Transportation Demand Module 

The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight and passenger rail,  freight shipping, and miscellaneous transport such as recreational boating. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. 

Key Assumptions 

Light-Duty Vehicle Assumptions

The light-duty vehicle Manufacturers Technology Choice Model (MTCM) includes 63 fuel saving technologies with data specific to cars and light trucks (Tables 7.1 and  7.2) including incremental fuel economy improvement, incremental cost, first year of introduction, and fractional horsepower change. 

The vehicle sales share module holds the share of vehicle sales by manufacturers constant within a vehicle size class at 2007 levels based on National Highway Traffic and Safety Administration data. [1] EPA size class sales shares are projected as a function of income per capita, fuel prices, and average predicted vehicle prices based on endogenous calculations within the MTCM. [2] 

The MTCM utiizes 63 new technologies for each size class and manufacturer based on the cost-effectiveness of each technology and an initial availability year.  The discounted stream of fuel savings is compared to the marginal cost of each technology. The fuel economy module assumes the following: 

• The economic effectiveness of all fuel technologies are evaluated on the basis of a 3-year payback period using a real discount rate of 15 percent. 
• Fuel economy standards reflect current law through model year 2011. For model years 2012 through 2016, fuel econony standards reflect NHTSA and EPA's proposed standards.  For model years 2017 through 2020, the standards reflect EIA assumed increases that ensure a light vehicle combined fuel economy of 35 mpg is achieved by model 2020.  For model years 2021 though 2030, fuel economy standards are held constant at model year 2020 levels with fuel economy improvements still possible based on an economic cost benefit analysis only. 
• Expected future fuel prices are calculated based on an extrapolation of the growth rate between a five year moving average of fuel price 3 years and 4 years prior to the present year.  This assumption is founded upon an assumed lead time of 3 to 4 years to significantly modify the vehicles offered by a manufacturer.

Degradation factors are used to convert new vehicle tested fuel economy values to "on-road" fuel economy values (Table 7.3).  The degradation factors represent adjustments made to tested fuel economy values to account for the difference experienced between fuel economy performance realized in the CAFE test procedure compared fuel economy realized under normal driving conditions. 

Commercial Light Duty Fleet Assumptions 

The Transportation Demand Module is designed to divide commercial light-duty fleets into three types: business, government, and utility. Based on this classification, commercial light-duty fleet vehicles vary in survival rates and duration in fleet use before being sold for use as personal vehicles (Table 7.4). The average length of time vehicles are kept before being sold for personal use is 4 years for business use, 5 years for government use, and 6 years for utility use.  Of total automobile sales to fleets, 80.6 percent are used in business fleets, 6.5 percent in government fleets, and 12.9 percent in utility fleets. Of total light truck sales to fleets, 59.5 percent are used in business fleets, 3.6 percent in government fleets, and 36.8 percent in utility fleets. [3]  Both the automobile and light truck shares by fleet type are held constant from 2004 through 2035. In 2006, 18.1 percent of all automobiles sold and 18.2 percent of all light trucks sold were for fleet use. The share of total automobile and light truck sales to decline over the forecast period based on historic trends. 

Alternative-fuel shares of fleet vehicle sales by fleet type are held constant at year 2005 levels.  Size class sales shares of vehicles are held constant at 2005 levels (Table 7.5). [4] Individual sales shares of new vehicles purchased by technology type are assumed to remain constant for utility, government, and for business fleets [5] (Table 7.6). 

Annual VMT per vehicle by fleet type stays constant over the forecast period based on the Oak Ridge National Laboratory fleet data. 

Fleet fuel economy for both conventional and alternative-fuel vehicles is assumed to be the same as the personal new vehicle fuel economy and is subdivided into six EPA size classes for cars and light trucks. 

The Light Commercial Truck Model 

The Light Commercial Truck Module of the NEMS Transportation Model represents light trucks that have a 8,501 to 10,000 pound gross vehicle weight rating (Class 2B vehicles). These vehicles are assumed to be used primarily for commercial purposes. 

The module implements a twenty-year stock model that estimates vehicle stocks, travel, fuel economy, and energy use by vintage. Historic vehicle sales and stock data, which constitute the baseline from which the forecast is made, are taken from a recent Oak Ridge National Laboratory study. [6] The distribution of vehicles by vintage, and vehicle scrappage rates are derived from R.L. Polk company registration data. [7],[8] Vehicle travel by vintage was constructed using vintage distribution curves and estimates of average annual travel by vehicle. [9],[10] 

The growth in light commercial truck VMT is a function of industrial output for agriculture, mining, construction, trade, utilities, and personal travel. These industrial groupings were chosen for their correspondence with output measures being forecast by NEMS. The overall growth in VMT reflects a weighted average based upon the distribution to total light commercial truck VMT by sector. Forecasted fuel efficiencies are assumed to increase at the same annual growth rate as conventional gasoline light-duty trucks (<8,500 pounds gross vehicle weight). 

Consumer Vehicle Choice Assumptions 

The Consumer Vehicle Choice Module (CVCM) utilizes a nested multinomial logit (NMNL) model that predicts sales shares based on relevant vehicle and fuel attributes. The nesting structure first predicts the probability of fuel choice for multi-fuel vehicles within a technology set. The second level nesting predicts penetration among similar technologies within a technology set (i.e., gasoline versus diesel hybrids). The third level choice determines market share among the different technology sets. [11] The technology sets include: 

• Conventional fuel capable (gasoline, diesel, bi-fuel and flex-fuel), 
• Hybrid (gasoline and diesel), 
• Plug in hybrid (10 mile all electric range and 40 mile all electric range) 
• Dedicated alternative fuel (CNG, LPG, methanol, and ethanol), 
• Fuel cell (gasoline, methanol, and hydrogen), and 
• electric battery powered (nickel-metal hydride and lithium ion) [12] 

The vehicle attributes considered in the choice algorithm include: price, maintenance cost, battery replacement cost, range, multi-fuel capability, home refueling capability, fuel economy, acceleration and luggage space. With the exception of maintenance cost, battery replacement cost, and luggage space, vehicle attributes are determined endogenously. [13] Battery costs for plug-in hybrid electric and all-electric vehicles are based on a production based function over several technology phase periods. The fuel attributes used in market share estimation include availability and price. Vehicle attributes vary by six EPA size classes for cars and light trucks and fuel availability varies by Census division. The NMNL model coefficients were developed to reflect purchase decisions for cars and light trucks separately. 

Where applicable, CVCM fuel efficient technology attributes are calculated relative to conventional gasoline miles per gallon. It is assumed that many fuel efficiency improvements in conventional vehicles will be transferred to alternative-fuel vehicles. Specific individual alternative-fuel technological improvements are also dependent upon the CVCM technology type, cost, research and development, and availability over time. Make and model availability estimates are assumed according to a logistic curve based on the initial technology introduction date and current offerings. Coefficients summarizing consumer valuation of vehicle attributes were derived from assumed economic valuation compared to vehicle price elasticities. Initial CVCM vehicle stocks are set according to EIA surveys. [14] A fuel switching algorithm based on the relative fuel prices for alternative fuels compared to gasoline is used to determine the percentage of total VMT represented by alternative fuels in bi-fuel and flex-fuel alcohol vehicles. 

Freight Truck Assumptions 

The freight truck module estimates vehicle stocks, travel, fuel efficiency, and energy use of three size classes: light medium (Class 3), heavy medium (Classes 4 -6), and heavy (Classes 7-8). Within the size classes, the stock model structure is designed to cover 38 vehicle vintages and to estimate energy use by four fuel types: diesel, gasoline, LPG, and CNG. Fuel consumption estimates are reported regionally (by Census Division) according to the distillate fuel shares from the State Energy Data Report [15]. The technology input data specific to the different types of trucks including the year of introduction, incremental fuel efficiency improvement, and capital cost of introducing the new technologies, are shown in Table 7.7. 

The freight module uses projections of dollars of industrial output to estimate growth in freight truck travel. The industrial output is converted to an equivalent measure of volume output using freight adjustment coefficients. [16],[17] These freight adjustment coefficients vary by North American Industrial Classification System (NAICS) code with the deviation diminishing gradually over time toward parity. Freight truck load-factors (ton-miles per truck) by NAICS code are constants formulated from historical data. [18] 

Fuel economy of new freight trucks is dependent on the market penetration of various emission control technologies and advanced technology components.[19] For the advanced technology components, market penetration is determined as a function of technology type, cost effectiveness, and introduction year. Cost effectiveness is calculated as a function of fuel price, vehicle travel, fuel economy improvement, and incremental capital cost. Emissions control equipment is assumed to enter the market to meet regulated emission standards. 

Heavy truck freight travel is estimated by class size and fuel type based on matching projected freight travel demand (measured by industrial output) to the travel supplied by the current fleet. Travel by vintage and size class is then adjusted so that total travel meets total demand. Initial heavy vehicle travel, by vintage and size class, is derived using Vehicle Inventory and Use Survey (VIUS) data. [20] 

Initial freight truck stocks by vintage are obtained from R. L. Polk Co. and are distributed by fuel type using VIUS data. [21] Vehicle scrappage rates are also estimated using R. L. Polk Co. data. [22] 

Freight and Transit Rail Assumptions 

The freight rail module uses the industrial output by NAICS code measured in real 1987 dollars and converts these dollars into an adjusted volume equivalent. Coal production from the NEMS Coal Market Module is used to adjust coal based rail travel. Freight rail adjustment coefficients (used to convert dollars to volume equivalents) are based on historical data and remain constant.[23],[24] Initial freight rail efficiencies are based on historic data taken from the Transportation Energy Databook. [25] The distribution of rail fuel consumption by fuel type is also based on historical data and remains constant over the projection. [26] Regional freight rail consumption estimates are distributed according to the State Energy Data Report. [27] 

Domestic and International Shipping Assumptions 

Similar to the previous sub-module, the domestic freight shipping module uses the industrial output by NAICS code measured in real 1987 dollars and converts these dollars into an adjusted volume equivalent. 

The freight adjustment coefficients (used to convert dollars to volume equivalents) are based on historical data. Domestic shipping efficiencies are based on the model developed by Argonne National Laboratory. The energy consumption in the international shipping module is a function of the total level of imports and exports. The distribution of domestic and international shipping fuel consumption by fuel type is based on historical data and remains constant throughout the forecast. [28] Regional domestic shipping consumption estimates are distributed according to the residual oil regional shares in the State Energy Data Report. [29] 

Air TravelDemand Assumptions 

The air travel demand module calculates the domestic and international ticket prices for travel as a function of fuel cost.  Domestic and international revenue passenger miles are based on historic data, [30] per capita income, and ticket price. The revenue ton miles of air freight are based on merchandise exports, gross domestic product, and fuel cost. [31] 

Airport capacity constraints based on the FAA’sAirportCapacityBenchmarkReport2004are incorporated into the air travel demand module using airport capacity measures. [32] Airport capacity is defined by the maximum number of flights per hour airports can routinely handle, the amount of time airports operate at optimal capacity, and passenger load factors. Capacity expansion is expected to be delayed due to the economic environment and fuel costs. 

Aircraft Stock/EfficiencyAssumptions 

The aircraft stock and efficiency module consists of a world, US and Non-US, stock model of wide body, narrow body, and regional jets by vintage. Total aircraft supply for a given year is based on the initial supply of aircraft for model year 2008, new passenger sales, and the survival rate by vintage (Table 7.8). [33] New passenger sales are a function of revenue passenger miles and gross domestic product. 

Wide and narrow body planes over 25 years of age are placed as cargo jets according to a cargo percentage varying from 50 percent of 25 year old planes to 100 percent of those aircraft 30 years and older. The available seat-miles per plane, which measure the carrying capacity of the airplanes by aircraft type, vary over time, with wide bodies remaining constant and narrow bodies increasing. [34] The difference between seat-miles demanded and available seat-miles represents potential newly purchased aircraft. If demand is less than supply, then passenger aircraft is either parked or exported, starting with twenty nine year old aircraft, at a pre-defined rate. Aircraft continue to be parked until equilibrium is reached. If supply is less than demand planes are either imported or unparked and brought back into service. 

Technological availability, economic viability, and efficiency characteristics of new aircraft are assumed to grow at a fixed rate. Fuel efficiency of new aircraft acquisitions represents an improvement over the stock efficiency of surviving airplanes. A generic set of new technologies (Table 7.9) are introduced in different years and with a set of improved efficiencies over the base year (2007). Regional shares of all types of aircraft fuel use are assumed to be constant and are consistent with the State Energy Data Report estimate of regional jet fuel shares. 

Legislation and Regulations 

Energy Independence and Security Act of 2007 (EISA2007) 

The EISA2007 legislation requires the development of fuel economy standards for work trucks (8,500 lbs. to less than 10,000 lbs GVWR) and commercial medium- and heavy-duty on-highway vehicles (10,000 lbs or more GVWR). The new fuel economy standards require consideration of vehicle attributes and duty requirements and can prescribe standards for different classes of vehicles, such as buses used in urban operation or semi-trucks used primarily in highway operation. The Act provides a minimum of 4 full model years lead time before the new fuel economy standard is adopted and 3 full model years after the new fuel economy standard has been established before the fuel economy standards for work trucks can be modified. Because these fuel economy standards are pending and NEMS does not currently model fuel economy regulation for work trucks or commercial medium- and heavy- duty vehicles, this aspect of the Act is not included in AEO2010. 

A fuel economy credit trading program is established based on EISA2007. Currently, CAFE credits earned by manufacturers can be banked for up to 3 years and can only be applied to the fleet (car or light truck) from which the credit was earned. Starting in model year 2011 the credit trading program will allow manufacturers whose automobiles exceed the minimum fuel economy standards to earn credits that can be sold to other manufacturers whose automobiles fail to achieve the prescribed standards. The credit trading program is designed to ensure that the total oil savings associated with manufacturers that exceed the prescribed standards are preserved when credits are sold to manufacturers that fail to achieve the prescribed standards. While the credit trading program begins in 2011, EISA2007 allows manufacturers to apply credits earned to any of the 3 model years prior to the model year the credits are earned, and to any of the 5 model years after the credits are earned. The transfer of credits within a manufacturer’s fleet is limited to specific maximums. For model years 2011 through 2013, the maximum transfer is 1.0 mpg; for model years 2014 through 2017, the maximum transfer is 1.5 mpg; and for model years 2018 and later, the maximum credit transfer is 2.0 mpg. NEMS currently allows for sensitivity analysis of CAFE credit banking by manufacturer fleet, but does not model the trading of credits across manufacturers.  The AEO2010 does not consider trading of credits since this would require significant modifications to NEMS and detailed technology cost and efficiency data by manufacturer, which is not readily available.  

The CAFE credits specified under the Alternative Motor Fuels Act (AMFA) through 2019 are extended. Prior to passage of this Act, the CAFE credits under AMFA were scheduled to expire after model year 2010. Currently, 1.2 mpg is the maximum CAFE credit that can be earned from selling alternative fueled vehicles. EISA2007 extends the 1.2 mpg credit maximum through 2014 and reduces the maximum by 0.2 mpg for each following year until it is phased out by model year 2020. NEMS does model CAFE credits earned from alternative fuel vehicles sales. 

American Recovery and Reinvestment Act o f2009 and Energy Improvement and Extension Act of 2008 

ARRA Title I,  Section 1141 modified the EIEA2008 Title II, Section 205 tax credit for the purchase of new, qualified plug-in electric drive motor vehicles.  According to the legislation, a qualified plug-in electric drive motor vehicle must draw propulsion from a traction battery with at least 4 kilowatthours of capacity and is propelled to a significant extent by an electric motor which draws electricity from a battery that is capable of being rechargrd from an external source of electricity. 

The tax credit for the purchase of a plug-in electric vehicle is $2,500 plus, starting at a battery capacity of 5 kilowatthours, an additional $417 per kilowatthour battery credit up to a maximum of $7,500 per vehicle.  The tax credit eligibility and phase-out are specific to an individual vehicle manufacturer.  The credits are phased out once a manufacturer's cumulative sales maximum after December 31, 2009.  The credit is reduced to 50 percent of the total value for the first two calendar quarters of the phase-out period and then to 25 percent for the third and fourth calendar quarters before being phase out entirely thereafter.  The credit applies to vehicles with a gross vehicle weight rating of less than 14,000 pounds. 

ARRA also allows a tax credit of 10 percent against the cost of a qualified elevctric vehicle with a battery capacity of at least 4 kilowatthours subject to the same phase out rules as above.  The tax credits for qualified plug-in electric drive motor vehicles and electric vehicles are included in AEO2010. 

Energy Policy Act of 1992 (EPACT) 

Fleet alternative-fuel vehicle sales necessary to meet the EPACT regulations are derived based on the mandates as they currently stand and the Commercial Fleet Vehicle Module calculations. Total projected AFV sales are divided into fleets by government, business, and fuel providers (Table 7.10). 

Because the commercial fleet model operates on three fleet type representations (business, government, and utility), the federal and state mandates are weighted by fleet vehicle stocks to create a composite mandate for both. The same combining methodology is used to create a composite mandate for electric utilities and fuel providers based on fleet vehicle stocks. [35] 

Low Emission Vehicle Program (LEVP) 

The LEVP was originally passed into legislation in 1990 in the State of California. It began as the implementation of a voluntary opt-in pilot program under the purview of Clean Air Act Amendments of 1990 (CAAA90), which included a provision that other States could opt in to the California program to achieve lower emissions levels than would otherwise be achieved through CAAA90. 14 states have elected to adopt the California LEVP. 

The LEVP is an emissions-based policy, setting sales mandates for 6 categories of low-emission vehicles: low-emission vehicles (LEVs), ultra-low-emission vehicles (ULEVs), super-ultra low emission vehicles (SULEVs), partial zero-emission vehicles (PZEVs), advanced technology partial zero emission vehicles (AT-PZEVs), and zero-emission vehicles (ZEVs). The LEVP requires that in 2005 10 percent of a manufacturer’s sales are ZEVs or equivalent ZEV earned credits, increasing to 11 percent in 2009, 12 percent in 2012, 14 percent in 2015, and 16 percent in 2018 where it remains constant thereafter. In August 2004, CARB enacted further amendments to the LEVP that place a greater emphasis on emissions reductions from PZEVs and AT-PZEVs and requires that manufacturers produce a minimum number of fuel cell and electric vehicles. In addition, manufacturers are allowed to adopt alternative compliance requirements for ZEV sales that are based on cumulative fuel cell vehicle sales targets for vehicles sold in all States participating in California’s LEVP. Under the alternative compliance requirements, ZEV credits can also be earned by selling battery electric vehicles. Currently, all manufacturers have opted to adhere to the alternative compliance requirements. The mandate still includes phase-in multipliers for pure ZEVs and allows 20 percent of the sales requirement to be met with AT-PZEVs and 60 percent of the requirement to be met with PZEVs. AT-PZEVs and PZEVs are allowed 0.2 credits per vehicle. EIA assumes that credit allowances for PZEVs will be met with conventional vehicle technology, hybrid vehicles will be sold to meet the AT-PZEV allowances, and that hydrogen fuel cell vehicles will be sold to meet the pure ZEV requirements under the alternative compliance path. 

Transportation Alternative Cases 

High Technology Case 

In the high technology and low technology cases for cars and light trucks, the conventional fuel saving technology characteristics are based on NHTSA and EPA values.[36] Tables 7.10, 7.11, 7.12, 7.13, and 7.14 summarize the High and Low Technology matrices for cars and light trucks. Tables 7.15 and 7.16 reflect the high and low technology case assumptions for heavy trucks. These reflect optimistic and pessimistic values, with respect to efficiency improvement and capital cost, for advanced engine and emission control technologies as reported by ANL. [37] 

For the Air Module, the high technology case reflects earlier introduction years for the new aircraft technologies and a greater penetration share.  The low technology case is reflected by a delay in the introduction of new aircraft technologies. Tables 7.17 and 7.18 reflect these cases.

Transportation Tables

Transportation Demand Module Notes