Skip to content U.S. Department of Transportation/Federal Highway AdministrationU.S. Department of Transportation/Federal Highway Administration

Office of Planning, Environment, & Realty (HEP)
Planning · Environment · Real Estate

HEP Events Guidance Publications Glossary Awards Contacts

Three photos: a city skyline, a truck on a road, and a school bus.

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

Jody McCullough
Federal Highway Administration


Webinar Agenda

  1. Handbook Overview
  2. Background on GHGs in Transportation
  3. GHG Analysis in the Transportation Planning Process
  4. Methods and Tools for GHG analysis
    • Key Methods
      • Fuel-based Methods
      • VMT-based Methods
    • Alternative Approaches, Strategy Analysis Methods, & Additional Considerations
  5. Summary
  6. Presentations from Sample Areas: XXXXXXXX
  7. Questions & Answers

NOTE: Modify based on length and purpose of Webinar. This agenda assumes a 90 minute webinar:

Note: This Handbook presentation material could be shortened by removing the "Background on GHGs in Transportation."


Handbook Overview


Need for Handbook

Cartooon drawing of a man with a question mark over his head.

While there is no federal requirement for State DOTs and MPOs to consider the GHG impacts of their transportation plans, some states and MPOs have begun to develop policies to address climate change mitigation through transportation planning decisions. States and metropolitan planning organizations also sometimes have state or local requirements or other specific reasons for considering GHGs associated with their transportation systems. States and MPOs also may wish to consider GHG emissions as one factor within a performance-based planning and programming process.

Although there are a number of existing resources that describe GHG analysis tools and models, they may be daunting for agencies with limited emissions analysis experience.


Handbook Purpose

Handbook for Estimating Transportation Greenhouse Gases for Integration into the Planning Process cover. Three photos: A city skyline, a truck on a road, and a school bus.

Primary audience: MPOs and State DOTs

Content: Describes methodologies that may be used, as well as tools and data sources that can be used for development of GHG inventories, forecasts, and analyses of GHG plans and mitigation strategies

Document is intended largely for areas with limited experience conducting emissions analysis.

Handbook helps agencies understand:

It includes:


Including GHG Analysis in the Transportation Planning Process

Flowchart. Regional vision and goals. Alternate Improvement Strategies (Operations and Capital). Evaluation & prioritization of strategies. Development of Transportation Plan (LRP). Development of Transportation Improvement Programs (STIP). Project Development. Systems Operations (Implementation). Monotor system performance (Data). Circled by Feedback, Critical Factors and inputs. Safety. Non-discrimination. Air Quality. Environmental Issues. Economic Development. Public Involmentment. Date, and Fiscal Constraint.

It is important to note that climate change and greenhouse gas emissions can be considered within the planning process. This diagram shows key elements of the transportation planning process. A comprehensive transportation planning process has a holistic approach and considers all factors; planners should not treat 'climate change' (or any factor) as completely separate, but can be integrated throughout decisionmaking within the planning process.

Discussion of climate change is becoming more common in transportation planning documents. Some long-range transportation plans (LRTPs) in particular are highlighting climate change among a new generation of environmental and sustainability issues that shape transportation planning objectives.

The 2008 FHWA study, Integrating Climate Change into the Transportation Planning Process, examined how a number of State DOTs and MPOs are approaching the subject and identified opportunities for practitioners to address climate change within several key elements of transportation plans. Each of these elements can incorporate climate change directly, by explicitly addressing climate change, and indirectly, by addressing elements of transportation that are linked to climate change. Components within both statewide and metropolitan transportation plans that can include climate change are:

Even if the public and elected officials do not hold climate change considerations on the top of the priority list, issues such as environmental sustainability, energy conservation, and fuel savings may be important (e.g., national security, economic benefits, stewardship of the planet) to the community, and these goals typically relate closely to GHG reduction.


Types of GHG Analysis within the Planning Process

Inventory Development: An inventory provides information on the magnitude of emissions and their sources. An inventory is usually performed for a recent year, depending on data availability. The level of detail that an inventory provides is determined by the methodology used.

Forecasts/Analyses of Alternative Scenarios: In the case of a forecast, the organization will typically analyze emissions under a business-as-usual scenario. This can reflect anticipated changes in fuel economy, fleet composition, travel patterns, and other variables likely to impact emissions. In order to identify the most effective ways to reduce emissions, the agency may choose to analyze alternative scenarios that estimate the anticipated impact of various policy choices or investments. Some areas also are beginning to include climate change mitigation (and adaptation) in scenario planning.

GHG Strategy analysis: Analyzing the effects of GHG strategies may be incorporated as part of the overall forecasting process. It is important to note, however, that standard travel forecasting approaches are not well geared toward analyzing certain types of strategies, such as strategies that reduce non-recurring delay, reduced heavy-duty vehicle idling (e.g., truck stop electrification), a low carbon fuel standard, and many others. Consequently, it may be important to conduct specific analyses of GHG reduction strategies or packages of strategies as part of the planning process. Moreover, as agencies move toward more performance-based planning and programming approaches, they may wish to analyze the GHG effects of different projects and programs in order to help prioritize investments for funding.


Handbook Sections

Handbook includes:

  1. Introduction
  2. Overview: Estimating GHG Emissions in the Planning Process
  3. What Methodologies are Applicable in Your Situation?
  4. Fuel-based Methods
  5. VMT-based Methods
  6. Alternative GHG Estimation Approaches
  7. Specific Transportation Strategy Analysis Methods
  8. Additional Considerations in GHG Analysis: Lifecycle Analysis and GHG Emissions from Transportation Construction & Maintenance
  9. References

The Handbook begins with an introduction and overview about estimating GHG emissions in the planning process, including:

Section 3 is designed to help the user understand what methods are most applicable to their situation, and to understand what factors to consider in selecting a method.

Section 4 to 8 provide information on methods that can be used to analyze GHG emissions. Each methodology reviewed includes the following information:

  1. Table summarizing Selection Criteria - Each type of method serves certain needs better than others and has strengths and weaknesses in application, due to data requirements, outputs produced, and sensitivity to different factors. The table provides highlights
  2. A general description of the methodology
  3. Highlights of strengths and limitations
  4. Key Steps (step by step procedures) and data needs and options
  5. Examples of State DOTs and/or MPOs that have applied the method.

Many methods can be applied at different levels of complexity, based on the amount and quality of data available and the purpose and needs of the analysis.

This Webinar covers Fuel-based and VMT-based methods in most detail since these are most commonly used for GHG analysis. The analysis of GHG-reducing transportation strategies, alternative approaches, and other considerations such as life cycle analysis and emissions from transportation construction and maintenance will also be covered, though briefly.

Section 9 provides references to web sites and documents with more detailed documentation on models and tools.


Background On Greenhouse Gases In Transportation


Greenhouse Gases

Carbon Dioxide (CO2): Carbon dioxide enters the atmosphere through the burning of fossil fuels (oil, natural gas, and coal), solid waste, trees and wood products, and also as a result of other chemical reactions (e.g., manufacture of cement). Carbon dioxide is also removed from the atmosphere (or "sequestered") when it is absorbed by plants as part of the biological carbon cycle.

Methane (CH4): Methane is emitted during the production and transport of coal, natural gas, and oil. Methane emissions also result from livestock and other agricultural practices and by the decay of organic waste in municipal solid waste landfills.

Nitrous Oxide (N2O): Nitrous oxide is emitted during agricultural and industrial activities, as well as during combustion of fossil fuels and solid waste.

Fluorinated Gases: Hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride are synthetic, powerful greenhouse gases that are emitted from a variety of industrial processes. Fluorinated gases are sometimes used as substitutes for ozone-depleting substances (i.e., CFCs, HCFCs, and halons). These gases are typically emitted in smaller quantities, but because they are potent greenhouse gases, they are sometimes referred to as High Global Warming Potential gases ("High GWP gases").

CO2 is the most significant gas emitted by transportation sources, but mobile sources also emit CH4 and N2O, as well as fluorinated gases.


GHGs are Different

Cartoon drawing of the Earth with N. and S. America, Europe, and Africa.GHG emissions differ from criteria air pollutants currently regulated under the Clean Air Act:

Greenhouse gases are different from other air pollutants in important ways.

Although the transportation community has had more than 15 years of experience addressing air quality issues within the transportation planning process, GHG emissions are different from the criteria air pollutants currently regulated under the Clean Air Act, as noted here.

As a result of these differences, even States and MPOs that have experience with emissions analysis for transportation conformity may have questions about how to address GHG emissions. Moreover, States and MPOs that have no air quality problems may be interested in analyzing GHG emissions as part of efforts to support sustainability.


Transportation GHGs

About one third (27%) of GHG emissions inthe U.S. come from transportation.

Bar chart. Tg CO2 eq. 1990 to 2010. Electric power industrut under 2000. Transportation 1,500 rising. Industry 1,500 lowering. Under 500 and mostly steady: Agricluture, Commercial, and Residential.

Most transportation emissions come fromon-road sources.

Pie Chart. Ships and boats 2%. Passenger cars 43%. Light-duty-trucks 19%. Medium-and heavy duty trucks 22%. Aircraft 8%. All other transportation sources 6%.

Source: U.S. Environmental Protection Agency, 2010 U.S. Greenhouse Gas Inventory. Note: Does not include U.S. territories


Factors affecting GHG Emissions from Transportation

Flowchart as described in the text.

Energy consumption, particularly fossil fuel consumption, is the principal driver of motor vehicle GHG emissions. Energy consumption and GHG emissions are dependent on a number of characteristics of vehicle fleet makeup and vehicle activity:

Important variables related to vehicle fleet makeup include the age distribution of vehicles and the mix of passenger cars, light trucks, heavy trucks, and other vehicles in the fleet, all of which affect the average fuel economy of the fleet. Vehicle activity variables that affect energy consumption and GHG emissions include VMT and speed.


GHG Analysis In The Planning Process


Why Include GHGs in the Planning Process?

4 stick figure characters with 4 puzzle pieces.

 

There are many reasons that State DOTs and MPOs may be interested in analyzing GHG emissions in the transportation planning process. Specifically:

For more information on performance measures, see Moving Ahead for Progress in the 21st Century Act (MAP-21): A Summary of Highway Provisions," Federal Highway Administration, July 17, 2012, http://www.fhwa.dot.gov/map21/summaryinfo.cfm.


Why Include GHGs in the Planning Process? (continued)

Weaving together integrated planning and NEPA. A drawing of the cross over between transportation agencies, resource agencies, and the public with data strategy and analysys, inter-agency cooperation, and intra-agency coordination. Linking planning and NEPA and integrated planning are the diagonals in the weave.

 

Complement PEL efforts – GHGs can be analyzed at several points in the transportation decision-making process. While GHG analysis is possible for individual projects, analyzing GHGs during the planning process can be more meaningful, given their system-wide impacts, broader geographic scope, and longer time scale. Incorporating GHG emissions analysis in the planning process can complement the PEL approach, which encourages collaboration and integration between transportation and natural resource agencies on the planning and environmental review processes. This approach encourages planners to analyze data and consider the costs and benefits of decisions in a comprehensive way. It can also help eliminate potential duplication of planning and NEPA processes, creating one cohesive flow of information. In addition, encouraging resource and regulatory agencies to get involved in the early stages of planning provides them an opportunity to help shape planning decisions, instead of just reacting to project proposals.

The PEL approach is a collaborative and integrated method of transportation decision-making where environmental issues are considered early in transportation planning and carried through to the project development and environmental review processes. The PEL approach emphasizes interagency coordination and partnerships to lead to a balanced decision-making process. Essentially, PEL weaves consideration for planning and the environment throughout the transportation decision-making process, beginning with planning and continuing through project development, design and construction. This approach can incorporate GHG analysis as well.

Additional information on the PEL approach is available through the FHWA website, "Planning and Environment Linkages: Program Overview," http://environment.fhwa.dot.gov/integ/index.asp.


Methods and Tools

This section will cover the primary methods for GHG analysis, some of the tools available for States and MPOs preparing to perform an analysis of GHGs, and will introduce how the GHG Handbook is organized to provide information about these methods.


Methods for Estimating On-Road GHG Emissions

Fuel Consumed x Emission Factors = CO2 Emissions

Note: The emissions factor will depend on the fuel type

VMT x Emission Factors = GHG Emissions

Note: The emissions factor will depend on vehicle type, technology/fuel type, speeds and operating conditions; different emissions factors are available for CO2, N2O, and CH4

There are 5 primary methods that are used for estimating GHG emissions discussed in the GHG Handbook.

Fuel-based methods and VMT-based methods are the most common.

Fuel-based inventories and forecasts are typically best for state-level analysis due to the availability of state fuel sales data, while VMT-based methodologies may be used at multiple levels. Both State DOTs and MPOs generally have methods to estimate VMT, and most MPOs have travel demand models to forecast future VMT under different scenarios for use in the planning process. Each type of method can typically be applied at different levels of sophistication, based on the amount and quality of data available and the purpose and needs of the analysis.


Methods for Estimating On-Road GHG Emissions (continued)

Other approaches discussed in the Handbook include:

There are three other primary methods that are used to estimate emissions discussed in the GHG Handbook:


What are the most appropriate methods to use?

The diagram poses three questions to the analyst: 'What is the goal of the analysis?' 'What data, tools, and resources do we have available?' and 'What variables do we want to analyze?' Under the first question, the analyst should consider the type of analysis and time frame (inventory - year(s), forecast - year(s), strategy analysis - what specific strategies to consider); geographic scope (state, metropolitan area, local); emissions and sources to be included (CO2 only or also CH4 & N2O; all transportation, on-road vehicles, or subset; operational, lifecycle, construction & maintenance); and analysis precision required (regulatory/compliance, approximate/sketch plan). Under the second question, the analyst should consider data availability (motor fuel sales; HPMS, travel surveys, odometer surveys; roadway speed limits, traffic speed surveys; fleet mix data); modeling capabilities (non-network-based approaches, network-based 3-step travel model, network 4-step or activity-based model); and resources available (staff time, budget). Under the third question, the analyst should consider fuels and vehicle technologies (fleet mix changes, vehicle technology changes, alternative fuel penetration); travel demand (land use changes, transportation demand management, freight flow changes); operations and speed factors (traffic congestion levels, vehicle idling, speeds and eco-driving); and cross-cutting factors to analyze or consider (fuel prices, population and employment levels, and other demographic and economic factors).

Given the variety of methods available for GHG analysis, it is important to recognize that not all methods are applicable in all circumstances. There are a number of key factors that affect the appropriate selection of a methodology. As shown in the figure below, key questions that the analyst should consider are:

"What is the goal of the analysis?" Answering this question will typically include several components:

A State DOT or MPO might also want to consider whether they are interested particularly in measuring the transportation activity of residents living within their jurisdictional boundaries or whether they are interested in all travel that occurs within their boundaries - including all through traffic. Allocating emissions between origins, destinations, and pass through areas can become complicated.

"What data, tools, and resources are available?" Answering this question will include several components:

"What variables do we want to analyze?" Answering this question will include several components:


Fuel Based Methods

Cartoon of a man pumping gas.Cartoon of a fuel truck at a gas station.Cartoon of a fuel pump.


Fuel-based Methods: An Overview

Fuel Consumed
(e.g., gallons)
x Emission Factors
(e.g., CO2 per gallon)
= CO2 Emissions

Fuel-based methods are most applicable where fuel data are available and fuel purchased in the geographic area is used by vehicles operating within the same area. This tends to be the case at a larger scale such as at the state level for developing GHG inventories based on historical data on fuel consumption. This method includes an implicit assumption that emissions can be attributed to purchase location.

To develop a fuel-based inventory, states typically estimate CO2 emissions by obtaining historic fuel use data by fuel type and then apply emissions factors to convert fuel use into CO2 emissions, which are directly proportional to fuel consumption for each fuel type (motor gasoline, diesel, LPG, etc.).

Note - Most often, fuel-based inventories have been developed as part of a multi-sector GHG inventory, which may be developed in connection with a state climate action plan. Fuel-based methods may be used at a county or regional level if fuel sales data are available, but are less appropriate at those levels because it may not be reasonable to assume that fuel use and purchase locations coincide.

One limitation of using fuel-based methods is that forecasts of fuel use typically take into account broad factors like population growth, economic growth, and vehicle technologies, so are useful for developing a basic forecast of anticipated trends, but generally are not tied to transportation planning decisions (e.g., impacts of transportation investments, operational strategies).


Fuel-based Methods: Collecting Fuel Consumption Data

Fuel Consumed
(e.g., gallons)
x Emission Factors
(e.g., CO2 per gallon)
= CO2 Emissions

Common Data Sources:

For on-road vehicles, the most common fuel types are gasoline and diesel, although CNG, LPG, and other fuels may also make up a portion of energy used in transportation. Fuel consumption data are typically based on state fuel tax records, but may be taken from various sources, including:

Output: Fuel consumption by fuel type.

Some states that have developed a statewide GHG inventory and forecast have used statewide VMT projections (usually taken from the State DOT) together with vehicle fuel economy projections (usually taken from DOE's Annual Energy Outlook) to calculate growth factors for on-road gasoline and on-road diesel.

Note: While fuel-based methods can also be applied at the regional or county level in some cases, the applicability of fuel-based methodologies at a regional or county level depends on the level of geographic detail provided in state fuel sales data and the assumption that such fuel is used in the same area in which the sales occur or, at least, are attributed to the sales location. Some states provide a regional breakdown, but most do not.


Fuel-based Methods: Calculating Emissions

Fuel Consumed
(e.g., gallons)
x Emission Factors
(e.g., CO2 per gallon)
= CO2 Emissions

Common Sources / Tools:

A fuel-based inventory involves calculating CO2 emissions based on fuel data. This relies on a direct relationship between fuel carbon content and emissions of CO2 during combustion, and is not applicable for other GHGs.

The EPA's State Inventory and Projection Tool (SIT) is a useful tool for states interested in developing such a GHG inventory.

The SIT is a spreadsheet model that helps states to estimate their GHG emissions from all sectors. It provides the option of using state-specific data or using default data that is generated by Federal agencies and some other sources. This tool uses fuel sales and default data to estimate CO2. Based on its structure, the SIT approach is most appropriate for developing a transportation GHG inventory as part of a broader statewide inventory development process for all sectors, and for statewide analyses that do not require detailed breakdowns of transportation GHG emissions by transportation mode or by local jurisdiction.

www.epa.gov/statelocalclimate/resources/tool.html


Fuel-based Methods: Emissions Factors

Transportation Fuel

Emission Factors

Kilograms CO2 Per

Unit of Volume

Kilograms CO2 Per

Million Btu

Aviation Gasoline

8.32

per gallon

69.19

Biodiesel

-B100

0

per gallon

0

-B20

8.12

per gallon

59.44

-B10

9.13

per gallon

66.35

-B5

9.64

per gallon

69.76

-B2

9.94

per gallon

71.80

Diesel Fuel

10.15

per gallon

73.15

Ethanol/Ethanol Blends

-E100

0

per gallon

0

-E85

1.34

per gallon

14.79

-E10 (Gasohol)

8.02

per gallon

66.30

-M100

4.11

per gallon

63.62

-M85

4.83

per gallon

65.56

Motor Gasoline

8.91

per gallon

71.26

Jet Fuel, Kerosene

9.57

per gallon

70.88

Natural Gas

54.60

per thousand cubic feet

53.06

Propane

5.74

per gallon

63.07

Residual Fuel

11.79

per gallon

78.80

Emissions Factors, available at: http://www.eia.gov/environment/data.cfm

Source: U.S. Energy Information Administration

This table shows an example of emissions factors for different types of fuel, based on information from EIA. It is important to note that emissions factors can be reported in different units -- for instance, per unit of volume (gallons), or per unit of energy (Btus), so it is important to match the form of the emissions factors and the fuel consumption data.


Example: Vermont Statewide GHG Inventory and Forecast

A map of Vermont as described in the text.

In Vermont, the state GHG inventory was developed as part of a multi-sector inventory process, and was developed using SIT software and methods provided in the Emission Inventory Improvement Program (EIIP) guidance document for the transportation sector. EIIP is a jointly sponsored effort between EPA and the National Association of Clean Air Agencies (formerly State and Territorial Air Pollution Program Administrators/Association of Local Air Pollution Control Officials (STAPPA/ALAPCO). Among other initiatives, the EIIP has developed preferred methods for collecting data and calculating emissions and developing more consistent documentation. CO2 emissions factors for on-road vehicle fuel in units of pounds (lb) per million British thermal units (MMBtu) were used. The default data for motor gasoline within SIT were replaced with gasoline consumption estimates from state tax data provided by the Vermont Department of Motor Vehicles and Legislative Joint Fiscal Office.

For developing projections, on-road vehicle CO2 emissions were forecast by estimating future fuel consumption by fuel type, and applying SIT CO2 emissions factors. The fuel consumption was estimated by applying VMT projections, along with adopted changes in vehicle technology and use of biofuels. The VMT projections were developed by Vermont's Department of Environmental Conservation (VTDEC) using historical road type growth curves from the Vermont Agency of Transportation or (VTrans). The data suggested that VMT would grow at an average rate of 1.3 percent per year between 2002 and 2009, 1.4 percent from 2009-2012, and 1.2 percent from 2012-2018. An assumption was made that the 1.2 percent growth rate would apply through 2030. Gasoline and diesel emissions were adjusted to reflect the effects of California's light-duty vehicle GHG standards, which Vermont adopted in 2005. The standards apply to new vehicles beginning with model year 2009.

The projected fuel consumption for new vehicles without the California standards was estimated by applying the projected new vehicle fuel economy from EIA's Annual Energy Outlook to the estimated VMT. SIT CO2 emission factors for diesel and gasoline consumption were then applied to calculate CO2 emissions. Per-mile emissions factors from SIT were also used to estimate CH4 and N2O emissions. VMT for model year 2009 and newer vehicles was estimated for each year using a default percentage of VMT for the model year from the SIT tool. Emissions for the phased-in vehicles under the standards were estimated by applying the emission levels set by the standards to the estimated VMT. The emission reductions resulting from the standards were estimated by subtracting estimated emissions for phased-in light-duty vehicles from the estimated emissions for these vehicles without the standards. The Vermont Biofuels Association provided the projections for biodiesel consumption. The biodiesel projections were subtracted from the diesel consumption projections. Ethanol consumption in Vermont is very low and was not forecasted.

Image Source: http://www.maps.com/map.aspx?pid=2045


VMT-Based Methods

Photo of a highway and heavy traffic. Overhead view of a multi-lane highway, bridges, and fly overs.

VMT influences transportation GHG emissions because the level of travel activity is a determinant of fuel consumption. While there are many sources of VMT data available, this section focuses on relatively simple methods of obtaining VMT information based on odometer data from vehicles, household travel surveys, and land use information. These VMT methods are generally intended for calculating passenger GHG emissions (not freight). They also are largely intended for developing inventories, although extrapolations of historical trends can be made to develop forecasts, recognizing a high degree of uncertainty in these results. A brief description of each of these methods is provided.


VMT

(miles)

x

Emission Factors

(grams / mile)

= GHG Emissions

This section discusses VMT-based inventory and forecasting approaches. All of these approaches involve two main components:

  1. Developing VMT estimates - tend to rely upon travel and land use forecasting tools. The Handbook Section 5.1 describes relatively simple options relying on vehicle, household, and land use data where a network-based travel forecasting model is not available. These methods may be most applicable for areas seeking to develop a GHG inventory in a relatively quick manner. The Handbook Section 5.2 describes expanded options based on HPMS data and the use of a network-based travel forecasting model, which tend to be more robust and allow for more sophisticated analyses of speeds and other factors.
  2. Estimating emissions - can range from applying a simple emissions factor (in grams per mile) to the VMT estimate, or may involve use of sophisticated emissions models in order to calculate emissions from travel.

VMT-based Methods: Estimating VMT

VMT

(miles)

x

Emission Factors

(grams / mile)

= GHG Emissions

The first step in developing an estimate of GHG emissions is to estimate VMT (can be historical, current year, or forecasts of future levels). Several approaches are discussed in the Handbook.


VMT-based Methods: Estimating VMT using Vehicle, Household, and Land Use Data

Simple Approaches

Simple approaches, which may be defined as "sketch planning" approaches, for estimating VMT are highlighted here. In general, it would be better to use calibrated and validated travel forecasting and emissions models. But, these simplified methods can be used when more sophisticated tools or the resources to apply those tools are not available.

  1. One way to determine VMT for inventories is to directly observe the number of miles driven through periodic odometer readings. In some areas, odometer data are collected as part of vehicle safety inspections, air pollution vehicle inspection and maintenance (I&M) programs , or as part of the vehicle registration process. One important value of these data are that they can typically match information on miles traveled with specific types of vehicles (e.g., make and model), which when combined with fuel economy information, can be used to calculate fuel consumption and GHG emissions.
  2. Household travel surveys represent another source of VMT data. The most commonly available types of household travel surveys are the NHTS, statewide household travel surveys, and MPO household travel surveys. For the most part, these travel surveys recruit a socioeconomically and geographically diverse range of volunteers to have their travel activities monitored. As part of the travel survey, respondents are asked to report information such as the age of their car(s), odometer readings, and to estimate their annual mileage driven. In addition, daily mileage driven is estimated for the survey days by either directly estimating mileage using a GPS device or by using self-reported mileage from the respondents. Post-processing the survey data may also be possible to estimate VMT if physical addresses or parcels associated with trip ends are recorded.
  3. Land Use Data Methods rely on land use data to estimate VMT typically use land use-based trip generation factors to estimate vehicle trips and then multiply the trips by average trip lengths to calculate VMT. These approaches are often used at a small scale, such as for a municipality or to report GHG emissions at a small geographic scale across a metropolitan region where accurate and complete land use data are available.

VMT-based Methods: Estimating VMT using HPMS Data or Network-based Travel Model

Traffic count and Travel Model data

HPMS - Another way of developing estimates and forecasts of GHG emissions relies on VMT from the Highway Performance Monitoring System or HPMS. The HPMS is a program administered by the FHWA, which requires that all State DOTs submit annual traffic count, highway inventory, revenue generation, and safety information as a condition of receiving Federal funding. Since it is impractical to count traffic or evaluate the pavement quality of every roadway segment in a state, models are used to translate a sample of data into the regional and statewide data required by FHWA. Related to GHG emissions estimation, the traffic count data are typically aggregated into VMT by roadway functional class at a variety of geographic levels.

Travel model data - Network-based travel forecasting models assign VMT to the roadway network. Network-based travel forecasting models are computer programs that are developed to estimate future travel patterns in a given area based on variables that influence both transportation supply and demand. Key structural and input variables for these models often include land use, socio-demographic characteristics, travel modes, transportation network, and travel costs. The models can be simpler or more complex, depending on the resources and needs of the region. In contrast to the HPMS data, network-based travel models are forward looking and generally produce a reasonably reliable forecast of future travel patterns. Therefore, these models can generally be relied on to forecast future GHG emissions (provided that they are well calibrated and validated, and provided that analysts can reliably predict future VMT by vehicle type and the GHG emissions characteristics of future vehicles).


VMT-based Methods: Estimating Emissions

VMT

(miles)

x

Emission Factors

(grams / mile)

= GHG Emissions

Emissions rates depend on vehicle type, technology/fuel type,speeds, and operating conditions

There are multiple ways to apply emissions factors

There are a range of ways in which GHG emissions can be developed relying on VMT inputs - ranging from very simple sketch planning approaches to use of more complex models (which corresponding greater data needs). The selection of approach will depend in part of the level of sophistication required, availability of data, and existing modeling that may already be conducted for air quality purposes.

It is important to note that transportation agencies may be able to collect emissions factors for use in GHG analysis by working with their state air quality or environmental agency. These factors could be developed based on national defaults or they could reflect location-specific fleet information, and may be developed using MOVES.

Simple CO2 emission factors obtained from published sources by can be multiplied with estimated VMT to produce an estimate of CO2 emissions. Such factors are typically not sensitive to aspects like vehicle speed and fleet mix. For instance, the U.S. EPA has a simple GHG emissions factor of 460.2 grams of CO2 equivalent per light duty vehicle mile traveled - http://www.epa.gov/cleanenergy/energy-resources/refs.html.

More complex methods will involve use of look up tables of emissions factors that account for additional factors, such as fleet characteristics and speeds.

Finally, EPA's MOVES model (or EMFAC in California) is an emissions model that can be used to directly calculate emissions factors or total emissions levels, when VMT data are used as inputs.


VMT-based Methods: Estimating Emissions (continued)

EPA'S MOVES

(Motor Vehicle Emission Simulator)

For resources on using MOVES, see:

http://www.epa.gov/otaq/stateresources/ghgtravel.htm

Guidance: Using MOVES for Estimating State and Local Inventories of On-Road Greenhouse Gas Emissions and Energy Consumption:

http://www.epa.gov/otaq/stateresources/ghgtravel.htm

The best tool available to produce estimates of on-road transportation GHG (and other) emissions is EPA's MOVES model. In California, the EMFAC model may be used. The MOVES model estimates energy consumption and emissions, including atmospheric CO2, CH4, N2O, and CO2e. MOVES can estimate emissions at the national, county (or custom, multi-county), or project scales and for annual or shorter periods of time.

The level of effort needed to use MOVES depends on the type of analysis and the existing capabilities of the organization. Using MOVES at the National scale (where the model relies mostly or entirely on national default input data) is relatively simple. Likewise, if an area is already using MOVES for transportation conformity analysis or for development of emissions inventories or forecasts for air quality planning purposes (i.e., state implementation plans), adding GHGs to the list of pollutants being modeled in the analysis involves almost no extra effort. On the other hand, if an area is starting from scratch with MOVES, and wishes to perform an analysis involving extensive use of local data, more effort will be required.

There are two calculation types in the MOVES model: to produce emissions inventories or emission rates.


VMT-Based Methods: Example DVRPC Regional Inventory (Philadelphia)

Map of Philadelphia area as described in the text.

Delaware Valley Regional Planning Commission (DVRPC) GHG Inventory

One approach to developing a GHG inventory and forecasts using a transportation demand model can be seen in the inventory developed by DVRPC. DVRPC developed a regional GHG emissions inventory that relies on travel demand model outputs to allocate GHG emissions to different traffic analysis zones.

HPMS data were used to determine VMT. Through traffic was estimated based on the travel demand model trip table that shows trips with origins and destinations outside the region. VMT from through traffic was subtracted from total VMT to focus the analysis on travel within the region. VMT was then apportioned to municipalities based on trip origins, destinations and trip length. Emissions were mapped per acre, per population and per employee.

The map above to the top shows emissions per acre, which indicates that GHG emissions are higher in Philadelphia's urban core. If emissions for trips are allocated 50 percent to the trip origin and 50 percent to the trip destination, the map on the bottom shows that emissions are higher on a per population and per worker basis in the suburban and exurban areas around Philadelphia. The DVRPC inventory helps make the case for the role of smart growth in reducing the GHG emissions intensity of development in the region. DVRPC's inventory is available at: http://www.dvrpc.org/EnergyClimate/inventory.htm


VMT-Based Methods: Example Atlanta Regional Commission GHG Forecasting

A graph showing the potential on-road CO2 emissions in Atlanta through 2030 given a variety of different scenarios. The given scenarios are future local plans (trend), which projects the highest number of on-road emissions at about 158 thousand tons per day. This is followed by Envision6, which predicts about 149 thousand tons; trend + EISA, which predicts about 110 thousand tons per day; Envision6 + EISA, which predicts about 101 thousand tons per day; density land use + EISA, which predicts about 95 thousand tons per day; TPB Concept 3 + transit focused land use + EISA, which predicts about 90 thousand tons per day; and C3 +TFLU + 2009 CAFE, which also projects about 90 thousand tons per day.

 

As part of PLAN 2040 the long range plan for the Atlanta region, ARC undertook a detailed examination of alternative growth and development options to help policy and decision makers better understand the impact of growth patterns on the region. Understanding differing growth scenarios help policymakers and the public understand the benefits and impacts of alternative futures. As part of PLAN 2040 development, eight different land use scenarios were examined to test their effect on land conservation, mode share, congestion mitigation and access to jobs. By looking at these scenarios, insight was gained on the potential impacts that different land use patterns could have on transportation system performance. ARC performed the scenario analysis using its 4-step travel demand model and MOBILE6 to model the emissions impacts of various land use scenarios describing different types of possible growth. Changes in land use and the transportation network were used as inputs in the travel demand model, which fed into the MOBILE6 calculations. The result allowed ARC to demonstrate the impact of a variety of strategies, including Federal fuel efficiency standards, land use policies encouraging density, as well as the current regional plan, as shown below. ARC has since conducted additional analyses using MOVES.

http://documents.atlantaregional.com/plan2040/docs/tp_PLAN2040RTP_072711.pdf


Other Approaches


Alternative GHG Estimation Approaches

Methods to address specific needs:

* http://onlinepubs.trb.org/onlinepubs/ncfrp/ncfrp_rpt_004.pdf,

To estimate emissions by commodity flow methods:

  1. Gather commodity flow data
  2. Calculate ton-miles by mode
  3. Estimate emissions factors and calculate emissions

To estimate emissions using EERPAT:

  1. Collect demographic data to generate synthetic households
  2. Collect input data to apply land use and transportation system characteristics
  3. Collect data on mitigation strategy assumptions, vehicle fleets, costs, and other inputs
  4. Calculate fuel consumption and estimate GHG emissions

For example: Oregon GHG Scenario Analysis. The GreenSTEP model in Oregon tested 144 scenarios in the first round of modeling for their Statewide Transportation Strategy for reducing GHGs.


Specific Strategy Analysis Methods

Fuel-based and VMT-based methods typically are used to assess baseline GHG emissions estimates, but in many cases, additional off-model analyses may need to be conducted to assess specific strategies. These "off model" analyses typically use simple spreadsheet calculations or sketch planning tools to estimate benefits of strategies not accounted for in other forecasting tools.

The Handbook contains detailed information on analyzing TDM strategies, land use strategies, transportation system management and eco-driving strategies and freight-related strategies.

TDM:

Land Use:

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. 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 elasticities, or relationships between factors such as population density, land use mix, and urban design.

For example, the Blueprint Sacramento regional vision planning process used I-PLACE3s, a public domain software package designed to integrate community participation, urban planning and design, and quantitative analysis.

TSM/Ecodriving:

Freight strategies


Additional Considerations in GHG Analysis

Cartoon drawing of a paving machine.

In addition to emissions coming directly from motor vehicles, GHG analysis can account for emissions from other sources.

Lifecycle analysis (LCA) examines and considers emissions from upstream activities in addition to those directly from the vehicle tailpipe. 2 methods described in the Handbook:

LCA for alternative fuel vehicles (using the GREET model)

LCA for electric transit services

In addition, construction of infrastructure consumes significant amounts of energy, mostly in the production of materials needed in the construction process. Once new infrastructure is in place, additional energy must be expended over time to maintain it. Some areas have conducted analyses for construction and maintenance energy consumption and emissions. NYSDOT developed a tool called MOVES-RREGGAE that combines construction and maintenance emissions information with operational emissions rates from MOVES; FHWA is currently conducting work to develop up-to-date emissions information and a spreadsheet tool to facilitate estimating these emissions at the planning level.


Summary


Key Points

In summary:


Contact Information

Jody McCullough
Federal Highway Administration
Office of Planning
1200 New Jersey Avenue SE
Washington, DC 20590
Jody.McCullough@dot.gov
202-366-5001

Take Questions from the webinar participants.

Updated: 07/10/2013
HEP Home Planning Environment Real Estate
Federal Highway Administration | 1200 New Jersey Avenue, SE | Washington, DC 20590 | 202-366-4000