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An Update on Public Transportation's Impacts on Greenhouse Gas Emissions (2021)

Chapter: Appendix A - GHG Analysis Methodology

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Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
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Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
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Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
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Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
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Page 40
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
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Page 41
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
Page 41
Page 42
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
Page 42
Page 43
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
Page 43
Page 44
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
Page 44
Page 45
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
Page 45
Page 46
Suggested Citation:"Appendix A - GHG Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2021. An Update on Public Transportation's Impacts on Greenhouse Gas Emissions. Washington, DC: The National Academies Press. doi: 10.17226/26103.
×
Page 46

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36 To allow readers to walk through the analytical steps used, this appendix provides details of the public transportation GHG analysis summarized in the main body of the report, including calculation formulas and reference tables for the GHG emissions factors used in the assessment. Vehicle Typology The NTD provides transit data by mode names and vehicle types. For the purposes of this study, these have been summarized into six mode types: bus, commuter rail, ferry, heavy rail, light rail, and van (see Table A-1). Calculating Emissions from Transit Vehicle Activity The GHG calculations are activity × emissions factor by transit agency, mode, and fuel type, as described here: • CO2 – Compressed natural gas, diesel, gasoline, hydrogen, liquefied natural gas, liquefied petroleum gas: Gallons of fuel use × kg CO2 per gallon = kg CO2 – Electricity: kWh of electricity use × kg CO2 per kWh = kg CO2 – Biofuels (biodiesel and ethanol): Gallons of fuel use × kg CO2(b) = kg CO2(b); biogenic CO2 reported separately • CH4 and N2O – Hydrogen; rail and ferry diesel and biodiesel: Gallons of fuel use × kg GHG per gallon × GWP = kg GHG CO2e – Electricity: kWh of electricity use × kg GHG per kWh × GWP = kg GHG CO2e – Other bus and van fuels: Miles of vehicle travel × kg GHG per mile × GWP = kg GHG CO2e. (In cases where miles of vehicle travel by fuel were unreported, gallons of fuel use × kg GHG per gallon × GWP = kg GHG CO2e was substituted.) ■ CNG ■ Diesel fuel ■ Ethanol ■ Motor gasoline ■ LNG ■ LPG ■ Biodiesel Upstream (“well-to-pump”) CO2e calculated separately based on fuel use. A P P E N D I X A GHG Analysis Methodology

GHG Analysis Methodology 37   Activity Data The activity data used to calculate emissions from transit revenue vehicles are the energy use data and vehicle mileage data reported in the NTD. The most recent data year at the time of the analysis was 2018. NTD data for 2019 were released in November 2020, after the completion of the analysis in this report. These data show a similar overall level of transit ridership to that of 2018, indicating that the 2018 analysis is generally comparable to 2019. There were 54.4 billion passenger miles traveled over 9.9 billion passenger trips in 2019, and 54 billion passenger miles over 9.9 billion passenger trips in 2018 (FTA 2020a). Table A-2 presents a summary of the fuel use activity data used for the analysis. Table A-3 summarizes vehicle mile data by mode and fuel. To better match fuel use data and represent the full range of transit vehicle activity, total vehicle miles were used rather than revenue vehicle miles. Energy use data were only reported by “full reporters” to the NTD; as such, smaller transit agencies are left out of this activity dataset. Energy, vehicle, and passenger data from 523 “full reporter” transit agencies (at least 30 vehicles and/or fixed guideway or high intensity busway) are included in this analysis. NTD Mode NTD Mode Name Mode Type NTD Vehicle Type Mode Type MB Bus Bus Over-the-Road Bus Bus RB Bus Rapid Transit Bus Articulated Bus Bus CB Commuter Bus Bus Bus Bus IB Intercity Bus (Rural Module) Bus School Bus Bus PB Publico Bus Double Decker Bus Bus TB Trolleybus Bus Trolleybus Bus AR Alaska Railroad Commuter Rail Commuter Rail Passenger Coach Commuter Rail CR Commuter Rail Commuter Rail Commuter Rail Self- Propelled Passenger Car Commuter Rail YR Hybrid Rail Commuter Rail Commuter Rail Locomotive Commuter Rail FB Ferryboat Ferry Ferryboat Ferry HR Heavy Rail Heavy Rail Heavy Rail Passenger Car Heavy Rail CC Cable Car Light Rail Vintage Trolley Light Rail IP Inclined Plane Light Rail Inclined Plane Vehicle Light Rail LR Light Rail Light Rail Monorail Vehicle Light Rail MG Monorail and Automated Guideway Light Rail Streetcar Rail Light Rail SR Streetcar Rail Light Rail Cable Car Light Rail DR Demand Response Van Aerial Tramway Light Rail JT Jitney Van Light Rail Vehicle Light Rail VP Vanpool Van Automated Guideway Vehicle Light Rail Minivan Van Automobile Van Van Van Cutaway Van Other Van Sports Utility Vehicle Van Table A-1. Mode type typology and NTD mode name and vehicle type.

38 An Update on Public Transportation’s Impacts on Greenhouse Gas Emissions Fuel Use (Gallons and kWh) Bus Commuter Rail Ferry Heavy Rail Light Rail Van Total Biodiesel (gallons) 46,590,869 143,818 1,100,743 – – 1,236,833 49,072,263 Compressed Natural Gas (gallons) 173,772,949 – – – – 8,286,190 182,059,139 Diesel Fuel (gallons) 372,781,007 101,488,109 41,233,792 – – 16,395,644 531,898,552 Electric Battery (kWh) 9,895,626 – – – – 812 9,896,438 Electric Propulsion (kWh) 71,459,861 1,733,406,171 – 3,873,732,974 1,029,184,381 – 6,707,783,387 Ethanol (gallons) – – – – – 46,850 46,850 Gasoline (gallons) 9,972,623 – – – – 99,372,365 109,344,988 Hydrogen (gallons) 137,559 – – – – – 137,559 Liquefied Natural Gas (gallons) 2,754,682 – – – – 528,447 3,283,129 Liquefied Petroleum Gas (gallons) 2,364,130 – – – – 7,626,854 9,990,984 Table A-2. Public transportation fuel use by vehicle type, 2018. Vehicle Miles (includes passenger car miles for rail) Bus Commuter Rail Ferry Heavy Rail Light Rail Van Total Biodiesel 189,697,235 230,681 101,738 – – 13,845,889 203,875,543 Compressed Natural Gas 517,119,149 – – – – 60,242,887 577,362,036 Diesel Fuel 1,518,684,875 201,594,805 4,485,677 – – 130,312,075 1,855,077,431 Electric Battery 4,230,386 – – – – 5,236 4,235,622 Electric Propulsion 10,727,845 211,215,029 – 709,171,041 132,959,517 – 1,064,073,432 Ethanol – – – – – 515,536 515,536 Gasoline 24,243,615 – – – – 905,167,673 929,411,288 Hydrogen 729,080 – – – – – 729,080 Liquefied Natural Gas 3,166,647 – – – – 2,453,751 5,620,398 Liquefied Petroleum Gas 3,018,975 – – – – 39,746,015 42,764,990 Total 2,271,617,806 413,040,515 4,587,415 709,171,041 132,959,517 1,152,289,062 4,683,665,356 Table A-3. Public transportation vehicle miles by fuel type and vehicle type, 2018.

GHG Analysis Methodology 39   The authors used service and vehicle inventory data as reported by reduced reporters in the NTD to estimate the energy use and emissions of those systems based on the performance indicators calculated from the full reporters. Energy use and passenger miles were estimated for 384 reduced and other reporter transit agencies. The NTD reporting structure required several data changes to fit GHG accounting needs: • In cases where more than one fuel type was associated with a vehicle (such as a flex-fuel vehicle using both gasoline and compressed natural gas), the fuel estimation for reduced reporters was allocated on a 60% fossil fuel, 40% alternative fuel basis. • In cases where the fuels used were fossil fuel and electric, the fuel estimation was allocated at 80% fossil fuel and 20% electric. • Vehicle mileage for multi-fuel vehicles was allocated using these same proportions. The mileage of vehicles with more than one fuel was approximately 0.3% of total vehicle miles. • NTD does not separate biodiesel bus miles from diesel bus miles, so those mileages were allocated proportional to fuel use. The resulting estimated biodiesel vehicle mileage was 4% of total vehicle miles. • In cases where fuel usage was reported as “other” or with no type, it was allocated by type according to vehicle technology information reported by the agency or other indicators of likely fuel type. Vehicles traveling approximately 4% of total vehicle miles, largely commuter rail vehicles, were included in these estimations. The net result was a database of fuel use and vehicle mileage by vehicle type among 907 transit agencies. The reduced and other reporter agencies are 42% of the agencies in this dataset, but they include just 5% of the transit vehicles (7,172 of 139,689 total transit vehicles) and 4% of the transit vehicle miles in the study (164,634,348 of 4.7 billion miles). The dataset in this report excludes 2,035 rural, reduced asset, and other transit agencies that did not report enough data to NTD to enable estimation of vehicle activity by fuel. The included activity data analyzed in this report from full reporters and reduced reporter estimations equate to 82% of 2018 miles in the APTA Public Transportation Fact Book, based on which the excluded activity is primarily bus and van transit (APTA 2019). A close examination of vehicle-level activity reporting by agency and fuel finds some irregu- larities that could not easily be addressed within the scope of this project. For example, the vehicle mileage by fuel reporting does not always match agency total mileage by mode. Also, NTD documentation suggests that biodiesel be reported as diesel, so there is likely to be some mixed reporting of those fuels. The NTD does not report newer or less common fuels, such as renewable diesel, so those may be mixed in with biodiesel or other fuels. At a nationwide scale, none of these variances are large enough to have a meaningful impact the overall results of the study. The spreadsheet tool that accompanies this project includes transit-agency–level data. Emissions Factors The GHG analysis used commonly accepted emissions factors for the transportation fuels listed previously, as follows (see also Table A-4): • The CO2 values for fuels other than electricity were sourced from “Emissions Factors for Greenhouse Gas Inventories” (U.S. EPA 2020b). This is a well-documented source of up-to-date data that aligns with emissions factors in other major reporting programs. Another straight- forward source for emissions factors in common measurement units that can be used as a reference is the Climate Registry’s “2020 Default Emissions Factors” document (TCR 2020). • EPA emissions factors (U.S. EPA 2020b) were also used for CH4 and N2O emissions.

40 An Update on Public Transportation’s Impacts on Greenhouse Gas Emissions • Intergovernmental Panel on Climate Change Fifth Assessment Report (AR5) 100-year GWPs for CH4 (28) and N2O (265) were used to convert those GHGs to CO2e (Myhre et al. 2013). • Upstream, “well-to-pump” emissions factors from Argonne National Laboratory’s GREET 2020 model, using high heating values, were used to calculate the upstream emissions associated with transit vehicle operations as a separate figure from direct emissions (see Table A-5) (Wang et al. 2020). • For electricity use, U.S. EPA’s eGRID 2018 Summary Tables were used to assign CO2, CH4, and N2O electricity emissions factors to each transit agency by matching the transit agency headquarters zip code in NTD to the corresponding eGRID Subregion (U.S. EPA 2020a). An estimate for Puerto Rico was developed using local power production information, and Source: U.S. EPA 2020a, U.S. EPA 2020b. Emissions Factors Per Energy Unit All Vehicles CO2 Units CH4 CO2e N2O CO2e Units CNG 7.32 kg/gallon of diesel equivalent 0.00388 0.00356 kg/gallon of diesel equivalent Diesel Fuel 10.21 kg/gallon 0.01148 0.02120 kg/gallon Electricity, National Average 0.43 kg/kWh 0.00108 0.00144 kg/kWh Electricity, Lowest Subregion 0.11 kg/kWh 0.00023 0.00024 kg/kWh Electricity, Highest Subregion 0.76 kg/kWh 0.00235 0.00325 kg/kWh Motor Gasoline 8.78 kg/gallon 0.01064 0.02120 kg/gallon Hydrogen (Wang et al. 2020) 14.48 kg/gallon of diesel equivalent 1.49562 0.08684 kg/gallon of diesel equivalent LNG 4.50 kg/gallon 0.00388 0.00356 kg/gallon LPG 5.68 kg/gallon 0.00784 0.01590 kg/gallon CO2 (b) Units CH4 CO2e N2O CO2e Units Biodiesel 9.45 kg/gallon 0.00392 0.00265 kg/gallon Ethanol 5.75 kg/gallon 0.00252 0.00265 kg/gallon By Vehicle Type Buses (Also Used for Vans) CH4 CO2e N2O CO2e Units CNG 0.28000 0.00027 kg/mile Diesel Fuel 0.00027 0.01142 kg/mile Electricity National Average 0.00108 0.00144 kg/kWh Motor Gasoline 0.00026 0.00087 kg/mile LNG 0.28000 0.00027 kg/mile LPG 0.00095 0.00451 kg/mile Biodiesel 0.00025 0.01140 kg/mile Ethanol 0.00062 0.00848 kg/mile Locomotives Diesel Fuel 0.02240 0.06890 kg/gallon Electricity National Average 0.00108 0.00144 kg/kWh Ships and Boats Diesel 0.00868 0.13250 kg/gallon Personal Vehicles Passenger Car 0.00025 0.00212 kg/mile Light-Duty Truck 0.00034 0.00265 kg/mile All Light-Duty Vehicles 2018 0.00027 0.00224 kg/mile Electricity National Average 0.00108 0.00144 kg/kWh Table A-4. Direct and indirect emissions factors.

GHG Analysis Methodology 41   that estimate was applied to the U.S. Virgin Islands as well [Center for Climate Strategies (CCS) 2014]. Table A-4 shows the national high, low, and average electricity emissions factors for reference, but the full set of eGRID subregions were used in the analysis. – Note that some transit agencies are producing renewable energy or sourcing grid- connected renewable electricity that was cleaner than their grid subregion. There was no national data source for those contractual arrangements so they are not included in this report. However, eGRID includes utility-scale grid-connected renewables in its regional averages. • GREET (Wang et al. 2020) life-cycle emissions factors for compressed gaseous hydrogen from natural gas without CO2 sequestration were applied to hydrogen fuel use. For the purposes of this report, the resulting emissions are classified as indirect rather than upstream to allow a more apples-to-apples comparison to indirect electricity emissions. Motor gasoline in the United States is typically oxygenated to some degree with ethanol. This is often labeled E10 or 10% ethanol, but the actual makeup is variable by season, location, distributor, and more, and customers rarely receive this information. For this reason, most GHG accounting protocols do not require accounting of this share of motor gasoline CO2 separately, and the authors have not done so in this report (TCR 2019). There is ambiguity in the NTD about fuel units that adds a small amount of uncertainty to the GHG calculations. Transit agencies that use compressed natural gas are encouraged to report that fuel in either gallons of gasoline equivalent [114,000 British Thermal Units (BTU)] or gallons of diesel equivalent (138,000 BTU), but there is no notation in the publicly accessible data indicating which unit has been used. For the purposes of this study, the compressed natural gas emissions factors were converted into gallons of diesel equiva- lent. Similar questions arise about all of the fuels reported in gallon equivalents (hydrogen, liquefied natural gas, and liquefied petroleum gas)—the emissions factor source may not be using the same gallon unit as the agency reporters. These fuels make up just 15% of the total emissions results, so this ambiguity of units does not have a significant impact on the study findings at a broad scale. Fuel GHG Emissions CO2e Units Fuel Description Biodiesel 3.70 kg per gallon Biodiesel Production from Soybeans CNG 2.16 kg per gallon of diesel equivalent Compressed Natural Gas from North American Natural Gas Diesel Fuel 2.17 kg per gallon U.S. Low-Sulfur Diesel Electricity National Average 0.02 kg per kWh Electricity Distributed net of Electricity Not Distributed (the same as electricity transmission and distribution (T&D) losses in eGRID) Ethanol 4.08 kg per gallon Average Ethanol Produced in the U.S. (at the Refueling Station) Hydrogen Life-cycle emissions factor used as indirect emissions factor, so no upstream emissions assumed LNG 1.62 kg per gallon Liquefied Natural Gas as a Transportation Fuel from North American Natural Gas LPG 1.28 kg per gallon Liquefied Petroleum Gas from Natural Gas and Petroleum Motor Gasoline 2.60 kg per gallon Reformulated Gasoline (E10) Blending and Transportation to Refueling Station Source: Wang et al. 2020. Table A-5. Upstream (well-to-pump) emissions factors.

42 An Update on Public Transportation’s Impacts on Greenhouse Gas Emissions Transportation Efficiency: Calculating Avoided Emissions from Transit Passenger Travel The net GHG benefits of transit as calculated for this project include the avoided GHG emissions of private automobile use by transit passengers, also called transportation efficiency. The NTD-reported passenger mile data were the basis for this analysis using the calculations described here: • Avoided CO2 – Passenger miles × mode shift factor (0.329) = avoided vehicle miles – Avoided vehicle miles/miles per gallon (22.5 2018 FHWA on-road light-duty vehicles) = avoided gallons of fuel – Gallons of fuel use × kg CO2 per gallon = kg CO2 • Avoided CH4 and N2O – Avoided miles of vehicle travel × kg GHG per mile × GWP = kg GHG CO2e • Upstream GHGs (well-to-pump) – Calculated using GREET emissions factors Mode Shift Factor APTA’s 2017 Who Rides Public Transportation provided a summary of 69 transit agency surveys, representing the choices of 233,925 passengers (APTA 2017). An update to APTA’s 2017 dataset adds four newer transit agency surveys (APTA 2020). These newer surveys now allow transit passengers to indicate that they would otherwise use ridehailing services such as Uber or Lyft. Adjusting for the “other transit” category, the vehicle alternatives passengers indicated in the newest APTA summary are 12% ridehailing, 14% drive alone, 10% carpool (which is divided by 2.5 passengers per carpool for this analysis), and 3% taxis (APTA 2020). The result is that 32.9% of transit passenger miles would otherwise be replaced by personal vehicle miles. The term “personal vehicle” is used to indicate automobiles and light trucks and includes ridehailing and taxi vehicles for hire. The average personal vehicle on the road in 2018 had a fuel economy of 22.5 mpg. Mode Shift Factor as Applied in Previous Studies Previous analysis of transit’s GHG impact approached passenger GHG savings differently. A study using 2005 NTD data apportioned every passenger mile to an avoided vehicle trip and used vehicle occupancy to estimate total VMT savings (1.08 occupancy for work trips and 1.90 occupancy for other trips) (Davis and Hale 2007). The result was an effective mode shift factor of 0.745, or about 75% of transit passenger miles replaced by personal vehicle miles. A lower mode shift factor accounting for trips that would have otherwise been taken by zero-carbon modes, including walking, biking, or no trip, such as are used here, is a better match to real-world activity. However, there is significant local variability that any national value leaves out, and more granular data should be developed. As mentioned previously, this study uses the latest APTA survey data to calculate a mode shift factor of 0.329, meaning that 33% of transit passenger miles would otherwise be replaced by personal vehicle miles. APTA’s “Recommended Practices: Quantifying Greenhouse Gas Emissions from Transit” (APTA 2018), uses older APTA 2017 survey data and finds a slightly lower mode shift factor (0.302) for transit systems serving areas with 1 million residents or more, but a higher factor (0.508) for transit systems serving less than 1 million people. These data show that in smaller communities, fewer transit passengers indicate that they would otherwise walk, and more indicate that they would otherwise get a ride from someone else.

GHG Analysis Methodology 43   Applying the older mode shift data used in the APTA Recommended Practice to the 2018 NTD data results in only a small difference nationally (4%) from the analysis in this study, but individual agencies analyzing their GHGs should use a locally appropriate factor. A breakout of the newest survey data by transit service area population was not available for this study, and the authors concluded that there was value to using the updated numbers because ridehailing is such a significant new transportation choice; however, further research into this factor would be beneficial for future analyses. Personal Vehicle Emissions The emissions savings from avoided personal vehicle use are based on a national average fuel economy for automobiles and light trucks of 22.5 mpg (FHWA 2019a) and the GHG emissions factors for motor gasoline. Table A-6 shows that the GHG footprint for a typical gasoline-powered personal vehicle in 2018 was 0.51 kg CO2e per mile, or 5.9 MT CO2e at the average annual driving distance of 11,556 miles (FHWA 2019a). Electric vehicles made up approximately 0.4% of all light-duty vehicles in 2018 (EEI 2019 and FHWA 2019a). The transportation efficiency calculations do not include electric personal vehicles because of a lack of data about the location of electric vehicles and their limited preva- lence in 2018; however, in the future this will become a more important factor, and data about electric vehicle adoption by urbanized area should be cultivated. Table A-6 shows that a personal electric vehicle driven 11,556 miles in 2018 would have contributed 0.5 to 2.7 MT CO2e emis- sions, depending on the emissions factor associated with the electricity powering the vehicle. Chapter 3 discusses the GHG impacts of personal electric vehicles on the personal vehicle emissions savings on a national level for 2018. Emissions from first- and last-mile or transit access by passengers are not included in this study due to data constraints, but transit access modes are an important part of transit’s overall contribu- tion to community GHG solutions and should be considered as part of climate action planning. Land Use Efficiency: Calculating Avoided Emissions from Community Travel The GHG emissions saved by the broader impact of transit on VMT in the community, such as through shorter trips and fewer personal vehicle trips (also called indirect effect), are a part of the net GHG benefits of transit in this study. NTD-reported passenger mile data were the basis for this analysis using the calculations described here: • Avoided CO2 – Passenger miles × mode shift factor (0.329) = avoided passenger vehicle miles – [(Avoided passenger vehicle miles × transit multiplier) − avoided passenger miles] = avoided community vehicle miles Personal Gasoline Vehicle Personal Electric Vehicle Fuel Economy (FHWA 2019a) 22.5 mpg 30 kWh per 100 miles Direct and Indirect GHG Emissions per Vehicle Mile (kg CO2e) 0.39 Upstream GHG Emissions per Vehicle Mile (kg CO2e) 0.12 Total GHG Emissions per Vehicle Mile (kg CO2e) 0.51 2018 Average Miles Driven per Vehicle in U.S. (FHWA 2019a) 11,556 Average 2018 U.S. Personal Vehicle GHG Footprint (MT CO2e) 5.9 0.03 to 0.23 0.01 0.04 to 0.24 11,556 0.5 to 2.7 Table A-6. Personal vehicle GHG emissions, 2018.

44 An Update on Public Transportation’s Impacts on Greenhouse Gas Emissions – Avoided community vehicle miles/miles per gallon (22.5 2018 FHWA on-road light-duty vehicles) = avoided gallons of fuel – Gallons of fuel use × kg CO2 per gallon = kg CO2 • Avoided CH4 and N2O – Avoided community vehicle miles × kg GHG per mile × GWP = kg GHG CO2e • Upstream GHGs (well-to-pump) – Calculated using GREET emissions factors Transit Multiplier The transit multiplier is the total VMT reduction associated with transit, including both trans- portation efficiency and land use efficiency VMT savings divided by the transportation efficiency VMT savings to create a multiplier. The multiplier allowed the researchers to take research find- ings about transit’s impact on VMT in 28 communities and apply them to every transit agency in this study in a regionally specific way. Transit multiplier = (transportation efficiency VMT) + (land use efficiency VMT) (transportation efficiency VMT) • Transportation Efficiency: VMT reduction of transit passengers (also called transit direct effect on VMT) • Land Use Efficiency: VMT reduction in the community. Even residents who do not ride transit themselves save VMT, such as through shorter trips and fewer driving trips (also called transit indirect effect on VMT). The transit multipliers for this study were developed using a multilevel structural equation model and a database of household travel survey data in 28 regions matched with socioeconomic, built environment, and regional characteristics. The model found that the effect of transit in the community is much larger than the avoided auto use of transit passengers alone, but rather changes in the built environment in communities that are well served by transit create VMT savings several times larger than that passenger impact. The modeling found a range of multi- pliers from 6.1 to 9.5 in the 28 regions. The average transit multiplier, using the combined data of the 28 regions, was 7.43 (see Appendix B). The modeling generated a set of equations that were used to estimate the transit multiplier for every transit agency in this study based on transit passenger miles per capita, which was calculated as NTD passenger miles divided by the sum of urbanized area (UZA) populations for all of the UZAs in the transit agency service area. The transit multipliers were calculated using the following formulas based on coefficients developed through the model: Transportation efficiency VMT: = [0.001 × (−2.882 + (0.002 × (transit passenger miles per capita − 130.05)))] + [0.0017 × 2.871 × (−2.882 + (0.002 × (transit passenger miles per capita – 130.05)))] Land Use Efficiency VMT: = [0.093 × (−0.098 + (0.0004 × (transit passenger miles per capita – 130.05)))] + [−0.091 + (−0.0001 × (transit passenger miles per capita – 130.05))]

GHG Analysis Methodology 45   Personal Vehicle Emissions The GHG emissions associated with avoided personal vehicle use in the community are calculated based on avoided VMT using the same method described in the Personal Vehicle Emissions subsection of the Transportation Efficiency: Calculating Avoided Emissions from Transit Passenger Travel section of this appendix. Previous Research on Land Use Efficiency The previously mentioned study of 2005 transit impacts found that transit led to emissions reductions of 37 MMT CO2 annually in the United States, including a land use multiplier— transit’s indirect impact on household VMT—of approximately 2× (Bailey et al. 2008). This means that for every personal vehicle mile saved by a transit rider, nearly two more vehicle miles are saved in the community. More recent analysis of Portland, Oregon, has shown the transit land-use multiplier to be 3× (Ewing and Hamidi 2014, Gallivan et al. 2015). Table A-7 provides a summary of land use multiplier studies and highlights the range of estimates in this area of research. The range of 1.4 to 9 in the research comes both from a range of research approaches and real-world variable impact across places. This is still a new area of study, and there have been inconsistencies in the scope of the studies, in the land use measures that have been used, and with the survey methods and statistical modeling techniques that have been used. Some studies were national in scope (e.g., Neff 1996); others focused on particular metro- politan areas or cities. Some relied on data aggregated to geographic units; others used individual- or household-level data. Holtzclaw (2000) used a straightforward VMT and transit passenger mile per capita comparison between San Francisco and less transit-oriented suburbs. Bailey et al. (2008) and several later studies used a structural equation model statistical approach that controlled for characteristics of the area, including land use, transportation systems, and demographics. Several issues arise when applying the existing land-use multiplier literature to NTD transit activity data. First, what is being multiplied? Many study findings are described in terms of total Study Study Areas Land Use Multiplier Pushkarev and Zupan (1982) U.S. metro areas with at least 2 million population 4 Neff (1996) U.S. urbanized areas 5.4–7.5 Newman and Kenworthy (1999) 32 global cities 5-7 Holtzclaw (2000) Matched pairs in the San Francisco Bay Area 1.4–9 Bailey et al. (2008) Entire United States 1.9 New York Metropolitan Transportation Authority (2009) MTA service territory 1.29–6.34 Los Angeles Metropolitan Transportation Authority (2012) Los Angeles County 5.3 Ewing and Hamidi (2014) Portland’s Westside light-rail transit 3.04 Litman (2020) 130 U.S. cities 4 Table A-7. Summary of land use multiplier studies.

46 An Update on Public Transportation’s Impacts on Greenhouse Gas Emissions VMT saved in the community per transit passenger mile. This combines the direct VMT savings of transit passengers with the broader VMT savings due to transit’s impacts on land use. Furthermore, it appears that some of the research includes a vehicle occupancy figure within the multiplier, while in other approaches a vehicle occupancy adjustment is external. Similarly, the mode shift element for transit passengers is incorporated in variable ways. This study makes explicit the application of the elements of its GHG calculations in the methodology and accompanying materials to help improve transparency in this arena. To avoid confusion with previous research, the authors refer to the value developed in this study as a “transit multiplier.” As described in Chapter 2, the transit multiplier when applied to NTD passenger mile data using the formula [((Avoided passenger vehicle miles × transit multiplier) − avoided passenger miles) = avoided community vehicle miles] results in VMT reductions in the range of previous studies. Exclusion of Congestion Impacts One of the major changes when the APTA Recommended Practice was updated in 2018 was the exclusion of congestion relief in the GHG benefit calculations (APTA 2018). Previously, a reduction in personal vehicle GHG emissions was calculated based on fewer personal vehicles on the road due to transit ridership resulting in improved efficiency among the remaining personal vehicles. Davis and Hale (2007) found a 3 MMT CO2 benefit from public transpor- tation due to congestion relief nationally as the transportation efficiency effect enabled more efficient use of private vehicles. However, there is now a lack of consensus in the literature on transit’s congestion impacts. The literature on the subject is well summarized in the APTA Recommended Practice, and inclusion of transit congestion relief as part of a GHG impact assessment is no longer recom- mended. Therefore, the researchers have excluded congestion from this project as well. The authors looked at other sources of congestion data and analysis, such as FHWA’s Status of the Nation’s Highways, Bridges, and Transit: Conditions and Performance, 23rd Edition (FHWA 2019b), but have not found a published data source that would allow adequate analysis of the full range of congestion impacts within the scope of this research effort. APTA’s Multimodal Urban Mobility Index, under development, provides an innovation in measuring transportation access across modes but does not yet readily translate to national GHG impacts (Economic Development Research Group, Inc. 2018). Additional Method Resources Appendix B provides a full technical description of the modeling used to develop the transit multipliers used in this study. In addition, for those looking to calculate transit GHG emissions themselves, the spreadsheet tool published with this report includes several sample GHG impact calculations and the emissions factor tables from this appendix, along with the 2018 GHG impact findings by individual transit agency.

Next: Appendix B - Transit Multiplier Methodology »
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 An Update on Public Transportation's Impacts on Greenhouse Gas Emissions
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Transportation is a major source of the greenhouse gas (GHG) emissions that are causing climate change. As communities work to cut emissions and become more resilient, they are including public transportation advances as a significant part of their climate action strategies.

The TRB Transit Cooperative Research Board's TCRP Research Report 226: An Update on Public Transportation's Impacts on Greenhouse Gas Emissions provides updated national analysis of public transportation’s role as a climate solution by documenting its 2018 GHG impacts.

Supplemental materials to the report include three factsheets (Fact Sheet 1, Fact Sheet 2, and Fact Sheet 3); various key findings regarding transit as a climate solution; a PowerPoint presentation summarizing the findings and research and a template for transit agencies to add their own data for climate communications; and a simple spreadsheet tool that provides this study’s 2018 GHG impact findings by transit agency and allows the user to apply several of the future scenarios to see how their transit agency’s GHG impacts change with electrification, clean power, and ridership increases.

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