National Academies Press: OpenBook

Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process (2012)

Chapter: Chapter 4 - Technical Framework for GHG Emissions Analysis

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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
×
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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Suggested Citation:"Chapter 4 - Technical Framework for GHG Emissions Analysis." National Academies of Sciences, Engineering, and Medicine. 2012. Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process. Washington, DC: The National Academies Press. doi: 10.17226/22805.
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35 estimated reduction in CO2 emissions for different types of strategies. It seems likely that transportation professionals will be called on to assess carbon footprints more often in the coming years, and thus this report provides an overview of the tools that are available. Background Much research has occurred on transportation and non- transportation GHG emissions. Walsh et al. (2008) compared emissions of cars, SUVs, peak and off-peak public transit, and bicyclists. Dürrenberger and Hartmann (2002) created a model, based on factors in Switzerland, for calculating regional CO2 emissions based on households, transportation systems, and economic activity. Chu and Meyer (2009) ana- lyzed CO2 emissions of truck-only toll lanes using EPA’s MOBILE6.2 modeling software. Stepp et al. (2009) used sys- tem dynamics functions to model transportation demand impacts on GHG mitigation. Smith et al. (2007) described the agricultural strategies of several countries, and Golub et al. (2009) noted that land use–based GHG mitigation policies must consider global and regional impacts. A variety of methods have been used to develop a GHG emissions inventory for transportation, but most are of limited use for metropolitan planning organization (MPO) planning and strategy analysis. Most inventories are devel- oped based on fuel type and fuel sales data by state or country, many following the Intergovernmental Panel on Climate Change guidelines for a national inventory (IPCC 2012). The main drawback with this methodology is its lack of distinc- tion between different modes, vehicle types, and geographic areas, a breakdown that is required for strategy analysis. Other methods use local inspection and maintenance data to develop registration and mileage accumulation or use vehicle miles traveled (VMT) data, usually compiled for transportation network planning (U.S. Environmental Pro- tection Agency 2010a). Glaeser and Kahn (2008) used the This chapter describes an analysis framework for considering GHG emissions in transportation planning and project development. The framework assists in answering important questions for key decision points in the planning and decision- making processes. In particular, the information focuses on four levels of decision making identified in the TCAPP framework: • Long-range transportation planning (LRP), including statewide, metropolitan, and other regional planning; pro- gramming (PRO), including statewide and metropolitan transportation improvement programs (TIPs); • Corridor planning (COR); and • Environmental review and National Environmental Policy Act (NEPA) compliance (ENV) and project permitting (PER). The framework, discussed in greater detail in the Practitio- ners Guide, provides checklists, strategy options, options for analytic methods, and a basic overview of calculation meth- ods and data sources for each method. A range of tools and methods applicable for different scales and resource inputs is provided. Although the planning process is relevant for different scales of analysis, the level of detail and tools and methods that are appropriate for GHG analysis and strategy development may differ widely from situation to situation. The framework and resource materials presented here are intended to be useful for planning at all scales of analysis and in all geographic contexts. They are also designed to be multi- modal, including analysis methods for transit as well as high- way travel. This chapter also discusses emissions calculators. Although emissions calculators do not fit into the four decision-making contexts listed above, they are discussed here because of their increasing use in estimating the carbon footprint of facilities and services. Such estimators are used, in particular, by tran- sit agencies to determine a GHG emissions baseline and an c h a p t e r 4 Technical Framework for GHG Emissions Analysis

36 National Household Travel Survey, “which contains informa- tion on gasoline usage associated with travel by private auto- mobile, family characteristics, and zip code characteristics.” Although their study distinguishes road and rail traffic, and focuses at the regional level, it only includes two modes and does not distinguish fuel types. Like most other methods, freight is not addressed separately in their study. Most studies only measure direct or tailpipe emissions asso- ciated with traffic movements. However, many recent life- cycle analysis (LCA) studies of alternative vehicle and fuel technologies indicate that the indirect emissions that result from supplying the vehicles, fuels, and built infrastructures are of a similar order of magnitude as the direct emissions and should be incorporated into studies on carbon footprints (DeLucchi 2003; U.S. Department of Energy 2012; U.S. Envi- ronmental Protection Agency 2010a; Chester and Horvath 2008; The Climate Registry 2008; Natural Resources Canada 2012). These indirect multipliers are found to vary a good deal across modes of travel, and they affect metropolitan areas dif- ferently, depending on the mix of auto and truck VMT. GhG analysis Framework The analysis framework for conducting GHG emissions anal- ysis is organized around 13 key questions grouped into five basic steps of analysis as shown in Table 4.1. These analysis steps and key questions are, for the most part, common across all four decision-making contexts of the TCAPP framework; that is, they can be used for long-range planning, programming, corridor planning and environmen- tal review and permitting. However, they might be addressed at different decision points in each context and could require different analysis methods. The 13-question process is pre- sented as an idealized process. Iterations among the various questions might be necessary, and local agencies may consider issues in a different sequence than presented here. Readers are referred to the Practitioners Guide for more detailed informa- tion on how these questions relate specifically to TCAPP. Determine Information Needs 1. What stakeholders should be included in GHG strategy development and evaluation? Objective: Identify key stakeholders who should be included in the development and analysis of GHG mitigation strategies. Discussion: Stakeholder involvement is an integral part of collaborative planning and decision making. This initial step in GHG planning ensures that key stakeholders with a specific interest in GHG emissions and climate change issues are included in the process. Table 4.2 provides a checklist of the key types of stakeholders that should be considered as part of GHG analysis. The TCAPP website provides guidance and techniques for creating meaningful stakeholder collaboration. 2. What is the scope of GHG emissions analysis? Objective: Define the scope of GHG emissions consid- ered as part of the long-range planning, programming, Table 4.1. GHG Analysis Framework Analysis Step Key Questions Step Question I. Determine information needs 1. What stakeholders should be included in GHG strategy development and evaluation? 2. What is the scope of GHG emissions analysis? II. Define goals, measures, and resources 3. What goals, objectives, and policies relate to GHG reduction? 4. What GHG-related evaluation criteria and metrics will be used? 5. What are the baseline emissions for the region or study area? 6. What is the goal or target for GHG reduction? 7. How will GHG considerations affect funding availability and needs? III. Define range of strategies for consideration 8. What GHG reduction strategies should be considered? 9. Are strategies and alternatives consistent with a long-range plan and/or other relevant plans that meet GHG reduction objectives? IV. Evaluate GHG benefits and impacts of candidate strategies 10. What calculation methods and data sources will be used to evaluate the GHG impacts of projects and strategies? 11. What are the emissions and other impacts of a particular project, strategy, or design feature? V. Select strategies and document overall GHG benefits and impacts of alternatives 12. What GHG-reducing strategies should be part of the plan, program, or project? 13. What are the net emissions impacts for the overall plan, program, corridor, or project alternatives considered and the selected alternative?

37 corridor planning, or project development and environ- mental documentation. Discussion: This step involves determining (1) emissions sources, (2) transportation modes, (3) the time frame of analy- sis, and (4) the geographic boundaries of the analysis. Table 4.3 provides a checklist and explanation of each topic. The scoping of GHG emissions may depend on issues that are considered in subsequent steps, such as any relevant policies or goals related to GHG emission reductions. For additional resources, see ICF Consulting (2006) for a discussion of target metrics, emissions sources covered, and measurement benchmarks. Define Goals and Measures 3. What goals, objectives, and policies relate to GHG reduction? Objective: Identify relevant policies related to GHG reduc- tion, as well as goals and objectives for the plan or project that may inform what types of GHG targets should be set, metrics evaluated, analysis methods used, and strategies considered. Discussion: Goals, objectives, and policies can come from many sources. They may originate from external policies and goals (e.g., federal or state); policies, goals, and objectives established by a higher-level planning document, such as an LRP; and goals and objectives established by stakeholders for a particular transportation plan, corridor study, or project. Participants should be aware of any existing policies that relate to GHG emissions, such as federal requirements or guidance for addressing GHGs in transportation planning, state reduction targets, long-range planning goals, or agency- wide policies to take actions that reduce GHG emissions. Stakeholders in plan or project development may set specific goals and objectives consistent with these policies, or in the absence of such policies may still decide that reducing GHG emissions is a goal of the plan or project. GHG-related poli- cies, goals, and objectives, as well as the importance placed on GHG reduction, may affect the scope of GHG emissions to be considered (as defined in Step 2). For the project development and environmental permitting step, in particular, an important question is whether GHG reductions are part of the purpose and need for the project. If they are, it may be especially important to demonstrate quan- titatively that the project reduces GHG emissions and to include additional GHG reduction and mitigation strategies as appropriate. If GHG reductions are not part of the purpose and need statement, GHG may still be an important consider- ation, but this should be determined in consultation with project stakeholders. 4. What GHG-related evaluation criteria and measures will be used? Objective: Define the GHG-related evaluation criteria and metrics to be used to measure the impact of the transporta- tion project or program under consideration. Discussion: This step involves determining what GHG- related measures will be reported, such as CO2, total GHGs, or another proxy or related measure such as VMT or energy con- sumption. It also involves determining other GHG-related criteria on which projects and strategies will be evaluated, such as cost-effectiveness and feasibility. Table 4.4 provides a list of potential emissions metrics. The evaluation criteria and metrics selected should be consistent with any higher-level planning documents, such as the LRP. CO2 represents about 95% of all mobile-source GHG emis- sions. A complete accounting of GHGs will also include meth- ane (CH4), nitrous oxide (N2O), and refrigerants, which can collectively be measured in CO2 equivalents (CO2e) based on the global warming potential of each. The GHG contribution of these other gases is usually small and may not be worth the additional effort of estimating them with precision. CH4 and Table 4.2. Key Stakeholders in GHG Planning and Analysis ____ State DOT ____ Policy and executive ____ Planning ____ Environmental ____ Project development ____ Traffic operations ____ Metropolitan planning organization (MPO)/Regional planning agency (RPA) ____ Transit agencies—policy, capital planning, and operations ____ Counties and municipalities ____ Port authorities ____ Federal resource agency ____ Other state agencies ____ Environmental—policy, air quality, permitting ____ Energy ____ Planning ____ Housing, economic, and community development ____ Industry ____ Freight and logistics ____ Utilities ____ Construction ____ Advocacy groups ____ Philanthropic organizations ____ Academic and research ____ General public

38 (i.e., CO2e). Finally, black carbon is a potential GHG, but existing science and analytic methods are insufficient to sup- port quantifying it in a GHG inventory. VMT may be an adequate proxy for GHG emissions if only strategies affecting VMT are analyzed. It will not be an appro- priate metric for strategies that affect traffic flow conditions or vehicle and fuel technology, and its usefulness will be lim- ited for strategies that include mode shifting to transit or rail (which may increase VMT for some vehicle types while decreasing it for others with different efficiency). The transportation agency may also decide to focus on energy Table 4.3. Scope of GHG Emissions Considered Scope Consideration Discussion Emissions Source Direct emissions from vehicles (tailpipe emissions) Direct calculation; should be included in all cases. Full fuel-cycle emissions Includes emissions from production and transport of fuel (including electricity generation). Important if strategies using alternative fuels (e.g., biofuels, electricity, hydrogen) are to be examined. Construction, maintenance, and operations May be important for capital-intensive strategies such as new construction, but existing data are limited. Induced travel Includes emissions from increased travel over time in response to improved travel conditions. May be important for strategies providing significant time and/or cost savings (particularly to highway travelers) or impacts on land use patterns. Modes Private vehicles Passenger cars, passenger trucks, and motorcycles. Typically included in all analyses. Commercial vehicles Light commercial trucks, single-unit trucks, combination trucks, and intercity buses. Typi- cally included in most analyses, but may be omitted if looking only at strategies affecting passenger travel. Transit: Buses Important to include if strategies that affect the level or efficiency of transit service are to be evaluated. Transit: Rail Light rail, streetcar, heavy rail, and commuter rail. Intercity passenger rail For statewide and interregional analysis. Air For statewide and interregional analysis. Rail and marine freight May be included for comprehensive transportation sector analysis; important if strategies that involve mode shifting from truck to rail are to be analyzed. Other School buses, refuse trucks, government fleets. May be included as part of highway vehicle travel inventories (private and commercial vehicles). Time Frame Base year: ____ Horizon/analysis year(s): _____ _______ Cumulative for period: ______ to ______ GHG reductions from a strategy or alternative may be compared against GHG emissions in the base year and/or baseline GHG emissions in the horizon/analysis year. Cumulative GHG emission reductions may also be of interest. Geographic Boundaries State MPO planning area Corridor (boundaries defined in corridor study or __________________) Roadway segment (endpoints: ______________and____________________) Other: _________________________ Usually, the geographic analysis area for a state or metropolitan long-range plan or TIP will be the respective state or MPO planning area. A corridor study may address only a single trans- portation facility that is the focus of the study, or it may be defined to include a broader area of influence as set forth in the study scope. N2O can be calculated from emission factor models such as U.S. EPA’s motor vehicle emissions model MOVES (Motor Vehicle Emission Simulator) and the California Air Resources Board’s EMFAC (Emission Factors), but refrigerants cannot. However, it may be important to include them when strate- gies that might affect these particular GHGs are evaluated. Examples include natural gas vehicles (which have high methane emissions) and programs to recapture refriger- ants. In other cases, it may be reasonable to simply factor CO2 emissions by a ratio of total GHGs to CO2 emissions by vehi- cle type to gain a complete accounting of GHG emissions

39 Table 4.4. Possible GHG Emissions Metrics Carbon dioxide (CO2) Carbon dioxide equivalents (CO2e), including ___Methane (CH4) and nitrous oxide (N2O) ___Refrigerants VMT (as proxy) consumption (often measured in British thermal units [Btu]) as a supplement or alternative to GHG emissions. The rela- tionship between energy consumption and GHG emissions depends on the fuel type. However, if alternative fuel strate- gies are not being evaluated, GHG emissions will closely track energy consumption. Energy consumption may be of interest for other reasons (e.g., energy security and energy indepen- dence) aside from the environmental motivations associated with climate change. Cost-effectiveness is typically measured in dollars spent per metric ton of GHG emissions reduced (see Chapter 3). The cost-effectiveness calculation could be based only on the direct costs of implementing a project or strategy, or it may include other monetary and nonmonetary costs and benefits such as vehicle operating cost savings, travel time savings, crash cost savings, or the value of air pollution versus health benefits. Costs can be distinguished according to costs to the public sector versus net costs or benefits to society as a whole. A negative cost per ton indicates that the strategy results in net social benefits. Other common evaluation criteria include • Feasibility: Including political, institutional, financial, and/ or technical feasibility; • Equity: The extent to which different population groups are positively or negatively affected; • Certainty: The level of confidence that the projected GHG reductions can actually be achieved; • Leakage: Whether the projected GHG reductions might result in GHG increases outside of the planning area; and • Synergistic effects: Whether the project or strategy is likely to lead to other outcomes or support other actions that will further reduce GHG emissions. For additional resources, see ICF Consulting (2006) for a discussion of target metrics, emissions sources covered, and measurement benchmarks. 5. What are the baseline emissions for the region or study area? Objective: Establish a baseline (no-action) GHG emissions inventory using the selected GHG-related metric(s) and scope of emissions for both the base year and any analysis year(s). The baseline inventory should account for any adopted state, multistate, or federal regulation such as vehicle fuel effi- ciency standards, GHG emissions standards, and low-carbon or renewable fuel standards. Discussion: The baseline inventory is normally developed considering all relevant transportation activity occurring within the study area (e.g., MPO model area or a defined cor- ridor), as well as the adopted baseline land use and socio- economic forecasts. Different methods can be used to develop a baseline inventory. The method should be selected based on data availability, level of effort, and accuracy or precision of information needed. In addition, the method for developing the baseline inventory is likely to serve as a starting point for analyzing the GHG impacts of proposed alternatives. If quantitative reduction targets or metrics related to a per- centage reduction in emissions are not set, it may not be nec- essary to develop a baseline inventory. Instead it may only be necessary to evaluate, either quantitatively or qualitatively, the expected change in GHG emissions as a result of a particu- lar project or strategy. Methods A and B for estimating baseline GHG emissions are oriented primarily toward a systems- or network-level analysis; Methods C and D are more suited to corridor- or project-level analysis (see Table 4.5): • Method A: VMT trend extrapolation with VMT-based emission factors; • Method B: Travel demand and emissions factor models; • Method C: Traffic counts, forecasts, and transit operating data with emission factors; and • Method D: Traffic simulation models. If this method pro- duces fuel consumption estimates, CO2 emission factors can be applied directly as shown in Table 4.6. 6. What is the goal or target for GHG reduction? Objective: Define a quantitative target or qualitative goal for GHG reductions compared with the baseline inventory or fore- cast. Goals or targets may be externally determined (e.g., with state or federal guidance) or may be established for the project or plan through a stakeholder and public involvement process. Discussion: Quantitative targets may be expressed in abso- lute terms (metric tons CO2 or CO2e), percentage terms, or as a not-to-exceed threshold. They may be expressed compared with a base year, historic year (e.g., 1990), or baseline forecast in the analysis year. A target may be set specifically for trans- portation emissions to be affected by the plan or process (e.g., reduce net corridor emissions by 10% from baseline through project strategies), or the planning activity or project may be measured for its ability to contribute to a broader cross- sectoral target (e.g., support the state’s effort to reduce GHG emissions by 20% in 2050 from 1990 levels). Some options for expressing goals or targets are shown in Table 4.7.

40 Table 4.5. Methods for Estimating Baseline GHG Emissions Method Comments Method A: VMT trend extrapolation with VMT-based emission factors Description: The simplest approach available for transportation GHG inventory development at a substate level. It relies on externally generated data to develop a regional estimate of GHG emissions. Situations in which to apply: •  Travel model is not available, does not cover all modes, or forecasts for analysis year(s) not yet  developed. •  Detailed and precise inventory not needed. Calculation methods: •  Highway (passenger and commercial vehicles) – Obtain historic VMT data by vehicle type for the past 10 or more years for the analysis area from the Highway Performance Monitoring System (HPMS). – Extrapolate to future years using trend projection or a projection already developed by a state or regional agency. – Apply GHG emission factors (g/mi) appropriate for base and horizon years (see Practitioners Guide). •  Transit – Obtain National Transit Database (NTD) service and fuel consumption data for the past 5 to 10 years, apply GHG emission factors, and extrapolate to future. Consult with local transit agen- cies to project service levels for future years under existing service plans (e.g., continue same service levels, grow in proportion to population) and characteristics of transit fleet (fuel type and efficiency). Emissions from buses running on public roads should be subtracted from the high- way inventory to avoid double-counting, since buses will be included in vehicle counts. Data sources: •  HPMS: historic VMT data. •  The Climate Registry’s General Reporting Protocol (GRP): Emission rates (g/gal for CO2, g/mi for CH4 and N2O). •  National Transit Database (NTD): Historic transit VMT and fuel consumption by transit mode. •  EPA Emissions and Generation Resource Integrated Database (eGRID): Historic GHG emissions  rates for electricity (g/mW-h). •  U.S. Department of Energy’s Annual Energy Outlook: Projections of fuel efficiency by mode and regional emissions rate (for electricity consumption) through 2030. Method B: Travel demand and emissions factor models Description: This approach uses the regional or statewide travel demand model and HPMS data to develop fore- casts of VMT by road type, vehicle type, and speed to which emission factors from EPA’s MOVES  model or another emission factor model (such as EMFAC) are applied. Situations in which to apply: •  Long-range planning and programming: Recommended when a travel model is available and a no- build scenario has been developed. The no-build scenario refers to a future scenario that does not include projects proposed in the long-range plan. In some areas, this may be referred to as the existing plus committed (E+C) scenario. E+C forecasts represent conditions if no further transpor- tation improvements were implemented beyond what is already funded to complete construction within the last year of the TIP. •  Corridor planning: Recommended when a travel model has sufficient network detail to represent  traffic conditions in the study corridor. Calculation methods: •  Run the regional travel demand model for the no-build scenario; output link-level volumes and  speeds by MOVES road type. •  Run MOVES to obtain a lookup table of CO2 emission factors by vehicle type, facility type, and speed. •  Adjust emission factors for any differences in future year vehicle efficiency and/or carbon content  standards not reflected in MOVES. •  Apply adjusted MOVES emission factors to travel demand model output. •  Calculate base and horizon year(s) transit VMT by mode based on performance statistics (route  miles and headways) from the travel demand model or operating data and projections from local transit agencies. •  Apply transit emission factors. Data sources: •  HPMS and travel demand model outputs (VMT by speed and vehicle type). •  MOVES emission factors (g/mi). •  VMT percentage distribution by vehicle type could come from HPMS, roadside vehicle counts,  inspection and maintenance program odometer data, or MOVES national defaults. •  Other data (transit, emissions). (continued on next page)

41 Method C: Traffic counts, forecasts, and transit operating data with emission factors Description: Traffic counts for the base year are projected to future years using growth factors, and VMT- or speed-based emission factors are applied. Situations in which to apply: •  When this method is already being used to determine base year and design year no-build traffic  forecasts with associated traffic capacity analyses for documenting project need. •  When the analysis is focused on improving GHG emissions from a subset of a roadway network as  opposed to a regional network change. •  When an adopted regional forecasting model is not available, but it is expected that area popula- tion and employment growth will not follow growth trends of the previous 10 years. Calculation methods: •  Identify affected road network links, including all those whose traffic is expected to be affected by  the project. •  Conduct traffic counts to determining existing volumes and peaking characteristics on links. •  Determine existing land use served by links. •  Determine trip generation by land use. •  Identify existing through trips. •  Identify percentage of various vehicle types in existing traffic. •  Determine future land use in the design year. •  Grow traffic volumes to the design year based on additional land use, while assuming trip genera- tion and peaking characteristics similar to the base year. •  Determine (based on peaking characteristics and road capacity) the number of congested and  uncongested hours or periods per year. •  Estimate link speeds during congested periods. There could be more than one congested speed  given that different hours will have different levels of congestion. The link speed limit can be assumed for uncongested periods. •  Determine VMT traveled by speed (base year and no-build design year) within the GHG study area. •  Apply MOVES or EMFAC emission factors to determine GHG emissions for the base year and  design year. Data sources: •  Available counts, forecasts, and vehicle mix from past studies or ongoing traffic monitoring programs. •  New project area traffic counts, forecasts, and vehicle mix done specifically for the project. •  Land use growth forecasts from land use plans, recently approved traffic impact assessments,  and/or interviews with local planners. •  Road link characteristics. •  MOVES or EMFAC model. Method D: Traffic simulation model Description: A traffic simulation model is used in conjunction with operations-based emission factors to model current and forecast operating conditions and GHG emissions. Situations in which to apply: Traffic simulation models offer an opportunity to add additional variables in both traffic capacity analysis and GHG analysis. Simulations can account for the effect on GHG emissions of intersection and inter- change operations, including queuing in highly congested situations, as well as design characteristics such as sharp curves and steep grades. Simulations might be used in GHG analysis when •  Simulation modeling is already being done as a part of traffic capacity analysis. •  It is important to the selection of a preferred alternative to capture additional subtleties in traffic- related GHG emissions. •  It is important to capture the effect of project design and operations on the emissions of a variety  of different motor vehicle types; e.g., bus fleets using buses with different fuel types. •  The GHG study area is targeted enough to make it reasonable to create and run a simulation model. Simulations are typically used for analysis in areas with heavy peaking, congestion, queuing, or stop-and-go operations. Also, simulations are generally done to analyze peak travel periods and often focus on a portion of a road network. Therefore, simulation model results should be used with results from the traffic counts method above to capture all GHG emissions across the links potentially affected by a proposed project. Table 4.5. Methods for Estimating Baseline GHG Emissions (continued) Method Comments (continued on next page)

42 Table 4.6. CO2 Emission Factors by Fuel Type Fuel CO2 Emission Factor (kg/gal) Gasoline 8.81 Diesel 10.15 E10 (gasoline with 10% ethanol) 7.98 Table 4.7. Target Reduction Targets Percent reduction: ___% from year _____ levels by year _____ Absolute reduction: ___ metric tons CO2e versus baseline case or current year in year ____ Threshold value: no greater than ____ metric tons CO2e in year _____ Not all projects or plans will have quantitative targets. In some cases, projects or strategies may be evaluated simply for their ability to contribute to GHG reductions (expected direction of impact). In such cases, a qualitative goal may be established, such as “ensure that the project does not increase GHG emissions compared with the baseline” or “ensure that the project contributes to GHG reductions.” Quantitative tar- gets are most likely to be applied at the system level (statewide or regional LRP or improvement program), and less likely to be applied at a corridor or project level. However, the selec- tion and scoping of corridor and project studies should be consistent with regional and statewide long-range plans that have been developed to meet any applicable GHG reduction goals or targets. 7. How will GHG consideration affect funding availability and needs? Objective: Determine how considering GHG issues in the transportation process may affect revenue sources, as well as revenue needs for planning and implementation. Discussion: This question is most likely to be relevant at the long-range plan and programming levels, although it may also affect corridor- and project-level decisions. GHG considerations may affect transportation plan and program finance in at least three ways: • Revenue sources (such as federal or state funds) may be available that are specifically dedicated toward GHG reduction or that require GHG reductions as a condition for funding. As of the fall of 2010 there were no federal aid highway programs specifically directed at GHG reduction, although there has been discussion of incorporating GHG criteria into the Congestion Mitigation and Air Quality Improvement Program or establishing a similar dedicated program for air quality and/or GHG improvements. The Federal Transit Administration’s Transit Investments for Greenhouse Gas and Energy Reduction program explicitly funded GHG reduction projects; • Some GHG reduction strategies, such as tolling and pric- ing strategies, may generate additional transportation rev- enues that are then made available for implementation of GHG reduction strategies and/or other transportation purposes; and • The evaluation of GHG strategies within the planning and project development process may require additional fund- ing to provide personnel resources to develop inventories, Calculation methods: •  Standard traffic simulation models can be used. •  Outputs from simulation models useful to GHG emissions include VMT by vehicle type and by speed, the number of hours spent idling, and fuel consumption (if available). Existing traffic simu- lation models do not provide outputs of GHG emissions, so these need to be postprocessed. •  If the traffic simulation model produces fuel consumption estimates, CO2 emission factors can be applied directly (see Table 4.6). •  If the traffic simulation model does not produce fuel consumption estimates, either average speeds should be calculated by link and used in conjunction with speed-based emission factors from MOVES or EMFAC or, preferably, the detailed traffic model output should be postprocessed for use with the MOVES model. (See Practitioners Guide.) Data sources: •  Traffic forecasts derived as noted in previous method and intersection and/or interchange turning movement studies. •  Design characteristics taken from conceptual or preliminary designs, including lanes, grades, curves, and so forth. Table 4.5. Methods for Estimating Baseline GHG Emissions (continued) Method Comments

43 conduct planning for GHG strategies, and analyze emis- sions reductions. It is also possible that the desire to fund GHG-reducing projects may be a significant factor influ- encing decisions about overall transportation revenue streams. Define Range of Strategies for Consideration 8. What GHG reduction strategies should be considered? Objective: Identify GHG-reducing projects or strategies that should be evaluated for inclusion in the LRP, TIP, corri- dor plan, or project design. Discussion: The process for screening potential GHG reduction strategies typically involves four basic steps: • Identify projects or strategies already considered for other purposes, such as air quality improvement or congestion relief, that may have GHG benefits; • Develop a list of other potential strategies; • Assess the general magnitude of effectiveness, cost- effectiveness, cobenefits and impacts, political feasibility, jurisdictional authority, and funding constraints for each strategy; and • Select strategies for further consideration based on these factors. At the screening stage, existing studies on strategy effective- ness are generally used to identify the general level of GHG benefit, cost, cost-effectiveness, and cobenefits associated with each strategy. More detailed evaluation is often conducted at later stages to refine these estimates for local conditions. The screening stage could also consider what planned or proposed projects may increase GHG emissions and whether these should be evaluated further for their GHG impacts. Table 4.8 provides a list of potential GHG reduction projects and strategies and identifies the level(s) of TCAPP application for which each is most suited. It is likely that transportation agencies are already undertaking a number of these strategies. Table 4.8. Potential GHG Reduction Projects and Strategies Potential GHG Reduction Projects and Strategies Likely Levels of Application LRP PRO COR ENV Transportation System Planning and Design Bottleneck relief X X X X High-occupancy vehicle/high-occupancy toll (HOV/HOT) lanes X X X X Toll lanes or roads X X X X Truck-only toll lanes X X X X Fixed-guideway transit expansion X X X X Intercity rail and high-speed rail X X X X Bicycle facilities and accommodation X X X X Pedestrian facilities and accommodation X X X X Rail system improvements X X X X Marine system improvements X X X Intermodal facility and access improvements X X X X Transportation System Management and Operations Traffic signal timing and synchronization X X X X Incident management X X X X Traveler information systems X X X X Advanced traffic management systems X X X X Access management X X X Congestion pricing X X X X Speed management (limits, enforcement) X X X (continued on next page)

44 Truck and bus idle reduction X X X Transit fare measures (discounts and incentives) X X Transit frequency, Level of Service, and coverage X X Transit priority measures (signal preemption, queue bypass lanes, shoulder running) X X X X Land Use and Smart Growth Integrated transportation and land use planning X X Funding incentives and technical assistance to local governments for code revision, planning, and design practices X X Parking management and pricing X X X Designated growth areas, growth boundaries, and urban service boundaries X Transit-oriented development, infill, and other location-targeting incentives X X X Freight villages and consolidation facilities X X Travel Demand Management and Public Education Employer-based commute programs X X Ridesharing and vanpooling programs X X Telework and compressed work week X X Nonwork transportation demand management programs (e.g., school pool, social marketing, individualized marketing) X X Eco-driving X Vehicle and Fuel Policies Alternative fuel and/or high-efficiency transit vehicle purchase X X X X Alternative fuel and electric vehicle infrastructure X X Government fleet purchases X Construction, Maintenance, and Operations Practices Low-energy and/or GHG pavement and materials X X Construction and maintenance equipment and operations X X Alternative energy sources or carbon offsets X X X Right-of-way management (e.g., vegetation) X X Building and equipment energy efficiency improvements X X Note: Inclusion of type of strategy or project in this table does not guarantee that it will reduce GHG emissions. The GHG impacts of any given strategy or project must be evaluated based on local conditions and data. Table 4.8. Potential GHG Reduction Projects and Strategies (continued) Potential GHG Reduction Projects and Strategies Likely Levels of Application LRP PRO COR ENV In such cases, they may want to assess whether the benefits of existing strategies have been adequately quantified, or whether more analysis should be done to quantify these benefits. 9. Are program, corridor, or project alternatives consistent with a long-range plan and/or other relevant plans that meet GHG reduction objectives? Objective: Determine whether projects considered for the TIP, corridor alternatives and strategies, or project alternatives and strategies are consistent with a higher-level plan (such as an LRP) that has been developed with GHG reduction goals in mind. Discussion: The LRP is intended to be an overarching transportation plan and policy document for a state or region. As such, projects listed in the TIP are expected to be consis- tent with the goals, objectives, policies, and major projects set forth in this plan. Corridor-planning processes and projects selected for more detailed development activities should also be consistent with the LRP. In addition, if a corridor plan has been developed for a transportation corridor, projects

45 evaluated within this corridor should be consistent with that plan. Ideally, the LRP or corridor plan will have been devel- oped considering land use, as well as transportation issues (e.g., as part of a regional or corridor vision for transportation and growth), since land use patterns can significantly affect transportation flows and thus GHG emissions at this level. If the state or region has not yet developed a plan that includes GHG reduction objectives, it may not be possible to screen projects or strategies according to this criterion. How- ever, consideration may still be given to whether a project would be expected to increase or decrease GHG emissions. Evaluate GHG Benefits or Impacts of Projects and Strategies 10. What calculation methods and data sources will be used to evaluate the GHG impacts of projects and strategies? Objective: Define what level of analysis is required to sup- port the decision-making process, and identify appropriate analysis tools and data. Discussion: Three general levels of analysis are defined in Table 4.9: (A) order of magnitude assessment, (B) sketch- level analysis, and (C) analysis using network or simulation models. Different amounts of effort may be appropriate for different strategies based on the importance of that strategy for GHG reductions, uncertainty with respect to its impacts, and availability of resources and data for assessment. This step may include consideration of how to evaluate projects or other strategies that are proposed specifically with the objective of reducing GHG emissions. It also may include consideration of how to evaluate the GHG impacts of projects or actions that are proposed for inclusion in the plan for other purposes such as mobility, safety, or air quality. Table 4.9 shows the different methods that can be considered for esti- mating the GHG impacts of projects and strategies. 11. What are the emissions impacts of specific projects and strategies? Objective: Apply appropriate analysis tools to analyze strategies and estimate GHG emissions impacts of individual projects or strategies proposed for inclusion in a long-range plan, TIP, corridor plan, or project design. Discussion: A variety of tools and methods are available for analyzing the GHG benefits of different transportation proj- ects, policies, strategies, or design features. These are briefly described below. Some of the available tools and methods do not directly calculate GHG emissions, but only calculate travel impacts. This listing is not a comprehensive assessment of these tools; examples of other tools not listed here may include transit ridership forecasting models, freight analysis tools, and land use scenario planning tools. With any of these approaches, travel impacts (changes in VMT and, optionally, speeds by mode) can be used as a basis for estimating GHG emissions if they are applied with emission factors developed from an emissions factor model or method. Tables 4.10 and 4.11 show how different analysis tools can be used. There is considerable research and development underway on GHG analysis methods, and this list may not include all currently available tools or reflect the most recent updates to models. In addition, individual agencies or consul- tants have developed their own tools or methods for propri- etary or internal use that could be applied or adapted in other settings. Select Strategies and Document Overall GHG Benefits and Impacts of Alternatives 12. What GHG-reducing strategies should be part of the plan or project? Objective: Determine which strategies should be part of the final plan or project. Discussion: The selection of final strategies will consider GHG impacts as part of a larger process of selecting projects or strategies considering the full range of evaluation criteria. Typically, some sort of multicriteria evaluation process will be used, such as a weighted scoring system (in which points are assigned to various evaluation factors) or a multicriteria matrix (in which impacts for each factor are arrayed in a table and evaluated qualitatively by decision makers). Projects or strategies that are specifically intended to support GHG reduction may be advanced at this time. This may include consideration of whether projects or actions that increase GHG emissions should be excluded. Information on the GHG benefits and cost-effectiveness of individual strategies, developed in previous steps, may be con- sidered as part of the overall process of developing a plan or project alternative. In addition, consideration should be given to potential interactive effects among strategies to develop plan or project alternatives that include logical groupings of strategies. For example, a regional plan that includes transit as a GHG reduction strategy may also logically include transit- supportive land use policies to enhance the benefits of transit. Roadway improvement projects to relieve congestion might logically include pricing to manage demand. 13. What are the net emissions impacts for the overall LRP, TIP, corridor, or project alternatives considered and the selected alternative? Objective: Estimate GHG emissions for draft LRP alterna- tives, TIP, corridor, or project alternatives compared with baseline emissions and GHG reduction goals. Discussion: This step is an assessment of the overall impacts of proposed and final alternative(s) considering the various GHG reduction or mitigation strategies that are

Table 4.9. Calculation Methods and Data Sources Level of Analysis Comments (A) Order of magnitude assessment Description: This approach uses existing data from other sources to provide information on the approximated magni- tude of benefits and cost-effectiveness that might be expected from different GHG reduction strategies. Situations in which to apply: •  Initial screening of strategies for more detailed analysis •  Limited time and resources available •  Locally specific estimates not needed Calculation methods: •  Review existing sources of effectiveness and cost-effectiveness data. •  Consider factors unique to metropolitan area that might affect effectiveness of specific strategies, such as – Size of region – Land use patterns – Congestion levels – Availability and competitiveness of transit and nonmotorized modes – Amount of freight traffic in region – Electricity generation sources (affects light and heavy rail transit benefits) – Political climate and effects on feasibility (including public acceptability). Data source: •  A summary of cost-effectiveness by strategy is provided in the Practitioners Guide Appendix. (B) Sketch-level analysis Description: This approach involves basic, off-model analysis (i.e., not using a travel demand or simulation model) of the GHG impacts of individual strategies, using a variety of methods as appropriate for each strategy. Situations in which to apply: •  Strategy screening and/or selection is desired using locally specific data •  Limited time and resources are available •  Order-of-magnitude estimates are desired, but precise, rigorous estimates are not required. Calculation methods: •  A variety of analysis tools and methods, each with different data requirements, may be needed for different  types of strategies. Examples of methods include elasticities, spreadsheet calculators, the COMMUTER or TRIMMS model, or other techniques such as the APTA methodology for transit GHG benefits. •  Refer to Table 4.11 for an overview of applicable tools by strategy. More details on analysis tools are  provided in the Practitioners Guide Appendix. Data sources: Because of their wide variation, sketch methods are not described in detail in this report, but examples are provided in other reports as referenced in the Practitioners Guide Appendix. (C) Network or simulation model analysis Description: This approach involves using a network model such as the regional travel demand model (in conjunction with other preprocessor, postprocessor, or off-model techniques) to analyze strategies at a systems level or a traffic simulation model to analyze strategies at a corridor or project level. Situations in which to apply: •  Strong regional importance is placed on GHG emission reductions and the selection of the most effec- tive and cost-effective strategies is desired. •  Robust calculations are needed to support meeting state and/or regional targets •  Sufficient data and analysis resources are available, including a travel demand model with adequate  capabilities. Calculation methods: •  Network models may be directly suitable for analyzing some strategies, such as major capacity improve- ments, transit investments, land use, pricing, and nonmotorized improvements; however, only the more sophisticated models may be suitable for some of these strategies. See Section 6 in the Practitioners Guide Appendix for further discussion. •  Additional analysis tools and methods may be used in conjunction with travel model data for strategies  that cannot be directly modeled. Examples include the use of a 4-D postprocessor to analyze microscale land use and nonmotorized changes, or the ITS deployment and analysis system (IDAS) model for ana- lyzing intelligent transportation systems (ITS) strategies. •  The use of traffic simulation models for strategy analysis is similar to their use for corridor- or project- level inventory development, as described in Step 5, Method D. Refer to Table 4.11 for an overview of methods by strategy. See Section 6 in the Practitioners Guide Appendix for more detail on these methods. Data sources: Network model and off-model techniques are not described in detail in the Practitioners Guide or its Appendix. 46

47 Table 4.10. Example Analysis Tools for GHG Analysis Category of Tool Description Examples Travel demand and related models Regional, statewide, or subarea models of the transportation network. Travel demand models (Cube, EMME/2, Trans- CAD, VISSUM) Integrated transportation-land use models (PECAS, TRANUS, UrbanSim) Intelligent Transportation Systems Deployment and Analysis System (IDAS) Traffic simulation models Detailed models to evaluate traffic conditions on specific facilities or for areawide networks. TSIS-CORSIM, VISSIM, Paramics, SimTraffic, TransModeler, SIDRA TRIP GHG inventory and policy analysis tools Tools specifically designed for creating GHG inventories and analyzing reduction strategies. CCAP Transportation Emissions Guidebook Clean Air and Climate Protection (CACP) Climate and Air Pollution Planning Assistant (CAPPA) Climate Leadership in Parks (CLIP) FHWA carbon calculator tool GreenDOT GreenSTEP State Inventory Tool (SIT) URBEMIS Other travel demand analysis tools Models and tools for assessing the impacts of strategies to reduce vehicle travel. COMMUTER model TRIMMS Land use scenario planning tools (INDEX, Smart Growth INDEX PLACE3S, CommunityViz, CorPlan, and others) Emissions factor and fuel economy models Models for developing emissions or energy use factors that can be applied to travel changes. GlobeWarm Motor Vehicle Emissions Simulator (MOVES) Emission Factor model (EMFAC) Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model VISION model Other off-model methods Application of elasticities, case examples, and other customized methods to analyze specific strategies. Elasticities Case examples Other tools proposed for inclusion. It may be conducted for multiple alternatives for the purpose of assisting with the selection of a preferred alternative, or as documentation that the selected alternative meets its reduction target. Various methodologies are available for calculating GHG emissions at the overall plan or project level, similar to the methodologies used to calculate a baseline for the study area (Question 5). However, it may also be necessary to apply adjust- ments to account for strategies that cannot be directly mod- eled using the baseline assessment tools. The methods discussed in Table 4.12 include • Travel demand and emissions factor models; • Travel demand model with enhancements and/or off- model strategy analysis; • Traffic forecasts and transit projections with emission fac- tors; and • Traffic simulation models. The Practitioners Guide is cited in Table 4.12, as well as in other tables. Very specific information is presented in this Guide on the analysis tools used for GHG emissions analysis and their requirements. For example, an entire section of the Guide is devoted to the use of the MOVES model. Readers interested in greater detail on analysis tools should refer to this document. carbon Footprint analysis and GhG emissions calculators One of the GHG analysis (and institutional) contexts that has received increasing attention in recent years has been the esti- mation of the carbon footprint of a system, service, or facility. These analyses differ from those presented earlier in this chapter. But as they are likely to be much more common in the future, information on the types of tools that are available for such analyses is presented here. Such analyses use an emissions

Table 4.11. Greenhouse Gas Strategy Evaluation Tools by Strategy Tool or Method G H G In ve nt o ry D ev el o p m en t H ig hw ay N et w o rk Im p ro ve m en ts U rb an T ra ns it E xp an si o n In te rc it y R ai l a nd B us N o nm o to ri ze d Im p ro ve m en ts R ai l & M ar in e Im p ro ve m en ts IT S /O p er at io ns & M an ag em en t S p ee d M an ag em en t Id le R ed uc ti o n Tr an si t S er vi ce Im p ro ve m en ts R o ad w ay P ri ci ng La nd U se & S m ar t G ro w th T D M & P ub lic E d uc at io n Ve hi cl e & F ue l P o lic ie s C o ns tr uc ti o n an d M ai nt en an ce P ra ct ic es Travel Demand and Related Models Travel demand models: Basica X X X Travel demand models: Enhancedb X X X Xc X X X X X Integrated transportation–land use models X X X Xc X X X ITS Deployment Analysis System (IDAS) X Traffic microsimulation models X X X GHG Inventory and Policy Analysis Tools Center for Clean Air Policy (CCAP) Guidebook X X X X X X X Clean Air and Climate Protection (CACP) X Climate and Air Pollution Planning Assistant (CAPPA) X X X X X X X X X Climate Leadership in National Parks (CLIP) X X X X X X X FHWA carbon calculator tool X TBD GreenDOT X X X X X GreenSTEP X X X X X X X X X X State inventory tool X URBEMIS X X X Other Travel Demand Analysis Tools COMMUTER model X X TRIMMS X X Land use scenario planning tools X X Emissions Factor and Fuel Economy Modelsd GlobeWarm X X X X X X X X MOVES X X X X X X X X X EMFAC X X X X X X X X X GREET X X VISION X X Other Off-Model Methods Elasticities X X X X X X Case examples Various Notes: a Basic regional travel demand models typically do not include transit or nonmotorized modes, auto ownership, freight, or time-of-day effects. b Enhanced regional travel demand models may include some or all of the following: transit networks and mode choice, nonmotorized conditions and mode choice, consideration of time-of-day shifting, a freight model, or feedback improvements to better capture network effects. c Intercity policy and project analysis requires a statewide model (with inclusion of transit for transit strategies). d Emissions factor and fuel economy models must be used in conjunction with transportation models to analyze strategies that affect travel activity. The strategies associ- ated with these models cannot be analyzed by the models listed here directly, but they can be analyzed with the travel activity models that provide inputs to these emis- sions factor models. In addition to these models, other data sources exist for emissions factors for different modes, including the Annual Energy Outlook, Transportation Energy Data Book, and EPA’s eGRID database. 48

49 Table 4.12. Calculation Methods and Data Sources for GHG Analysis Method Comments (A) Travel demand and emissions factor models Description: This approach uses only the regional or statewide travel demand model and an emissions factor model to assess the GHG emissions associated with the LRP, TIP, or corridor plan. Situations in which to apply: •  Network model used to develop baseline GHG projections for LRP. •  Off-model strategies not proposed for inclusion. •  Off-model strategies assessed, but do not need to be included in GHG inventory. Calculation methods: •  Run the travel demand model for the LRP, TIP, or corridor plan and output link-level volumes and speeds by MOVES road type (see Practitioners Guide). •  Run MOVES to compute emission factors and apply to travel demand model output to calcu- late total emissions. For details on interfacing the travel demand model with MOVES, see Practitioners Guide. •  If the travel demand model does not have a transit component, determine transit VMT by mode and/or vehicle type under each plan alternative and apply emission factors. Data sources: See Methods A and B in Table 4.5. (B) Travel demand model with enhancements and/or off-model strategy analysis Description: This approach applies additional modeling enhancements and/or off-model techniques to include the impacts of strategies not directly assessed in the regional model (e.g., transporta- tion demand management, nonmotorized investment, microscale land use design, traffic operations) in the quantitative inventory. Situations in which to apply: •  Total GHG needs to be compared with state or regional targets. •  There is a desire to include a full range of strategy impacts in the quantitative plan or TIP assessment. Calculation methods and data sources: •  Run the travel demand model with the MOVES emissions factor model, incorporating any model enhancements developed for specific strategy analysis (see Practitioners Guide). •  Apply adjustments for off-model strategies as described in Practitioners Guide. •  Compare total emissions for the plan or TIP to target reductions, if applicable. Data sources: See Methods A and B in Table 4.5 and Practitioners Guide. (C) Traffic forecasts and transit projections with emission factors Description: Forecast traffic volumes and transit vehicle frequencies, multiplied by road segment length within the study area, to which are applied VMT or speed-based emission factors. Situations in which to apply: •  See Method C in Table 4.5. The same methods and level of detail would be used for the assessment of alternatives as for establishing base year and design year no-build conditions. •  Traffic forecasts that account for induced development estimated as a part of an indirect impacts assessment may need to be developed. Calculation methods: •  See Method C in Table 4.5. The same methods and level of detail would be used for the assessment of alternatives as for establishing base year and design year no-build conditions. However, they would be applied to each year from the opening of the proposed project to the design year. VMT by speed information would be generated for the year of project opening and the design year. •  Interim year forecasts can be determined by straight-line projection unless information is available that indicates population and employment growth will occur at another rate. •  The results for each year are totaled to obtain GHG emissions for the no-build alternative and each detailed study alternative over the life of the project. •  No-build and build results are compared. Data sources: •  See Method C in Table 4.5. •  Growth rates from local land use plans. (continued on next page)

50 Table 4.12. Calculation Methods and Data Sources for GHG Analysis Method Comments (D) Traffic simulation models Description: A traffic simulation model is used in conjunction with operations-based emission factors to model current and forecasted operating conditions and GHG emissions. Situations in which to apply: •  See Method D in Table 4.5. The same methods and level of detail would be used for the assessment of alternatives as for establishing base year and design year no-build conditions. •  Traffic forecasts that account for induced development estimated as a part of an indirect impacts assessment may need to be developed. Calculation methods: See Method D in Table 4.5. Data sources: See Method D in Table 4.5. (continued) calculator, a methodology that identifies the many sources of carbon emissions that can be associated with the develop- ment, construction, operation, and recycling of a system’s components. This section reviews some of the major analysis tools for conducting a carbon footprint, especially for transit applications. Much of this section is drawn from Weigel et al. (2010). In the transportation sector, publicly available GHG emis- sions calculators fall under two main categories, each reflect- ing different emerging needs of GHG emissions reporting: 1. Registry and inventory-based calculators, most suitable for standardized voluntary reporting, carbon trading, and regulatory compliance; and 2. Life-cycle analysis (LCA) calculators, most suitable for pursuit of government funding and for demonstrating the benefits of transit over private automobile travel, or the advantages of one type of transit submode or vehicle type over another. Inventory calculators are designed for a broad user base of corporations and municipalities and quantify total agency end-use GHG emissions, which may be reported to a volun- tary data registry (e.g., EPA’s Climate Leaders program) or a registry for carbon credit trading (e.g., the Chicago Climate Exchange). LCA calculators quantify not only end-use GHG emissions, but also upstream and/or downstream GHG emis- sions associated with the provision (and disposal) of fuels and vehicles. LCA calculators may enable the evaluation of government-sponsored initiatives to reduce full life-cycle emissions from agency operations. Most GHG emissions calculators estimate only the total quantity of GHG emissions; see Tables 4.13 and 4.14 (Weigel et al. 2010). Among the calculators identified in these two tables, the GREET fuel-cycle model (U.S. Department of Energy 2012), LEM (Delucchi 2003), and GHGenius (Natu- ral Resources Canada 2012) normalize GHG emissions esti- mates by available energy. Many of the life-cycle calculators provide distance-normalized outputs of GHGs (U.S. Depart- ment of Energy 2009; Natural Resources Canada 2012; Transport Canada 2012; Center for Neighborhood Tech- nology 2012). Transport Canada’s Urban Transportation Emission Calculator outputs passenger-distance normal- ized GHG emissions, but only for nonroad modes (Trans- port Canada 2012). Although many of the calculators do not normalize GHG emissions, normalization may be possible through input data used to generate estimates of total GHG emissions. For example, in a mobile emissions calculator in which CH4 and N2O emissions are estimated from VMT data (either historic or forecasted), the same VMT data may be used to normalize the emissions. In the case of a purchased electricity calculator, GHG emissions calculations will not require VMT or passenger miles traveled data, but the nor- malization of the calculation results will require the collec- tion of such data. Inventory calculators based on a reporting protocol (The Climate Registry 2008; U.S. Environmental Protection Agency 2012; World Resources Institute 2004; ICLEI et al. 2008) follow what has become a standard three-scope division of emissions: direct emissions controlled by the agency (Scope 1), indirect emissions that occur outside of the agency (Scope 2), and optional emissions (Scope 3). Guidance reports for many of these calculators typically provide instructions on how to perform GHG emissions calculations for various combinations of input data, includ- ing guidance on the preferred hierarchy of calculation methods, calculation formulas, default emissions factors by vehicle and fuel technology, and example calculations. Spreadsheet resources, such as the EPA’s simplified GHG emissions calculators (U.S. Environmental Protection Agency

51 Table 4.13. Lifecycle GHG Emissions Calculators for Vehicles and Fuels Calculator Format Output Puget Sound Clean Air Agency and Puget Sound Clean Cities Coalition: Evergreen Fleets Emissions Calculatora Online forms For each vehicle, total tons of CO2. Transport Canada: Urban Transportation Emission Calculatora Guidance report and online forms For each vehicle type: kg CO2e (upstream, operation, and total); kg criteria air contaminants; vehicle kilo- meters (road vehicles) and passenger kilometers (nonroad vehicles) of annual travel. Travel Matters, Center for Neighborhood Technology: Transit Planning Calculatora Online forms and spreadsheets Total annual lbs CO2 by mode; lbs CO2/mile by vehicle type. Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) Fleet Footprint Calculator 1.0a Spreadsheet with user guide Total short tons of CO2e and barrels of petroleum used. GREET Fuel-Cycle Model 1.8c.0a Software and reference spreadsheets For each fuel type: Well-to-pump Btu/mmBtu of energy consumption; g/mmBtu of CO2e, CO2, CH4, and N2O; well-to-wheel Btu/mile of energy consumption; and g/mile of CO2e, CO2, CH4, and N2O. GREET Vehicle-Cycle Model 2.7 Spreadsheets For each vehicle type: Well-to-pump, vehicle cycle, vehicle operation, and total Btu/mile of energy con- sumption; and g/mile of CO2e, CO2, CH4, and N2O. Life-cycle Emissions Model (LEM) Software For each combination of vehicle type and fuel type pro- cess: Well-to-pump g/GJ of CO2e, CO2, CH4, N2O, and HFC-134a; life cycle g/mi of CO2e, CO2, CH4, and N2O, and HFC-134a. GHGenius 3.15 Spreadsheets For each combination of vehicle-type and fuel-type process: Well-to-pump g/GJ of CO2e, CO2, CH4, N2O, and HFC-134a; life-cycle g/km of CO2e, CO2, CH4, N2O, and HFC-134a. Economic Input–Output Life-Cycle Analysis (EIO-LCA) Online forms Per $1M of economic activity and for each sector: Total metric tonnes of CO2e and total CO2e of CO2, CH4, N2O, and CFCs. EPA: Motor Vehicle Emission Simulator (MOVES)a,b Software CO2e and total energy consumption. a Partial lifecycle: upstream fuel emissions. b MOVES is currently available in a draft version. A complete version is scheduled to officially replace Mobile 6.2 as the U.S. EPA's on-road, mobile source, emission factor software. 2012), generally enable calculations through built-in for- mulas and default or user-entered emission factors. Online calculators, such as CRIS (The Climate Registry 2012), provide similar functionality through an internet web browser, although downloadable software programs typi- cally provide a calculation capability based on a signifi- cantly larger number of user inputs, selections, or reference data sets. In transportation applications, a key focus of GHG emis- sions calculations relates to the types of vehicles and fuels that will be present during the analysis time frame. Two main approaches are used by the calculators to estimate mobile combustion GHG emissions, one based on the amount of fuel used and the other based on the number of vehicle miles traveled. The most accurate method for estimating CO2 emissions from mobile combustion is to estimate by the volume of fuel used, the measured carbon content of the fuel per unit of energy (or per unit of volume or mass), and the measured heat content (or density) of the fuel used, represented as E F R KCO2 44 12= × × ×( ) where ECO2 = emissions of CO2 (kg), F = fuel use (gal), R = heat content (Btu/gal) (or fuel density [kg/gal]), and K = carbon content (kg C/Btu) (or kg C/kg fuel). CH4 and N2O emissions may also be estimated by multi- plying the amount of fuel used by the vehicle fuel economy, and a distance-based emission factor, represented as E F M GCH4 = × ×

52 Table 4.14. Vehicle and Fuel Scopes of GHG Emissions Calculators Calculator Vehicle Scope Fuel Scope World Resources Institute: The Greenhouse Gas Protocol—Calculating CO2 Emissions from Mobile Sources taxi, bus, local bus, coach, freight truck, light rail, tram, subway, (gasoline, diesel, CNG, ethanol) bus, (gasoline) passenger car and (diesel) locomotive. gasoline, diesel, residual fuel oil, LPG, CNG, LNG, ethanol, B100, jet fuel, aviation gaso- line, E85 (both with biofuel or fossil fuel), B20 (both with biofuel or fossil fuel) The Climate Registry: General Reporting Protocol Version 1.1, CRIS, Mobile Combustiona (gasoline and diesel) passenger cars, light trucks, heavy-duty vehicles, ships and boats, (diesel) locomotives, (methanol, CNG, and ethanol) buses, light-duty vehicles, and heavy-duty vehicles, (LPG) light duty-vehicles and heavy-duty vehicles, and (LNG) heavy-duty vehicles. motor gasoline, diesel fuel No. 1 and No. 2, aviation gasoline, jet fuel (Jet A or A-1), kerosene, residual fuel oil (#5 and #6), crude oil, B100, E100, methanol, LNG, LPG, propane, ethane, isobutane, n-butane, CNG California Climate Action Registry: General Reporting Protocol Version 3.1, Direct Emis- sions from Mobile Combustiona (gasoline and diesel) passenger cars, light trucks, ships and boats, (diesel) locomo- tives, heavy-duty vehicles, (biodiesel) heavy-duty vehicles, (methanol, CNG, and ethanol) buses, light-duty vehicles, and heavy-duty vehicles, (LPG) light-duty vehi- cles and heavy-duty vehicles and (LNG) heavy-duty vehicles. motor gasoline, diesel fuel No. 1 and No. 2, aviation gasoline, jet fuel (Jet A or A-1), kerosene, residual fuel oil (#5 and #6), crude oil, B100, E100, methanol, LNG, LPG, propane, ethane, isobutane, n-butane, CNG ICLEI Local Government Operations Protocol: Vehicle Fleet (Mobile Combustion)a (gasoline and diesel) passenger cars, light trucks, heavy-duty vehicles, ships and boats, (diesel) locomotives, (methanol, CNG, and ethanol) buses, light-duty vehicles, and heavy-duty vehicles, (LPG) light-duty vehicles and heavy-duty vehicles and (LNG) heavy-duty vehicles. motor gasoline, diesel fuel No. 1 and No. 2, aviation gasoline, jet fuel (Jet A or A-1), kerosene, residual fuel oil (#5 and #6), crude oil, B100, E100, methanol, LNG, LPG, propane, ethane, isobutane, n-butane, CNG Environmental Defense Fund Fleet Greenhouse Gas Emissions Calculatorb (gasoline, diesel, residual fuel oil #5 & #6, avgas, jet fuel, LPG, ethanol, biodiesel, LNG, CNG, electricity) passenger cars, light-duty trucks, vans, SUVs, medium and heavy-duty vehicles, (gasoline and diesel) ships and boats, (diesel) locomotives, (residual oil #5 & #6) ships and boats. gasoline, diesel, residual fuel oil #5 and #6, avgas, jet fuel, LPG, ethanol, biodiesel, LNG, CNG, electricity EPA Climate Leaders: Simplified GHG Emissions Calculator—Direct Emissions from Mobile Combustion Sourcesa,c (gasoline and diesel) passenger cars, light trucks, heavy-duty vehicles, ships and boats, (diesel) locomotives, (methanol, CNG, and ethanol) buses, light-duty vehicles, and heavy-duty vehicles, (LPG) light-duty vehicles and heavy-duty vehicles, and (LNG) heavy-duty vehicles. motor gasoline, diesel fuel No. 1 and No. 2, aviation gasoline, jet fuel, residual fuel oil (#5 and #6), crude oil, B100, ethanol, E100, methanol, LNG, LPG, propane, ethane, isobutane, n-butane, CNG Puget Sound Clean Air Agency and Puget Sound Clean Cities Coalition: Evergreen Fleets Emissions Calculatorb (gasoline, ethanol) small cars, midsize cars, large cars, light vans, heavy vans, pick-up trucks, full size SUV trucks, large >10,000 lbs trucks, (diesel, biodiesel) small trucks, large >10,000 lbs., (hybrid) Prius, Civic, Camry, and Escape. gasoline, E85 (corn), E85 (cellulosic), diesel, B99, B75, B50, B20, B5 Transport Canada: Urban Transportation Emission Calculator light-duty passenger vehicles, light-duty commercial vehicles, medium-duty com- mercial vehicles, heavy-duty commercial vehicles, public transit buses, public transit trolley buses, light rail, subway/metro, heavy rail (diesel-fueled) commuter rail. gasoline, diesel, propane, CNG, LNG, E10, E85, M85, ED10, B100, hybrid, plug-in hybrid, electric vehicle, fuel cell LEM light-duty passenger cars, battery-powered electric vehicles, fuel cell vehicles, full-size buses, minibuses, minicars, heavy-rail transit, light-rail transit, medium- and heavy-duty trucks, diesel trains. gasoline, methanol, ethanol, diesel, biodiesels, CNG, LNG. Electricity: Coal, petroleum, natural gas, nuclear, solar, biomass, hydro. (continued on next page)

53 Table 4.14. Vehicle and Fuel Scopes of GHG Emissions Calculators Calculator Vehicle Scope Fuel Scope GHGenius 3.15 For fuel calculations: Light-duty vehicle, heavy-duty vehicle, bus, truck. For vehicle calculations: passenger cars, light trucks, other. gasoline, methanol, ethanol, butanol, petrol diesel, FT diesel, biodiesels, H2, CNG, LNG; Electricity: coal, fuel oil, natural gas, nuclear, wind, biomass, hydro, other. Economic Input–Output Life-Cycle Assessment automobile, light truck, heavy-duty truck, railroad rolling stock, ships and boats. petroleum (oil and gas), electricity GREET Fuel-Cycle Model 1.8c.0 passenger cars, light-duty vehicles 1, light- duty vehicles 2. gasoline, diesel, CaRFG, LPG, crude naphtha, CNG, LNG, methanol, dimethyl ether, FT diesel, naphtha, LPG, E5-10, E50-90, E100, gaseous hydrogen, liquid hydrogen, bio- diesel. Electricity: Residual oil, natural gas, coal, nuclear power, biomass, other; Ethanol: Corn, woody biomass, herba- ceous biomass, corn stover, forest residue, sugar cane GREET Fleet Footprint Calculator 1.0 school bus, transit bus, shuttle/paratransit bus, transport/freight truck, medium-/ heavy-duty pickup truck, other. gasoline, diesel, biodiesel (B100), corn ethanol (E100), cellulosic ethanol (E100), CNG, LNG, LPG, liquid hydrogen, gaseous hydrogen; Electricity: Residual oil, natural gas, coal, nuclear power, biomass, wind/ solar/hydro GREET Vehicle-Cycle Model 2.7 For both passenger car and SUV (conven- tional or lightweight materials): Internal combustion engine vehicle, hybrid electric vehicle, fuel cell vehicle. Process fuels: residual oil, diesel, natural gas, coal, electricity Travel Matters, Center for Neighborhood Technology: Transit Planning Calculator Online form: vehicles reported by transit agency on Form 408 (Revenue Vehicle Inventory Form) for National Transit Data- base 2002 data report. Online form: (bus and van): diesel, B20, bio- diesel (B100), CNG, electrodiesel, ethanol, fuel cell/natural gas, fuel cell/electrolysis; (rail electricity): biomass, coal, gas, geo- thermal, hydro, nuclear, oil, solar, wind, other Spreadsheet: Bus, commuter rail, heavy rail, light rail/trolleybus. Spreadsheet: (bus) diesel, B20, CNG/LNG, electricity, fuel cell/electrolysis, (rail) electricity EPA: MOVES intercity bus, light commercial truck, motor home, passenger car, passenger truck, school bus, transit bus. Alternative vehicle and fuel technologies: Conventional internal combustion (IC), advanced IC, moderate hybrid–conventional IC, full hybrid–conven- tional IC, hybrid-advanced IC, moderate hybrid–advanced IC, full hybrid–advanced IC, electric, fuel cell, hybrid fuel cell. CNG, diesel fuel, electricity, E85, gasoline, LPG Note: CNG = compressed natural gas; LPG = liquid petroleum gas; LNG = liquid natural gas; CRIS = Climate Registry Information System; FT = Fischer–Tropsch; CaRFG = California reformulated gasoline. a CH4 and N2O calculations are limited to combinations of vehicles and fuels shown in the fuel scope field, in which fuels are shown in parentheses, followed by the vehicles available for the fuel type. CO2 calculations are performed for any vehicle shown. b Calculations are limited to combinations of vehicles and fuels shown in the fuel scope field, in which fuels are shown in parentheses, followed by the vehicles available for the fuel type. c Fuels shown in italics are not available in the spreadsheet calculator, but are available in the calculation guide. Source: Weigel et al. 2010. (continued)

54 where ECH4 = emissions of CH4 (g), F = fuel use (gal), M = vehicle fuel economy (mi/gal), and G = emission factor (g CH4/mi). If fuel usage data are unavailable for a particular vehicle type, CO2 emissions may be estimated from VMT by dividing data for each vehicle type by its corresponding fuel economy using data from the EPA, which are typically included within the calculators. From this fuel usage estimate, CO2 emissions may be calculated by E V M R KCO2 44 12= ( )× × ×( ) where ECO2 = emissions of CO2 (kg), V = VMT, M = vehicle fuel economy (mi/gal), R = heat content (Btu/gal) (or fuel density [kg/gal]), and K = carbon content (kg C/Btu) (or kg C/kg fuel). In addition to the operations-oriented GHG emissions, most carbon footprint analyses include both upstream and down- stream emissions associated with the construction and disposal of materials associated with providing transportation service. Many more carbon footprint analyses applied to transpor- tation services and agencies are likely simply because of the significant role that the transportation sector plays in GHG emissions. The institutional motivation for conducting such analyses will likely fall into two major areas: (1) monitor- ing of GHG emissions footprints over time in response to program requirements or (2) providing information to key stakeholders and the public on the impact of a particular organization or service on GHG emissions. More sophisti- cated approaches and methods will probably be developed in the coming years to account for all transportation-related GHG sources. However, as noted by Weigel et al. (2010), though many existing calculators may be drawn on to develop a complete analysis of vehicle and fuel GHG emissions, such an analysis usually requires careful integration and modifica- tion of existing calculators in order to match the agency’s decision-making requirements. conclusion This chapter has presented a framework for GHG emissions analysis. It is intended simply to provide an overview of the analysis approach; the Practitioners Guide and its Appendix provide much greater detail on how this framework can be used and the tools and data that are available to transporta- tion professionals for conducting GHG emissions analysis. Importantly, the framework outlined in this chapter can be used at different levels of analysis, from metropolitan or regional planning to project development studies. The types of tools and data that analysts would use vary by scale of application, but the questions they should be asking them- selves are still those found in Table 4.1.

Next: Chapter 5 - Case Studies of GHG Emissions Analysis »
Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process Get This Book
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TRB’s second Strategic Highway Research Program (SHRP 2) Report S2-C09-RR-1: Incorporating Greenhouse Gas Emissions into the Collaborative Decision-Making Process identifies where and how greenhouse gas (GHG) emissions and energy consumption fit into a conceptual decision-making framework, including key decision points.

The report presents background information on the role of GHG emissions in the transportation sector, factors influencing the future of emissions, GHG emissions reduction strategies, as well as information on cost effectiveness and feasibility of these reduction strategies. It also presents case studies to illustrate different scales and institutional contexts for GHG analyses.

A web-based technical framework, Integrating Greenhouse Gas into Transportation Planning, which was developed as part of SHRP 2 Capacity Project C09, provides information on the models, data sources, and methods that can be used to conduct GHG emissions analysis. The framework is part of the Transportation for Communities: Advancing Projects through Partnerships (TCAPP) website. TCAPP is organized around decision points in the planning, programming, environmental review, and permitting processes. TCAPP is now known as PlanWorks.

SHRP 2 Capacity Project C09 also produced a Practitioners Guide that presents information on how GHG emissions can be incorporated into transportation planning when using different types of collaborative decision-making approaches and includes an appendix with detailed technical information for GHG analyses.

An e-book version of this report is available for purchase at Amazon, Google, and iTunes.

In June 2013, SHRP 2 released a project brief on SHRP 2 Project C09.

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