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From page 17... ... 3 2 Performance Evaluation Framework 2.1 Methodology Overview The background section of the terms of reference for this project noted the limitations of using averages for the energy performance of rail and other competing modes. In particular it noted that:  Passenger rail fuel consumption data may not fully represent impacts, since they are based on broad averages that include many different variations in distance traveled, amenities provided, speeds, operating environment, type of train operated, and form of propulsion. Read the entire page →
From page 18... ... 4 simulation comparison; however, the user also has the ability to modify the default characteristics or define new characteristics for each mode if desired. The requirement for an "evaluation of opportunities to improve fuel and energy efficiency and reduce GHG emissions for intercity and commuter passenger rail" means that the rail simulation module requires additional details on the technological attributes of equipment such that the energy/emissions performance of alternative technologies can be assessed. Read the entire page →
From page 19... ... 5 The mode-specific data constraints and associated methodological details for rail, bus, LDV and air are each discussed in the following subsections. 2.3 Highway Modes (LDV and Bus) Read the entire page →
From page 20... ... 6 attained by longer distance intercity scheduled carriers and the average occupancy reported for all operators surveyed in the ABA would be higher than that of scheduled carriers (since charter carriers realize very high load factors and account for over 50% of the operators surveyed) Read the entire page →
From page 21... ... 7  the EPA's sales-weighted composite vehicle,  a composite based on the estimated mix of personal LDVs used in local trips,  a composite based on the estimated mix of personal LDVs used for intercity trips, and  a composite based on the estimated LDV mix for taxis. In relation to the EPA sales-weighted vehicle-mix, the vehicle composite for local commuting assumes a shift from large to smaller vehicles, the intercity travel mix assumes a shift from smaller to larger vehicles and the taxi mix assumes a larger proportion of midsize vehicles, no pickup trucks and a higher proportion of hybrid vehicles (Note: these alternates are illustrative estimates at this point – to be refined as data is located) Read the entire page →
From page 22... ... 8 A similar process is used to characterize the 2011 "driven fleet" to reflect the relative performance of older vehicles with an appropriate vehicle age distribution. The algorithm processor assumes that 50% of the difference in fleet-average fuel economy of the new model year relative to the 2011 sales-weighted fleet is due to drive-train efficiency (engine and/or transmission efficiency is scaled by 50% of the fuel economy difference) Read the entire page →
From page 23... ... 9 Table 2. MY 2011 LDV Sales-Weighted Characterization Data Model Development Phase Class Derived Averages for EPA Classes of MY 2011 LDVs Derived Composites small mid/S W MV/ SmtSUV Lg/cSUV / smPU PUtruck LgtSUV Local d) Read the entire page →
From page 24... ... 10 2.3.3 Adjustment of LDV Characteristics to Reflect Driving Conditions The characteristics developed above are for the running performance of LDVs. All LDVs experience worse fuel economy on start-up and this initial fuel penalty increases with colder temperatures. Read the entire page →
From page 25... ... 11 Table 3. Adjustments Made to Test-based Characteristics to Reflect Actual Driving Conditions and the Driven Fleet Factor Assumption / Treatment in the Model Source Reference Road/tire condition resistance factors An estimated 10/30/50/10 mix of concrete/smooth/medium-/rough-asphalt pavement is adopted relative to an estimated 30/70 mix of concrete/smooth-asphalt for test conditions. Read the entire page →
From page 26... ... 12 CY usage distribution in 2011 as adopted in its GHG inventory [EPA, 430-R-12-001, April, 2012] reduces the fleet efficiency to 91.32% of the sales-weighted 2011 MY's efficiency (or 1/.9132 = 1.095 times more fuel is consumed by the 2011 driven-fleet) Read the entire page →
From page 27... ... 13 The EPA has developed a range of speed profiles to characterize the influence of traffic congestion on individual vehicle speed variations on freeway, urban and arterial streets. However, no single drive schedule provides a realistic characterization of a specific commuter or intercity trip. Read the entire page →
From page 28... ... 14 The air mode has some complexities that require flight segmentation in order to assess GHG intensity. The warming effects of emissions from aircraft at cruise altitudes are higher than emissions on the ground and low altitudes. Read the entire page →
From page 29... ... 15 International Civil Aviation Organisation (ICAO) asked the Intergovernmental Panel on Climate Change (IPCC) Read the entire page →
From page 30... ... 16 great-circle miles (GC-mi) in length. Read the entire page →
From page 31... ... 17 Table 6. Proportional Aircraft Usage (%-seat-miles) Read the entire page →
From page 32... ... 18 Table 8. Direct Results from the Raw Regression Results AC Type Number of data points Adjusted R Square Coefficient Coefficient Values t Stat P-value TP 48 0.9674 kg/seat-LTO 10.62 11.30 7.16E-15 kg/GC-skm 0.011222 4.59 3.43E-05 SRJ* Read the entire page →
From page 33... ... 19 ICAO-based LTO fuel was then allocated to the cruise portion of the flight. The resulting coefficient (kg/GC-km) Read the entire page →
From page 34... ... 20 Table 9. Derived Fuel Intensity Coefficients by Aircraft Type AC Type Regression Bias due to Forced-Zero Origin Coefficient Units Original Coefficient Values Derived Values 1 Average Trip Distance (km) Read the entire page →
From page 35... ... 21 GHG (kg-CO2e) Read the entire page →
From page 36... ... 22 1) accelerate the mass of the vehicle, its rotating elements and the load it is carrying to a desired speed, and 2) Read the entire page →
From page 37... ... 23 Attributes for personal automobiles and taxis were derived with the simulation model in a one-time simulation of the 2011 driven fleet composite vehicle. The following assumptions were made for the highway access/egress modes:  Taxis were assumed to travel 1.5 km for every km of passenger carrying travel;  drop-off/pick-up was assumed to have 60% return-to-origin travel and 40% being part of a 2-person trip that incurs 10% extra travel distance. Read the entire page →
From page 38... ... 24 2.7 Regional Characterization 2.7.1 Region and Season Definitions The model provides default regional characterization data for four regions of the continental U.S. and electricity generation characteristics are further disaggregated into 9 sub-regions. Read the entire page →
From page 39... ... 25 Table 14. Direct and Upstream Carbon Fuels Usage in Electricity Generation by Region in 2011 Region Electricity Generation Upstream Fuel Increment Carbon fuels (BTU/kWh) Read the entire page →

From page 17...

... 3 2 Performance Evaluation Framework 2.1 Methodology Overview The background section of the terms of reference for this project noted the limitations of using averages for the energy performance of rail and other competing modes. In particular it noted that:  Passenger rail fuel consumption data may not fully represent impacts, since they are based on broad averages that include many different variations in distance traveled, amenities provided, speeds, operating environment, type of train operated, and form of propulsion.