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Handbook for Estimating Transportation Greenhouse Gases for Integration into the Planning Process

Chapter 7 - Specific Transportation Strategy Analysis Methods

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A range of tools and approaches can be used to analyze the effects of transportation GHG reduction strategies that cannot be directly accounted for in standard travel forecasting methods. These "off-model" analyses often use simple spreadsheet calculations or sketch planning methods. A wide range of tools are available, and samples of these analyses are described in more detail below. Note that some of the methodologies described below may not always be applicable to a regional or state-level analysis, but could be used to generate data for these analyses.

7.1 Transportation demand management strategies

Several spreadsheet-based calculators are available to estimate the impact of TDM strategies (i.e., reducing VMT, including transit improvements, ridesharing programs, and bicycle and pedestrian improvements). These calculators use a variety of empirical information from case studies and statistical analyses of price elasticities and travel time elasticities to predict the impact of TDM measures on either a site-specific basis or a region-wide basis. Most of the calculators focus on commute reduction measures that can be implemented by or through employers.

Table 27. Sample TDM Analysis Tools and Approaches


Brief Description


Designed to analyze the impacts of transportation control measures such as transit employer-based transportation demand management programs and transit improvements, on VMT, criteria pollutant emissions, and CO2. For more information see:


Developed by the University of South Florida. It is conceptually similar to the COMMUTER model, and can provide travel activity estimates. It was recently updated to include some emissions derived from MOVES. 1 For more information see:


Spreadsheet based tool intended to evaluate the impact of strategies at employer sites and local public strategies based on the California Air Pollution Controls Officers Association (CAPCOA) research ( Results have been validated with case studies in the San Francisco Bay Area.

Example Method for Assessing TDM Policies: Travel Efficiency Assessment Method (TEAM)

Developed for U.S. EPA, TEAM uses Trip Reduction Impacts of Mobility Management Strategies (TRIMMS) with outputs from regional travel demand models and other relevant data (e.g., transit fares) to assess the potential VMT reduction for TDM and other "travel efficiency" strategies in larger geographic areas. Emissions factors from MOVES are then applied to the travel activity results from TRIMMS. Key steps in this approach include:

Step 1: Identify strategies of interest
Step 2: Select the sketch-planning tool (may be TRIMMS or some other tool)
Step 3: Collect the data
Step 4: Complete the VMT analysis
Step 5: Conduct the MOVES analysis to generate emission factors
Step 6: Compare strategies

The flow chart below lays out these steps.

Figure 12. Key Steps in the TEAM Approach

A diagram showing the key steps in the TEAM approach. On the left are two boxes stacked on top of each other that read 'identify strategies of interest' and 'select the tool.' These boxes are connected to three boxes lined up in a row to the right saying, 'data collection,' 'VMT analysis,' and 'MOVES analysis.' To the right of this row are two boxes stacked on top of each other reading 'strategy ' and 'potential emissions reduction.' Arrows pointing from left to right connect the boxes.
Source: U.S. Environmental Protection Agency, "Analyzing Emission Reductions from Travel Efficiency Strategies: The TEAM Approach. " Developed by ICF International, September 29, 2011.

A more detailed assessment of many of these tools' capabilities, inputs, and outputs is available in a recent report from U.S. EPA. 2

Strengths and Limitations

Key strengths and limitations of tools used to estimate the impacts of TDM strategies are noted in the table below.

Table 28. Strengths and Limitations of Tools Used to Estimate Impacts of TDM Strategies



  • Can use outputs from existing travel demand models.
  • Default data and existing modeling tools are available.
  • Allows quick comparison of results for different scenarios that use the same input or baseline data
  • Elasticity values, which are important for determining impacts, can be altered by the user if data are available, or defaults can be used.

  • Using default data will reduce regional sensitivities.
  • Lack of familiarity with MOVES may be a limitation to using this methodology.
  • Due to data limitations, assumptions may need to be used.
  • Local travel time and price elasticity values are typically difficult to obtain, so national defaults are often used.
  • The effects of TDM strategies on network speeds and congestion are not captured in sketch planning tools like TRIMMS.

Example: Metropolitan Washington Council of Governments (MWCOG)

Metropolitan Washington Council of Governments' (MWCOG) Commuter Connections Program implements several Transportation Emission Reduction Measures (TERMs) to assist the region in meeting conformity requirements. The TERMS included are: Maryland and Virginia Telework, Guaranteed Ride Home, Employer Outreach, Mass Marketing, and Integrated Rideshare-Software Upgrades Project. The COMMUTER model is used as part of the analysis of the Employer Outreach TERM. The impacts of employer outreach are estimated by first inputting employer baseline ("before") mode shares and commuter assistance program strategies into the model. The model then estimates the "after" mode split and the average vehicle ridership when the program is in place. The COMMUTER model uses time and cost coefficients that are based on coefficients that are used in the region's transportation modeling. Adjustments may be made to these coefficients due to new data collected from a Household Travel Survey. 3 See

7.2 Land use strategies

Off-model techniques are particularly useful for analysis of land use strategies because travel demand models typically do not capture the impact of small scale land use changes, including land use mixing, pedestrian accessibility and friendliness, and increased density, on travel patterns. There is an extensive body of research on the impact of such factors, known as the "4 Ds" (density, diversity, design, and destinations). Off-model techniques must typically be applied to account for them.

A number of tools exist to conduct off-model analyses of land use strategies. Some, such as INDEX and PLACE3S, can interface with travel demand model outputs. Other tools typically estimate changes in VMT based on relationships between factors such as population density, land use mix, and urban design.

See below for a sample of transportation and land use analysis tools and approaches.

Table 29. Sample Transportation and Land Use Analysis Tools and Approaches


Brief Description


Robust sketch planning model. Can interface with travel demand model and contains 4D adjustments to account for smart growth developments.


Robust sketch planning model. Can interface with travel demand model and contains 4D adjustments to account for smart growth developments.


User friendly model originally developed by the California Air Resources Board to assist local agencies with estimating emissions impacts of land use projects. Allows user to estimate potential vehicle travel and emission reduction benefits of site-based strategies, such as pedestrian/bicycle facilities, transit, on-site services, telecommuting, and alternative work schedules. It does not function well for large-scale, mixed-used, or smart growth plans

Sustainable Communities Model

Regional model can be configured for sub-area and project-level analyses. Uses California factors only. Requires extensive data from user, including trip generation, VMT, and fuel. Calculates effects from a variety of GHG mitigation techniques to determine the most cost-effective option. Allows communities to optimize planning and design decisions that result in the greatest environmental benefit for the least cost.


Uses GIS-based sketch planning that offers immediate 40-year future scenario planning with the purpose of informing non-technical users about the trade-offs and costs of planning decisions in relation to GHG output. Uses data generated from analysis by regional travel forecasting models.


GIS-based decision support software for planners and resource managers. It is an ArcGIS® extension that adds interactive analysis tools and a decision-making framework to the ArcGIS platform. Scenario 360 helps you view, analyze and understand land-use alternatives and impacts.


Cape Cod, Massachusetts Pilot Project

The Interagency Transportation, Land Use, and Climate Change Pilot Project conducted in Cape Cod, Massachusetts integrated climate change mitigation and adaptation measures into a transportation and land use planning strategy. Transportation and land use scenarios were evaluated using CommunityViz, and tested against performance indicators such as VMT and GHGs. The Volpe Center then worked with the National Park Service (NPS), the Cape Cod Commission, and the Commonwealth of Massachusetts to determine how to incorporate elements of a refined scenario into the region's planning efforts and long-range plans. 4

Blueprint Sacramento

Sacramento's regional vision planning process used integrated land use, transportation modeling and extensive community involvement. The process developed a "blueprint" for how the region will grow and develop over the 50-year horizon. A number of different modeling tools were used to simulate the impact of different land use strategies on the demand for transportation and the creation of GHG emissions, among other impacts.

The primary technical component of the Blueprint development process was the I-PLACE3s platform, a public domain software package designed to integrate community participation, urban planning and design, and quantitative analysis. The Blueprint used a version of the software that could operate over the Internet, providing real-time feedback during public workshops. The software allowed users to apply a range of zoning designations to each land parcel in a given area. There are options to vary inputs such as building density and the number of available parking spaces. I-PLACE3s was able to calculate changes in each scenario and then display the results in tables and charts for easy comparison. By running the software over the Internet, the system did not require sophisticated equipment - it was possible to use laptops donated by local businesses.

The Sacramento Area Council of Governments (SACOG) utilized two additional tools to supplement the I-PLACE3s model. The first was MEPLAN, a land use and economic forecasting model that allocated growth to the region's transportation analysis zones, including variables for development policies, development costs, and rents. Outputs from MEPLAN were disaggregated to the parcel level and used to populate the I-PLACE3s database. The second tool was the regional travel demand model, SACMET, which used the impact assessment output from I-PLACE3s. SACMET was enhanced with data from household travel surveys to adjust vehicle trips and vehicle miles traveled based on land use density, mix of uses, and distance measures at the zonal level. SACMET and MEPLAN have since been replaced by new generation models that better capture the relationships between land use and transportation, economic systems, and demographic changes. The integrated framework allows for better understanding of infrastructure investments and policy options.

SACOG found that use of such a comprehensive data-driven approach to be very effective. Once the system was built, it could be adjusted relatively simply by changing assumptions and other policy variables. The technical approach and transparency facilitated development of multiple scenarios, and helped to build public support, as participants could better understand the source of future decisions.
For more information, see:

7.3 Transportation system management and eco-driving strategies

Transportation System Management (TSM) strategies include measures such as traffic surveillance, work zone management, electronic toll collection, traffic incident management, road weather management, emergency management, and traveler information services. TSM strategies also include measures such as ramp metering and signal timing that reduce recurring delay, as well as other types of intelligent transportation system (ITS) technologies that reduce non-recurring delay due to incidents, weather conditions, work zones, and special events. TSM strategies typically reduce emissions by reducing idling and delay, and allowing for smoother traffic flow. Eco-driving involves public education efforts to encourage drivers to operate their vehicles more smoothly, with fewer rapid starts and stops, as well as other practices, such as keeping tires fully inflated. The benefits of these strategies are not captured in most regional travel models, and therefore, off-model analyses are often conducted for these strategies.

Tools to analyze TSM strategies can be characterized as follows:

Example: Implementing Integrated Corridor Management (ICM) strategies on the U.S. 75 corridor in Dallas, Texas

The Integrated Corridor Management (ICM) initiative demonstrated the benefits of integrating ITS technologies on U.S. 75, a major corridor in Dallas, Texas. By integrating ITS assets and implementing ITS strategies regionally, ICM improves mobility, safety and reduces fuel consumption.

The analysis, modeling and simulation of Integrated Corridor Management (ICM) strategies on U.S. 75 combined a macroscopic trip table manipulation for determining trip patterns; a mesoscopic analysis for assessing the impact of driver behavior in reaction to ICM strategies; and a mesoscopic traffic simulation model for reflecting the effects of signal timing. The analysis used 2007 as the model base year, and focused on morning peak periods.

The analysis assessed mobility, reliability and variability, and emissions and fuel consumption. Mobility measures included travel time, delay (defined as the total observed travel time less the travel time under noncongested conditions), and throughput (defined as the number of vehicles and persons per hour by direction). Reliability and variability were calculated from multiple simulated runs under all scenarios. Emissions and fuel consumption were determined by calculating and matching emission rates to reference values in MOBILE6. The values were monetized by applying costs per ton of pollutants released and the purchase price of fuel.

The study evaluated comparative travel time information (pre-trip and en-route traveler information); incident signal retiming plans for arterials; incident signal retiming plans for frontage roads (frontage roads run parallel to U.S. 75); light-rail transit (LRT) smart parking system; Red Line capacity increase (Red Line is a LRT); LRT station parking expansion (private parking); and, LRT station parking expansion (valet parking).

Benefits were savings in travel time, increased travel time reliability, reduced fuel consumption, and reduced emissions. Expected annual savings included 740,000 person-hours of travel, and a reduction of fuel consumption by 981,000 gallons of fuel. For more information, see:

7.4 Freight strategies

Freight strategies within the purview of DOTs and MPOs include idle reduction programs and policies; truck driver eco-driving programs; logistics improvements (e.g., use of ITS tools to reduce truck clearance times at international borders and weigh stations); freight bottleneck removal; overall congestion relief; incentives for retrofit of older diesel engines; and mode shift strategies. The U.S. EPA SmartWay Transport Partnership offers information to analyze the benefits of some of these strategies. For example, the SmartWay web site ( includes several calculators and models that provide fuel consumption rates of idling trucks and of idle reduction solutions; guidance for states that want to incorporate idle reduction projects in their air quality plans; current and prior idle reduction projects funded by SmartWay and others, and the environmental and related benefits of these projects; and other key tools and information on the effectiveness and benefits of reducing idling from trucks and locomotives. EPA also has created the SmartWay Transport Partnership Freight Logistics Environmental and Energy Tracking Performance Model (FLEET), which can also be found on EPA's website at

Sketch analyses can also be applied to freight strategies. These are typically spreadsheet calculations that use assumptions about the effectiveness and penetration rate of strategies. Examples of such analyses can be found in Moving Cooler.7 Consideration of freight emission reduction strategies will need to take into account future changes in fuel economy of freight trucks, such as the joint DOT and EPA fuel efficiency and GHG emission program for medium- and heavy-duty vehicles. 8 States and MPOs can also analyze strategies to support technology and fuel changes, such as through providing alternative fuel infrastructure.

Example: Southern California Association of Governments (SCAG)

The Southern California Association of Governments' (SCAG) "Regional Goods Movement Plan" supports state and local goals to reduce GHG emissions. SCAG has done extensive analysis of the air quality and GHG emissions impacts of a number of different freight strategies. The strategies considered focus primarily on truck and locomotive emissions, since SCAG is actively engaged in planning improvements to highway and railroad systems.

For example, SCAG's regional "Clean Truck Corridor Strategy" involves the creation of a bi-directional corridor that would be restricted to truck traffic and have limited ingress/egress points. This freight corridor would streamline the flow of freight trucks moving to and from the Ports of Los Angeles and Long Beach. By creating a dedicated truck lane, the freight corridor would be a catalyst for the use of zero-and/or near-emission truck technologies. Incentives would be provided for zero or near-zero emission trucks and clean truck infrastructure (including wayside power).

SCAG's analysis included four categories of advanced truck technologies: advanced natural gas vehicles, hybrid-electric vehicles, plug-in hybrid electric vehicles, and battery electric vehicles. For each category, SCAG described the current state of technology, expected developments over the next 10-20 years, and barriers to advancement. SCAG estimated the expected emissions benefit, incremental vehicle cost, and timeframe for commercial availability for each technology and truck weight class. SCAG developed hypothetical scenarios for deployment of these emission reduction technologies in 2023 and 2035, including region-wide emissions benefits and costs. The figure below shows emissions reductions for advanced technology HHDVs (the heaviest class of heavy duty vehicles) in 2035.

Figure 13. 2035 Emission Reduction for Advanced Technology HDVs

A graph showing the estimated percent reduction in NOx, PM2.5, and GHGs per HHDV for NGV, hybrid, PHEV, and BEV options. BEV reduces the most emissions - up to 100% for NOx, about 80% for PM2.5, and 56-59% for GHGs. The other technologies generally reduce NOx by 25-55% and PM2.5 by 4-30%. For GHGs, NGV reduces 20-36%, hybrid reduces 5-20%, and PHEV reduces 10-22%.

Source: Southern California Association of Governments, "Environmental Mitigation Strategies, Task 10.2 Report," prepared by ICF International, September 2011.

Other strategies analyzed by SCAG included an enhanced truck inspection and maintenance program, conditional use permits for warehouses, increased enforcement of ant-idling regulations, expansion of on-dock rail, expansion of near-dock rail, grade separation of rail intersections, an off-peak delivery program, and improved transportation system management. SCAG used forecasts for truck traffic and estimates of vehicle emissions based on the EMFAC model and other sources to estimate the CO2 emissions impacts. SCAG also considered strategies to reduce emissions from locomotives. They quantified the benefits and costs of several strategies to reduce locomotive emissions, including the accelerated deployment of Tier 4 locomotives, railroad main line electrification, and strategies focused on switching locomotives.

For more information, see:

1 At this time, emissions included in TRIMMS are exclusively for the year 2011 and do not include all MOVES pollutant processes.

2 U.S. EPA, "Potential Changes in Emissions Due to Improvements in Travel Efficiency - Final Report," prepared by ICF International, March 2011.

3 National Capital Regional Transportation Planning Board, Metropolitan Washington Council of Governments, "Commuter Connections Transportation Demand Management Evaluation Project - Transportation Emission Reduction Measures (TERMS): Revised Evaluation Framework 2008-2011," prepared by LDA Consulting. May 18, 2010.

4 Research and Innovative Technology Administration, Volpe National Transportation Systems Center, "Interagency Transportation, Land Use, and Climate Change Pilot Project. "

5 FHWA, "Traffic Analysis Toolbox, Volume II: Decision Support Methodology for Selecting Traffic Analysis Tools," July 2004.

6 Macroscopic simulation models are based on the deterministic relationships of the flow, speed, and density of the traffic stream, with simulation taking place on a section-by-section basis rather than by tracking individual vehicles. Microscopic simulation models, in contrast, simulate the movement of individual vehicles based on car-following and lane-changing theories. Mesoscopic simulation models combine the properties of both microscopic and macroscopic simulation models; as such, they provide less fidelity than microsimulation tools but are superior to the typical planning analysis techniques. For more information on these types of tools, see FHWA's Traffic Analysis Tools Program at:

7 Cambridge Systematics, "Moving Cooler: an analysis of transportation strategies for reducing greenhouse gas emissions," Urban Land Institute, October 2009.

8 "Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and heavy-Duty Engines and Vehicles," Federal Register 76:179, September 15, 2011, p. 57106.

Updated: 03/27/2014
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