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Guide to Deploying Clean Truck Freight Strategies (2017)

Chapter: Chapter 6 - Tool Case Studies

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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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Suggested Citation:"Chapter 6 - Tool Case Studies." National Academies of Sciences, Engineering, and Medicine. 2017. Guide to Deploying Clean Truck Freight Strategies. Washington, DC: The National Academies Press. doi: 10.17226/24957.
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39 This chapter offers sample case studies demonstrating scenarios in which the tool can be used. The tool and user guide are available on the TRB website (by searching for “NCHRP Research Report 862” at www.TRB.org). The case studies are organized by agencies that might use the tool: an MPO, a state DOT, and a port authority. For each user type, a scenario was developed that demonstrates how the tool can be used to assess truck emissions of different pollutants, esti- mate costs of clean truck programs, and compare different strategies. Although the scenarios are shown from different agency perspectives, they are not necessarily agency specific; for example, both a port operator and an MPO may be interested in looking at incentivizing the deployment of CNG trucks to reach NOx targets. In addition to providing realistic examples of how the tool can be employed to answer differ- ent truck emissions questions, the case studies provide step-by-step guidance on how to use the tool and interpret the results in the context of addressing the scenario. Each subsection begins with a description of the case study scenario. For each case study, there are multiple analysis types described to demonstrate different ways to approach answering questions presented by the scenario. Some analyses allow the user to determine the emissions reductions of different strategies, while others determine how to address cost questions. For each analysis type, a table is provided with sample inputs for each selection in the tool and guidance on those inputs. The choices in the tool include the following selections: • Analysis type. Any or all three analysis types can be used to look at a problem. The Truck Deployment Analysis allows users to look at full costs of programs plus drop-in fuels (where there is no capital cost). The Funding Impact Analysis allows users to see how many trucks they can replace or modify for a given dollar amount. The Incentive Analysis shows the pay- back period for incentives that cover part of the capital costs, with the remaining costs covered by fuel cost savings. • Year of modification. The analysis year is when the replacements/modifications take place. For instance, if you are working on long-range plans that might go out to 2040, you need to pick analysis years before that. Generally, you might want to look at 2025, 2030, and 2035 as the phase-in times for the new programs or rules. • Area of interest. Area of interest is the geographic scale that determines the emissions factors used in the calculations. The larger the geographic scale, the more freeways are used, while the smaller geographic scales have more local roads. If your organization is an MPO, you would use Metropolitan. The geographic scale affects the mix of roadway types that go into the emissions factors. This tool is not an emissions inventory tool that will calculate all truck emissions for a given geographic area. • Type of truck. The four truck types represent different segments of the heavy-duty truck populations. Single-unit short-haul trucks are typically urban pickup and delivery trucks in C H A P T E R 6 Tool Case Studies

40 Guide to Deploying Clean Truck Freight Strategies the Class 3–5 size. Single-unit long-haul trucks are typically box trucks that travel within a regional area and are generally Classes 6–7. Combination short-haul trucks are typically dray- age trucks that travel shorter distances. Combination long-haul trucks are line-haul trucks that travel large distances. • Type of modification. This option is only included in Truck Deployment Analysis and Incen- tive Analysis. The user can select one type of modification. In some analysis types, this is fol- lowed by a selection of specific modifications; for example, by selecting the Alternative Fuels modification type, the user can then select the specific alternative fuel strategy in the menu. Some modification types are restricted to certain types of trucks; thus, some modification types cannot be selected when the user selects some truck types, and vice versa. • Number of trucks to be replaced. Emissions reductions and costs will be multiplied by the value entered here. Users can enter 1 if they want to see per-truck results. • Annual mileage accumulation. This is the average miles traveled each year by the types of trucks selected for analysis. The default values come from the EPA’s MOVES model. The more annual miles in this field, the more emissions benefits there will be. • Range of model years to modify/scrap. These are the model years to which the strategies will be applied. Targeting older trucks will usually yield more reductions because fleets with older MY trucks are assumed to have higher average emissions rates. • Long-haul annual idle hours. This input only applies to strategies involving idle-reduction strategies, which are only included for programs targeting long-haul combination-unit trucks. • Fuel costs. Units for most alternative fuels are in diesel gallon equivalents in order to nor- malize for differences in energy content between the different fuels. Default values are national averages at the time the tool was developed. More up-to-date and regional fuel prices can be found from other sources, including the Alternative Fuels Data Center’s Fuel Prices webpage. • Electricity generation region. The selection of the electricity mix changes the assumed GHG emissions per unit of electricity consumed. The user can assume a national value or select the region in which the targeted trucks operate. This affects the emissions results for strategies involving electric trucks. • Capital costs. These are inputs for the replacement truck or equipment costs. If the truck is replaced, the tool assumes that the old truck is scrapped. The default values included in the tool are based on research of costs in 2015. Replacing defaults with more up-to-date or local averages will improve cost and cost-effectiveness estimates in the results. After each table of input guidance, selected results from using those inputs are shown. Results from the example runs are discussed and compared to address some of the questions presented in the scenario description. 6.1 MPO Case Study 6.1.1 Scenario An MPO in New York State is updating its long-range transportation plan (LRTP) going out to 2040 as well as developing a regional freight plan. The MPO is looking at ways to reduce regional GHG emissions from freight trucks. The agency decides to apply for federal grant fund- ing for a project to upgrade trucks in the region. Use the tool to help determine which strategies the MPO should pursue. 6.1.1.1 Truck Deployment Analysis – Alternative Fuels The Truck Deployment Analysis allows the user to estimate the impacts and costs of different clean truck strategy options. For each input option, enter the selections presented in Table 16.

Tool Case Studies 41 Category Selection Notes Analysis Analysis Truck Deployment Analysis This analysis allows the user to estimate full costs and emissions impacts of a program. Scope Year of Modification 2030 The modification year is when the modifications or replacements take place. Because the LRTP goes out to 2040 in this scenario, the user should assume modifications happen sometime before that. If 2040 is selected, the tool assumes all changes occur in 2040, and the emissions benefits will be smaller because the tool assumes the baseline fleet is cleaner in 2040. Area of Interest Metropolitan Geographic scale determines the emission factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Short Haul For this scenario, combination short-haul trucks are selected since they will operate within the metropolitan region. Type of Modification Alternative Fuel Note that only one can be selected at a time. Accelerated retirement will be considered in a separate analysis. Other modifications are not considered because retrofits do not have positive GHG benefits and will be obsolete in 2030, tires have small GHG benefits, and aerodynamics and idle reduction are only available for combination-unit long-haul trucks. Modifications Alternative Fuel(s) Select all Click the checkmark button at the top of the column to select all. Results will be displayed for each fuel separately. Strategies involving drop-in alternative fuels (i.e., biodiesel and renewable diesel) can be used in existing diesel trucks; all other alternative fuel selections assume existing trucks are gasoline or diesel trucks that must be replaced as part of the strategy. Vehicle Data Number of Trucks to Be Replaced 100 The results can be divided by 100 to calculate the per-truck impacts. Average Annual Mileage Accumulation Leave default values The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) 2000–2017 This range is based on replacing pre-2018 trucks since the Heavy-Duty GHG Phase 1 rule will have been fully phased in by 2018, and the Phase 2 regulations begin. Long-Haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region NPCC (Northeast Power Coordinating Council) This electricity region includes New York. CO2 Leave default value (254 g/kWh) The default value will update depending on the Electricity Generation Region selected. Capital Costs Cost Leave default values Default values are based on recent (2015) estimates. Replacing defaults with more up-to-date or local averages will improve cost and cost-effectiveness estimates in the results. Table 16. Truck deployment analysis for alternative fuels.

42 Guide to Deploying Clean Truck Freight Strategies Results. Table 17 summarizes the impacts of replacing diesel with alternative fuel options on CO2 emissions. Note that the tool produces a number of other results not shown in the table; only CO2 impacts are shown here since CO2 was the targeted pollutant in this scenario. The results show that using 100 CNG trucks in place of diesel trucks results in 1,657 fewer tons of CO2 being released each year, or a reduction of 16.6 tons per truck per year. Based on the assumed capital and operations costs and lifetime of the trucks, the CNG strategy costs $1,024 per ton of CO2 avoided. The renewable CNG (RCNG) and renewable diesel (R100) strategies yield the largest emis- sions reductions at 4,743 and 4,900 tons, respectively. The strategies with a low-NOx engine added do not show different emissions reductions because low-NOx engines do not reduce CO2 emissions. B20 and R100—the two drop-in fuels—are the most cost-effective. Note that the availabil- ity of these fuels may limit implementation, especially early in the development of these fuel markets; the availability of alternative fuels is discussed elsewhere in the guide. 6.1.1.2 Truck Deployment Analysis – Accelerated Retirement The previous Truck Deployment Analysis allowed the user to estimate the impacts and costs of replacing older trucks with alternative fuel trucks or using alternative fuels in existing trucks. The following analysis allows the user to see the impacts and costs of replacing older trucks with newer models of diesel trucks. For each input option, enter the selections presented in Table 18. Results. Table 19 shows the CO2 emissions benefit of replacing 100 older diesel trucks with new models. The CO2 emissions reductions are significantly smaller than reductions from alternative fuel options, with alternative fuel reductions two to ten times greater than those from replacing old trucks with newer models. The smaller CO2 reductions paired with the high cost of replacing trucks also make this strategy less cost-effective than the alternative fuel options. Even though Modification Annual CO2 Emissions Reduced (tons) Cost- Effectiveness ($/ton) CNG 1,657 $1,024 RCNG (Renewable CNG) 4,743 $358 CNG + Low-NOx Engine 1,657 $1,094 RCNG + Low-NOx Engine 4,743 $382 B20 (Biodiesel) 980 $89 R100 (Renewable Diesel) 4,900 $121 Hybrid 3,214 $321 Electric 5,526 $271 Table 17. Impacts of replacing diesel with alternative fuel.

Tool Case Studies 43 Category Selection Notes Analysis Analysis Truck Deployment Analysis This analysis allows the user to estimate full costs and emissions impacts of a program. Scope Year of Modification 2030 The modification year is when the modifications or replacements take place. Because the LRTP goes out to 2040 in this scenario, the user should assume modifications happen sometime before that. If 2040 is selected, the tool assumes all changes occur in 2040, and the emissions benefits will be smaller because the tool assumes the baseline fleet is cleaner in 2040. Area of Interest Metropolitan Geographic scale determines the emissions factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Short Haul For this scenario, combination short-haul trucks are selected since they will operate within the metropolitan region. Type of Modification Accelerated Retirement This selection assumes that trucks of older model years (selected on the Vehicle Data page) will be replaced with trucks of later model years. Vehicle Data Number of Trucks to Be Replaced 100 The results can be divided by 100 to calculate the per-truck impacts. Average Annual Mileage Accumulation Leave default values The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) 2000–2017 This range is based on replacing pre-2018 trucks since the Heavy-Duty GHG Phase 1 rule will have been fully phased in by 2018, and the Phase 2 regulations begin. Long-Haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long- haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Regional Mix n/a This selection does not apply because accelerated retirement assumes replacement with new gasoline or diesel trucks, not electric trucks. CO2 n/a This selection does not apply for accelerated retirement. Capital Costs Cost Leave default value Default value is based on recent (2015) estimates. Replacing the default with a more up-to-date or local average will improve cost and cost-effectiveness estimates in the results. Table 18. Truck deployment analysis for accelerated retirement. Modification Annual CO2 Emissions Reduced (tons) Cost- Effectiveness ($/ton) Accelerated Retirement 433 $2,187 Table 19. Accelerated retirement CO2 emissions benefit.

44 Guide to Deploying Clean Truck Freight Strategies many of the alternative fuel options also include replacing old trucks with expensive advanced- technology trucks, their high emissions reductions make the cost-effectiveness better than that of this strategy. Thus, in terms of both CO2 reductions and cost-effectiveness, the alternative fuel strategies are better than accelerated retirement with new diesel trucks, with electric trucks offering the greatest CO2 benefits, and the drop-in fuels being most cost-effective. However, the selection of one of these strategies for a clean truck program will depend heavily on vehicle and fuel availability and actual market prices. For example, electric trucks may not be widely available at the time of an incentive program, or there may not be enough charging or fueling infra- structure to support expansion of alternative fuel trucks; diesel trucks do not face the same uncertainty, with CO2 emission rates largely guided by the federal fuel efficiency standards and infrastructure plentiful, but there is significant uncertainty in diesel prices that could affect cost-effectiveness. 6.1.1.3 Funding Impact Analysis The Funding Impact Analysis assumes that the user knows the amount of funding available or being requested to invest in clean truck strategies. For each input option, enter the selections presented in Table 20. Results. For each strategy option, the tool calculates the number of trucks that can be modified or replaced for the funding amount, or $1 million in this scenario. For the alternative fuel and accelerated retirement options, the number of trucks assumes that the old truck is scrapped and that the program is paying the total cost of the new vehicle (i.e., the old truck has no value because it is being scrapped). Strategies that have no capital cost (such as the drop-in fuels—B20 and R100) are not included in the Funding Impact Analysis. Results are shown in Table 21. The Number of Trucks to Modify/Replace is the estimate of the number of modified trucks the investment will pay for. Although replacing a diesel truck with a new advanced diesel or alternative fuel truck can reduce pollutants much more than replacing the tires on an older diesel truck, replacing tires is much cheaper. In this scenario, less than 10 trucks could be replaced with new or alternative fuel vehicles, while hundreds of trucks could be outfitted with exhaust aftertreatment devices or advanced tires; however, note that DOCs and DPFs do not reduce CO2 emissions. Thus, for the same amount of money, a low-cost strategy such as tire replacement can have a bigger total emissions impact than a high-cost strategy such as truck replacement. However, while program administrators may be able to affect more trucks with a low-cost strategy (e.g., putting low rolling resistance tires on 555 trucks), they should also be aware that they may have to implement an extensive outreach plan or they may not be able to get full par- ticipation and achieve the estimated CO2 reductions. Thus, the fewer the trucks to be modified or replaced, the larger the emissions benefit per truck; the greater the number of trucks, the more cost-effective the investment is per truck. 6.1.1.4 Incentive Analysis The Incentive Analysis lets the user estimate the impacts of partially subsidizing modifications or replacements. The Incentive Analysis assumes that the public agency promotes strategies that reduce operating (i.e., fuel) costs for truck owners and the owners will be willing to pay for part of the cost. This analysis type only works for strategies that reduce fuel costs. For each input option, enter the selections presented in Table 22.

Category Selection Notes Analysis Analysis Funding Impact Analysis This analysis allows the user to estimate the number of trucks and emissions impacts of implementing various strategies with a known amount of funding. Scope Year of Modification 2030 The modification year is when the modifications or replacements take place. Because the LRTP goes out to 2040 in this scenario, the user should assume modifications happen sometime before that. If 2040 is selected, the tool assumes all changes occur in 2040, and the emissions benefits will be smaller because the tool assumes the baseline fleet is cleaner in 2040. Area of Interest Metropolitan Geographic scale determines the emissions factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Short Haul For this scenario, combination short-haul trucks are selected as they will operate within the metropolitan region. Funding Amount Leave default value ($1,000,000) Vehicle Data Average Annual Mileage Accumulation Leave default values The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) 2000–2017 This range is based on replacing pre-2018 trucks since the Heavy-Duty GHG Phase 1 rule will have been fully phased in by 2018, and the Phase 2 regulations begin. Long-Haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region NPCC This electricity region includes New York. CO2 Leave default value (254 g/kWh) The default value will update depending on the Electricity Generation Region selected. Capital Costs Cost Leave default values Default values are based on recent (2015) estimates. Replacing defaults with more up-to-date or local averages will improve cost and cost-effectiveness estimates in the results. Table 20. Funding impact analysis. Modification Number of Trucks to Modify/Replace Annual CO2 Emissions Reduced (tons) CNG 5 82.8 RCNG 5 237.1 Hybrid 5 82.8 DOC 5 237.1 DPF 5 160.7 Low Rolling Resistance 666 – Single Wide 64 – Accelerated Retirement 555 409.8 Table 21. Funding impact analysis results.

46 Guide to Deploying Clean Truck Freight Strategies Results. Table 23 shows some of the results from the Incentive Analysis. The only alternative fuel strategy options in this analysis are to replace conventional diesel trucks with hybrid or elec- tric versions. For each option, the tool shows the amount of emissions reduced, the cost of pur- chasing these trucks, and the fuel savings from operating these trucks in place of the old trucks. The tool also shows the impacts if an agency running a clean truck program funds only a por- tion of the new truck cost. The Incentive Level column refers to the portion of the capital cost Category Selection Notes Analysis Analysis Incentive Analysis This analysis allows the user to examine the impacts of offering various levels of incentives. Scope Year of Modification 2030 The modification year is when the modifications or replacements take place. Because the LRTP goes out to 2040 in this scenario, the user should assume modifications happen sometime before that. If 2040 is selected, the tool assumes all changes occur in 2040, and the emissions benefits will be smaller because the tool assumes the baseline fleet is cleaner in 2040. Area of Interest Metropolitan Geographic scale determines the emission factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Short Haul For this scenario, combination short-haul trucks are selected since they will operate within the metropolitan region. Type of Modification Alternative Fuel Note that only one can be selected at a time. Modifications Alternative Fuel(s) Select all (Hybrid; Electric) Click the checkmark button at the top of the column to select all. This analysis only considers strategies that will offset capital costs with fuel cost savings; in the tool, this includes only hybrid and electric options under the alternative fuel strategies. Vehicle Data Number of Trucks to Be Replaced 100 The results can be divided by 100 to calculate the per-truck impacts. Average Annual Mileage Accumulation Leave default values The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) 2000–2017 This range is based on replacing pre-2018 trucks since the Heavy-Duty GHG Phase 1 rule would have been fully phased in by 2018, and the Phase 2 regulations begin. Long-haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values ($2.13/gal diesel) Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region NPCC This electricity region includes New York. CO2 Leave default value (254 g/kWh) The default value will update depending on the Electricity Generation Region selected. Capital Costs Cost Leave default values Default values are based on recent (2015) estimates. Replacing defaults with more up-to-date or local averages will improve cost, cost-effectiveness, and payback estimates in the results. Table 22. Incentive analysis.

Tool Case Studies 47 covered by the agency. As expected, the cost-effectiveness improves (i.e., the dollar per ton goes down) as the agency covers more of the new truck cost. The last column shows the payback period, or the number of years it would take for the truck owners to save enough in fuel costs to recover their portion of the truck cost. Payback periods of over 3 years are generally not acceptable to most trucking companies or truck own- ers. Although agencies can improve their cost-effectiveness and cover more trucks by covering a smaller portion of the truck cost, truck owners may not be interested in participating if there are long payback periods. While replacing trucks with hybrid or electric trucks would result in large GHG benefits, the costs are high—over $175,000 for a hybrid and $240,000 for an electric combination short haul—resulting in long payback periods. In this example, truck owners may not be interested in partially subsidized hybrid or electric trucks because the payback periods are well over 3 years; in fact, at incentive levels of 50% or less, truck owners may never recover their share of the purchase cost over the assumed 12-year lifetime of the truck. Note that because the payback periods are based on fuel cost savings, these results are influ- enced significantly by the assumed fuel costs. The default fuel prices in the tool (e.g., $2.13 per diesel gallon) are based on current averages, which are historically low; a doubling of the diesel price could lower the payback period to 5 years for hybrid trucks and 6 years for electric trucks at a 75% incentive level. Similarly, the payback period and cost-effectiveness are affected by the truck costs, which could drop significantly for programs in future years. Thus, the user should consider refining the assumed costs in the tool when using the Incentive Analysis to calculate payback periods. 6.2 State DOT Case Study 6.2.1 Scenario In Tennessee, there has been concern about trucks producing PM emissions while idling over- night. The state DOT is considering setting up an incentive program to pay for idle-reduction technologies on heavy-duty long-haul trucks. The agency wants to know the level of incentive to provide to truck owners to make the program a success and the cost of the program to provide incentives for 200 trucks within the state. Modification CO2 Emissions Reduced (tons/yr) Additional Annual Capital Costs Annual Fuel Savings Incentive Level Cost- Effectiveness of Incentive ($/ton) Years to Pay Off Non-Incentive Capital Cost with Fuel Savings Only Hybrid 3,214 $1,484,600 $453,568 25% $115 29 50% $231 20 75% $346 10 Electric 5,526 $2,026,267 $528,349 25% $92 35 50% $183 23 75% $275 12 Table 23. Results from the incentive analysis.

48 Guide to Deploying Clean Truck Freight Strategies 6.2.1.1 Incentive Analysis – Idle Reduction The Incentive Analysis lets the user estimate the impacts of partially subsidizing modifications or replacements. The Incentive Analysis assumes that the public agency promotes strategies that reduce operating (i.e., fuel) costs for truck owners and that the owners will be willing to pay for part of the cost. This analysis type only works for strategies that reduce fuel costs. In this scenario, the state DOT is considering covering a portion of the cost for idle-reduction equipment, which will help reduce the fuel used to meet truck power demands while stationary. This analysis allows the user to compare the impacts and costs of subsidizing different types of equipment at different incentive levels. For each input option, enter the selections presented in Table 24. Results. Table 25 shows some of the results from the Incentive Analysis. For each idle- reduction option, the tool shows the amount of emissions reduced, the cost of purchasing 200 pieces of each type of equipment (default values do not include installation costs), and the amount of money saved on fuel by reducing engine idling. The results of the Incentive Analysis also show the cost implications of a program administra- tor providing various levels of funding to cover the equipment cost. The Incentive Level column refers to the portion of the capital cost covered by the program administrator, and the Total Program Costs column shows how much the administrator would pay for the equipment costs at those different incentive levels. The last column shows the payback period, or the number of years it would take for the truck owners to save enough in fuel costs to recover their portion of the equipment cost. Payback periods of over 3 years are generally not acceptable to most trucking companies or truck own- ers. Although program administrators can improve their cost-effectiveness and cover more trucks by covering a smaller portion of the equipment cost, truck owners may not be interested in participating if there are long payback periods. As shown in the results, modifying 200 trucks with the different idle-reduction options yields PM reductions ranging from 0.35 to 0.39 tons per year. Although the reductions are similar, the costs vary widely between idling equipment types. Per year, costs range from $40,000 for fuel-operated heaters to $480,000 for auxiliary power units for 200 trucks; thus, assuming a 5-year useful lifetime for the equipment, fuel-operated heaters would cost $200,000 while an APU program would cost $2.4 million. Many funding programs do not cover the full cost of the upgrade and require vehicle owners or users to cover the remaining costs. The results of the Incentive Analysis show the cost-effectiveness and years to pay off the remaining equipment cost for the truck owner (in fuel savings) if the funding agency covers 25%, 50%, or 75% of the capital cost. Because of the relatively low cost for fuel-operated heaters, a truck owner would save enough money in fuel to pay off the equipment in less than half a year, even if the agency only covers 25% of the cost. Additionally, such a program would only cost the agency $50,000 to cover 25% of the cost of heaters. In contrast, at a 25% incentive level, the more expensive APUs would take nearly 5 years to pay back in fuel savings, which is nearly the assumed useful lifetime of an APU. As with any of the clean truck strategies, an implementing agency must consider other factors beyond cost-effectiveness when selecting a strategy. For example, direct fire heaters are unneces- sary in warm climates and will not be attractive for drivers in those areas. Automatic stop/start strategies may not be popular with drivers and may require additional incentives or outreach for implementation.

Tool Case Studies 49 Category Selection Notes Analysis Analysis Incentive Analysis This analysis allows the user to examine the impacts of offering various levels of incentives. Scope Year of Modification 2020 The modification year is when the modifications take place. In this scenario, the user should select the year closest to when the program is being fully implemented. Note that the later the modification year, the lower the reduction benefits will be because the tool assumes that the average truck will be cleaner in the future. Area of Interest State Geographic scale determines the emissions factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Long Haul In the tool, idle-reduction strategies are only applied to combination long-haul trucks. Type of Modification Idle Reduction Indicated in the scenario. Modifications Idle Reduction Select all (Fuel- Operated Heaters; Auxiliary Power Units; Auto Stop/Start) Click the checkmark button at the top of the column to select all. The tool only considers strategies that apply directly to vehicles; thus, infrastructure-based strategies such as truck-stop electrification are not included here. Vehicle Data Number of Trucks to Be Replaced 200 Indicated in the scenario. Average Annual Mileage Accumulation Leave default value (86,943) Default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) Leave default values (1990–2020) Idle-reduction strategies should apply to any age truck. Long-Haul Annual Idle Hours Leave default value (964) Default values are average hours determined from MOVES by the modification year and geographic scale. Fuel Costs Cost per Unit Leave default values ($2.13/gal diesel) Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region n/a This selection does not apply; idle-reduction strategies in the tool are not fueled by electricity. CO2 n/a This selection does not apply; idle-reduction strategies in the tool are not fueled electricity. Capital Costs Cost Leave default values Default values do not include installation costs. Costs vary widely. Replacing defaults with more up-to-date or local averages will improve cost, cost-effectiveness, and payback estimates in the results. Table 24. Incentive analysis for idle reduction.

50 Guide to Deploying Clean Truck Freight Strategies 6.2.2 Scenario The Tennessee DOT has received $2 million to reduce PM emissions from urban delivery trucks operating in the state by incentivizing truck owners to replace their vehicles with alterna- tive fuel trucks. The agency wants to know which strategy is the most cost-effective and which trucks and fuels to target. 6.2.2.1 Truck Deployment Analysis – Alternative Fuels The Truck Deployment Analysis lets the user estimate the full emissions and cost impacts of different strategies to reduce PM emissions in the urban delivery trucks being targeted in this hypothetical scenario. Using this analysis, the user can compare the impacts of different alternative fuel strategies. For each input option, enter the selections presented in Table 26. Results. The results from the Truck Deployment Analysis are summarized in Table 27. Because there are gasoline options for single-unit short-haul trucks, the emissions reduction results depend on the baseline fuel of the truck being replaced. Gasoline trucks generally have lower PM emissions than equivalent diesel trucks, so PM reductions are smaller when switch- ing from gasoline to an alternative fuel truck. Certain modifications—biodiesel and renewable diesel—are drop-in fuels that replace diesel fuel and thus only apply to diesel baselines. The tool calculates emissions reductions for NOx, PM2.5, and CO2, but only the PM2.5 reduc- tions are shown in the table since they were the targeted pollutant in this scenario. In the Truck Deployment Analysis, the Additional Annual Costs column takes into account the annualized costs of the replacement trucks (the upfront cost divided by the assumed useful life of the trucks, which is 8 years for single-unit short-haul trucks) and the costs or savings in operational fuel costs. The cost-effectiveness is the annual costs divided by the emissions reduc- tion tons per year. The PM reductions from replacing 100 trucks are all below 1 ton per year. In general, the strat- egies replacing diesel trucks result in higher reductions than replacing gasoline trucks because diesel trucks have higher baseline PM emissions. Modification PM2.5 Emissions Reduced (tons/yr) Annual Fuel Savings Incentive Level Total Program Costs Cost- Effectiveness of Incentive ($/ton) Years to Pay Off Non-Incentive Capital Costs with Fuel Savings Only Fuel- Operated Heater 0.351 $345,255 25% $50,000 $28,457 0.4 50% $100,000 $56,913 0.3 75% $150,000 $85,370 0.1 Auxiliary Power Unit 0.390 $383,617 25% $600,000 $307,330 4.7 50% $1,200,000 $614,661 3.1 75% $1,800,000 $921,991 1.6 Auto Stop/Start 0.390 $383,617 25% $100,000 $51,222 0.8 50% $200,000 $102,443 0.5 75% $300,000 $153,665 0.3 Table 25. Results from the incentive analysis.

Tool Case Studies 51 Category Selection Notes Analysis Analysis Truck Deployment Analysis This analysis allows the user to estimate full costs and emissions impacts of a program. Scope Year of Modification 2020 The modification year is when the modifications take place. In this scenario, the user should select the year closest to when the program is being fully implemented. Note that the later the modification year, the lower the reduction benefits will be because the tool assumes that the average truck will be cleaner in the future. Area of Interest State Geographic scale determines the emission factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Single Unit Short Haul, Gas and Diesel Single-unit short-haul trucks most closely represent local delivery trucks targeted in this scenario. Type of Modification Alternative Fuel Indicated in the scenario. Modifications Alternative Fuel(s) Select all Click the checkmark button at the top of the column to select all. LNG is not selectable because LNG is not typically considered for short-haul trucks. Results will be displayed for each fuel separately. Strategies involving drop-in alternative fuels (i.e., biodiesel and renewable diesel) can be used in existing diesel trucks; all other alternative fuel selections assume that existing trucks are gasoline or diesel trucks that must be replaced as part of the strategy. Vehicle Data Number of Trucks to Be Replaced Leave default values (100) The results can be divided by 100 to calculate the per-truck impacts. Average Annual Mileage Accumulation Leave default values The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) Leave default values (1990–2009) The user would adjust the values to represent the ages of trucks the agency wants to target. Long-Haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region SERC (Southeastern Electric Reliability Council) This electricity region includes Tennessee. Note, however, that this selection only affects CO2 emissions. CO2 Leave default value (588 g/kWh) The default value will update depending on the Electricity Generation Region selected. Capital Costs Cost Leave default values Default values are based on recent (2015) estimates. Replacing defaults with more up-to-date or local averages will improve cost and cost-effectiveness estimates in the results. Table 26. Truck deployment analysis for alternative fuels.

52 Guide to Deploying Clean Truck Freight Strategies The costs for these strategies are high, especially since most of the alternative fuel strategies require replacing trucks. For this reason, the cost-effectiveness of these strategies is generally poor, with most above $1 million per ton of PM emission avoided. The most cost-effective strategies are the two that do not require truck replacements: biodiesel and renewable diesel; these strategies only cost the additional price per gallon above diesel. And the price for these fuels may go down in the future, which would make them more competi- tive with diesel. Note, however, that it is unusual for public agencies to support this strategy by subsidizing the cost of alternative fuels like biodiesel. Thus, there may be little opportunity for agencies to promote this strategy beyond investment in fueling infrastructure and supporting fuel suppliers by using biofuels in their own fleets. 6.2.2.2 Funding Impact Analysis The scenario indicates that the DOT received $2 million for its alternative fuel program tar- geting urban delivery trucks. Knowing the funding amount, the Funding Impact Analysis allows the user to compare the benefits of implementing all of the strategies applicable to a given truck type. For example, with this analysis, the user can compare the amount of PM reductions the agency could get with $2 million by modifying diesel trucks with alternative fuels versus exhaust retrofits versus improved tires. For each input option, enter the selections presented in Table 28. Results. As noted in Table 28, the Funding Impact Analysis has to be run twice: once for gas- oline short-haul trucks and once for diesel short-haul trucks. The results of both Funding Impact Analysis runs are combined in Table 29, where only the alternative fuel strategies are shown. Baseline Fuel Modification Annual PM2.5 Emissions Reduced (tons) Additional Annual Costs Cost- Effectiveness ($/ton) Gasoline CNG 0.070 $1,147,788 $16,392,968 Gasoline RCNG 0.070 $1,147,788 $16,392,968 Gasoline CNG + Low NOx 0.070 $1,272,788 $18,178,247 Gasoline RCNG + Low NOx 0.070 $1,272,788 $18,178,247 Gasoline Propane 0.070 $1,099,567 $15,704,268 Gasoline Hybrid 0.077 $778,112 $10,097,128 Gasoline Electric 0.091 $1,055,225 $11,593,829 Diesel CNG 0.574 $1,165,881 $2,031,296 Diesel RCNG 0.574 $1,165,881 $2,031,296 Diesel CNG + Low NOx 0.574 $1,290,881 $2,249,082 Diesel RCNG + Low NOx 0.574 $1,290,881 $2,249,082 Diesel Propane 0.574 $1,102,963 $1,921,676 Diesel B20 (Biodiesel) 0.023 $19,217 $836,162 Diesel R100 (Renewable Diesel) 0.005 $131,772 $24,368,156 Diesel Hybrid 0.583 $785,023 $1,346,329 Diesel Electric 0.599 $1,081,820 $1,804,584 Table 27. Results from truck deployment analysis.

Tool Case Studies 53 The impacts vary depending on both the fuel of the truck being replaced and the modification. The Number of Trucks to Modify/Replace column indicates how many trucks can modified with $2 million to cover capital costs. Note that drop-in alternative fuels (i.e., biodiesel and renewable diesel) are not included because the tool assumes that incentive funding applies only to vehicle and vehicle equipment capital costs. Because of the cost of replacing trucks is high, replacement programs are generally expensive and cannot fully cover the cost of many trucks. With $2 million available for capital costs, a program administrator could fund the replacement of 21 gasoline or diesel trucks with CNG trucks or 27 with hybrid trucks. Note that the tool assumes that there is no value to the scrapped diesel truck being replaced and thus assumes the program covers the total cost of a new truck. Because gasoline trucks already have relatively low PM emissions, alternative fuel trucks do not offer large PM reduction benefits. Even though diesel trucks have larger PM emissions than Category Selection Notes Analysis Analysis Funding Impact Analysis This analysis allows the user to estimate the number of trucks and emissions impacts of implementing various strategies with a known amount of funding. Scope Year of Modification 2020 The modification year is when the modifications take place. In this scenario, the user should select the year closest to when the program is being fully implemented. Note that the later the modification year, the lower the reduction benefits will be because the tool assumes that the average truck will be cleaner in the future. Area of Interest State Geographic scale determines the emission factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Single Unit Short Haul, Gas/Diesel Single-unit short-haul trucks most closely represent local delivery trucks targeted in this scenario. In the Funding Impact Analysis, only one truck type can be selected at a time. This analysis must be run again by selecting Diesel here. Funding Amount $2,000,000 Vehicle Data Average Annual Mileage Accumulation Leave default values (14,585) The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) Leave default values (1990–2009) The user would adjust the values to represent the ages of trucks the agency wants to target. Long-haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region SERC (Southeastern Electric Reliability Council) This electricity region includes Tennessee. Note, however, that this selection only affects CO2 emissions. CO2 Leave default value (588 g/kWh) The default value will update depending on the Electricity Generation Region selected. Capital Costs Cost Leave default values Default values are based on recent (2015) estimates. Replacing defaults with more up-to-date or local averages will improve cost and cost-effectiveness estimates in the results. Table 28. Funding impact analysis.

54 Guide to Deploying Clean Truck Freight Strategies Baseline Fuel Modification Number of Trucks to Modify/Replace Annual PM2.5 Emissions Reduced (tons) Cost- Effectiveness ($/ton) Gasoline CNG 21 0.015 $16,446,519 Gasoline RCNG 21 0.015 $16,446,519 Gasoline CNG + Low NOx 19 0.013 $18,231,798 Gasoline RCNG + Low NOx 19 0.013 $18,231,798 Gasoline Propane 28 0.020 $12,340,379 Gasoline Hybrid 27 0.021 $11,698,759 Gasoline Electric 20 0.018 $13,338,716 Diesel CNG 21 0.121 $2,006,306 Diesel RCNG 21 0.121 $2,006,306 Diesel CNG + Low NOx 19 0.109 $2,224,092 Diesel RCNG + Low NOx 19 0.109 $2,224,092 Diesel Propane 28 0.161 $1,505,399 Diesel Hybrid 27 0.157 $1,546,154 Diesel Electric 20 0.120 $2,025,136 Table 29. Results from both funding impact analysis runs. gasoline trucks, these alternative fuel strategies have limited PM benefits. The funding level only allows for 20 to 30 trucks to be replaced, resulting in PM reductions only in the hundreds of pounds per year. Because of the relatively small reductions in PM emissions and the high cost of truck replace- ment, these strategies are not very cost-effective for reducing PM emissions. Even with the most cost-effective option (propane or hybrid trucks), it would cost over $1.5 million to reduce 1 ton of PM emission per year using an alternative fuel option. For the Funding Impact Analysis, only the vehicle capital costs are considered when calculating cost-effectiveness. 6.3 Port Operator Case Study 6.3.1 Scenario As one of the larger pollution emitters in the region, the port authority is under pressure to improve air quality in the vicinity of the port. The board has set aggressive emissions targets for 2030 to reduce NOx and PM by x% and CO2 by y% from the on-road trucks serving the port. The port authority sustainability team wants to compare a strategy that involves accelerated retirement (truck replacements) to a strategy that involves use of RNG in low-NOx engines. There is a landfill area near the port that generates RNG. 6.3.1.1 Truck Deployment Analysis – Alternative Fuels The Truck Deployment Analysis lets the user estimate the full emissions and cost impacts of different strategies to reduce emissions from the drayage trucks being targeted in this hypo- thetical scenario. Using this analysis, the user can estimate the emissions impacts of replacing

Tool Case Studies 55 100 diesel combination-unit short-haul trucks with trucks with advanced low-NOx engines fueled by renewable CNG. The results from this analysis will be compared to the results of the accelerated retirement analysis described in the following section to address the scenario. For each input option, enter the selections presented in the Table 30. Results. The results from this analysis are summarized and described in the following section to compare the results of the two analyses. 6.3.1.2 Truck Deployment Analysis – Accelerated Retirement As described in the scenario, the results of the alternative fuel truck deployment should be compared to accelerating the deployment of new diesel trucks to replace older models. For each input option, enter the selections presented in Table 31. Category Selection Notes Analysis Analysis Truck Deployment Analysis This analysis allows the user to estimate full costs and emissions impacts of a program. Scope Year of Modification 2030 The modification year is when the modifications or replacements take place. 2030 is described as the target year in the scenario, but the user can choose to select an earlier year to represent a time during the implementation of the program. Area of Interest Port Geographic scale determines the emission factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Short Haul Port scenarios assume that truck programs only apply to drayage trucks, which are categorized in the tool as combination short-haul trucks. Type of Modification Alternative Fuel Selection indicated in the scenario. Modifications Alternative Fuel(s) RCNG + Low-NOx Engine Selection indicated in the scenario. CNG selection assumes that existing diesel short-haul combination trucks are replaced as part of the strategy. Vehicle Data Number of Trucks to Be Replaced 100 The results can be divided by 100 to calculate the per-truck impacts. Average Annual Mileage Accumulation Leave default value (39,557) The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) Leave default values (2000–2017) This range is based on replacing pre-2017 trucks since the Heavy-Duty GHG Phase 1 rule will have been fully phased in by 2017, and the Phase 2 regulations begin. Long-haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region n/a This selection does not apply to CNG replacements. CO2 n/a This selection does not apply to CNG replacements. Capital Costs Cost Leave default value ($197,152) Default value is based on recent (2015) estimates. Replacing the default with a more up-to-date or local average will improve cost and cost-effectiveness estimates in the results. Table 30. Truck deployment analysis for alternative fuels.

56 Guide to Deploying Clean Truck Freight Strategies Results. The results of the alternative fuel deployment analysis described in the previous section and of the accelerated retirement deployment analysis described previously are shown in Table 32. These analyses assume that 100 MY 2017 or older conventional diesel trucks are replaced with either low-NOx trucks fueled with renewable CNG or with newer model diesel trucks. The results show that deploying 100 trucks with low-NOx engines and using renewable com- pressed natural gas would reduce NOx by 27 tons per year, PM by 0.97 tons per year, and carbon dioxide by 8,500 tons per year. Replacing trucks with new diesel trucks would reduce NOx by 18 tons per year, PM by 0.97 tons per year, and carbon dioxide by 756 tons per year. The alterna- tive fuel option shows larger emissions reductions than from accelerated retirement because the alternative fuel strategy employs advanced natural gas engines, which reduce NOx emissions, Category Selection Notes Analysis Analysis Truck Deployment Analysis This analysis allows the user to estimate full costs and emissions impacts of a program. Scope Year of Modification 2030 The modification year is when the modifications or replacements take place. 2030 is described as the target year in the scenario, but the user can choose to select an earlier year to represent a time during the implementation of the program. Area of Interest Port Geographic scale determines the emissions factors used in the calculations. The larger geographic scales assume more freeways are used, while the smaller geographic scales have more local roads. Type of Truck Combo Unit Short Haul Port scenarios assume that truck programs only apply to drayage trucks, which are categorized as combination short-haul trucks in the tool. Type of Modification Accelerated Retirement This selection assumes that trucks of older model years (selected on the Vehicle Data page) will be replaced with trucks of later model years. Vehicle Data Number of Trucks to Be Replaced 100 The results can be divided by 100 to calculate the per-truck impacts. Average Annual Mileage Accumulation Leave default value (39,557) The default values come from the MOVES model. More annual miles will result in more emissions benefits. Range of Model Years to Modify/Scrap (inclusive) Leave default values (2000–2017) This range is based on replacing pre-2018 trucks since the Heavy-Duty GHG Phase 1 rule will have been fully phased in by 2018, and the Phase 2 regulations begin. Long-haul Annual Idle Hours n/a Only applicable for strategies involving combo-unit long-haul trucks. Fuel Costs Cost per Unit Leave default values Default values are national averages; more up-to-date and regional fuel prices can be found at the Alternative Fuels Data Center’s Fuel Prices webpage. Electricity Generation Region n/a This selection does not apply because accelerated retirement assumes replacement with new gasoline or diesel trucks, not electric trucks. CO2 n/a This selection does not apply for accelerated retirement. Capital Costs Cost Leave default value ($123,152) Default value is based on recent (2015) estimates. Replacing the default with a more up-to-date or local average will improve cost and cost-effectiveness estimates in the results. Table 31. Truck deployment analysis for accelerated retirement.

Tool Case Studies 57 and assumes that the trucks are fueled with CNG produced from renewable sources (such as landfill gas in this scenario), which reduces life-cycle carbon emissions. Based on the estimates from the tool, replacing 100 diesel drayage trucks with ones having low- NOx engines will cost $1.6 million per year for the assumed 12-year useful life of combination trucks; thus, the upfront capital cost is $19.7 million for the replacements (excluding operations and maintenance costs). Replacing an older fleet with new diesel trucks will cost $1.0 million per year, or $12.3 million total for the trucks. Although trucks with low-NOx engines and RCNG show greater NOx emission reductions than with new diesel trucks, they cost over 50% more; thus, an accelerated retirement program could provide similar NOx and PM reductions but at a lower cost. If the port authority wanted to target a small number of trucks and get the most emissions reductions regardless of cost, the low-NOx strategy might be the best. However, if there is limited funding and the port wants to get the most NOx and PM emissions possible with that funding even if it means replacing more trucks, the accelerated retirement program might be a better option. Baseline Fuel Modification Annual Emissions Reduced (tons) Capital Cost (annualized) Cost-Effectiveness ($/ton) NOx PM2.5 CO2 NOx PM2.5 CO2 Diesel RCNG + Low NOx 26.88 0.967 8,500 $1,642,933 $72,571 $2,017,375 $230 Diesel Accelerated Retirement 18.30 0.967 756 $1,026,267 $48,504 $918,107 $1,174 Table 32. Results of alternative fuel deployment analysis and accelerated retirement deployment analysis.

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TRB's National Cooperative Highway Research Program (NCHRP) Research Report 862: Guide to Deploying Clean Truck Freight Strategies provides decision makers with a guide to assist in the potential deployment of fuel-efficient and low-emission truck freight strategies. The guide includes an analytical tool and a user manual to identify and evaluate appropriate strategies that can be deployed at the state, regional, and local levels. The guide will allow transportation practitioners to encourage the best use of the technological, operational, and infrastructure investment alternatives that mitigate truck freight impacts on criteria air pollutants, fuel efficiency, and greenhouse gas emissions.

Disclaimer - This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences, Engineering, and Medicine or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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