with people who previously were picked up at home but now drive to the park-and-ride. However, these factors are generally very small and are not usually considered in simple sketch planning methods.
For EPA guidance on this strategy, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf. For more information on this strategy, see the EPA TCM Information Document, "Park-and-Ride/Fringe Parking." http://www.epa.gov/otaq/stateresources/policy/transp/tcms/park-fringepark.pdf.This example assumes an addition of parking spaces to an existing park-and-ride facility that is not served by transit, and is based on parameters for an expansion to a park-and-ride lot along Maryland 22 at Bynum Run Park in suburban Baltimore, Maryland. Emissions impacts are calculated using a simple sketch planning technique. The inputs assumed for the sample include:11
Step 1: Estimate expected lot use.
= (Spaces added to lot) x (estimated utilization rate)
= (60 spaces) x (0.70)
= 42 spaces
Step 2: Calculate expected number of people reducing driving.
= (Spaces used) x (share who previously drove alone)
= (42 spaces) x (0.80)
= 33.6 fewer drivers per day
Step 3: Calculate annual VMT reduction.
= (Number of fewer drivers per day) x (estimated round trip) x (operating days)
= (33.6 fewer drivers) x (50 mi) x (250 days)
= 525,000 annual VMT reduction
Step 2: Calculate reduction in emissions.
= (Running emission factor) x (reduction in VMT)
Table 3-2 shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-2. Total Emissions Reduced (ton/year) from Park-and-Ride Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.01 | 0.01 | 4.09 | 0.41 | 0.34 | <0 .01 | 0.06 |
| 2010 | 0.01 | 0.01 | 3.15 | 0.29 | 0.24 | < 0.01 | 0.06 |
| 2020 | 0.01 | 0.01 | 2.17 | 0.14 | 0.13 | < 0.01 | 0.06 |
This sample is comprised of a new park-and-ride lot with new transit services. This sample is based on a new lot added along the I-59 corridor in Birmingham, Alabama.12 Emissions impacts are calculated using a simple sketch planning technique. The inputs assumed for the sample include:
Step 1: Estimate expected lot use.
= (Historical utilization) x (spaces in lot)
= (0.85) x (100 spaces)
= 85 spaces
Step 2: Calculate the number of people reducing driving.
= (Expected lot use) x (percent of users who previously drove alone)
= (85 spaces) x (0.83)
= 71 auto trips reduced per day
Step 3: Calculate annual VMT reduction.
= (Trips reduced) x (average commute trip length) x (operating days)
= (71 trips) x (12 mi) x (250 days)
= 213,000 annual VMT reduction
Step 4: Calculate the auto emissions reductions from the project.
= (Annual VMT reductions) x (auto running emissions factor)
Step 5: Calculate the emissions from the new bus service.
= (number of bus trips) x (bus trip length) x (bus running emissions factor)
= (8 trips) x (10.5 miles) x (bus running emissions factor)
Step 6: Calculate total emissions reductions.
= (Auto vehicle emissions reduced) - (bus emissions)
Table 3-3 shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-3. Total Emissions Reduced (ton/year) from Park-and-Ride Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | < 0.01 | <0.01 | 1.64 | 0.12 | 0.14 | < 0.01 | 0.02 |
| 2010 | < 0.01 | 0.01 | 1.26 | 0.09 | 0.10 | < 0.01 | 0.02 |
| 2020 | < 0.01 | 0.01 | 0.87 | 0.05 | 0.05 | < 0.01 | 0.02 |
High Occupancy Vehicle (HOV) lanes are intended to maximize the person-carrying capacity of a roadway by altering the design and/or operation of the facility to provide priority treatment for HOVs, such as carpools, buses, and vans. By providing two important incentives-reduced travel time and improved trip time reliability-HOV facilities encourage travelers to shift from single occupancy vehicles to HOV use. This shift should reduce vehicle trips, vehicle miles traveled (VMT), and associated emissions from these activities. In addition, HOV lanes are designed to operate at faster speeds, even during peak periods, and so the strategy also results in an increase in travel speeds for vehicles using the HOV lane.
HOV lanes affect air pollution emissions in several ways. First, restricting the additional lanes to certain vehicles encourages ridesharing among commuters, resulting in fewer vehicle trips and emissions of all pollutants. HOV lanes also increase travel speeds for HOV traffic that is able to utilize the lanes, and potentially along the entire roadway. Consequently, the speed changes may have different effects for different pollutants, and could even increase some emissions. Implementation of HOV lanes also could result in some additional emissions that may partially offset the benefits of vehicle trip reduction if some people who previously used transit now switch to carpools, thereby increasing the number of vehicles on the road. However, in general, HOV lanes would be expected to reduce all pollutants, as shown below in Table 3-4.
Table 3-4. High Occupancy Vehicles- Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
| |
|
|
|
|
|
|
Emissions impacts of HOV lanes are often estimated using sketch planning methods. More complex tools and models are also available, such as simulation tools and travel demand models, to examine impacts on speeds and traffic patterns in more detail.
For EPA guidance on this strategy, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf. For more information, see the EPA TCM Information Document, "High Occupancy Vehicle Lanes,"http://www.epa.gov/otaq/stateresources/policy/transp/tcms/high_occvehicles.pdf.
This sample is based on a project that extended HOV lanes by 2 miles on I-84 from East Hartford to downtown Hartford14.HOV lanes can be analyzed using various methods, including travel demand forecasting model approaches and vehicle queuing models. In this case, a sketch planning methodology is used to calculate the changes in emissions on the 2 mile segment of roadway, as well as additional emissions impacts associated with increased ridesharing for commuting (e.g., people who switch from driving alone to a carpool will affect their entire commute trip, not just the last two miles). The calculation relies on the following inputs (for simplicity, this example assumes no increase in bus use, only carpools, and that all carpoolers meet at a park-and-ride facility, so trip start emissions are not reduced, only running emissions):
Step 1: Estimate total traffic in corridor that are HOVs and SOVs during HOV enforcement hours, prior to implementation of lane expansion
= (Corridor traffic count per peak hour) x (hours with HOV restrictions) x (percent HOVs)
= (8,000 vehicles per hour) x (6 hours) x (0.15 HOVs) = 7,200 HOVs
(8,000 vehicles per hour) x (6 hours) x (0.85 SOVs) = 40,800 SOVs
Step 2: Estimate shift from SOVs to HOVs with lane expansion.
Reduction in SOV trips
= (SOV travelers) x (share that switch to HOVs)
= (40,800 SOVs) x (0.05)
= 2,040 reduced SOV trips
Increase in HOV trips
= SOV trip reduction / (average HOV occupancy)
= (2,040 reduced SOV trips) / 2.1
= 971 new HOV trips
Step 3: Estimate change in emissions on the expanded roadway segment by comparing no-build to build scenarios.
No build on segment
= (Total vehicle trips) x (trip length) x (auto running emissions factor at 9 mph) x (operating days)
= (48,000 vehicle trips) x (2 miles) x (auto running emissions factor at 9 mph) x (250 days)
Build on segment
= [(SOV trips) x (trip length) x (auto running emissions factor at 10 mph)] + [(HOV trips) x (trip length) x (auto running emissions factor at 35 mph)] x (operating days)
= [(40,800 - 2,040 SOV trips) x (2 miles) x (auto running emissions factor at 10 mph)] + [(7,200 + 971 HOV trips) x (2 miles) x (auto running emissions factor at
35 mph)] x (250 days)
Step 4: Calculate additional emissions reductions off the expanded segment.
Reduced SOV emissions
=(Reduced SOV trips) x (commute trip length - segment length) x (auto running emissions factor at 9 mph) x (operating days)
= (2,040 reduced SOV trips) x (12 miles - 2 miles) x (auto running emissions factor at 9 mph) x (250 days)
Added HOV emissions
(New HOV trips) x (commute trip length - segment length) x (auto running emissions factor at 35 mph) x operating days
(971 new HOV trips) x (12 miles - 2 miles) x (auto running emissions factor at 35 mph) x (250 days)
The following table shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-5. Total Emissions Reduced (ton/year) from High Occupancy Vehicles Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.26 | 0.56 | 216 | 22.9 | 34.4 | 0.18 | 2.20 |
| 2010 | 0.25 | 0.55 | 174 | 16.0 | 22.8 | 0.17 | 2.20 |
| 2020 | 0.25 | 0.54 | 130 | 7.41 | 13.6 | 0.17 | 2.21 |
Regional rideshare programs provide ride-matching services, employer outreach, and incentives to commute by carpool or vanpool (such as free gas cards, drawings, award programs, subsidies). Ridematching may be traditional (i.e., people establish regular carpool routines) or dynamic (real-time matching of individuals who want to travel to/from similar locations). The strategy encourages SOV commuters to share trips, thereby reducing vehicle trips and VMT.
Ridesharing programs reduce emissions by decreasing the amount of VMT. Consequently, the programs should generally reduce emissions for all pollutants, as shown below in Table 3-6.
Table 3-6. Ridesharing Programs/Incentives- Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
| |
|
|
|
|
|
|
Factors affecting the level of emissions impact include:
Ridesharing impacts are typically analyzed using sketch planning methods or use of EPA's COMMUTER Model. Care should be taken to avoid double-counting benefits of these programs with other related programs, since ridesharing is often incorporated into employer-based transportation demand management programs and is often bundled with additional TDM strategies.
For EPA guidance on this strategy, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf. In addition, for more information on this strategy, see the EPA TCM Information Document, "Area-Wide Rideshare Incentives," http://www.epa.gov/otaq/stateresources/policy/transp/tcms/areawide_incentive.pdf, and the COMMUTER Model documentation, http://www.epa.gov/oms/stateresources/policy/transp/commuter/420b05017.pdf.
This sample is based on a scenario where an area-wide ridesharing and incentive program was implemented by 45 percent of employers in the San Francisco-San Mateo-Redwood City Metropolitan Area.15 Ridesharing support programs include support for carpooling and vanpooling, and financial incentives include parking costs, transit fare/pass subsidies, or other financial incentives. A COMMUTER Model run was conducted using model default parameters and the specific inputs discussed below in the calculations.
Step 1: Estimate the number of commuters that will have access to new commuter options as a result of the ridesharing and incentives program.For this example, the Bureau of Labor Statistics was used to estimate the number of office and non-office employees in the San Francisco-San Mateo-Redwood City Metropolitan Area. In this metropolitan area, there are approximately 500,000 office employees and 425,000 non-office employees.16
Step 2: Determine the typical strategies offered and participation rates.
In the COMMUTER Model, employer-supported commute programs in a geographic area are represented by inputting the employer participation rates at various support levels. The respective rates assumed in the base case and strategy implementation case are listed below.
Base case:
| Program | No Participation | Level 1 | Level 2 | Level 3 |
|---|---|---|---|---|
Carpool |
90 percent | 10 percent | 0 | 0 |
Vanpool |
95 percent | 5 percent | 0 | 0 |
Transit |
90 percent | 10 percent | 0 | 0 |
Bicycle |
100 percent | 0 | 0 | 0 |
Action case:
| Program | No Participation | Level 1 | Level 2 | Level 3 |
|---|---|---|---|---|
Carpool |
90 percent | 0 | 10 percent | 0 |
Vanpool |
85 percent | 0 | 10 percent | 5 percent |
Transit |
82 percent | 5 percent | 10 percent | 3 percent |
Bicycle |
95 percent | 0 | 5 percent | 0 |
The COMMUTER Model defines a Level 1 program as the provision of information activities plus a quarter-time transportation coordinator. A Level 2 program is defined as Level 1 plus in-house matching services (carpool and vanpool), work hours flexibility (transit), or bicycle parking and shower facilitates (bicycle). A Level 3 program includes Level 2 plus a half-time transportation coordinator plus preferential parking and flexible work schedules (carpool), vanpool development and operating assistance and preferential parking (vanpool), or on-site transit pass sales (transit).
Step 3: Estimate total change in vehicle trips and VMT.
According to the COMMUTER Model, the employer provided support programs would lead to a reduction of 506 vehicle trips and 0.3 percent reduction in VMT, or 8,097 vehicle miles.
Step 4: Estimate emissions reductions (average commute speed of 35 mph).
= [(Vehicle trips reduced) x (per trip emissions factor)] + [(VMT reduced x (per mile running emissions factor)]
Table 3-7 shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-7. Total Emissions Reduced (ton/year) from Ridesharing Programs/Incentives Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.03 | 0.05 | 15.6 | 1.54 | 1.30 | 0.02 | 0.22 |
| 2010 | 0.02 | 0.05 | 12.0 | 1.09 | 0.91 | 0.02 | 0.22 |
| 2020 | 0.02 | 0.05 | 8.29 | 0.53 | 0.53 | 0.02 | 0.22 |
Particularly well suited for longer commutes, vanpools typically carry from seven to fifteen passengers, and operate weekdays, traveling between one or two common pick-up locations (typically a park-and-ride lot where a rider may leave their car, or a transit station) and the place of work. Vanpool programs typically provide vehicles owned by an organization to commuters who live in a common geographic area and who share an employment destination. The vans or buses may be operated by a driver or by the commuters themselves. Additionally, some programs provide outreach services to attract potential riders.
Vanpools reduce emissions by decreasing vehicle miles that occupants would otherwise travel by auto. Although an individual van may produce more emissions than an individual auto, vanpools typically replace 7 to 15 auto trips each, and therefore should result in reductions of all pollutants, as show in Table 3-8. Since personal vehicles make up a larger share of on-road CO, VOCs, and NH3 emissions than PM or NOX, this strategy will be more effective as strategy to reduce CO, VOCs, and NH3, rather than other pollutants.
Table 3-8. Vanpool Strategy - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
The level of emissions impact depends on:
Vanpool program impacts are typically analyzed using sketch planning methods. When analyzing vanpool programs, care should be taken to ensure that double-counting of emissions effects does not occur with ridesharing programs, employer-based TDM programs, and other related programs. These strategies may need to be assessed together as a new TDM strategy, instead of individual projects. For EPA guidance, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf.
This sample is based on a vanpool subsidy program in California.17 Emissions impacts are calculated based on the following assumptions:
Step 1: Estimate daily vanpool ridership.
= (Number of vanpools) x (average number of riders)
= 10 vanpools x 11 riders
= 110 daily vanpool ridership
Step 2: Calculate auto trip starts reduced per year.
= (Daily vanpool riders) x (percent of riders who previously drove alone) x (1 - percent of riders who drive to access point) x (2 trip per day) x (days of operation)
= (110 vanpool riders) x (.83) x (.25) x (2 trips) x (240 days)
= 11,413 annual auto trip starts reduced
Step 3: Calculate auto VMT reduced per year.
= (Daily vanpool riders) x (percent of riders who previously drove alone) x (2 trips per day) x (days of operation) x { (average one-way trip length)
- [(percent of riders driving to access point) x (auto trip length to access point)]}
= (110) x (0.83) x (2) x (240) (48 miles - [(0.75) x (5 miles)])
= 1,939,212 annual VMT reduced
Step 4: Calculate emissions reductions from autos.
= [(Auto trips reduced) x (auto trip start emissions factor)] + [(auto VMT reduced) x (auto running emissions factor)]
Step 5: Calculate emissions resulting from operation of the vanpool
= (Number of vans) x (average van trip length) x (2 trips per day) x (days of operation) x (van running emissions factor)
= (10) x (48 mi) x (2) x (240) x (van emissions factor, including start)
Step 6: Calculate net emissions reduction
= (Auto emissions reduction) - (van emissions)
Table 3-9 shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-9. Total Emissions Reduced (ton/year) from Vanpool Subsidy Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.02 | 0.05 | 14.6 | 1.30 | 1.22 | 0.02 | 0.21 |
| 2010 | 0.02 | 0.05 | 11.3 | 0.94 | 0.85 | 0.02 | 0.21 |
| 2020 | 0.02 | 0.05 | 7.70 | 0.49 | 0.45 | 0.02 | 0.21 |
This sample focuses on the establishment of new vanpools, which can occur due to financial incentives, provision of vans, or other services. This sample is based on a vanpool project in Dade County, Florida18 .The emissions calculation uses a sketch planning technique, relying on the following inputs:
Step 1: Estimate annual auto trips reduced.
= (Total number of vanpoolers) x (percent of riders who previously drove alone) x (2 trips per day) x (days of operation)
= (30 vans x 11.5 riders per van) x (0.80) x (2) x (240)
= 132,480 vehicle trips reduced
Step 2: Estimate annual auto VMT reduced.
= (Vehicle trips reduced) x (average distance to work)
= (132,480) x (30 mi)
= 4 million annual vehicle miles reduced
Step 3: Calculate emissions reductions from autos.
= [(Auto trips reduced) x (auto trip start emissions factor)] + [(auto VMT reduced) x (auto running emissions factor)]
Step 4: Calculate emissions resulting from operation of the vanpool.
= (Number of vans) x (average van trip length) x (2 trips per day) x (days of operation) x (van running emissions factor)
= (30) x (30 mi) x (2) x (240) x (van running emissions factor)
Step 5: Calculate net emissions reduction.
= (Auto emissions reduction) - (van emissions)
Table 3-10 shows the total annual amount of emissions reduced as a result of implementing this project.
Table 3-10. Total Emissions Reduced (tons/year) from Vanpool Program Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.02 | 0.07 | 31.9 | 1.47 | 2.04 | 0,03 | 0.42 |
| 2010 | 0.03 | 0.08 | 24.7 | 1.21 | 1.43 | 0.03 | 0.42 |
| 2020 | 0.04 | 0.09 | 16.6 | 0.83 | 0.77 | 0.03 | 0.42 |
Bicycle and pedestrian projects/programs include a wide range of investments and strategies to facilitate and encourage non-motorized travel. Examples of these strategies include: bicycle paths and lanes, sidewalks, bicycle racks or lockers, pedestrian urban design enhancements, bicycle share programs, and bicycle incentives. These projects can serve both commute and non-commute trips.
Bicycle and pedestrian projects/programs should reduce all pollutants by reducing VMT; however, impacts are likely to be small given limited shifts from driving and relatively short trip distances. Improved connections to transit services, however, can result in reductions in longer vehicle trips. General impacts of bicycle and pedestrian projects are shown below in the table below.
Table 3-11. Bicycle/Pedestrian Projects - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
The level of emissions impact depends on:
Bicycle and pedestrian project impacts are typically analyzed using sketch planning methods. For EPA guidance on this strategy, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf. For more information, see the EPA TCM Information Document, "Bicycle and Pedestrian Programs," http://www.epa.gov/otaq/stateresources/policy/transp/tcms/bicycle_ped.pdf.
This example includes development of a single 1.13 mile bike lane, and is based on a project in the San Francisco Bay Area, California, which included installation of new pavement, signage, and bike lane striping.19 The new bike lane provides residents bike access to education, employment, shopping, and transit. Within one-quarter mile of the project, there is a college, a shopping center, a light rail station, and an office building. The parameters of the project consist of:
Step 1: Estimate auto trips reduced.
Auto trips reduced can be estimated in various ways, including use of bicycle/pedestrian factors associated with different types of surrounding land uses, studies of similar bicycle projects, or modeling.
In this case, consistent with methods developed by the California Air Resources Board, auto trips reduced are calculated as a function of average daily traffic (ADT) on the roadway.
= (ADT) x (Adjustment on ADT for auto trips replaced by bike trips) x (operating days)
= (20,000) x (0.0109) x 200
= 43,600
Step 2: Estimate VMT reduced.
= (Auto trips reduced) x (length of bike trips)
= (43,600) x (1.8)
= 78,480
Step 3: Calculate annual emissions reduction.
= [(Annual auto trip starts reduced) x (auto trips end factor)] + [(annual auto VMT reduced) x (auto VMT factor)]
Table 3-12 shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-12. Total Emissions Reduced (tons/year) from Bike Lane Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | <0.01 | <0.01 | 0.75 | 0.70 | 0.07 | <0.01 | <0.01 |
| 2010 | <0.01 | <0.01 | 0.59 | 0.05 | 0.05 | <0.01 | <0.01 |
| 2020 | <0.01 | <0.01 | 0.41 | 0.03 | 0.03 | <0.01 | <0.01 |
This is an example of a pedestrian connection to transit that results in VMT reductions substantially longer that the actual pedestrian walkway. This project is based on the Cleveland Walkway to Gateway, which provides a link for transit riders arriving at Tower City Center, the main shopping and entertainment area of downtown Cleveland, to the Gateway Sports and Entertainment Complex. The climate-controlled walkway, which is about a quarter mile long, was designed in part to stimulate transit ridership in the metro area and relieve traffic congestion, especially during sporting events.20 Information on the project is as follows:
Step 1: Estimate the daily increase in transit trips.
= (Number of transit riders who used the walkway for 16 months) / (number of days studied) x (percent of walkway users who would not have taken transit in absence of walkway)
= (940,000) / (487 days) x (0.70)
= 1,351 daily new transit trips
Step 2: Estimate the reduction in vehicle trip starts.
= [1-Fraction of people who drive to public transit stations) / (avg. vehicle occupancy)] x (increase in transit riders)
= [(1-0.5)/1.5] x (1,351 trips)
= 446 vehicle trip starts reduction
Step 3: Estimate VMT reduction.
= (Increase in transit riders/average vehicle occupancy) x (average trip distance)
= (1,351)/(1.5) x (8)
= 7,205 reduction in VMT
Step 4: Estimate emissions reductions.
= (Auto trip start reduction) x (auto trip start emissions factor)] + [(VMT reduction) x (auto running emissions factor)]
The table below shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-13. Total Emissions Reduced (tons/year) from Walkway Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.05 | 0.10 | 26.1 | 2.79 | 2.46 | 0.03 | 0.39 |
| 2010 | 0.04 | 0.10 | 20.2 | 1.96 | 1.70 | 0.03 | 0.39 |
| 2020 | 0.04 | 0.10 | 14.0 | 0.96 | 0.91 | 0.03 | 0.39 |
New bus or rail services include any additions to the provision of services through the establishment of new routes, increased frequency, hours of operation or coverage of routes. Emissions reductions occur when the expanded service encourages people to replace driving trips with transit.
Improved transit service involves increasing the frequency or hours of service on existing transit routes. This strategy increases transit ridership and decreases auto trips in several ways. First, increased frequency of service generally results in increased ridership because transit becomes a more convenient transportation option. Waiting time for transit is reduced, leading to a faster trip (start to end). Second, increasing hours of service allows people to use the route at hours that were not previously available.
New transit routes and increased transit service frequency or hours of operation should reduce emissions of all pollutants by reducing VMT. However, emissions benefits will not be proportional for all pollutants, since the buses also emit pollution, and diesel buses produce higher levels of NOx and PM per mile compared to autos. Moreover, if the new services do not substantially increase transit ridership, there may be no net emissions reductions. General impacts of transit service enhancements are shown below in the table below.
Table 3-14. Transit Service Enhancements- Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
 |
|
|
|
|
|
|
These factors depend on supporting land use patterns, the availability of supporting facilities (e.g., transit station parking, bicycle racks), transit fares and parking prices, supporting services, and other factors. Transit service expansions are typically analyzed using sketch planning methods, based on transit ridership projections. EPA's COMMUTER Model can also be used to analyze the impacts of strategies, such as increased frequency of transit services. Some transit service expansions are combined with other complementary programs, such as transit marketing and incentives, or park-and-ride facilities, so the impacts of these programs should be considered together in order to avoid double-counting.
For EPA guidance on transit service expansion strategies, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf. For more information on this strategy, see the EPA TCM Information Document, "Improved Public Transit," http://www.epa.gov/otaq/stateresources/policy/transp/tcms/improved_transit.pdf.This strategy is comprised of a new commuter shuttle route running during peak period on weekdays.21 The program includes the following assumptions:
Step 1: Calculate increase in average ridership.
= (Estimated occupancy per bus) x (number of daily bus trips)
= (18 passengers) x (8 trips)
= 144 daily passenger-trips
Step 2: Calculate number of auto trip starts eliminated.
= (Average daily bus ridership) x (percent of riders who previously drove alone)
x (1- percent using auto to transit service)
= (144) x (0.75) x (1-.25)
= 81 daily auto trip starts eliminated
Step 3: Calculate auto VMT reduced.
= (Average daily ridership) x (1- portion of riders who did not previously drive) x {(average auto trip length)
- [(trip length for auto access to and from transit) x (portion using auto access to transit service)]}
= (144 passengers) x (0.75) x [(9.6 mi) - (0-0)]
= 1,037 daily VMT reduced
Step 4: Calculate transit bus emissions.
= (Daily bus trips) x (bus round trip miles) x (bus running emissions factor)
= (8) x (12 miles) x (bus emission factor)
Step 5: Calculate total annual emissions reduced.
= [[(Auto VMT reduced) x (auto running emissions factors)] + [(auto trip starts reduced)
x (auto trip start emissions factor)] - (bus emissions)] x (operating days)
The following table shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-15. Total Emissions Reduced (tons/year) from Transit Service Enhancement Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | <0.01 | <0.01 | 1.94 | Increase 0. 05 | 0.18 | <0.01 | 0.03 |
| 2010 | <0.01 | <0.01 | 1.60 | 0.13 | 0.12 | <0.01 | 0.03 |
| 2020 | <0.01 | <0.01 | 1.11 | 0.05 | 0.07 | <0.01 | 0.03 |
This strategy involves additional service on an existing bus route serving a bridge corridor in a major metropolitan area. The project includes the following assumptions:
Step 1: Calculate increase in average ridership.
= (Estimated occupancy per bus) x (number of daily trips per bus) x (number of buses)
= (25 passengers) x (6 trips) x (6 buses)
= 900 daily passenger-trips
Step 2: Calculate number of auto trip starts eliminated.
= (Average daily bus ridership) x (percent of riders who previously drove alone)
x (1- percent using auto to transit service)
= (900) x (0.50) x (1-0)
= 450 daily auto trip starts eliminated
Step 3: Calculate auto VMT reduced.
= (Average daily ridership) x (1- portion of riders who did not previously drive) x {(average auto trip length)
- [(trip length for auto access to and from transit) x ;(portion using auto access to transit service)]}
= (900 passengers) x (0.50) x [(8) - (0-0)]
= 3600 daily VMT reduced
Step 4: Calculate transit bus emissions.
= (Daily bus trips) x (bus round trip miles) x (bus running emissions factor)
= (8) x (16 miles) x (bus emission factor)
Step 5: Calculate total annual emissions reduced.
= [[(Auto VMT reduced) x (auto running emissions factors)] + [(auto trip starts reduced)
x (auto trip start emissions factor)] - (bus emissions)] x (operating days)
The following table shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-16. Total Emissions Reduced (tons/year) from Transit Service Enhancement Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | <0.01 | <0.01 | 1.94 | Increase 0.05 | 0.18 | <0.01 | 0.03 |
| 2010 | <0.01 | <0.01 | 1.60 | 0.13 | 0.12 | <0.01 | 0.03 |
| 2020 | <0.01 | <0.01 | 1.11 | 0.05 | 0.07 | <0.01 | 0.03 |
Increased marketing, provision of more widely accessible transit information, and additional customer service may increase the number of people using public transportation each day. As for passenger amenities, the provision of such things as transit shelters, benches, maps, and visually pleasing aesthetics, or improving the comfort of buses and trains may be a supporting strategy to increase ridership. In addition, service enhancements such as improved transfer facilities and timing of transit services to reduce wait times during transfer may also increase ridership.
Transit information/marketing/amenities will reduce all pollutants by encouraging shifts from driving to using transit, and thereby reducing VMT; these strategies do not involve provision of new bus service, and so there are no new bus emissions. General impacts are shown below in the table below:
Table 3-17. Transit Marketing - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
The level of emissions impact depends on:
Emissions impacts of transit marketing, information, and amenities are typically analyzed using sketch planning methods. EPA's COMMUTER Model can be used to analyze some types of service improvements, such as increased information about schedules and real-time traveler information, which can be analyzed as a reduction in waiting times. Note that transit service enhancements and marketing are often implemented in combination with service expansions or other complementary programs; if this is the case, the impacts of these programs should be considered together in order to avoid double-counting of emissions benefits and account for the increase emissions from any service expansion.
This project assumes major improvements in transit system amenities, including additions of bus shelters, real-time bus information, and enhanced signage. It is based loosely on a sample transit route service improvement on Central Coast Area Transit (CCAT) Route 9 in California.22 The project assumes the following inputs:
Step 1: Estimate increased transit ridership.
= [(Annual rides) / (service weekdays)] / 2
= (51,680/255)/2
= 101 new riders per day
Step 2: Calculate daily vehicle trips reduced.
= (New daily riders) x (percent prior drive alone) x (roundtrip)
= (101) x (0.47) x (2)
= 95 vehicle trips reduced from SOV switch
= [(New daily riders) x (percent prior carpool/vanpool) / (avg. occupancy of carpool/vanpool)] x (roundtrip)
= [(101) x (0.27) / (2.5)] x (2)
= 18.6 vehicle trips reduced from HOV switch
Total daily vehicle trips reduced = 95 + 18.6 = 114
Step 3:Calculate vehicle miles of travel reduced.
= (Daily vehicle trips reduced) x (Avg. trip distance)
= (114) x (20.2)
= 2,303 miles per day
Step 4:Estimate emissions reductions.
= [(Auto trip end emissions factor) x (trips reduced)] + [(auto running emissions factor) x (miles reduced)] x (operating days)
Table 3-18 shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-18. Total Emissions Reduced (tons/year) from Transit Service Enhancement Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.01 | 0.01 | 4.75 | 0.42 | 0.47 | <0.01 | 0.07 |
| 2010 | 0.01 | 0.02 | 3.70 | 0.30 | 0.32 | <0.01 | 0.07 |
| 2020 | 0.01 | 0.02 | 2.60 | 0.16 | 0.17 | <0.01 | 0.07 |
Transit pricing strategies are designed to reduce the costs associated with using transit, thereby creating incentives for people to shift from other traveling modes. Fare reductions can be implemented system-wide, in specific fare-free or reduced fare zones, or offered through employer-based benefits programs which are fully or partially paid by the employer.
By encouraging drivers to switch to transit, transit price reductions should reduce emissions of all pollutants, as shown in Table 3-19.
Table 3-19. Transit Pricing Strategy-Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
Since rider response to fare changes is relatively inelastic and transit makes up only a small share of total trips in most urban areas, transit pricing projects by themselves will generally have limited impacts on VMT and emissions on a regional basis. However, when fare changes are implemented in conjunction with other supporting strategies, and particularly when focused on congested areas with good transit service such as downtowns, universities, and major urban employment concentrations, the effect on traffic and emissions can be more notable.
The level of emissions impact depends on:
Transit pricing projects are often analyzed using sketch planning methods, such as by applying a transit fare pricing elasticity, which estimate the percent increase in transit ridership associated with a given percent reduction in transit fares. EPA's COMMUTER Model can also be used to analyze the effects of transit price changes on commuter routes, or employer-subsidized transit programs. For EPA guidance on transit pricing, see "Opportunities to Improve Air Quality through Transportation Pricing Programs," http://www.epa.gov/otaq/market/pricing.pdf,
"Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf and the EPA and DOT"s document, "Technical Methods for Analyzing Pricing Measures to Reduce Transportation Emissions," http://www.epa.gov/otaq/stateresources/policy/transp/tcms/anpricng.pdf.
This example is based on results from several fare-free transit programs, including a system-wide demonstration in Austin, Texas and a fare-free demonstration during off-peak periods in Denver.23 The inputs for the calculation of emissions benefits on the project are as follows:
Step 1: Estimate the increase in transit ridership from the program.
= (Existing transit ridership) x (percent increase in ridership)
= (10,000) x (0.75)
= 7,500 new transit riders
Step 2: Calculate the daily reduction in vehicle trip starts.
= (Increase in daily transit ridership) x (portion who previously drove) x (1- portion using auto to access transit service)
= (7,500) x (0.46) x (1-0)
= 3,450 auto trips reduced per day
Step 3: Calculate auto VMT reduced.
= (Increase in daily transit ridership) x (portion who previously drove) x (average trip length)
= (7,500) x (0.46) x (6 mi)
= 20,700 vehicle miles reduced per day
Step 4: Calculate annual emissions reduced.
= [(Auto trip starts reduced) x (auto trip start emissions factor)] + [(auto VMT reduced) x (auto running emissions factor)] x (days per year)
The table below shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-20. Total Emissions Reduced (tons/year) from Fare Free Transit Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.07 | 0.15 | 41.9 | 4.29 | 3.91 | 0.05 | 0.57 |
| 2010 | 0.07 | 0.14 | 33.0 | 2.36 | 2.74 | 0.04 | 0.58 |
| 2020 | 0.06 | 0.14 | 23.1 | 1.48 | 1.48 | 0.04 | 0.58 |
This example is based on a universal transit pass program called Eco Pass offered by the Santa Clara Valley Transit Authority, which offers significant fare discounts for participating employers.24 The emissions benefits of the project are calculate based on the following inputs:
Step 1: Estimate the increase in transit riders from the program.
= (New pass program participants) x (share new to transit)
= (26,400) x (0.61)
= 16,104 new transit riders
Step 2: Calculate the daily reduction in vehicle trip starts.
= (Increase in daily transit ridership) x (portion who previously drove) x (1- portion using auto to access transit service) x (2 trips per day)
= (16,104) x (0.96) x (1-0.25) x (2)
= 23,190 daily auto trip starts reduced
Step 3: Calculate daily auto VMT reduced.
= (Increase in daily transit ridership) x (portion who previously drove) x (average trip length) x (2 trips per day)
= (16,104) x (0.96) x (6 mi) x (2)
= 185,518 daily vehicle miles reduced per day
Step 4: Calculate annual emissions reduced.
= [(Auto trip starts reduced) x (auto trip start emissions factor)] + [(auto VMT reduced) x (auto running emissions factor)]
The table below shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-21. Total Emissions Reduced (tons/year) from Transit Pass Program Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.61 | 1.30 | 378 | 40.2 | 38.1 | 0.43 | 5.13 |
| 2010 | 0.59 | 1.27 | 163 | 28.5 | 26.5 | 0.39 | 5.15 |
| 2020 | 0.58 | 1.27 | 119 | 14.0 | 14.4 | 0.39 | 5.16 |
These strategies change the cost and/or convenience associated with driving a private vehicle, through pricing and management of parking on either end of the trip. While some policies increase the cost of parking through taxes or implementation of parking fees, some strategies reduce the supply of spaces through the creation of parking maximums for new development, regional parking caps, peak-hour parking bans, or curb-parking restrictions. Parking supply limits not only can increase the direct price of parking, but can also reduce the likelihood of finding parking at destinations, and may require walking one or more blocks for parking. Some parking management programs are designed to create an incentive for ridesharing, such as preferential spaces for carpools/vanpools or reduced parking prices for carpools/vanpools. All of these strategies reduce emissions by reducing the number of vehicle trips taken.
Parking pricing and management strategies should reduce emissions of all pollutants by reducing vehicle trips and VMT. General impacts of parking pricing/management enhancements are shown below.
Table 3-22. Parking Pricing/Management - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
The level of emissions impact depends on:
Parking pricing and supply limit strategies may be analyzed using sketch planning methods, or EPA's COMMUTER Model if the parking strategy focuses on work trips (including increased parking charges and preferential parking for carpools/vanpools). For EPA guidance on this strategy, see "Methodologies for Estimating Emissions and Travel Activity Effects of TCMs," http://www.epa.gov/ttn/naaqs/standards/ozone/data/1996_o3sp_final.pdf. For more information, also see TCM Information Document, "Parking Management," http://www.epa.gov/otaq/stateresources/policy/transp/tcms/parkingmgmt.pdf, and "Opportunities to Improve Air Quality through Transportation Pricing Programs," http://www.epa.gov/otaq/market/pricing.pdf.
This example reflects a downtown parking policy that limits the supply of parking. It is based on a program that had been operating in Portland, Oregon that set maximum ratios for the number of parking spaces per square foot of office space, based on the type of development and proximity to transit (ratios ranged from 0.7 to 1.0 space per 1000 square feet, compared to typical ratios of 4 spaces per 1000 square feet)25. Several different approaches can be used to analyze a program such as this, including examination of changes in parking prices, parking per employee, or parking per square foot.; A simple sketch planning method is used for this calculation, based on the following factors:
Step 1: Calculate reduction in parking supply due to the program.
= [(parking spaces per employee without policy) - (parking spaces per employee with policy)] x (number of employees)
= (0.44-0.38) x (92,000 employees)
= 5,520 fewer parking spaces
Step 2: Calculate reduction in daily vehicle trips.
= (fewer parking spaces) x (2 vehicle trips per day)
= (5,520) x (2)
= 11,040 vehicle trips reduced
Step 3: Calculate reduction in daily VMT.
= (vehicle trip reduction) x (average commute trip length)
= (11,040) x (5 miles)
= 55,200 vehicle miles reduced
Step 4: Calculate annual emissions reduction.
= [(vehicle trips reduced) x (trip start emission factor) + (VMT reduced) x (running emissions factor)] x commute days per year
= [(11,040) x (trip start emission factor) + 55,200 x (running emissions factor)] x 250
The table below shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-23. Total Emissions Reduced (tons/year) from Parking Pricing/Management Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.18 | 0.39 | 117 | 12.2 | 11.7 | 0.13 | 1.53 |
| 2010 | 0.18 | 0.38 | 91.8 | 8.61 | 8.09 | 0.12 | 1.53 |
| 2020 | 0.17 | 0.38 | 64.8 | 4.29 | 4.24 | 0.12 | 1.53 |
In this example, an employer offers a parking cash out incentive (i.e., provides employees that do not park at work a financial incentive) to encourage ridesharing, transit, and walking and bicycling, instead of driving alone to work26. The EPA's COMMUTER Model can be used to analyze the impacts of the program as a reduction in the price of alternatives to parking.; A simple sketch planning approach is shown below, based on inputs from the North Central Texas Council of Governments as follows:
Step 1: Calculate decrease in daily VMT.
= (Daily vehicle trips) x (average trip length)
= (100) x (14.11)
= 1411 daily VMT reduction
Step 2: Calculate annual running emissions reduction.
= (Daily VMT reduction) x (days of operation) x (running emissions factor)
= (1411) x (260) x (running emissions factor)
Step 3: Calculate annual trip starts reduction.
= (Daily vehicle trip reduction) x (days of operation) x (auto trip starts emission factor)
= (100) x (260) x (auto trip starts emission factor)
Step 4: Calculate annual total emissions reduction.
= (Auto running emissions reduction) + (auto trip starts emissions reduction)
The table below shows the annual emissions impacts resulting from implementation of the example strategy.
Table 3-24. Total Emissions Reduced (tons/year) from Parking Pricing/Management Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | <0.01 | 0.01 | 2.95 | 0.29 | 0.25 | <0.01 | 0.04 |
| 2010 | <0.01 | 0.01 | 2.27 | 0.21 | 0.17 | <0.01 | 0.04 |
| 2020 | <0.01 | 0.01 | 1.57 | 0.10 | 0.09 | <0.01 | 0.04 |
Road pricing strategies reduce emissions by changing the costs to consumers operating private vehicles. Examples include new or increased tolls on roads, high occupancy toll (HOT) lanes, or cordon pricing. As a price-based disincentive to vehicular travel, these policies would cause travelers to shift to other modes or share rides, with resulting emissions reductions. These strategies may also encourage shifts in travel by time of day if developed as a congestion pricing mechanism. Strategies may also impact travel speeds along congested corridors, with associated emissions impacts.
To the extent that pricing encourages reduced vehicle travel by shifting trips to alternate modes, emissions reductions will result across all pollutants. However, if speeds along roadways are also impacted as a result or if a congestion pricing strategy is implemented, effects will not be proportionate for all pollutants. Congestion pricing is designed to increase tolls during peak hours and thereby shift traffic to off-peak periods. In general, congestion pricing will reduce all pollutants, since vehicles traveling under congested travel conditions generally emit more pollution than under non-congested conditions; still, depending on speed changes, there is the possibility of an increase. General impacts of road pricing are shown below.
Table 3-25. Road Pricing - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
* Generally reduces emissions, but has the potential to increase emissions (in the case of congestion pricing where a new priced lane is added, and the pricing may shift drivers to alternate routes or shift travel to off-peak hours, in which case the increased speeds might be associated with increases in some emissions)
The level of emissions impact depends on:
Travel demand forecasting models can capture some of the impacts of road pricing strategies on mode shifts and diversion of traffic, and can be used as a basis for analyzing emissions impacts. A much simpler sketch planning analysis is shown in the sample calculation below. For EPA information on road pricing, see "Opportunities to Improve Air Quality through Transportation Pricing Programs," http://www.epa.gov/otaq/market/pricing.pdf.
In this example, a $0.75 toll charge is implemented on regional freeways27. Calculations regarding emissions impact of the project include the following assumptions:
Step 1: Calculate expected percentage vehicle mile reduction.
= (Percent increase in cost per vehicle mile) x (price elasticity of travel28)
= {[($0.75)/(8.4 mi)] / ($0.115)]} x (-.25)
= .194
Step 2: Calculate expected reduction in daily VMT.
= (Percent reduction) x (daily VMT)
= (.194) x (29,988,000)
= 5,817,672
Step 3: Calculate trip starts emission reductions.
= (Percent reduction) x [(daily VMT) / (average trip length)] x (365 days/year) x (trip starts emissions factor)
= (.194) x (3,570,000) x (trip starts emissions factor)
Step 4: Calculate annual running emissions reductions.
(Daily VMT reduction) x (365 days/year) x (auto running emissions factor)
= (5,817,672) x (365) x (auto running emissions factor)
Step 5: Calculate total annual emissions reductions.
(Auto trip starts emissions reduction) + (auto running emissions reduction)
The table below shows the annual emissions impacts resulting from implementation of the example strategy.
Table 3-26. Total Emissions Reduced (tons/year) from Road Pricing Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 27.8 | 59.7 | 21,297 | 1,773 | 1,096 | 19.7 | 235 |
| 2010 | 27.8 | 58.7 | 16,332 | 1,254 | 783 | 19.7 | 236 |
| 2020 | 26.4 | 58.0 | 11,226 | 614 | 415 | 19.7 | 236 |
This measure would impose fees based on miles driven. The fees could be collected annually through the vehicle registration process, with mileage calculated through odometer readings. Alternatively, under a Pay-As-You-Drive (variable price) auto insurance program, insurance premiums would be charged with a per-mile component, and could be levied on a monthly or semi-annual basis. VMT based pricing is intended as a price-based disincentive to vehicular travel, causing travelers to shift to other modes, share rides, avoid trips, or shorten trip lengths with resulting reductions in mobile source emissions.
To the extent that VMT pricing encourages reduced vehicle travel, emissions reductions will result across all pollutants. Unlike road pricing strategies, however, the impact on vehicle travel speed will be less, since the pricing is not focused on specific road facilities.
General impacts of VMT-based pricing are shown below.
Table 3-27. VMT-based Pricing - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
The level of emissions impact depends on:
The following is a hypothetical example of a Pay as You Drive insurance program in the Dallas-Fort Worth area. In this scenario, the following assumptions have been made:30
Step 1: Calculate daily reduction in vehicle miles traveled.
= (Daily vehicle miles) x (percent participation) x (percent reduction)
= (173,003,248) x (.10) x (.097)
= 1,678,131 daily vehicle miles reduced
Step 2: Calculate annual emissions reduction.
= (Daily VMT reduction) x (auto running emissions factor) x (operating days)
The following table shows the annual emissions impacts resulting from implementation of the example strategy.
Table 3-28. Total Emissions Reduced (tons/year) from VMT-based Pricing Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 8.04 | 17.2 | 4,694 | 493 | 439 | 5.70 | 67.8 |
| 2010 | 7.81 | 17.0 | 3.635 | 347 | 304 | 5.20 | 68.1 |
| 2020 | 7.61 | 16.7 | 2,530 | 170 | 163 | 5.19 | 68.1 |
This emissions reduction strategy would increase the tax rates applied to retail sales of motor fuels. Emissions reductions are achieved as drivers shift travel to other modes, share rides, reduce trips, or take shorter trips as a result of the higher costs of vehicle travel. As fuel pricing also creates an incentive for purchasing more fuel efficient vehicles, overall vehicle stock changes may further affect emissions over the long-term.
To the extent that fuel pricing reduce VMT, fuel pricing strategies will reduce all pollutants; however, unless fuel price increases are large, impacts on VMT may be minor. General impacts of fuel pricing are shown below.
Table 3-29. Fuel Pricing-Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
The level of emissions impact depends on:
It should be noted that gas taxes are often viewed as politically unacceptable, particularly large tax increases that would be necessary to affect travel demand significantly. The emissions impacts of fuel pricing can be analyzed using sketch-planning methods, relying on travel price elasticities. For more information, see EPA's document, "Opportunities to Improve Air Quality through Transportation Pricing Programs," http://www.epa.gov/otaq/market/pricing.pdf.
This regional fuel tax increase strategy includes the following assumptions:31
Step 1: Calculate expected percent reduction in VMT
= (Percent increase in cost per vehicle mile) x (price elasticity of travel)
= [($.25/17.8)] / ($0.115) x (-.2)
= - 0.024
Step 2: Calculate expected reduction in daily VMT
= (Percent reduction) x (daily VMT)
= (.024) x (75,000,000 miles)
= 1,800,000 miles
Step 3: Calculate annual trip starts emission reductions
= (Percent reduction) x [(daily VMT) / (average vehicle trip)] x (trip starts emissions factors)
= (.024) x [(75,000,000) / (8.4)] x (365 days/year) x (auto trip starts emissions factors)
= 78,214,285 x (auto trip starts emissions factors)
Step 4: Calculate annual running emissions reductions
= (Daily VMT reduction) x (365 days/year) x (auto running emissions factor)
= (1,800,000) x (365) x (auto running emissions factor)
= (657,000,000) x (auto running emissions factor)
Step 5: Calculate total annual emissions reductions
= (Auto trip starts emissions reduction) + (auto running emissions reduction)
The following table shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-30. Total Emissions Reduced (tons/year) from Fuel Pricing Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 8.63 | 18.5 | 5,308 | 541 | 492 | 6.11 | 72.7 |
| 2010 | 8.38 | 18.2 | 4,113 | 383 | 341 | 5.57 | 73.0 |
| 2020 | 8.16 | 18.0 | 2,873 | 188 | 184 | 5.57 | 73.1 |
Employer-based TDM programs are designed to encourage employers to offer a range of worksite programs to reduce the number of vehicles using the road system during peak travel hours while providing a wide variety of mobility options. These programs include development of transportation management associations/organizations (TMAs/TMOs), development of employer outreach programs, and regional incentives and marketing programs. Employer-based TDM programs typically focus on encouraging commuters to reduce their level of driving through worksite programs to support carpool/vanpools (e.g., on-site rideshare matching, preferential parking for carpools), programs to support transit use (e.g., transit benefits programs, transit information), compressed/ staggered work weeks, flexible work hours, and telecommuting, among others.
Emissions reductions resulting from implementation of these strategies will vary depending on project specifics. Those focused on reducing VMT will reduce all pollutants, while others will cause shifts in travel time (e.g., flextime) which will also affect emissions since vehicles are traveling at higher speed during less congested travel conditions. General impacts of employer-based TDM programs are shown below:
Table 3-31. Employer-Based TDM Programs - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
* = Generally will reduce emissions; however, in some cases (i.e., flex-time) may result in some increase in emissions, depending on speeds during peak and off-peak travel hours
The level of emissions impact depends on:
The emissions impacts of employer-based TDM programs can be analyzed using EPA's COMMUTER Model. For post-project analyses, sketch planning methods are often used. Note that some types of programs may have indirect effects that should be considered. For instance, telework and compressed work schedules reduce work vehicle trips, but individuals may add other trips on those days.Flexible work-hour schedules can also sometimes make carpooling more difficult.
For EPA guidance, see Guidance for Quantifying and Using Emission Reductions from Best Workplaces for Commuter Programs in State Implementation Plans and Transportation Conformity Determinations (EPA-420-B-05-016), October, 2005, http://www.epa.gov/otaq/stateresources/policy/transp/commuter/420b14004.pdf. For more information, see: TCM Information Documents, "Employer-Based Transportation Management Programs," http://www.epa.gov/otaq/stateresources/policy/transp/tcms/ emplyer_transmgt_prog.pdf http://www.epa.gov/otaq/stateresources/policy/transp/tcms/emplyer_transmgt_prog.pdf and COMMUTER Model guidance available at http://www.epa.gov/OMS/stateresources/policy/transp/commuter/420b05017.pdf.
This example of a regional employer outreach program is based on an evaluation of the CommuteSmart Program in Birmingham, Alabama, which focuses on encouraging a switch from drive alone commute trips to ridesharing, transit, walking, biking, teleworking, or flexible work hours schedules to move peak trips to off-peak periods. Each of these strategies yields different emission reduction (for example, teleworking eliminates vehicle trips while ridesharing involves combining trips and flexible work hours programs do not reduce vehicle trips)33. The COMMUTER Model was used to analyze potential impacts, relying on model default parameters and the specific inputs provided below in this sample calculation.
Step 1: Estimate the number of commuters that will have access to new commuter options as a result of the CommuteSmart program.
In the Birmingham area, there are approximately 200,000 office employees and 100,000 non-office employees.
Step 2: Determine the typical strategies offered and participation rates.
In the COMMUTER Model, employer-supported commute programs in a geographic area are represented by inputting the employer participation rates at various support levels. Programs specifically included in the model run to determine impacts on commute behavior included Employer Support Programs for carpooling,vanpooling, transit, and/or bicycling, and Alternative Wok Schedules, which accounts for emissions impacts resulting from employee flex time, telecommuting,staggered hours and/or compressed work weeks.
The respective increase in rates of area-wide employer participation in new TDM support programs are as follows:
| Program | No Participation |
Level 1 |
Level 2 |
|---|---|---|---|
Carpool |
-25 percent |
+15 percent |
+10 percent |
Vanpool |
-60 percent |
+20 percent |
+40 percent |
Transit |
-45 percent |
-5 percent |
+50 percent |
Bicycle |
0 percent |
0 percent |
0 percent |
The COMMUTER Model defines a Level 1 program as the provision of information activities plus a quarter-time transportation coordinator.& A Level 2 program is defined as Level 1 plus in-house matching services (carpool and vanpool), work hours flexibility (transit), or bicycle parking and shower facilitates (bicycle).
Step 3: Estimate the typical effects of the employer-based programs on commute behavior.
To quantify the effects of employer-based programs on commute behavior, the COMMUTER Model was run using the default inputs available from the model, or inputs based on assumptions as shown above in Step 2.
Step 4: Estimate total change in vehicle trips and VMT.
According to the COMMUTER Model, the employer-provided support programs would lead to a reduction of 8,944 vehicle trips and 2 percent reduction in VMT, or 124,249 vehicle miles. There is a 2.5 percent mode shift from peak to off-peak periods.
Step 4: Estimate annual emissions reductions (average commute speed of 35 mph).
= [(Vehicle trips reduced) x (per trip emission factor)] + [(VMT reduced) x (per mile running emission factor)]
The table below shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-32. Total Emissions Reduced (tons/year) from Employer-Based TDM Program Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.39 | 0.84 | 240 | 23.7 | 20.0 | 0.28 | 3.30 |
| 2010 | 0.38 | 0.82 | 185 | 16.7 | 14.0 | 0.25 | 3.31 |
| 2020 | 0.37 | 0.81 | 128 | 7.48 | 7.48 | 0.25 | 3.32 |
The intent of the Pinellas County, Florida TDM Public Education Campaign was to provide transportation information via several programs within a public education campaign to promote a shift from the use of single occupant vehicles (SOV) to alternatives such as bicycle, public transportation, and ridesharing. By educating the public about these transportation options and their cost-effectiveness, a substantial number of vehicles could be eliminated from the roadway, thereby reducing VMT.34. The inputs for emissions calculations regarding the program include:
Step 1: Estimate daily work trips.
= (Total employment) x (trip rate)
= 377,312 x 1.8
= 679,162 daily work trips
Step 2: Calculate reduction in work VMT.
= (Daily work trips) x (average trip length) x (trip reduction percent)
= (679,162) x (8.68) x (0.005)
= 29,476 reduction of work VMT
Step 3: Calculate annual emissions reductions.
To be conservative, this equation assumes no reduction in vehicle trip starts, only vehicle trip lengths. (VMT reduction) x (auto running emission factor) x (operating days)VMT reduction) x (auto running emission factor) x (250 days)
The following table shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-33. Emissions Reductions (tons/year) from TDM Outreach Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 6.00 | 8.79 | 519 | 253 | 49.2 | 1.59 | 15.1 |
| 2010 | 4.24 | 6.85 | 393 | 174 | 35.1 | 1.50 | 15.2 |
| 2020 | 2.45 | 4.91 | 275 | 66.4 | 19.0 | 1.53 | 15.2 |
Programs to reduce non-commute trips are being implemented to address the growth in non-work trips. Examples of non-commute travel that is being addressed with demand management measures include special event travel (to sporting events and entertainment venues), tourism travel, and school-based travel. Non-employer based TDM programs reduce emissions similar to employer-based TDM programs by encouraging alternative mode use, including carpooling, walking, or bicycling and providing incentives to use transit options. In addition, TDM programs can also be developed to target the general population, such as air quality awareness campaigns, and corridor-based programs. Beyond vehicle travel reduction, additional emissions benefits may be achieved if reduced congestion levels (e.g., outside schools and stadiums or along corridors undergoing construction) result in fewer idling vehicles.
Emissions reductions resulting from implementation of a non-employer based TDM strategy will vary depending on project specifics. In general, programs that target reducing VMT will reduce all pollutants. Other programs that shift travel times may have different effects on different pollutants due to changes in travel speeds. General impacts of non-employer-based TDM programs are shown below in the following table.
Table 3-34. Non-Employer-Based TDM Programs - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
* = Generally will reduce emissions; however, in some cases may result in some increase in emissions if results in increased speeds
The level of emissions impact depends on:
These TDM program efforts are typically analyzed using sketch planning methods. For more information on one application of this strategy, see the EPA TCM Information Document, "Special Events," www.epa.gov/otaq/stateresources/policy/transp/tcms/events.pdf.
The University Rideshare program in Atlanta includes a lump sum eligible to all colleges and universities within the 10 county region of the Atlanta Regional Commission. The intent is to provide startup funds for a student and staff-based rideshare program to encourage car and vanpooling. The program is designed to work closely with the Commission's Commute Connections Program.35 The sample includes the following assumptions:
Step 1: Estimate the number of auto trips eliminated per day.
= (Daily auto trips) x (mode-split diversion)Step 2: Estimate reduction in daily VMT.
Students = (Trips reduced per day) x (average trip length for students)
= (280) x (7)
= 1,960 daily student VMT reduced
Employees = (Trips reduced per day) x (average trip length for employees)
= (90) x (13)
= 1,170 daily employee VMT reduced
= 1,960 + 1,170 = 3,130 VMT reduced per day
Step 3: Calculate total annual emissions reduction.
= [(Auto trips eliminated) x (trip start emissions factor) + (VMT reduced) x (running emissions factor)] x (operating days)
= [(370 trip starts) x (trip start emissions factor) + (3,130 miles) x (running emissions factor)] x 160 days
The table below shows the annual emissions impacts resulting from the implementation of the example strategy.
Table 3-35. Total Emissions Reduced (tons/year) from University Rideshare Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.01 | 0.01 | 4.11 | 0.40 | 0.34 | <0.01 | 0.06 |
| 2010 | 0.01 | 0.01 | 3.17 | 0.28 | 0.24 | <0.01 | 0.06 |
| 2020 | 0.01 | 0.01 | 2.19 | 0.14 | 0.13 | <0.01 | 0.06 |
The SchoolPool carpool ridematching program promotes carpooling for children in all public and private schools in the County (kindergarten through college). There is one program that coordinates the activities, administered by TRANSPAC/ TRANSPLAN TDM for western, central and eastern Contra Costa. Staff distributes ridematch brochures in school registration packets at the beginning of each school year. The inputs used for this calculation are as follows:36
Step 1: Calculate daily auto trips reduced.
= (Number of participants) x (number of trip segments)
= (1204) x (3)
= 3,612 auto trips reduced per day
Step 2. Calculate daily VMT reduced.
= (Number of participants) x (number of trip segments) x (one-way trip length)
= (1204) x (3) (5.5)
= 19,866 daily VMT reduced
Step 3: Calculate annual reductions in emissions.
= ([(Daily VMT reduced x auto running emissions factor)] + [(daily auto trips reduced x auto trip start emissions factor)] x (operating days)
The following table shows the annual emissions impacts resulting from the implementation of the example strategy:
Table 3-36. Total Emissions Reduced (tons/year) from School Pool Program Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 0.05 | 0.10 | 30.1 | 2.90 | 2.51 | 0.03 | 0.40 |
| 2010 | 0.05 | 0.10 | 23.2 | 1.75 | 1.75 | 0.03 | 0.40 |
| 2020 | 0.04 | 0.10 | 16.1 | 1.01 | 0.94 | 0.03 | 0.40 |
Integrating land use planning with transportation planning can reduce emissions by reducing the demand for vehicle travel and reducing trip distances.Examples of land-use strategies include transit-oriented development (TOD) and clustered activity centers. Integrating land use and transportation planning helps to make common destinations accessible by alternative modes of transportation, including transit, walking, and biking.
Land-use policies that reduce VMT will typically reduce all pollutants; however, the emissions reductions will not be proportionate for all pollutants, since land use strategies may reduce vehicle trip making and reduce vehicle trip lengths (in the case of shorter trips, trip start emissions are still generated) or higher density development may increase localized traffic congestion (since it is often designed for lower travel speeds than more dispersed development), which will affect net emissions benefits. General impacts of land use strategies are shown below:
Table 3-37. Land Use Strategies - Overall Impact on Emissions
| PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
* = Generally will reduce emissions; however, in some cases may result in some increase in emissions if results in increased speeds
The level of emissions impact depends on:
Regional land use strategies should typically be examined using a regional travel demand forecasting tool to assess the implications of different growth patterns and transportation investments on vehicle travel, congestion, and speeds. Note that many TDF models are not very sensitive to adequately account for the vehicle trip reductions associated with more mixed-use, high density developments, pedestrian factors, and short trips, and model enhancements or adjustment factors may be needed. For examining specific infill developments, comparisons can be made based on different assumptions about where the growth would otherwise occur, per EPA guidance.It is important to note that the air quality impacts of land use policy changes are long term, generally outside the time frame associated with attainment of NAAQS. Given the complexity of accurately modeling the impacts of land use strategies, the sample calculation below uses a very simplified approach to show potential emissions impacts, but would not be adequate for SIP or conformity purposes.
For EPA guidance on calculation of emissions, see "Improving Air Quality through Land Use Activities," http://www.epa.gov/otaq/stateresources/policy/transp/landuse/r01001.pdf and related reference materials.
This sample is based on modeling conducted in Portland, Oregon, as part of the LUTRAQ (Land Use Transportation Air Quality Connection) project. LUTRAQ used the Western Bypass freeway around the Portland, Oregon metropolitan region as a case study to compare and evaluate the impacts of alternative land use patterns on automobile dependency, mobility, and air quality. The study found that alternative land use patterns significantly reduced automobile dependency, and as a result, would reduce auto emissions. Alternative land use patterns were defined by the transit-oriented development concept that focuses on future development around transit stations in mixed use, pedestrian designed environments. For the LUTRAQ evaluation, regional transportation modeling procedures were developed to forecast travel behavior associated with alternative land use patterns.
Based on regional analysis using the regional travel demand forecasting model, and enhancements to account for pedestrian factors and other urban design characteristics, the LUTRAQ alternative was estimated to reduce daily VMT by 8 percent compared to a highway-only alternative by the end of the modeling period horizon, based on both the land use and market-based mechanisms in the LUTRAQ package. The land use elements are responsible for a large portion of this VMT reduction. Isolating the effects of the land use elements (by comparing the LUTRAQ alternative with the Highway/Parking Pricing alternative) suggests that changes in urban design are responsible for about three-fourths of the VMT reduction. The LUTRAQ alternative is expected to result in 6 percent less VMT than the Highways/Pricing alternative. The LUTRAQ alternative also is expected to generate significantly higher shares of walk/bike trips and transit trips compared to the alternatives. Motor vehicle emissions impacts all go down in the LUTRAQ scenario, but by different percentages, based on changes in vehicle trip-making, VMT, and speeds, as shown below.37
Table 3-38. Portland's LUTRAQ Study: Emissions (Percent Reduction from No Build Alternative)
| Travel Indicator | Highways Only | Highways/Pricing | LUTRAQ |
|---|---|---|---|
| Daily VMT | 6,995,986 | 6,856,447 | 6,442,348 |
| Vehicle Trips per Household | 7.50 | 7.29 | 7.17 |
| HC/VOCs | -0.2 percent | -3.6 percent | -6.2 percent |
| NOx | 6.7 percent | 3.6 percent | -2.6 percent |
| CO | -0.6 percent | -4.0 percent | -6.7 percent |
For a very simplified calculation of emissions impacts for all pollutants, the following procedures were used:
The following table shows the estimated emissions impacts for this example in 2020, assuming implementation of the land use policy over 20 years; however, the sample calculation reflects the VMT figures reported in the LUTRAQ study. It should be noted that land use strategies generally influence travel and emissions over relatively long periods of time, as new development occurs in a region and population grows. Consequently, emissions impacts for 2006 and 2010 are not reported here.
Table 3-39. Total Emissions Reduced (tons/year) from Land Use Strategies Example
| Year | PM-2.5 | PM-10 | CO | NOx | VOCs | SOx | NH3 |
|---|---|---|---|---|---|---|---|
| 2006 | 6.00 | 8.79 | 519 | 253 | 49.2 | 1.59 | 15.1 |
9 A key factor used in evaluating changes in VMT resulting from park-and-ride programs is the previous mode of park-and-ride users. Analysis conducted by EPA in the early 1990s found that between 11 and 85 percent of park-and-ride patrons had driven alone to their destinations before they began using park-and-ride facilities.
10 Note that carpool/vanpool trips tend to be longer than overall regional average commute trip lengths. It is not uncommon for vanpool trips of 40 miles or more each way.
11 Documented in "Summary of Review of Costs and Emissions Information for 24 Congestion Mitigation and Air Quality Improvement Program Projects," developed by Hagler Bailly for U.S. EPA, 1999.
12 Documented in "A Guide for Estimating the Emissions Effects and Cost-Effectiveness of Projects Proposed for CMAQ Funding," by ICF International for the Birmingham Regional Planning Commission, 2002.
13 Compliance will affect traffic and speeds in the HOV lane, and may affect the extent to which people shift to HOVs.
14 Documented in "Summary of Review of Costs and Emissions Information for 24 Congestion Mitigation and Air Quality Improvement Program Projects," by Hagler Bailly for U.S. EPA, 1999.
15 Documented in "Summary of Review of Costs and Emissions Information for 24 Congestion Mitigation and Air Quality Improvement Program Projects," by Hagler Bailly for U.S. EPA, 1999.
16 Bureau of Labor Statistics, http://www.bls.gov/oes/current/oes_41884.htm
17 Documented in "Methods to Find the Cost-Effectiveness of Funding Air Quality Projects," by the California Air Resources Board, 2005.
18 Documented in "Off-Model Air Quality Analysis: A Compendium of Practice," by Federal Highway Administration, Southern Resource Center, 1999.
19 Documented in "Methods to Find the Cost-Effectiveness of Funding Air Quality Projects," by the California Air Resources Board, 2005.
20 Adapted from an example documented in "Benefits Estimates for Selected TCM Programs," by ICF International for the U.S.EPA, 1999.
21 Documented in "A Guide for Estimating the Emissions Effects and Cost-Effectiveness of Projects Proposed for CMAQ Funding," by ICF International for the Birmingham Regional Planning Commission, 2002.
22 Documented in "Cuesta Grade Transportation Demand Management Evaluation Draft Report," by Eric Schreffler and Transportation Management Services for the San Luis Obispo Council of Governments, 2003.
23 Documented in "TCRP Report 95: Traveler Response to Transportation System Changes - Transit Pricing and Fares," Chapter 12, by McCollom, Brian and Richard Pratt et al. for Transportation Research Board, Transit Cooperative Research Program, 2004.
24 Documented in "TCRP Report 107: Analyzing the Effectiveness of Commuter Benefits Programs," by ICF International and Center for Urban Transportation Research for Transportation Research Board, Transit Cooperative Research Program, 2005.
25 Documented in "Reducing Greenhouse Gas Emissions through the Transportation Partners Program: Recent Trends and Case Studies," by Apogee Research, Inc., for U.S. Environmental Protection Agency, 1995.
26 Documented in "8-Hour Attainment: Control Strategies: On Road," by ENVIRON Corp. for North Central Texas Council of Governments, 2006.
27 Documented in "Workbook: Transportation and Land-Use Strategies for reducing Mobile Source Emissions," by Charlier Associates for the Denver Regional Air Quality Council.
28 The price elasticity for travel reflects the percent change in VMT associated with a given percent change in the price of travel per mile. For instance, a price elasticity of -0.25 reflects that a 10 percent increase in travel costs will result in a 2.5 percent reduction in VMT. Price elasticities can vary based on many factors, including the starting cost of travel and availability of travel alternatives. The price elasticity used here was provided in the cited sample project.
29 The timing and process of fee collection may affect travel response by making the driver more or less aware of the per mile charge (e.g., annual fees versus fees paid on a daily or monthly basis).
30 ; Documented in "8-Hour Attainment: Control Strategies: On Road," by ENVIRON Corp. for North Central Texas Council of Governments, 2006.
31 Documented in "Workbook: Transportation and Land-Use Strategies for Reducing Mobile Source Emissions," by Charlier Associates for the Denver Regional Air Quality Council, 1997.
32 The price elasticity for travel reflects the percent change in VMT associated with a given percent change in the price of travel per mile. For instance, a price elasticity of -0.25 reflects that a 10 percent increase in travel costs will result in a 2.5 percent reduction in VMT. Price elasticities can vary based on many factors, including the starting cost of travel and availability of travel alternatives. The price elasticity used here was provided in the cited sample project.
33 Documented in "A Guide for Estimating the Emissions Effects and Cost-Effectiveness of Projects Proposed for CMAQ Funding," by ICF International for the Birmingham Regional Planning Commission, 2002.
34 Documented in "Off-Model Air Quality Analysis: A Compendium of Practice," by Federal Highway Administration, Southern Resource Center, 1999.
35 Documented in "Summary of Review of Costs and Emissions Information for 24 Congestion Mitigation and Air Quality Improvement Program Projects," developed by Hagler Bailly for U.S. EPA, 1999.
36 Documented in "SCHOOLPOOL-Carpool to School Program," prepared by Lynn Osborn for Central and Eastern Contra Costa, California, 2000.
37 Documented in "Making Connections with LUTRAQ," prepared for 1000 Friends of Oregon, available at: http://www.friends.org/resources/lut_reports.html
