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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix L - Heartland Corridor Case Study." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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156 A p p e n d i x L L.1 Background The purpose of this case study is to showcase the methodology and development of a con- ceptual analysis of a multistate endeavor and the ability to extract the most value from avail- able public domain data. Better data (including private domain data) can serve to improve the analysis further. The Heartland Corridor (HC) is a public-private partnership between the NS Railway, the FHWA, and states of Virginia, West Virginia, and Ohio to improve railroad freight operations to/from the Port of Norfolk to Midwest destinations, primarily Columbus, Ohio, and Chicago, Illinois. It was also the first multistate public-private rail corridor project in the United States. Construction began in 2007 and involved raising clearances in 28 tunnels and 24 other overhead obstacles. Approximately 5.7 miles of tunnels were modified. This new link opened for operation in September 2010. It is a direct high capacity rail route facilitating double-stacked intermodal trains between peripheral regions in Virginia and West Virginia to core Midwest markets. It has reduced the distance from Norfolk to Chicago by about 200 miles and decreased transit time by one day, thus providing cost and time benefits for shippers. In June 2010, NS announced the extension of a leg of the HC from Columbus to Cincinnati, with the help of the state of Ohio. The HC also includes three intermodal terminals at key loca- tions: Prichard, Roanoke, and Rickenbacker. The Rickenbacker terminal has been operational since 2008, Prichard opened in December 2015, and the Roanoke terminal is still in the planning stages. Another part of this project includes the relocation of the Commonwealth railway into the median of the western freeway in Portsmouth, Virginia, connecting the APM terminal that opened in July 2007, and a future fourth marine terminal for the Virginia Port Authority. The HC was selected for testing the methodology presented in the guidebook because an integrated corridor approach was adopted for planning investments, jurisdictional involvement, and stake- holder engagement. It also is accompanied by a fairly detailed bottom-up analysis in which the BCA plays an integral role in stakeholder engagement and funding. L.2 Introduction This section discusses the application of the 11-step BCA methodology to the HC. The data used for analysis were derived from publicly available free data sources. Some of the datasets used in the analysis include the Freight Analysis Framework (FAF4), Surface Transportation Board’s URCS, R-1 schedule reports for NS, and data acquired from USDOT’s Bureau of Eco- nomic Analysis and the American Association of Railroads’ (See Section L.5). The analysis rep- resents an initial or conceptual level of analysis, as opposed to a more detailed study. Analyses conducted as part of Step 11 of the guidebook are often a feature of feasibility and investment Heartland Corridor Case Study

Heartland Corridor Case Study 157 grade studies (for example, those that use Monte Carlo simulation), but can be used in all stages of analysis for large projects. A BCA was completed for the HC by considering a project lifetime of 35 years after completion in 2010. Four sets of O-D pairs are applicable to this project. In this report three sets of O-D pairs were considered: Norfolk-Chicago, Norfolk-Columbus, and Norfolk-Detroit. The fourth O-D pair, Columbus-Cincinnati (which is an extension of the HC project) is not explored in this study. For each of the scenarios, the associated benefits and costs were considered for the project’s life- time. The project benefits included travel time savings, inventory cost reduction, reduced vehicle operating costs, safety benefits, and environmental benefits. Indirect benefits such as economic output through job creation in new intermodal terminals built as part of the project were also considered. The stakeholders associated with each of the benefits and costs were also identified and mapped. The results of the analysis are presented in tables for the various steps. The various sources of risks and uncertainties involved in the analysis are also identified and presented. An economic impact analysis conducted for the three intermodal terminals by other agencies is also included in this study as a distinctly separate account or category. Not all of the steps in the guidebook are included in this case study—some do not apply. The steps that are included reference the steps listed in Table 2 of the guidebook. L.3 Past Studies and History Around 1999, the Nick J. Rahall Appalachian Transportation Institute (RTI) was commis- sioned to evaluate freight flows and transport cost of the HC. This study provided information on existing transportation infrastructure in the region and noted that impediments to shippers were driven by lack of direct access to rail and ports for global shipments. The lack of access from an infrastructure investment standpoint resulted from an inability to ship double-stacked containers by rail, since rugged terrain necessitated numerous tunnels. Studies conducted by RTI (1) determined that the height of the tunnels would need to be increased to accommodate double-stacked containers, and described a need for an intermodal facility along the NS rail corridor, to be known as the HC. This study also concluded that West Virginia firms and ship- pers (as well as those in Ohio and Eastern Kentucky) faced shipping cost penalties ranging from $450 to $650 per container higher than in comparable competitor locations, which was assumed to be prohibitive in the context of global trade. A follow-up 2003 study focusing on the central corridor (2), examined alternative routes and concluded that the West Virginia route could save shippers and their customers over $759 million (year 2000 dollars) over a 20-year period, providing benefit-cost ratios of 1.8 to 5.9. The 2003 study provided a range of $46 million to $111.1 million in project costs for developing the tunnels and other infrastructure elements. It noted that the trip frequency was a single train per day in each direction between Chicago and Norfolk for single-stacked containers. The benefits calculated in the study relied on only private shipping and inventory cost savings and on the following assump- tions: 36 hours of savings, an average cargo value $1.49 per pound, a short-term interest rate of 6.125% used for discounting, and a 5% real cost of capital. The study also relied on confidential data obtained from NS to establish container volumes, which formed the basis for calculating the benefits of transitioning from single- to double-stacking along the corridor. The analysis suggests using the HC investment as a valuable economic development strategy. It was also one of the first efforts to note the mix of public and private interests in the proposed central corridor. A more recent study in 2011, led by Cambridge Systematics, Inc. et al., was presented in NCFRP Report 12 (3). The analysis presented various stakeholders associated with the project. It described the three categories of benefits identified for the project, namely transportation savings, inventory carrying costs, and diversion-based benefits (such as safety benefits and emissions reductions).

158 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments It considered three scenarios with different rates of intermodal traffic growth for double-stack trains, namely: low (4%), medium (6%), and high (8%). Discount rates of 3% and 7% were considered in the analysis. The resulting present value of benefits was mapped to the different stakeholders identified for a traffic growth rate of 4%. L.4 Methodology Steps STEP 1: Define the Project 1.A. Define the Type of Facility/Location to Include (a) Type of location/geographic scale The HC is a multistate project extending through the states of Virginia, West Virginia, Kentucky, and Ohio (see Figure L1). This project provides the most direct rail access from the Port of Virginia (Norfolk) to the major markets of Columbus and Chicago. According to FHWA, several components of the project (relocation, intermodal facilities, and other improvements) led to a designation of a project of national and regional significance (PNRS) (4). (b) Modal type The project is a freight rail project. Since intermodal terminals are involved, it is also an inter- modal (IM) project. (c) Connection to freight articulation node points The project includes the construction of three new intermodal terminals—the Rickenbacker, Prichard, and Roanoke terminals. Source: Wikimedia Commons (5) Figure L1. HC map.

Heartland Corridor Case Study 159 The project features include a bundling of several individual projects aimed at improving mobility and freight capacity (see Figure L2) along the main freight corridor: 1. Central Corridor Double-Stack Clearance Project. It involves heightening clearances in 28 tunnels and associated obstructions throughout Virginia, West Virginia, and Kentucky, enabling double-stack rail operations between Roanoke, Virginia, and Columbus, Ohio. 2. A new intermodal facility in Prichard, West Virginia. This project involves a regional inter- modal facility in a rural region. 3. A new intermodal facility in the Roanoke region of Virginia. This project involves a regional intermodal facility in an urban region. 4. New state-of-the-art mega-intermodal facility at the former Rickenbacker Airport in Columbus, Ohio. This is a regional intermodal facility in a rural area. The Rickenbacker inland terminal is now part of a large industrial logistics park that is also known as the Ricken- backer inland port. 5. Relocation of the Commonwealth Railway into the median of the Western Freeway in Portsmouth, Va. It connects the new APM Terminal that opened in July 2007 and the future fourth marine terminal for the Virginia Port Authority. It is a regional intermodal facility in a rural region. 6. Extension to Cincinnati. The HC was also extended west to include Norfolk Southern’s Columbus to Cincinnati line with aid from the American Recovery & Reinvestment Act. 1.B. Develop Options or Alternatives The central corridor project involved clearances in 28 tunnels and 24 other overhead obstruc- tions. The no-build alternative is assumed to be framed by NS’s alternate course of action had there not been public sector participation. If this project had not been undertaken in its current Source: Board (6 ) Figure L2. Location of corridor and terminals.

160 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments configuration, the capacity of the rail line would have remained the same as before and the alter- native route via Harrisburg would have been considered for double-stacked trains to Columbus and Chicago (see Figure L3), potentially without any public sector participation and intermodal terminals. (The distances are presented in Table L2.) The Appalachian Regional Commission (7) noted that NS had previously considered intermodal terminals before the emergence of double stacking. However, those options were not commercially viable as stand-alone projects. For the purposes of the BCA, the other existing alternate routes are compared and analyzed. The alter- nate route options include (1) via Knoxville and (2) via Harrisburg. The key drivers for choosing the HC route were the broader economic development and pub- lic benefits from the development of such facilities. Thus, public benefits served as a significant motivation for enhanced participation by public sector entities. The presence of intermodal facilities in any location along the corridor has the potential to provide: • Cost-competitive rail service options for moving freight: The corridor incurs cost penalties without the intermodal terminal. For instance, Prichard Intermodal terminal’s primary ben- efit has been identified as reduced logistics costs for the private sector, and the public sec- tor has benefitted through increased taxes, economic growth, and employment growth. The Prichard Intermodal terminal site alternative was chosen after comparison with six alternative sites along the HC (8). • Economic development benefits, including jobs to the regional and state economies which would be lost if rail cargo passes through the location (region or state): The economic develop- ment benefits associated with this terminal have included tax abatement, income tax credits, and benefits of a foreign trade zone (9). The Roanoke intermodal facility will play an important role for businesses located in Roanoke. It will be a transload facility, allowing products to be Source: Nick J. Rahall Transportation Institute (2) Figure L3. Alternative routes available to NS.

Heartland Corridor Case Study 161 reloaded to comply with loading requirements, helping companies locate more closely to their final customers, and providing an option for rail service for companies currently served only by trucks and thus giving them an option for faster shipments. None of these could be achieved if the facility were not built. • Generate new or induced demand for rail service: the Rickenbacker multimodal terminal serves to enhance access to major metropolitan markets. Assumptions: In the analysis, the route via Harrisburg (route 2) was used to compare ben- efits from the new corridor. RTI (2) provided a detailed description of all the route alternatives intended to connect Appalachia to Midwestern markets. Note: Because this analysis was conducted retrospectively, the alternatives considered for the analysis were the existing alternative routes for the O-D pairs. STEP 2: Determine Scope of Analysis 2.A. Define Approach for Type of Analysis Since the HC became operational in 2010, this BCA is conducted to understand the impact of a project retrospectively. The HC is analyzed in its entirety (less the Cincinnati Extension from Columbus), including the terminals. The intermodal terminals are also currently operational, except for the Roanoke terminal, which is still in the planning stages. The Rickenbacker terminal opened in 2008, while the Prichard terminal opened in 2015. The Rickenbacker terminal was proposed in order to create jobs and contribute to the state of West Virginia. The same approach was adopted for the Prichard terminal. This BCA is a conceptual level analysis with a goal to utilize public domain data and demonstrate all applicable steps. 2.B. Identify Public and Private Stakeholders Table L1 lists stakeholders identified for the HC project. 2.C. Identify the Jurisdictions Involved Table L2 identifies the jurisdictions along the path of the HC project. The states, counties, and cities that lie in the corridor’s path are included. The facilities connecting to the intermodal terminal are also identified. 2.D. Identify Populations that will be Impacted The impacted populations are identified in Table L3. 2.E. Define the Scope for Modeling and Informational Needs The various links and nodes that are impacted by different modes were documented, thus establishing a base area to be analyzed with publicly available data and tools. Rail and trucks are the major modes affected by the HC project. Stacking containers in double decks on trains will reduce truck traffic on highways along the major freight corridors in the three states (Virginia, West Virginia, and Ohio). The affected area, modes impacted, and links and nodes for each project category are presented in Table L4. The primary network links affected by the HC project are highlighted in the three maps of the states of Virginia, West Virginia, and Ohio in Figure L4, Figure L5, and Figure L6, respectively.

162 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Stakeholder Who Public/Private Applicable Beneit Metrics /Direct, Indirect, Indirect- Wider, or Economic impacts Asset provider, service provider î NS (central corridor) î State/Federal funding agencies and terminal operators (IM terminals) î NS’s (Rickenbacker Intermodal terminal) î State DOTs î Private î Public î Quasi-private in development. (NS and Columbus Regional Airport Authority [CRAA]) î Public agency î Transit time savings/direct î Jobs, gross output (GDP), induced land development and ˆiscal effects/economic impacts from facility î Intermodal efˆiciencies, hinterland access/indirect, indirect wider î Beneˆits from reductions in trucks on highways/indirect End user î Shippers î Private î Reduced inventory carrying cost; cost savings in shipping /indirect supply chain Other impacted party î Economic development agency î Environmental company î Affected Community î Public agency î Public î Jobs, gross output (GDP), land development and ˆiscal effects/economic impacts î Emission reduction/indirect externality î Safety beneˆits/indirect externality Table L1. Public and private stakeholders to benefits mapping. Project State(s) City(s) County(s) ConnectingFacilities Central Corridor Virginia (VA), West Virginia (WV),Kentucky (KY),Michigan (MI), Ohio (OH), Illinois (IL) Roanoke,Christiansburg, Blue�ield, Welch, Williamson, Prichard, Kenova, Portsmouth, Ashville, Rickenbacker, Columbus Over 50counties NS rail line; other state highways via the planned intermodal terminals Prichard terminal WV Prichard Wayne I-64 via US 52[8] Roanoke terminal VA Roanoke Roanoke I-81 [9] Rickenbacker terminal OH Columbus Franklin I-270, I-71, I-70,Highway 23 andHighway 33 Commonwealth Railway Mainline Safety Relocation project (CRMSRP) rail line VA Portsmouth City ofPortsmouth US 164 freeway and some partof US I-664 Extension to Cincinnati OH Cincinnati Hamilton I-71, I -75, I-471 Table L2. Jurisdictional involvement.

Project User Impact Data/Tool- Comments Central Corridor Shippers and Business in the three states The corridor was opened in Sep. 2010. A single NS intermodal train takes up to 300 trucks off America’s highways, reducing trafic congestion and repair costs. Rail transportation is also more fuel-eficient than trucking, which can lead to reduced emissions including greenhouse gases. Shippers beneit from cost eficiencies in shipping. FAF4. As noted in the guidebook, FAF commodity lows provide a high level characterization of rail shippers and receivers in the Mid-Atlantic, Midwest and Appalachian regions. Figure 7–Figure 12 show the rail shippers who are likely to beneit (e.g., transport equipment manufacturers, coal, nonmetallic minerals, foodstuffs, and agricultural shippers). Private or conidential databases can improve this mapping. Commuters and General public Beneit from reduced truck trafic on highways, improved safety, and reduced emissions and air quality. Bureau of Transportation Statistics (BTS) Table L3. Impacted populations and information sources. Source: U.S. Geological Survey (10) Figure L4. Virginia highway network with impacted networks. Table L4. Impact area for the project’s mapping of the links and nodes and impacted modes. Project Line-Haul Rail orHighway Links Nodes Modes Impacted Impacted States Central Corridor NS from Norfolk to Chicago Prichard/Roanoke/Rickenbackerterminals Rail, truck Illinois, Michigan,Ohio, West Virginia, Virginia Prichard terminal I-64 via US 52 HC intermodal node Rail, truck West Virginia Roanoke terminal I-81 HC intermodal node Rail, truck Virginia Rickenbacker terminal I-270, I-71, I-70, Highway 23 and Highway 33 HC intermodal node Rail, truck Ohio CRMSRP rail line US 164 freeway and some part ofUS I-664 HC link Rail, truck Virginia Extension to Cincinnati Central HC link Rail, truck Ohio

Source: U.S. Geological Survey (11) Figure L5. West Virginia highway network with impacted networks. Source: U.S. Geological Survey (12) Figure L6. Ohio highway network with impacted networks.

Heartland Corridor Case Study 165 These are the major roadways that will be affected as a result of diversion of flow from trucks to the rail corridor. Therefore, the safety improvements and savings in pavement maintenance and emissions will be related to the major highways highlighted in yellow (Interstate-81, Interstate-64, Route 460 in Virginia; Interstate-64, Interstate-77 in West Virginia; Interstate-70, US-33, Interstate 71, and Interstate-270 in Ohio). Impact area analysis using FAF4 data As a PNRS, the impact area for BCA of the project was first defined by the O-D pairs served by the corridor (spanning five states—Virginia, Ohio, Illinois, Michigan, and West Virginia) based on freight moving the full distance. This allows an approximation of a part of the travelshed for O-D served by the corridor. O-D key pairs defining the BCA Impact Area: The 3 O-D pairs are: • O-D pair 1: Norfolk-Chicago (and vice versa). • O-D pair 2: Norfolk-Columbus (and vice versa). • O-D pair 3: Norfolk-Detroit (and vice versa). FAF4 data were obtained for corresponding states of Virginia-Illinois, Virginia-Ohio, and Virginia-Michigan, respectively. The total flow in volume (weight in Ktons) and value were extracted from the FAF4 database. Much like the R-1 schedules, FAF flows are aggregate for the rail mode; therefore, a market share assumption for NS was used with the data and for the state O-D pairs chosen. This information is presented in detail in the following section. STEP 3: Account for Project Costs 3.A. Identify Lifetime Costs Specific to the Project Table L5 provides the costs for each of the six projects along with funding agencies. This breakdown provides a starting point for understanding who the stakeholders are, but it is a process that evolves over the life of the analysis. Fixed-variable costs associated with the corridor: operating, maintenance and administration Despite the improvements suggested in Table L1, there are fixed costs associated with track and locomotive maintenance and operations for existing train operations in the corridor that will continue regardless of the improvements. While actual route-level cost information is hard to obtain, the Class 1 carriers are required to provide system level information to the Surface Transportation Board that can be used to approximate these costs (as noted in the guidebook). • The fixed-variable costs were obtained from the R-1 report for NS. The R-1 report is published by the Surface Transportation Board and provides a comprehensive assessment of Class 1 carrier costs at the system level. In order to approximate fixed costs related to the corridor, the analysis relied on fixed components included in six categories reported in the R-1, Schedule 410 (ways and structures, locomotive maintenance, freight car maintenance, other equipment costs, trans- port costs, and a miscellaneous costs category). Purely volume-sensitive items in the R-1 cost categories were removed and are considered separately on the benefit side. The fixed operating and maintenance costs (per ton-mile) for NS were estimated as $0.07 (year 2012 dollars). • The value for total ton-miles traveled in the new HC, a distance of 1049 miles, was obtained by multiplying total flow (Ktons) and the distance. The total flow for the year 2012 between O-D pair Norfolk-Chicago was 376.5 Ktons (15). FAF4 data are available only from 2012 onward, so this analysis used the data for 2012. • The total operating cost for the year 2012 was obtained by multiplying the cost per ton-mile and the total ton-miles (i.e., 376.5 Ktons * 1000 * 1049 miles * 0.07 = $27,646,679.61).

166 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments • Similarly operating costs for all years in the analysis period were estimated by using a traffic growth rate of 35 for the flows and 1% inflation rate for the costs per ton-mile. This represents a conservative estimate of growth in operations and management fixed-variable costs. • Summing the costs for all the years produced the total operating cost for the lifetime of the project for this O-D pair. Source: U.S. Department of Transportation (13 ). Project Total Cost Funding SourcesFederal State Local Private Central Corridor Double-Stacked Clearance Project $191.6 million (2010$)1 SAFETEA-LU funds ($83.4 million) Virginia Rail Enhancement Fund ($9.8 million); Ohio Rail Development Commission grant ($0.8 million) - Norfolk Southern Railroad ($98.4 million) Extension to Cincinnati $6.1 million (2012 $) ARRA funds ($3.6 million) -- Railroad ($2.5 million) Prichard Intermodal Facility [8],[9] $35 million (2015 $) TIGER III award ($12 million) - - Roanoke Region Intermodal Facility $35 million (2010 $) Virginia Rail Enhancement Fund ($12.6 million) - Norfolk Southern Norfolk Southern Railroad ($5.4 million) Rickenbacker Intermodal Terminal $70 million (2008 $) SAFETEA-LU funds ($27.7 million) - - Norfolk Southern Railroad ($42.3 million) Commonwealth Railway Relocation $60 million SAFETEA-LU funds ($15 million) DRPT Rail Enhancement Funds (Fiscal Year 07) ($4.8 million); DRPT Rail Enhancement Funds (Fiscal Year 08 & 09) ($21.0 million) Governor's Transportation Funds - $5.0 million Commonwealth Match of Federal Funds ($3.75 million); Commonwealth Railway, Inc. 30% match of DRPT funds Table L5. Project costs and funding sources. Recommendations and Justification 1. Several sources and reports exist to help determine the exact dates and costs for the project. This analysis uses the official FHWA website as a source of actual costs. 2. For variable costs, use the STB’s R-1 report. It provides fixed variable costs for every year for each of the class-I railroads in the United States. This analysis uses the 2014 R-1 report costs to estimate the variable cost for operating the HC (adjusted to 2012 dollars). These costs included both standard operating and maintenance costs for maintaining the existing tracks, electronic commu- nications systems (signals, etc.), and locomotives. The R-1 database is helpful for BCA given its cost by commodity breakdown. The commodity categories were matched to FAF. 1The actual cost of $191.6 million is approximately 72% higher than the high end range of $111 provided by the 2003 RTI study.

Heartland Corridor Case Study 167 3.B. Define Analysis and Determine Residual Values Parameters Since the main aim of this project involved rail service and related intermodal facilities, it was reasonable to use a longer period as an analysis timeframe. Rail infrastructures have long ser- vice lives. Using the guidelines in the BCA guidebook, the chosen analysis period consisted of 35 years. This timeframe represents a balance between not projecting too far out while still allow- ing a long enough period for benefits to accumulate over and above the period in which costs are incurred. One approach suited to the conceptual nature of the BCA is to adopt a straight line depreciation value approach as shown in Table L6. STEP 4: Identify Benefit Triggers and Metrics This step requires a determination of the triggers or sources of benefits to the public sector, general public, and/or private sector. 4.A. Identify Planning Objectives to Be Met The HC project was designated as a PRNS in the 2005 SAFETEA-LU legislation. This project was intended to improve efficiency by facilitating double-stacked trains carrying freight. Also, since the East Coast ports did not have stacking capacity, there was a need for a rail-to-truck intermodal terminal, as recognized by West Virginia transportation and economic officials. Hinterland access to Midwest markets through intermodal terminals for global trade was another trigger for this project (11). According to the Appalachian Regional Commission (ARC) (12), the vision was driven by three key motivations: improved transport options, economic develop- ment, and international trade. The project can be classified as “capacity enhancement” for line-haul and terminal. Hence the following potential benefit triggers were identified as linked to the three motivations. Reductions in transit time Prior to the improvement, for containers to reach the lower Appalachian area, the two choices were either through West Coast ports then by rail via the Chicago hub or via East Coast ports. If coming through an East Coast port such as Norfolk, the rail options were single-stack direct or double-stack on a route that added over 200 miles and around 24 hours to the journey time, hence increased cost. Therefore, trade to this region was penalized. The central corridor removed 200 miles for freight moving the entire route from Norfolk to Chicago (see Figure L7).The distance reductions and the corresponding original routes are presented in Table L7. These transit time reductions are important for the competitiveness of rail service in the context of global trade. Throughput/capacity and cost reductions The original route was used to transport coal to the Port of Virginia, and the lines could not accommodate double stacking because of height restrictions, as well as the square profile of the conveyance. The clearance through western Virginia and West Virginia accommodated railcars Project Type of Modal Investment (see Table B1 Appendix B) Straight line depreciation RV (see Table B1 Appendix B) Project Lifetime (see Table B1 Appendix B) Approximate Value Terminal Year Heartland clearance project Freight rail Percent of construction costs 35 years Not included in this BCA Intermodal terminals at Prichard/Roanoke/ Rickenbacker Freight transfer center No residual value 25 years Not applicable Table L6. Analysis timeframes and suggested residual values.

168 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments of up to only 19′1″ multi-levels. Hence, double stacking was not possible before the clearance project was undertaken (6). Double stacking has been known to allow up to 400–600 TEU (or 200–300 containers) of container carrying capacity, leading to cost efficiencies in transport of cargo. Transportation savings from the new rail route The savings will stimulate new demand for rail freight between the Port of Norfolk and the Midwest markets. Benefits will accrue from cost savings to shippers based on a comparative assessment of truck to rail shipping costs. Economic development A key benefit trigger includes regional development associated with terminals and economic devel- opment effects such as jobs. A second category of benefits from terminals providing access to hinter- land markets is the ability of the project to induce new demand from mode shifts for key O-D pairs. Additional benefit triggers As a rail service intermodal corridor, additional benefits are possible for key O-D pairs to the extent that NS can compete with trucks in the long-haul markets in gaining intermodal share. These public benefits that stem from truck diversions to the intermodal rail option include: Source: Board (6) Figure L7. HC vs. alternative routes. Norfolk to New distance via HC (miles) Original route 1 (miles) Distance saved (miles) Original route 2 (miles) Distance saved (miles) Chicago 1049 1169 120 1251 202 Columbus 667 967 300 1038 371 Detroit 875 1164 289 1078 203 Table L7. Freight rail routes from Norfolk to Chicago/Columbus/Detroit.

Heartland Corridor Case Study 169 • The environment: Traffic diversion from trucks to rail reduces emissions from trucks. In addi- tion, the shorter distances between various O-D pairs (Norfolk-Chicago; Norfolk-Columbus; Norfolk-Detroit) will reduce emissions from rail in the new corridor. • Safety: Traffic diversion from trucks to rail will help reduce accidents on adjacent highways. National gains As a PNRS, the corridor project has the potential to generate national economic gains by improving trade competitiveness in shipping brought about by double-stacking on key O-D pairs and reductions in overall transit time. 4.B. Identify Applicable Direct and Indirect Benefit Measures and Metrics 4.C. Identify All Applicable First-Order TEE Metrics Benefit metrics and measures are provided for each project associated with HC: • Central corridor – Reduction in transit time (distance savings in miles for the full O-D pair). – Reduction in inventory cost (reductions in inventory capital cost in transit per day) as one source of a supply chain benefit. – Public benefits associated with emissions cost reductions. • Prichard/Roanoke/Rickenbacker intermodal facilities – Economic benefits through job creation and induced land development from the devel- opment of terminal construction, measured in number of jobs, increases in value added ($), or increased tax base. These are not directly justifiable in a BCA but will be included separately. – Benefits from increased rail market share attributable to potential short and long-haul truck diversions. This reflects the new user base measured in additional rail tonnage generated. – Public benefits associated with equivalent diverted trucks—pavement maintenance cost savings, safety cost savings, emission reductions, and change in fuel taxes from diversions. • Relocation of Commonwealth railway – Safety cost reductions from at-grade crossing elimination (14). This category of benefits was not specifically quantified in the calculations as it is expected to be captured in other categories. • Extension to Cincinnati – Rail mode accessibility to additional markets. (Note: This part of the project is not explored in this analysis.) 4.D. Collect and Analyze Freight Flow Data and Attributes of Major Markets Inventory Profile and Shippers: To analyze the impact of the project for the shippers and other end users, FAF4 total flow data were used to create an inventory profile of the impact area. As noted before, one segment (Columbus-Cincinnati) is not considered in this analysis. The intermodal terminals are assumed to be part of the investment alternative and benefits are considered separately. Figure L8 shows that coal and transportation equipment are the primary commodities (and implied shippers) moving from Virginia to Illinois by rail. Figure L9 shows that commodities such as pharmaceuticals, natural sands, base metals, and foodstuffs are among others flowing by multiple modes (intermodal) from Virginia to Illinois. Figure L10 shows a variety of commodities moving by rail from Ohio to Virginia. Figure L11 shows a variety of commodities flowing by multiple modes (intermodal) from Ohio to Virginia, such as foodstuffs, wood products, and waste/scrap.

Commodity 0 50 100 150 200 250 KT on s 2012 2013 2014 2015 Figure L8. FAF4 total flow from Virginia to Illinois by rail mode. 0 10 20 30 40 50 60 70 Ce re al gr ai ns O th er ag pr od s. A ni m al fe ed M ea t/s ea fo od M ill ed gr ai n pr od s. O th er fo od stu ffs A lc oh ol ic be ve ra ge s To ba cc o pr od s. N at ur al sa n ds N on m et al lic … G as ol in e Fu el o ils B as ic ch em ic al s Ph ar m ac eu tic al s Fe rti liz er s Ch em ic al pr od s. Pl as tic s/r ub be r W oo d pr od s. N ew sp rin t/p ap er Pa pe r a rt ic le s Pr in te d pr od s. Te x til es /le at he r N on m et al m in .… B as e m et al s A rti cl es -b as e m et al M ac hi n er y El ec tr o n ic s M ot or iz ed v eh ic le s Tr an sp or t e qu ip . Pr ec isi o n … Fu rn itu re M isc . m fg . p ro ds . W as te /sc ra p M ix ed fre ig ht K To ns Commodity 2012 2013 2014 2015 Figure L9. FAF4 total flow from Virginia to Illinois by multiple modes and rail. 0 100 200 300 400 500 600 700 800 K To ns Commodity 2012 2013 2014 2015 Figure L10. FAF4 total flow from Ohio to Virginia by rail.

Heartland Corridor Case Study 171 Figure L12 shows the total flow from Michigan to Virginia by rail. Nonmetallic minerals and basic chemicals are the main commodities flowing through this link. Figure L13 shows the total flow from Michigan to Virginia by multiple modes (intermodal). Motorized vehicles and machinery are some of the popular commodities flowing through this link, as well as waste/ scrap, foodstuffs, and plastic/rubber. The FAF4 data for “multiple modes and rail” include modes other than rail but includes mostly intermodal containerized cargo that moves by two or more modes; hence it is neces- sary to consider only the data relevant to rail. Because it was not clearly known, an assumption was made about the percentage of flow by rail. This analysis started with 10% for rail from the multiple modes and mail and is subject to sensitivity analysis performed in Step 10 further in this report. 0 10 20 30 40 50 60 O th er a g pr od s. A ni m al fe ed M ea t/s ea fo od M ill ed g ra in p ro ds . O th er fo od st uf fs N at ur al sa nd s N on m et al lic m in er al s M et al lic o re s C oa l G as ol in e Fu el o ils C oa l-n .e .c . B as ic c he m ic al s Ph ar m ac eu tic al s Fe rti liz er s C he m ic al p ro ds . Pl as tic s/ ru bb er Lo gs W oo d pr od s. N ew sp rin t/p ap er Pa pe r a rti cl es Pr in te d pr od s. Te xt ile s/ le at he r N on m et al m in . p ro ds . B as e m et al s A rti cl es -b as e m et al M ac hi ne ry El ec tro ni cs M ot or iz ed v eh ic le s Tr an sp or t e qu ip . Pr ec is io n in st ru m en ts Fu rn itu re M is c. m fg . p ro ds . W as te /s cr ap M ix ed fr ei gh t K T on s Commodity 2012 2013 2014 2015 Figure L11. FAF4 total flow from Ohio to Virginia by multiple modes and rail. 0 50 100 150 200 250 K T on s Commodity 2012 2013 2014 2015 Figure L12. FAF4 total flow from Michigan to Virginia by rail.

172 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Assumptions on the use of FAF4 data for analysis of the HC While FAF is a freely available resource database for the entire country, its use involves assumptions as discussed in the guidebook. Nonetheless, it provides a useful place to start a conceptual benefit cost analysis when those assumptions are well articulated and tested. The cor- ridor analysis for this case study requires approximations of flows attributable to the HC. Ideally, freight flows assigned to the network allow one to isolate corridor volumes for any O-D pair. For this corridor, the team initially investigated the value of the GEOFreight tool developed by the BTS. Upon further examination of the tool and discussion with Oakridge National Laboratories (ORNL), the assigned rail flows in the tool referred to 1998 so the tool was abandoned (2) from further consideration. Since freight network assignment is a time-intensive process, this analysis follows the guidebook approximation procedure of apportioning market share to extract flows for NS and specific to the HC. The market share assumptions were based on the miles operated by each of the major Class I railroads in the states of Virginia, West Virginia, Ohio, and Illinois. These data were obtained from the American Association of Railroads (AAR) fact sheets for indi- vidual states. Figure L14, Figure L15, Figure L16, and Figure L17 shows the track miles operated by Class I railroads in the states of West Virginia, Virginia, Ohio and Indiana, respectively, for the year 2012 (since HC travels through Indiana to reach Illinois). Given this as the basis of market shares, and the new route of the HC from Norfolk to Virginia, it is suggested that NS is the primary railroad operating in this region. These data were used to assume an initial market share parameter of 60% for NS in the FAF4 flow (in Ktons) and value (in millions of dollars) data in all of the benefit calculations and as a constant for all years of the analysis period. These values could be changed to perform a sensitivity analysis to deter- mine impacts on the final BCA results. Some reports from NS provide estimates of carloads transported through the HC. However, the credibility of such information is not verifiable. 0 10 20 30 40 50 Lo gs C er ea l g ra in s O th er a g pr od s. A ni m al fe ed M ea t/s ea fo od M ill ed g ra in p ro ds . O th er fo od st uf fs A lc oh ol ic b ev er ag es N on m et al lic m in er al s M et al lic o re s Fu el o ils C oa l-n .e .c . B as ic c he m ic al s Ph ar m ac eu tic al s Fe rti liz er s C he m ic al p ro ds . Pl as tic s/ ru bb er W oo d pr od s. N ew sp rin t/p ap er Pa pe r a rti cl es Pr in te d pr od s. Te xt ile s/ le at he r N on m et al m in . p ro ds . B as e m et al s A rti cl es -b as e m et al M ac hi ne ry El ec tro ni cs M ot or iz ed v eh ic le s Tr an sp or t e qu ip . Pr ec is io n in st ru m en ts Fu rn itu re M is c. m fg . p ro ds . W as te /s cr ap M ix ed fr ei gh t K T on s Commodity 2012 2013 2014 2015 Figure L13. FAF4 total flow from Michigan to Virginia by multiple modes and rail. 2Personal conversations between ORNL and S. Vadali.

Heartland Corridor Case Study 173 Source: AAR (15) Figure L14. Class I railroads operating in West Virginia. Source: AAR (15) Figure L15. Class I railroads operating in Virginia.

174 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Therefore, this analysis uses the AAR’s rail track miles operated (15), by the major Class I rail- roads in 2012 (see Table L8). This analysis also uses the NS’s estimates of track miles operated in the states along the HC project as a basis to decide the market share for NS and hence the proportion of total flow of commodities in the corridor. Since such approximations from aggre- gate data are inherently subject to uncertainty, the analysis follows the guidebook practice of considering freight flows as inherently risky on the benefit side. STEP 5: Develop Forecasts This analysis aimed to draw value from the use of public domain data such as FAF for con- ceptual analysis. While the Waybill data could have been used, the FAF was chosen to provide rail freight flow data for the O-D pairs owing to the illustrative nature of this case study. Both the weight and value of the commodities were used in the analysis. Rail and multiple modes and mail were chosen in order to consider the rail and intermodal volumes flowing through the O-D pairs. The analysis sought to estimate consumer surplus welfare benefits for both existing users and new or induced users. The guidebook notes that FAF forecasts assume fixed networks and fixed mode shares over the forecast horizon. Source: AAR (15) Figure L16. Class I railroads operating in Ohio.

Heartland Corridor Case Study 175 Source: AAR (15) Figure L17. Class I railroads operating in Indiana. State NS CSX Total % NS %CSX Indiana 1486 1444 3192 47 45 West Virginia 806 1311 2117 38 62 Ohio 2207 1893 4134 53 46 Virginia 2079 1057 3136 66 34 Average % 51 47 Source: AAR Table L8. Total miles operated. Assumptions (existing users) • Due to FAF data features, the NS adjusted corridor FAF flows were assumed to reflect existing users. • Domestic freight flows between the O-D pairs, as well as export and import flows, were all considered in the analysis. • Analysis period: 2012–2045.

176 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Assumptions (new users—modal diversion estimation) • The introduction of intermodal efficiencies via double stacking and intermodal terminals provided the potential to create new rail demand from products previously shipped by truck for each of the O-D pairs. • Truck flows (Ktons) were obtained from the FAF4 for the year 2012 for the Virginia-Illinois O-D pair, as well as the reverse direction. • Potential diversion was estimated by following the guidebook spreadsheet (Diversion1) using the hybrid approach combining divertible commodities and a conservative mode choice elas- ticity of 0.5 (see Table L9). The modal elasticity is a sensitivity parameter since it influences the volume of new users. A feasibility analysis and investment grade study could improve this estimation by using improved data and models. STEP 6: Quantify and Value Applicable First-Order Public and Private Metrics and Information Needs 6.A. Quantify and Value First-Order TEE Metrics • Shipping cost savings to existing users: In this analysis, transit time savings were valued by using a shipping cost estimate, which closely approximates logistical costs to existing rail users. A cost/ton for the new route versus old route provided the basis. The conventional or typical approach would use time values to value crew time, reliability, and damage aspects of assets and/or cargo separately. However, in this case a logistical cost (shipping cost) approxi- mation was considered. • Inventory carrying cost savings to existing users: These are calculated as inventory carry- ing cost savings from the travel time reduction; commodity-specific daily discount rates are applied, and the savings in cost are calculated for the total value of goods transported for each O-D pair. Commodity Code VA to IL (actual flow) IL to VA (actual flow) Total Truck Flow in 2012 (KTons) Potential Diversion % (to rail from truck) Total KTons in 2012 Total M$ in 2012 Total Truck KTons in 2012 Total M$ in 2012 Cereal grains 0.0495 0.3749 13.1221 16.6258 13.17 Significant 40% Significant 40% Significant 40% Significant 40% Other ag products 0.9445 7.2224 9.1394 11.6813 10.08 Large 80% Animal feed 1.6571 1.0055 43.6789 40.1487 45.34 Large 80% Meat/ seafood 22.2156 172.3199 44.7435 198.0734 66.96 Small 20% Milled grain products 17.7674 38.2681 90.1805 139.3187 107.95 Other foodstuffs 95.2797 300.6499 136.7098 232.1786 231.99 Alcoholic beverages 19.7799 28.843 0 0 19.78 Table L9. Diversion estimation—potential new users.

Heartland Corridor Case Study 177 • Shipping cost savings to new users. The HC’s double-stacking initiative results in improved capacity and throughput, which in turn results in diversion from truck to rail and related benefits. For instance, the shippers who divert from truck to rail would benefit from cost efficiencies in shipping via rail instead of truck. 6.B. Identify and Access Data Sources for Valuation Using the guidebook as a reference, the data sources included in Table L10 were considered for the analysis. The valuation measures adopted are free of double counting and rely on distance- sensitive logistical shipping cost proxies instead of traditional crew time costs. For instance, the last column of Table L10 shows the use of the freely available Surface Transportation Board’s URCS tool for providing FAF equivalent commodity-specific distance and time-sensitive logisti- cal costs for the O-D pair used in this analysis (which includes distance variable costs: fuel, crew time, and loss and damage costs) by cargo/commodity type. Section L.5 details the extraction of cost estimates for the O-D pairs from URCS so that only the variable portions of the cost are included in the analysis. 6.C. Examine Models and Sources for Performance Metrics and Valuation Measures, and Quantify Benefits Shipping cost saving (existing and new shippers) • Assumptions: – The new route reduces the distance between Norfolk and Chicago by 200 miles, reducing the transit time by 1 day. This reduction is reflected in the savings realized in the shipping costs to existing shippers and customers. – There are two types of shipping cost savings: one is directly attributable to the reduced dis- tance and benefits the existing shippers in the Mid-Atlantic and Midwest states. The second is due to the new user base (shippers), i.e., from the rail intermodal cost efficiencies that lead to diversion of long-haul truck volumes to rail. First-order TEE metrics Quanti ication metrics Data needs Public domain data and tools Valuation Travel time savings for impacted mode (rail in this case): Existing users. Shipping cost savings, transport cost/unit of time. Distance (miles), transit time (days), and directional lows by commodity (tonnage- weight and value). FAF4, Network analysis, URCS data from Surface Transportation Board (16), AAR (15). Commodity speciic logistical shipper cost savings (including fuel, loss and damage, crew costs) less inventory costs developed from URCS. Inventory costs savings. Travel time savings: New users (pricing eficiencies). Diverted volumes (from trucks to rail), Shipping cost savings for diverted volumes. Directional truck lows diverted by corridor segment. FAF4, Truck-rail modal elasticity, Trucking rates per ton-mile. Cost savings from diversion- difference in trucking rates over rail. Highway maintenance and repair costs. Reduction in pavement maintenance costs, per mile marginal cost of highway use. Cost per mile of highway use. Guidebook (Appendix E). Cost savings in pavement maintenance for highways from diversion (truck to rail). Table L10. Direct TEE metrics and publicly available data sources and tools.

178 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments – The analysis period was set from 2012 to 2045, with the base year set to 2012 for the BCA. – The variable shipping costs for each commodity category were estimated by using STB’s URCS tool (see Section L.5) The URCS data was set to base year 2012 dollars. – Total flows between the various O-D pairs (Norfolk-Chicago; Norfolk-Columbus; Norfolk- Detroit) were obtained from FAF4 flow data. Using these, the operating costs/ton-mile were obtained with the tool. These values were used for operating cost estimates in the BCA calculation. A sample calculation is provided below with the assumptions made. Reduced inventory carrying cost Since inventory costs are not included as part of STB URCS, this is included as a separate category reflective of a part of logistical benefits reflecting cost savings in carrying costs. • Assumptions: – For the O-D pair, Norfolk-Chicago, the transit time saved (original route vs. new route) is equal to 1 day. – The reduced inventory carrying costs are calculated using the procedure suggested in the guidebook adjusted for 24 hours (one-day transit time saving) based on the value of cargo developed from the inventory profile and daily discount rates. Reductions in Inventory Costs = Commodity value (in $) * Daily discount rate (L1) * Transit time saved. The results obtained using the above formula are tabulated and presented in Table L11. The total discounted inventory cost savings computed for the analysis period of the project is calculated as $2,329.2 million ($2012) for the Norfolk-Chicago O-D pair (both directions), $1,797.8 million for the Norfolk-Columbus O-D pair, and $673.6 million for the Norfolk- Detroit O-D pair. New users—modal diversion estimation Following the guidebook worksheets, this analysis used two different approaches to esti- mate diversion. The first approach used a rule of thumb for divertible commodities and per- centages to approximate diversion. The second approach used a hybrid approach combining mode choice elasticity (0.5 as a conservative estimate) and the list of divertible commodities. Both were applied to the FAF4 truck volumes for the O-D pair. Both were valued by using the difference between a conservative truck shipping rate per ton-mile and the rail costs per ton-mile. Finally, the divertible percentages were multiplied by the total flow using trucks in order to obtain the volume of trucks diverted to rail for each commodity group and for each year in the analysis period (see Table L12). Costs savings per ton per mile for rail over truck for each year were estimated by using a conservative truckload shipping rate of $0.146 per ton per mile (obtained from a recent Congressional Budget Office 2015 report [17]) compared to rail cost per ton-mile. Pavement maintenance cost savings—state department of transportation benefits The potential truck diversions for major O-D pairs from parallel truck facilities and the relocation project (such as I-81, US 460, US 52, etc.) will lead to cost savings for highway agen- cies in maintenance expenditures. These are quantified by using estimates of diverted trucks and the per mile marginal cost of highway use (for trucks on urban and rural interstates) (see Table F1).

Heartland Corridor Case Study 179 STCG Commodity Daily discount rate Savings (M$ in 2012) 1 Live Animals and Fish 0.15 0.00 2 Cereal Grain (including seed) 0.05 0.00 3 Agricultural Products Except for Animal Feed (other) 0.15 0.17 4 Animal Feed and Products of Animal Origin 0.15 0.10 5 Meat, Fish, and Seafood and Their Preparations 0.15 0.00 6 Milled Grain Products and Preparations, and Bakery Products 0.15 1.73 7 Other Prepared Food Stuffs, and Fats and Oils 0.15 5.10 8 Alcoholic Beverages 0.15 0.07 9 Tobacco Products 0.15 0.01 10 Monumental or Building Stone 0.05 0.00 11 Natural Sands 0.05 0.01 12 Gravel and Crushed Stone 0.05 0.00 13 Other Nonmetallic Minerals 0.05 0.00 14 Metallic Ores and Concentrates 0.05 0.00 15 Coal 0.05 0.39 16 Crude Petroleum Oil 0.05 0.00 17 Gasoline and Aviation Turbine Fuel 0.05 0.98 18 Fuel Oils 0.05 0.01 19 Other Coal and Petroleum Products 0.05 0.00 20 Basic Chemicals 0.05 0.24 21 Pharmaceutical Products 0.15 0.72 22 Fertilizers 0.05 1.10 23 Other Chemical Products and Preparations 0.05 0.10 24 Plastics and Rubber 0.05 0.82 25 Logs and Other Wood in the Rough 0.05 0.00 26 Wood Products 0.05 0.03 27 Pulp, Newsprint, Paper, and Paperboard 0.05 0.01 28 Paper or Paperboard Articles 0.05 0.07 29 Printed Products 0.05 0.15 30 Textiles, Leather, and Articles of Textiles or Leather 0.05 0.48 31 Nonmetallic Mineral Products 0.05 0.02 32 Base Metal in Primary or Semi-Finished Forms and in Finished Basic Shapes 0.1 2.35 33 Articles of Base Metal 0.1 0.39 34 Machinery 0.1 2.88 35 Electronic and Other Electrical Equipment and Components, and Ofice Equipment 0.1 2.62 36 Motorized and Other Vehicles (including parts) 0.1 1.67 37 Transportation Equipment 0.1 39.01 38 Precision Instruments and Apparatus 0.1 1.26 39 Furniture, Mattresses and Supports, Lamps, Lighting Fittings, Illuminated Signs 0.1 0.32 40 Miscellaneous Manufactured Products 0.1 0.78 41 Waste and Scrap (except of agriculture or food) 0.1 0.11 43 Mixed Freight 0.1 0.11 TOTAL savings $63.78 Table L11. Sample inventory cost savings estimate.

180 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments STEP 7: Analyze Public Externalities and Information Needs (Safety and the Environment) 7.A. Quantify Externalities Safety and environmental effects are among the two main externalities and sources of public benefits in this case. • The new HC route increases capacity and therefore reduces the number of shipments, result- ing in fewer emissions. The truck demand diverted from parallel highways and urban neigh- borhoods also has the potential for delivering environmental benefits. Since the project has the potential to divert truckloads, there are fewer truck vehicle-miles traveled on highways, thereby increasing safety and reducing truck related emissions. For emissions, the emission factors provided in guidebook were used. • The relocation of the Commonwealth railway line eliminates several at-surface grade cross- ings along the corridor, thereby reducing the chances of public interaction with rail and improving safety. Emissions savings Table L13 presents the emissions factors used in the analysis, assuming medium and heavy- duty truck types. Environmental benefits were calculated for truck diversion and from shipment efficiencies for existing rail users. For emission savings from rail’s transit time/distance reduction, the emission factors presented in Table L14 are used. Commodity (SCTG2) Potential Diversion Percentage(from truck to rail) Valuation: Cost Ef�iciencies in Moving by Rail Over Truck Live animals Zero Difference in truckload rate over rail rate Cereal grains Signi�icant 40% Difference in truckload rate over rail rate Coal Small 20% Difference in truckload rate over rail rate Fuel oils Signi�icant 40% Difference in truckload rate over rail rate Wood products Large 80% Difference in truckload rate over rail rate Chemical products Small 20% Difference in truckload rate over rail rate Table L12. Diversion from truck to rail percentage. Table L13. Emissions factors and damage costs for trucks. Pollutant Emission Factor (from Environmental Protection Agency [18]) Cost Range (2013 $) (19)CO2 1.456 Kg per vehicle-miles $40 to $70 per short tonCH4 0.018 Kg per vehicle-miles $1813 per short tonN2O 0.011 Kg per vehicle-miles $7174 per short tonPM10 1.433 grams per mile $326,935 per short tonSO2 0.539 grams per mile $42,240 per short ton

Heartland Corridor Case Study 181 Safety benefits The Value of Statistical Life figures (VSLs) were obtained from the TIGER BCA Resource Guide (19), as suggested in the guidebook (see Table L15). 7.B. Select Metrics for Valuation of Externalities No specialized tools were used for this conceptual BCA, with the exception of STB URCS data and STB’s R-1 databases. The USDOT’s TIGER BCA guidance was used to provide the VSLs, value of property damage, and value of injuries, as suggested in the guidebook. Calculations for Norfolk-Chicago (O-D pair) are: • Total emission savings = $21.5 million (existing rail users). • Total emissions savings = $46.7 million from trucks diverted (using the conservative hybrid approach. These benefits are much higher at $669.6 million if simple thumb rules are used, which we feel might be overly optimistic). • Total safety benefits = $112.79 million from trucks diverted (using the hybrid approach). • Lost fuel taxes from diverted trucks = $28.24 million (using the hybrid approach equivalent number of trucks from truck tonnage diverted, the average states diesel tax rates for trucks traversing the entire distance, and federal tax rates). Private sector consumer and producer surplus approximations to shippers and freight opera- tors serving the Norfolk-Chicago O-D pair therefore amount to $2.6 billion excluding public benefits to affected community, cost savings to highway agencies, and loss in fuel taxes. 7.C. Review Federal Funding Guidelines for Reporting of Specific Externalities A separate safety analysis of the segment level benefits of the Commonwealth safety railway relocation project which eliminated 14 grade crossings between Maersk/A.P. Moller (APM) Ter- minal and I-664 was not conducted given that the corridor as a whole was evaluated following a conceptual BCA. This project addressed community and safety impacts that were important for NS and CSX to compete for cargo at the Maersk/APM terminal. It is expected that the effect of the rail relocation would be captured in the currently included truck diversions to rail direct from the Maersk Terminal to the relocated line. Grams/ton-mile HC/VOC CO Nox PM10 Co2 Double-stack train 0.005 0.4 0.01 Eastern railroad 0.018378 0.056189 0.34854 0.010351 21.35 Table L14. Emissions factors for rail (guidebook Table H2). AIS Level Severity Fraction of VSL AIS 1 Minor 0.003 $27,600 AIS 2 Moderate 0.047 $432,400 AIS 3 Serious 0.105 $966,000 AIS 4 Severe 0.266 $2,447,200 AIS 5 Critical 0.593 $5,455,600 AIS 6 Un-survivable 1 $9,200,000 Property damage only (2013 $) $3,927.00 Unit Value ($ 2013) Table L15. VSLs.

182 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments STEP 8: Analyze Higher-Order Quantifiable Metrics 8.A. Determine Whether WEBs Should be Considered 8.B. Select WEBs to Analyze The logistical cost changes and efficiencies that are quantified in earlier steps should pave the way for broader productivity gains to the nation from cost savings to current shippers. WEBs could also potentially arise from the ability to stimulate new demand by capturing the interactions between access to international markets through Virginia ports, domestic sourcing markets, and global trade that development of terminals like Rickenbacker and Pritchard make possible. This requires a clear understanding of all the terminals, how the freight volumes synergistically interact in relation to terminal lift capacity, and the implications of access changes for trade flows. These are indirect spillover, induced, or higher-order externalities that accrue to the nation. Logistical reorganization effects cannot be quantified in this case. 8.C. Perform Valution of WEBs Currently, there are no models or tools that allow users to determine these linkages for trans- formational rail projects and it is not a trivial task to understand their connections to WEBs. As noted in the guidebook, this remains an area where additional research could add value to the evaluation of multijurisdictional projects, helping to reveal the larger national benefit of such projects. This analysis attempted to capture some of these benefits as part of the direct and indirect effects by (a) considering diversion potential and ability to capture rail traffic and (b) cost efficiencies to existing private shippers. In doing so, it was important to understand that the key motivation for intermodal terminals is primarily to alter demand (induce modal shift) from truck to rail for both long-haul and short-haul markets. These shipping efficiencies could potentially lead to broader gains in light of global trade and exogenous factors such as the Panama Canal expansion and East Coast port competitiveness. For this study and BCA, they are approximated by using a low diversion elasticity starting at 0.5. In essence, the diversion poten- tial is used to approximate additional gains from induced demand. Second, national gains to existing shippers are approximated using approximation methods as suggested in Step 8 of this guidebook based on consumer and producer surplus to shippers and operators. For the Norfolk-Chicago O-D pair combined, these benefits could translate to $256 million over the same period. This value is estimated as a conservative estimate based on the following assumptions: • Welfare benefit to existing shippers: $2,559 million from shipping and inventory cost savings (Norfolk-Chicago). • Coal, transport equipment, and fertilizers as constituting the major share of industry sectors served by NS (Figure L8 and Figure L12). Following analysis of industries served by rail by Christensen Associates (20), the typical price-cost mark ups for these sectors are observed around 0.2. Assuming a conservative 10% average markup for industries served suggests con- tributions to overall value added on the order of $256 million over the entire duration (guide- book Equation 22). Double counting with EIA and BCA This step shows how EIA can support policy goals related to economic development and the costs associated with these elements of the project. In particular, the economic benefits from the development and construction of intermodal facilities that are not conventionally considered for BCA are considered in a separate account as jobs, regional employment, tax impacts, and gross regional product. An EIA was not specifically conducted for this study. However, the study considered several analyses that referred to these impacts. Each of the studies is discussed in the following paragraphs.

Heartland Corridor Case Study 183 Rickenbacker terminal The Rickenbacker terminal (completed in 2008) was reported to have led to an estimated 12,500 additional jobs, $750 million in new development, and 1,300 acres of future development (see the Duke Realty assessment of the Rickenbacker Terminal (21)). The new and future develop- ments are likely to generate significant tax revenues for Columbus, Ohio (particularly industrial land). Because of the terminal’s public-private ownership, these economic impact benefits should accrue not only to the public sector in terms of jobs and taxes, but also to NS in terms of the project’s effects on logistics of cluster-related land development in support of domestic and global trade. The Pickaway Progress Partnership, an economic development organization, noted that this terminal provides direct access via the HC to international markets through the Port of Virginia. Pritchard terminal The Prichard terminal (completed in 2015) is seen as a key to future economic development and job creation in Wayne County. The nearest competitive facility is 140 miles away in Ken- tucky. The terminal encompasses 100 acres between US 52 and the Big Sandy River, 78 acres of which are owned directly by NS (a significant financier for the project). The Journal of Commerce reported that the state port authority expects 1500 warehousing and distribution center jobs to be created. A study by DMJM Harris/AECOM conducted in 2007 (8), which relied extensively on private sector data and tools, estimated an increase of between 700 and 1,000 jobs by 2025 and an increase in economic output of $47 to $69 million as a consequence of the Pritchard Terminal. Roanoke facility The Roanoke facility was evaluated for its short-term construction economic impacts in terms of jobs and its short-term business development/attraction opportunities (22). This analysis was conducted by AECOM using Bureau of Economic Analysis’s Regional Input-Output Modeling System II (RIMS II) multipliers and monthly project costs. STEP 9: Benefit-Cost Analysis 9.A. Determine and Apply Appropriate Discount Rates Due to the potential extent of public benefits, the USDOT’s recommendation of 3% was used as the discount rate, which places more value on benefits occurring farther into the future. If 7% is used, then greater value is placed on benefits occurring closer to the base period. 9.B. Employ Best Practices for Treatment of Transfers, Tolls, and User Charges Private sector consumer and producer surplus approximations to shippers and freight opera- tors serving the Norfolk-Chicago O-D pair amount to $2.6 billion excluding public benefits to affected community, cost savings to highway agencies, and loss in fuel taxes. The lost fuel taxes from diverted trucks are estimated as $28.24 million (using the hybrid approach equivalent number of trucks from truck tonnage diverted, the average states diesel tax rates for trucks traversing the entire distance, and federal tax rates). 9.C. Address Equity Considerations As a multijurisdictional project involving public and private stakeholders, five classes of stake- holders were considered in relation to costs: • Public users. • Public sector providers/asset providers. • Public. • Private sector users-shippers. • Private sector providers/asset providers and service providers.

184 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments The HC’s project stakeholders, benefits, and costs are shown in Table L16 and Table L17 using stakeholder matrices. The WEBs national gains were seen as optional. STEP 10: Develop Decision Criteria and Report BCA Results 10.A. Develop and Employ Final Decision Criteria The NPV is recommended for reporting. The BCR can also be reported. For each of the projects in the HC case, the evaluation included in this analysis was based on positive NPV for evaluating the alternatives. 10.B. Report BCA Results The five elements listed in the guidebook are reported below: • Assumptions: – Benefits were taken into account beginning in 2012. – The analysis timeframe was assumed to be from 2012 to 2045. – For costs, an inflation rate of 1% was used in all the estimates as applicable. – A discount rate of 3% was used, and then 5% and 7% were used for sensitivity testing. Monte Carlo simulation was used to demonstrate its potential value even in conceptual analysis for large-scale projects like the HC. • Metrics and data used: – The benefit metrics include shipping cost savings (from distance reduction), shipping cost savings (from diversion-new users), reduced inventory carrying costs, reduced pavement maintenance costs, emissions savings (from distance reduction), emission savings (from trucks diverted), and safety benefits (from trucks diverted). Benefit Affected Stakeholder Type (Public, Private, Public- Community) Affected Stakeholder Shipping cost savings including reductions in loss and damage Private Nation, state transportation agencies, rail-reliant shippers and the region Reduced inventory carrying cost Private Rail shippers and the region Safety benefits Traveling public, public agencies, public community All stakeholders Emissions savings All stakeholder types—public and private; adjacent community All stakeholders Pavement maintenance savings Public Highway agencies Table L16. HC project stakeholders and benefits. Project component Reported costs Base year adjusted (Million $) Central Corridor $191.6 million (2010) $201.74 Commonwealth rail relocation $60 million $63.17 Prichard terminal $35 million (2015) $33.90 Rickenbacker terminal $70 million (2008) $74.65 Roanoke terminal $35 million (2010) - Ohio terminal - - R-1 operating and maintenance cost $940.10 Total Cost $1,313.56 Operating and maintenance cost Table L17. Project costs ($2012) included in BCA.

Heartland Corridor Case Study 185 • BCA estimation process: – Shipping cost savings: The new double-stack HC represents the shortest distance and travel time between Norfolk, Virginia, and Chicago, Illinois. Shipping goods via this new route yields savings in distance traveled and hence shipping cost savings. Shipping costs were estimated for each O-D pair from URCS database. – Supply chain–related inventory carrying costs: The HC double-stack initiative reduces the average transit time for shipping commodities between Norfolk and markets in the West and Midwest. – Pavement maintenance cost savings from truck volumes diverted to rail. – Emissions reductions from truck volumes diverted and from a shortened distance to final destination. – Safety benefits from trucks diverted. • Norfolk-Chicago O-D Pair: Results from analysis of two different scenarios using a 3% and 7% discount rate are presented in Table L18 and Table L19, respectively. A multiple account BCA (MA-BCA) reporting of the benefits includes all the results presented in Table L20. • Norfolk-Columbus O-D Pair: Results from analysis of two different scenarios using a 3% and 7% discount rate are presented in Table L21 and Table L22, respectively. A multiple account BCA reporting of the benefits includes all the results presented in Table L23. • Norfolk-Detroit O-D Pair: Results from analysis of two different scenarios using a 3% and 7% discount rate are presented in Table L24 and Table L25, respectively. A multiple account BCA reporting of the benefits includes all the results presented in Table L26. (Using 3% discount rate) Range of estimates (in M$)—Impacted Mode Rail Range of estimates (in M$)—Impacted Mode Truck Total Total Costs Account Version 1* Version 2# Version 1* Version 2# Version 1* Version 2# Capital cost $373.46 $373.46 Fixed operating cost $964.44 $964.44 Incremental cost $1,337.90 $1,337.90 Benefits Account Shipping cost savings from distance reduction $229.89 $229.89 Shipping cost savings from diversion $840.25 $38.48 Reduced inventory carrying cost $2,329.19 $2,329.19 Pavement cost savings $137.88 $9.69 Emission savings from distance reduction $21.45 $21.45 Emission savings from diversion $669.67 $46.74 Safety benefits less lost fuel taxes $1920.82 $84.55 Incremental benefits $6,149.15 $2,759.98 NPV $4811.24 $2759.98 BCR 4.60 2.06 National Benefits not included in NPV $256 $256 *, # Corresponds to two different approaches of diversion calculations adopted; Version 1 using potential diversion % from truck to rail; Version 2 refers to hybrid approach of price elasticity factored in at 0.5. Table L18. BCA reporting table (Norfolk-Chicago O-D pair) (3% discount rate).

(Using 7% discount rate) Range of estimates (in M$)—Impacted Mode Rail Range of estimates (in M$)—Impacted Mode Truck Total Total Costs Account Version 1* Version 2# Version 1* Version 2# Version 1* Version 2# Capital cost $373.46 $373.46 Fixed operating cost $550.99 $550.99 Incremental cost $924.45 $924.45 Benefits Account Shipping cost savings from distance reduction $131.30 $131.30 Shipping cost savings from diversion $480.08 $21.99 Reduced inventory carrying cost $1,329.21 $1,329.21 Pavement cost savings $78.78 $5.54 Emission savings from distance reduction $12.12 $12.12 Emission savings from diversion $379.25 $26.56 Safety benefits $1,052.32 $64.41 Incremental benefits $3,463.06 $1,591.12 NPV $2,538.61 $666.67 BCR 3.75 1.72 National Benefits not included in NPV $146 $146 *, # Corresponds to two different approaches of diversion calculations adopted; Version 1 using potential diversion % from truck to rail; Version 2 refers to hybrid approach of price elasticity factored in at 0.5. Table L19. BCA reporting table (Norfolk-Chicago O-D pair) (7% discount rate). Costs Account ($2012) Version 1 Version 2 Capital cost $373.46 $373.46 Fixed operating cost $550.99 $550.99 Incremental Cost $924.45 $924.45 Private Benefits Account ($2012) Shipping cost savings from distance reduction $131.30 $131.30 Shipping cost savings from diversion $480.08 $21.99 Reduced Inventory carrying cost $1,329.21 $1,329.21 Public Account ($2012) - State DOT Agency Pavement cost savings $78.78 $5.54 Public Account - Environmental Emission savings from distance reduction $12.12 $12.12 Emission savings from diversion $379.25 $26.56 Public Account-Safety Safety benefits $1,052.32 $64.41 Public Account-Federal/National National gains from shipper savings (conservative estimate) $146 $146 Public Account - Local and Regional Economic Development Rickenbacker Terminal employment effects Job estimates range from 12,500 to 21,500 (direct, indirect jobs) Pritchard (DMJM Harris Study) 700–1,000 indirect jobs through 2025 Pritchard (DMJM Harris Study) –Economic output $47–$69 million through 2025 Range of estimates (in M$) Table L20. MA-BCA reporting table (Norfolk-Chicago) (7% Discount Rate).

Heartland Corridor Case Study 187 (Using 3% discount rate) Range of estimates (in M$)—Impacted Mode Rail Range of estimates (in M$)—Impacted Mode Truck Total Total Costs Account Version 1* Version 2# Version 1* Version 2# Version 1* Version 2# Capital cost $373.46 $373.46 Fixed operating cost $2596.72 $2596.72 Incremental cost $2970.18 $2970.18 Benefits Account Shipping cost savings from distance reduction $1384.07 $1384.07 Shipping cost savings from diversion $311.10 $(273.77) Reduced inventory carrying cost $1797.79 $1797.79 Pavement cost savings $170.41 $24.65 Emission savings from distance reduction $166.66 $ 166.66 Emission savings from diversion $827.65 $119.73 Safety benefits $2531.25 $366.17 Incremental benefits NPV BCR $7188.93 $4218.75 2.42 $3585.30 $615.12 1.21 *, # Corresponds to two different approaches of diversion calculations adopted; Version 1 using potential diversion % from truck to rail; Version 2 refers to hybrid approach of price elasticity factored in at 0.5. Table L21. BCA reporting table (Norfolk-Columbus O-D pair) (3% discount rate). (Using 7% discount rate) Range of estimates (in M$)—Impacted Mode Rail Total Total KCosts Account Version 1* Version 2# Version 2# Version 1* Version 2# Capital cost $373.46 $373.46 Fixed operating cost $1498.35 $1498.35 Incremental cost $1871.81 $1871.81 Benefits Account Shipping cost savings from distance reduction $798.10 $ 798.10 Shipping cost savings from diversion $191.91 $(168.88) Reduced inventory carrying cost $1027.47 $ 1027.47 Pavement cost savings $97.36 $14.08 Emission savings from distance reduction $95.08 $ 95.08 Emission savings from diversion $ 468.72 $ 67.81 SafetynBenefits $1300.57 $188.14 Incremental benefits $3979.21 $2021.80 NPV $2107.40 $149.99 BCR 2.13 1.08 *, # Corresponds to two different approaches of diversion calculations adopted; Version 1 using potential diversion % from truck to rail; Version 2 refers to hybrid approach of price elasticity factored in at 0.5. Range of estimates (in M$)—Impacted Mode Truck Version 1* Table L22. BCA reporting table (Norfolk-Columbus O-D pair) (7% discount rate).

188 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Costs Account ($2012) Version 1 Version 2 Capital cost $373.46 $373.46 Fixed operating cost $1498.35 $1498.35 Incremental cost $1871.81 $1871.81 Private Benefits Account ($2012) Shipping cost savings from distance reduction $798.10 $798.10 Shipping cost savings from diversion $191.91 $(168.88) Reduced inventory carrying cost $1027.47 $1027.47 Public Account ($2012) - State DOT Agency Pavement cost savings $97.36 $14.08 Public Account - Environmental Emission savings from distance reduction $95.08 $95.08 Emission savings from diversion $468.72 $67.81 Public Account - Safety Safety benefits $1300.57 $188.14 Public Account - Local and Regional Economic Development Rickenbacker Terminal employment effects Job estimates range from 12,500 to 21,500 (direct, indirect jobs) Pritchard (DMJM Harris Study) 700–1,000 indirect jobs through 2025 Pritchard (DMJM HarrisStudy)–Economic output $47–$69 million through 2025 Range of estimates (in M$) Table L23. MA-BCA reporting table (Norfolk-Columbus) (7% discount rate). (Using 3% discount rate) Range of estimates (in M$)—Impacted Mode Rail Range of estimates (in M$)—Impacted Mode Truck Total Total # # # Capital cost $373.46 $373.46 Fixed operating cost $683.56 $683.56 IncrementalcCost $1057.02 $1057.02 Benefits Account Shipping cost savings from distance reduction $134.26 $134.26 Shipping cost savings from diversion $237.59 $(39.53) Reduced inventory carrying cost $673.57 $673.57 Pavement cost savings $47.77 $6.02 Emission savings from distance reduction $18.31 $18.31 Emission savings from diversion $232.04 $29.25 Safety benefits $709.52 $89.47 Incremental benefits $2053.05 $911.35 NPV $996.03 $(145.68) BCR 1.94 0.86 *, # Correspond to two different approaches of diversion calculations adopted; Version 1 using potential diversion % from truck to rail; Version 2 refers to hybrid approach of price elasticity factored in at 0.5. Costs Account Version 1* Version 2 Version 1* Version 2 Version 1* Version 2 Table L24. BCA reporting table (Norfolk-Detroit O-D pair) (3% discount rate).

Heartland Corridor Case Study 189 rate) Range of estimates (in M$)—Impacted Mode Rail Mode Truck Costs Account Version 1* Version 2# Version 1* Version 2# Version 1* Version 2# Capital cost $373.46 $373.46 Fixed operating cost $391.56 $391.56 Incremental cost $765.02 $765.02 Benefits Account Shipping cost savings from distance reduction $76.87 $76.87 Shipping cost savings from diversion $135.75 $(22.59) Reduced inventory carrying cost $383.23 $383.23 Pavement cost savings $27.29 $3.44 Emission savings from distance reduction $10.37 $10.37 Emission savings from diversion $131.40 $16.57 Safety benefits $364.56 $45.97 Incremental benefits $1129.46 $513.86 NPV $364.44 $(251.16) BCR 1.48 0.67 *, # Correspond to two different approaches of diversion calculations adopted; Version 1 using potential diversion % from truck to rail; Version 2 refers to hybrid approach of price elasticity factored in at 0.5. Range of estimates (in M$)—Impacted(Using 7% discount Total Total Table L25. BCA reporting table (Norfolk-Detroit O-D pair) (7% discount rate). Costs Account ($2012) Version 1 Version 2 Capital cost $373.46 $373.46 Fixed operating cCost $391.56 $391.56 Incremental cost $765.02 $765.02 Private Benefits Account ($2012) Shipping cost savings from distance reduction $76.87 $76.87 Shipping cost savings from diversion $135.75 $(22.59) Reduced inventory carrying cost $383.23 $383.23 Public Account ($2012) - State DOT Agency Pavement cost savings $27.29 $3.44 Public Account - Environmental Emission savings from distance reduction $10.37 $10.37 Emission savings from diversion $131.40 $16.57 Public Account - Safety Safety benefits $364.56 $45.97 Public Account - Local and Regional Economic Development Rickenbacker Terminal employment effects Job estimates range from 12,500 to 21,500 (direct, indirect jobs) Pritchard (DMJM Harris Study) 700–1,000 indirect jobs through 2025 Pritchard (DMJM Harris Study)–Economic output $47–$69 million through 2025 Range of estimates (in M$) Table L26. MA-BCA reporting table (Norfolk-Detroit) (7% discount rate).

190 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Range of estimates (in M$) for 7% discount rate Costs Account ($2012) Version 1 Version 2 Capital cost $373.46 $373.46 Fixed operating cost $2440.90 $2440.9 Incremental Cost $2814.36 $2814.36 Private Benefits Account ($2012) Shipping cost savings from distance reduction $1006.27 $1006.27 Shipping cost savings from diversion $1287.82 $(169.48) Reduced inventory carrying cost $2739.91 $2739.91 Public Account ($2012) - State DOT Agency Pavement cost savings $203.43 $23.06 Public Account - Environmental Emission savings from distance reduction $117.57 $117.57 Emission savings from diversion $979.37 $110.94 Public Account - Safety Safety benefits $2717.45 $298.52 Public Account - Local and Regional Economic Development Rickenbacker Terminal employment effects Job estimates range from 12,500 to 21,500 (direct, indirect jobs) Pritchard (DMJM Harris Study) 700–1,000 indirect jobs through 2025 Pritchard (DMJM Harris Study)–Economic output $47–$69 million through 2025 Table L27. MA-BCA reporting table (all O-D pairs combined) (7% discount rate). Since the three O-D pairs constitute the HC’s major links served by the new double-stacking initiative, Table L27 combines the results obtained for the individual O-D pair. STEP 11: Evaluate and Integrate Risk and Uncertainty In the following sections, the steps prescribed in the guidebook were adopted for the analysis. There is uncertainty in estimates of: • Freight cargo volumes due to market share and lack of corridor volumes reflecting NS cor- ridor shares. • Modal diversion and estimates of new users. Methods to account for uncertainty and optimism bias applicable to this project on the ben- efit side included: • Transparency in the assumptions. • Sensitivity testing. • Monte Carlo simulation. • RDM. Transparency All of the assumptions, data sources, and equations used were discussed. All benefit categories were discussed. Sensitivity testing Fifteen different model parameters were studied, one at a time, during one set of sensitivity tests. This goes beyond what most conceptual BCAs observed in the literature consider, but

Heartland Corridor Case Study 191 there is practical value in conducting such an analysis for parameters impacting both the private benefits and public benefits in the case of such large-scale projects. The results from the Norfolk to Chicago O-D pair are shown in Table L28. The traffic growth, discount rate, and unit value of injury parameters were found to be the most important in terms of impact on the estimated NPV of the project. In contrast, the externality costs of emissions were found to be relatively unimportant. In addition to the type of sensitivity testing illustrated by Table L28, tests were performed in which several groups of parameters were set to values assumed to be pessimistic in order to counteract optimism bias. The results of those purposefully pessimistic scenarios indicated that the safety benefits of the project could be 40 or 50 percent less than expected, and the overall NPV of the project could be a bit less than expected if the costs of accidents were at the low end of what was considered feasible. Setting the externality costs of emissions to values perceived to be low did not have much impact on the overall NPV of the project. Monte Carlo simulation Distributions were assumed for the five input parameters. One hundred simulation runs were conducted, and a distribution was derived for the NPV and emissions savings (public benefit) parameters. For feasibility and investment grade studies, an analyst should conduct more than 100 simulation runs and derive the distributions of more than two key parameters, but the results produced are more than adequate for illustration. Table L29 shows the summary statis- tics for the two chosen benefit measures. Note that the interquartile range for NPV is quite a bit larger, in absolute and relative terms, than the interquartile range for emission savings (public). Summary statistics of the type shown in Table L29 are the best way to compactly summarize the results of a Monte Carlo simulation. Histograms depicting the distribution of model outputs are also useful. Parameter Low Value Considered High Value Considered Value of NPV @ Lower Limit (millions of $) Value of NPV @ Upper Limit (millions of $) Inflation Rate 0% 5% 4449.4 7611.9 Traffic Growth -1% 7% 2755.6 9213.9 Discount Rate 0% 7% 8090.5 2725.0 Market Share for NS for Norfolk-Virginia link 40% 100% 4446.0 5729.8 Allocation of Multiple modes and mail flow for HC 0% 20% 4422.3 5325.6 Final percentage to be used for multiple modes and mail 0.00 0.12 4422.3 5325.6 CO2 cost per ton $40 $70 4873.9 4910.4 CH4 cost per ton $1,500 $2,500 4868.5 4885.7 N2O cost per ton $5,000 $10,000 4851.1 4903.6 SO2 cost per ton $25,000 $100,000 4865.6 4904.2 PM10 cost per ton $100,000 $750,000 4563.9 5453.6 Crash rate growth rate -1% 5% 4062.8 5564.0 VSLs $5,000,000 $15,000,000 4817.7 4953.1 Unit value of injury $1,000,000 $4,000,000 3846.7 5977.7 Unit value of property damage crashes $2,500 $6,000 4872.1 4878.5 Table L28. Sensitivity testing, Norfolk to Chicago.

192 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Figure L18 shows such a histogram for NPV for two O-D pairs. In this case study, the risk of several individual projects is pooled between the private and public sectors, but it suggests that additional data can provide more insights into risks and the size of benefits. • From a practical standpoint, the distribution of NPV of the Norfolk-Chicago corridor shows much variability but also a certainty of benefits. The relatively long tail of the distribution suggests that NPV may be as much as twice as high as expected. It also suggests that this O-D pair has the greatest potential to generate both private and public benefits. • The Norfolk-Columbus O-D pair suggests a riskier benefit profile than the Norfolk-Chicago O-D pair. Robust decision making This is arguably the most difficult technique used here for demonstration in a case study, as proper application of this methodology requires, at a minimum, both a very large number of analyses (covering the space of plausible combinations of parameter values) and stakeholder feedback on the identification of interesting results in objective space. Here four values for dis- count rate and four values for crash rate growth rate were considered, yielding 16 combina- tions of parameter values. This was enough to make an illustrative case study but would not be adequate for a real analysis. Note that the two parameters chosen for this analysis were sources of deep uncertainty. There is no universally accepted correct way to set either parameter or assign either a probability distribution. Output Average Median Min Max NPV (in million $) 4882.8 4813.0 3593.7 4371.7 5265.2 7096.8 Emission Savings (public) 638.8 639.4 464.8 585.8 679.4 912.7 1st Quartile 3rd Quartile Table L29. Summary statistics, Monte Carlo simulation. 0 2 4 6 8 10 12 14 16 Fr eq u en cy NPV (millions of $) Norfolk-Chicago 0 2 4 6 8 10 12 14 10 00 to 1 10 0 12 00 to 1 30 0 14 00 to 1 50 0 16 00 to 1 70 0 18 00 to 1 90 0 20 00 to 2 10 0 22 00 to 2 30 0 24 00 to 2 50 0 26 00 to 2 70 0 28 00 to 2 90 0 Fr eq ue nc y NPV (millions of $) Norfolk-Columbus Figure L18. Histogram of NPV results, Monte Carlo simulation: Norfolk-Chicago, Norfolk-Columbus O-D pairs.

Heartland Corridor Case Study 193 Figure L19 shows the results of the example robust decision-making application. The two parameters were noted to be important for calculating both project NPV and project safety benefits. The outcomes when different combinations of parameter values were used are shown in objective space. A particularly noteworthy result is highlighted, in this case where the combi- nation of a 1% discount rate and a 5% crash rate growth rate produced quite high project safety benefits and NPV. In a proper application of robust decision making, analysts and stakeholders would interrogate results similar to those shown in Figure L19 and highlight what interests them. Note that the result highlighted here involves almost one billion dollars in estimated public safety benefits from modal shift, looking at the Norfolk to Chicago case alone. Summary The results shown in this document are purely illustrative, demonstrating possible outcomes when sensitivity testing, Monte Carlo simulation, and RDM are applied. • Sensitivity testing is recommended for the parameters most likely to generate risk. In the case study, there were 15 clearly identified model parameters that were both uncertain and likely to influence the results of the study. Sensitivity testing was performed on each of these model parameters. • It is important to use a few pessimistic scenarios to combat optimism bias on the benefit side and cost side. These scenarios should, typically, focus on traffic forecasts and project cost estimation, two areas in which optimism bias is particularly prominent. The case study did not include detailed models of traffic since a multistate analysis prevents the ability to have highly detailed freight forecasts. An alternative which is more suited for later stage BCA is the reliance on private domain data such as confidential Waybill and/or Tran- search as noted in the guidebook. The project costs should be typically subjected to scenarios. In this case, the project costs were actual costs. It would have been impossible to come up with a detailed pessimistic scenario that covered assumptions made with regard to diversion and induced demand. Instead of defining purposefully pessimistic scenarios focused on traffic forecasts and/or project cost estimation, such scenarios were defined focusing on the exter- nality costs of emissions and traffic accidents. The case study did include models of these two costs, and each included a handful of clearly identified and intuitively labeled uncertain model parameters. Monte Carlo simulation should be performed when there are multiple input parameters in a study that can be assigned probability distribution functions. It will often make sense to first 1% Discount Rate 5% Crash Rate Growth Rate 2000.0 3000.0 4000.0 5000.0 6000.0 7000.0 8000.0 500.0 1000.0 1500.0 2000.0 2500.0 3000.0 3500.0 4000.0 N PV Safety Benefits (millions of $) Results, Plotted in Objective Space Figure L19. Results of robust decision-making application (Norfolk-Chicago).

194 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments collect data on parameters of interest (e.g., empirical observations of the traffic growth rate or safety statistics for years in the recent historical past). An empirical distribution function can then be applied to the random variable that is the annual traffic growth rate in the case of traffic. Such a technique was not practical for the case study due to the large geographic scale of the study and the conceptual nature of study. The results of a Monte Carlo simulation are often compactly repre- sented by showing summary statistics including the mean, minimum, median, max, and first and third quartiles of key model outputs. These statistics are shown for two model outputs in the case study. These outputs are important model outputs, but in an actual study analysts would need to show summary statistics for more model outputs. Similarly, a histogram is provided showing the distribution of the NPV model output after 100 Monte Carlo runs. Analysts performing an investment grade study should run on the order of 10,000 model runs (the number will vary with model complexity) and describe the resulting distribution of multiple model outputs. RDM is arguably the most difficult technique to illustrate in a case study. Analysts performing RDM should identify plausible ranges for all deeply uncertain model parameters and run thou- sands of iterations using combinations of values for these parameters that span their plausible ranges. The analysts should then display the results in objective space, pointing out where different scenarios yield particularly interesting results in the space of the metrics that describe (estimated) project performance. This case study includes a graph showing a handful of results plotted in objective space with one result highlighted as exceptional. Critically, stakeholders need to explore and react to results like this in order to pick out results (in objective space) that they find particu- larly encouraging or discouraging. This is best conducted in an interactive manner as a way of stakeholder engagement. L.5 Data and Tools Used Table L30, Table L31, Figure L20, and Figure L21 summarize the data inputs for the BCA. URCS Steps Used in the Estimates 1. Select Railroad Cost program. 2. Choose URCS Unit Cost Data and select 2012 Railroad Unit Cost.XML as default. 3. Movement Characteristics: Defining Railroad Movement as Railroad = NS, Distance = 1,031 miles, Segment Type = Originate & Terminate. Data Source Use FAF4 To obtain total flows by Ktons and value between states of select O-D pairs. Surface Transportation Board’s URCS To calculate the shipping cost using rail mode for different commodity groups. Surface Transportation Board’s R-1 report AAR To obtain the track miles operated for rails. Used as an input for assumption of market share. Bureau of Economic Analysis To obtain the GDP per capita estimates for Ohio. NHTSA Safety facts Safety facts for highways are obtained. U.S. EPA Emission factor values are obtained. USDOT VSL Guidance VSL and other crash related valuation procedure referred. USDOT TIGER resource guide For valuation of safety and emission benefits procedure in BCA. To calculate the operation and maintenance costs of railroads. Table L30. Public data sources used in the BCA analysis.

Heartland Corridor Case Study 195 4. Freight Car Characteristics (Using example of coal transport below): • Number of cars: 50. • Type of car: Hopper Covered. • Freight car ownership: Railroad. 5. Shipment Characteristics: • Tons per car = 50. • Commodity = 204 Grain Mill Products. • Shipment Size = Unit train move. 6. Calculate Costs. 7. Output. Railroad Distance Segment Type Number of Cars Type of Car Tons per Car Commodity NS 1251 Originate & terminate 10 Railroad 50 Prepared feed Multiple car move NS 1251 Originate & terminate 50 Hopper- covered Hopper- covered Railroad 50 Grains Unit train NS 1251 Originate & terminate 25 Box car-50ft Railroad 60 Other food and kindred products Multiple car move Freight Car Ownership Shipment Size Table L31. Input parameters for selected commodity groups. Figure L20. Milled grains for base case (distance = 1,251 miles; circuity factor = 1.19).

196 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments The URCS tool is used to estimate costs for two scenarios: the base case (distance = 1,251 miles) and the new route (distance = 1,049 miles) (see Figure L20). While running the base case, a cir- cuity factor of 1.19 is given as input, while the new route uses the default circuity factor values (Table L31). Calculation for Norfolk-Chicago Shipping cost savings from a reduction in circuity ($/ton) = Cost/ton (for new route, 1,049 miles) - Cost/ton (base case, 1,251 miles) (Figure L21). Total savings = Savings ($//ton) * Total flow (Ktons) * 1,000 (See Table L32). The total discounted savings adjusted to base year is obtained as $226.17 million. (This estimate is obtained using the market share assumption of 60% for HC and 3% intermodal traffic growth rate and 1% inflation factor). L.6 Conclusions The data and tools used as part of this analysis are all from publicly available sources. Three O-D pairs are considered for analysis, which are part of the HC, namely Norfolk-Chicago, Norfolk-Columbus, and Norfolk-Detroit. The main trigger for the benefits includes the distance reduction for current rail users and the capacity improvement resulting in throughput for new users diverted from truck. The benefit categories considered include shipping cost savings for Figure L21. Milled grains for new route (distance = 1,049 miles).

Table L32. A sample of the discounted savings for the year 2012. Commodity Shipping cost savings in 2012 $ Live Animals and Fish 0.00 Cereal Grain (including seed) 649.71 Agricultural Products Except for Animal Feed (other) 291.08 Animal Feed and Products of Animal Origin 6062.07 Meat, Fish, and Seafood and Their Preparations 135.09 Milled Grain Products and Preparations, and Bakery Products 401941.14 Other Prepared Food Stuffs, and Fats and Oils 625018.13 Alcoholic Beverages 2633.16 Tobacco Products 17.83 Monumental or Building Stone 0.00 Natural Sands 29076.55 Gravel and Crushed Stone 0.00 Other Nonmetallic Minerals 1514.57 Metallic Ores and Concentrates 1.33 Coal 578214.70 Crude Petroleum Oil 0.00 Gasoline and Aviation Turbine Fuel 272608.94 Fuel Oils 607.18 Other Coal and Petroleum Products 0.00 Basic Chemicals 39736.21 Pharmaceutical Products 15208.54 Fertilizers 1096562.52 Other Chemical Products and Preparations 1928.03 Plastics and Rubber 145168.13 Logs and Other Wood in the Rough 165.88 Wood Products 14638.80 Pulp, Newsprint, Paper, and Paperboard 873.66 Paper or Paperboard Articles 20282.42 Printed Products 5780.55 Textiles, Leather, and Articles of Textiles or Leather 11750.77 Nonmetallic Mineral Products 516.95 Base Metal in Primary or Semi-Finished Forms and in Finished Basic Shapes 114588.82 Articles of Base Metal 27829.09 Machinery 70148.26 Electronic and Other Electrical Equipment and Components, and Office Equipment 4022.96 Motorized and Other Vehicles (including parts) 75731.82 Transportation Equipment 2906713.38 Precision Instruments and Apparatus 1009.27 Furniture, Mattresses and Mattress Supports, Lamps, Lighting Fittings, and Illuminated Signs 9493.00 Miscellaneous Manufactured Products 7299.89 Waste and Scrap (except of agriculture or food ) 9133.54 Mixed Freight 2165.07 Total (all comm.) $6,499,519.03

198 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments current users and new users, reduced inventory costs, pavement maintenance cost savings, reduced emission benefits, and safety benefits. From the BCA table presented in this report for all three O-D pairs combined, the benefits realized through shipping cost savings and reduced inventory costs are significant. Overall, the benefits are greater than the capital cost and operat- ing cost incurred. These results are also subject to sensitivity testing considering different cases of the input parameters used in the analysis such as traffic growth, inflation rate, cost parameters, and discount rate. References 1. Rahall Transportation Institute. Transportation and the Potential for Intermodal Efficiency Enhancements in Western West Virginia. Report prepared on behalf of the Appalachian Regional Commission, the West Virginia DOT and West Virginia Planning and Regional Development Council. Huntington: 2000. 2. Nick J. Rahall Transportation Institute, N.J., Central Corridor Double-Stack Initiative Appalachian Transpor- tation Institute. 2003. 3. Cambridge Systematics, Inc., Economic Development Research Group, Inc., Halcrow, Inc., DecisionTek LLC, and Boston Strategies International. Framework and Tools for Estimating Benefits of Specific Freight Network Investments. NCFRP Report 12. Transportation Research Board of the National Academies, Wash- ington, D.C., 2011. 4. Federal Highway Administration. Projects of National and Regional Significance. 2012 Report to Congress Project Information. USDOT, FHWA. http://ops.fhwa.dot.gov/freight/policy/rpt_congress/pnrs12rptcong/ index.htm. Accessed 2016. 5. Heartland Corridor. https://commons.wikimedia.org/wiki/File:Heartland_Corridor.png. Accessed 2017. 6. Board, C. T. The Heartland Corridor. 2006. Available: http://www.virginiadot.org/ctb/resources/Agenda_ Item6_Heartland_CTB_Update_Dec2006_short.pdf. Accessed 2016. 7. Burton M. and D. Clarke. Heartland Corridor: Opening New Access to Global Opportunity. Appalachian Regional Commission, 2011. Available Online at. http://www.arc.gov/images/programs/transp/intermodal/ heartlandcorridor.pdf. Accessed 2015. 8. DMJM Harris and AECOM. Economic and Market Analysis for an Inland Intermodal Port, State of West Vir- ginia. Prepared for West Virginia Public Port Authority, 2007. 9. Realty, D. Rickenbacker Global Logistics Park—Economic Benefits 2015 2016]. Available from: http://www. rickenbackerglp.com/devopp/benefits.aspx. 10. U.S. Geological Survey. Reference map of the state of Virginia. Accessed on January 24, 2017. https:// nationalmap.gov/small_scale/printable/images/pdf/reference/pagegen_va.pdf 11. U.S. Geological Survey. Reference map of the state of West Virginia. Accessed on January 24, 2017. https:// nationalmap.gov/small_scale/printable/images/pdf/reference/pagegen_wv.pdf 12. U.S. Geological Survey, Reference map of the state of Ohio. Accessed on January 24, 2017. https://national map.gov/small_scale/printable/images/pdf/reference/pagegen_oh.pdf 13. U.S. Department of Transportation. Project Profiles. Available from: https://www.fhwa.dot.gov/ipd/project_ profiles/wv_heartland.aspx. Accessed 2015. 14. Leach, P. T., Commonwealth Railway to Start Double-stack Service. JOC.COM, 2010. 15. American Association of Railroads, U.S. Freight Railroad Industry Snapshot, 2012. https://www.aar.org/ data-center/railroads-states#state/VA. Accessed 2016. 16. Economic Data: URCS. Surface Transportation Board. 2012. 17. Austen, D., Pricing Freight Transport to Account for External Costs. 2015, Congressional Budget Office. 18. U.S. Environmental Protection Agency. Emission Factors for Greenhouse Gas Inventories. 2014. https://www. epa.gov/sites/production/files/2015-07/documents/emission-factors_2014.pdf. Accessed 2016. 19. U.S. Department of Transportation Tiger Benefit-Cost Analysis (BCA) Resource Guide. 2014. https://www. transportation.gov/policy-initiatives/tiger/tiger-benefit-cost-analysis-bca-resource-guide. Accessed 2015. 20. Christensen Associates. A Study of Competition in the Railroad Industry and Analysis of Proposals that Might Increase Competition. Presentation to the Transportation Research Board Committee on Freight Rail Transportation and Regulation. 2014. http://onlinepubs.trb.org/onlinepubs/railtransreg/Eakin011014.pdf. Accessed 2016. 21. Realty, D. Rickenbacker Global Logistics Park: Benefits. 2015 Available from: http://www.rickenbackerglp. com/about/location.aspx. 22. AECOM, West Virginia Intermodal Facility: Economic and Transportation Impacts Study. 2014. Accessed 2016.

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TRB's National Cooperative Freight Research Program (NCFRP) Research Report 38: Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments explores how to conduct benefit-cost analyses (BCAs). A BCA is an analytical framework used to evaluate public investment decisions including transportation investments. BCA is defined as a collection of methods and rules for assessing the social costs and benefits of alternative public policies. It promotes efficiency by identifying the set of feasible projects that would yield the largest positive net benefits to society.

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