On the Road in 2035: Reducing Transportation’s Petroleum Consumption and GHG Emissions Massachusetts Institute of Technology Bandivadekar, Heywood, et al. Provide overview of study’s intent, time horizon, when written The objective of this report was to assess and compare options for reducing fuel consumption, especially fuels from petroleum, and well-to-wheel greenhouse gas emissions in the light-duty sector. The report first assesses the application of new vehicle and fuel technologies to the performance, cost, and life-cycle emissions of these vehicles and then considers the effects on the total on-the-road fleet of introducing those technologies using ‘plausible’ assumptions about how rapidly they could be developed, manufactured, and sold to buyers to replace existing vehicles and fuels and add to the total fleet. This report was written in July 2008 with sources almost entirely from between 2000 and 2008. The time horizon covers the next 25 years (to 2035) although there is some discussion of out to 2050 due to the very long time horizons needed for significant penetration of many alternative vehicle types into the light-duty fleet. Provide basic layout and results or findings The report concludes that a 30 to 50% reduction in fuel consumption is feasible compared to a ‘no-change’ scenario. In the short term, this will come as a result of improved conventional gasoline, diesel, and HEVs, with an estimated incremental cost of $1,500 to $4,500. In the long term, PHEVs and FCVs could enter the fleet and have an impact. Alternative fuels are unlikely to change GHG emissions significantly (Canadian oil sands or corn-based ethanol). No single technology or fuel will be able to solve the problems of fuel use and GHG emissions, so a comprehensive, coordinated effort must take place, and soon, in order to achieve these twin goals. Conventional gasoline engines offer potential for continuous improvement, as long as advances are directed towards improving fuel economy and not size and acceleration. Conventional gasoline and diesel engine technologies will converge. HEVs offer potential, although in the near term cost issues inhibit. PHEVs and FCVs both have cost, range, and infrastructure issues to overcome, especially FCVs. What modeling tool did it use/Identify key assumptions/endogenous-exogenous Microsoft Excel based fleet model is used to track LDV stock, including new vehicle sales, market shares of propulsion systems, travel, fuel use, fuel mix, and GHG emissions. This report uses an accounting model that is driven heavily by assumption. To compare fuel consumption and GHG emissions reduction potential, the size and performance (acceleration time) of future vehicles were held constant at 2005 levels. The Toyota Camry and Ford F-150 were used as the representative car and truck. Individual vehicle component characteristics (fuel economy, cost) were estimated, including aerodynamics, tires, weight reduction, transmission, and vehicle fuel type, such as turbocharged gasoline, diesel, hybrids, plug-in hybrid electric, electric, and fuel cell vehicles. Vehicle manufacturing and disposal energy and GHG emissions were estimated (GREET). Vehicle assumptions were estimated, such as aerodynamics, rolling resistance, specific power, indicated efficiency, frictional mean effective pressure, break mean effective pressure, weight, cargo, battery power and energy, etc. This information was used to create a list of vehicle types and the relative fuel economy, cost (production and RPE<1.4>), and lifecycle (WTW) GHG emissions compared to a 2035 gasoline vehicle. The factors that drive U.S. light-duty vehicle fuel consumption and GHG emissions vehicle fuel economy (mpg) (assumes a rate of on-road degradation factor) history: increase until 1990 and then flat vehicle weight: weight reduction impact on fuel economy estimated, assumed weight reduction of 6% Emphasis on Reducing Fuel Consumption (ERFC): the degree to which improvements in technology are being directed toward reducing onboard fuel consumption; fuel economy has stayed static while fuel efficiency has climbed; 50% ERFC assumed in Reference case, with associated weight reductions, impacting all fuel mode types. Average annual growth rate of new vehicle sales assumed 0.8% per year. Assumed scrappage rate with a logistic curve. vehicle miles travelled history: upward trend (double between 1970 and 2005) assumed VMT growth rate number of vehicles in fleet history: upward trend of overall sales, number of vehicles per licensed driver increased from 0.85 to 1.15 between 1970 and 2005 assumed vehicle sales growth rate driving per vehicle history: cost of driving has declined ($/mile) with vehicle travel increasing from 8,000 miles per year to around 12,000, partially due to the ‘rebound effect.’ Model assumes 0.5% increase (2005-2020), 0.25% (2021-2030), 0.1% after 2030, with assumed new car VMT of 16,000 miles Model assumes that fuel will be available at price that will not impact demand GHG intensity of the fuel history: constant, although increasing ethanol use has changed this since 2000. Included in WTW model: oil sands from Canada, ethanol at level of corn and cellulosic calculated by POLYSIS; assumed GHG intensity of these fuels; electricity mix Demand and supply side constraints were considered and based on these considerations, a variety of scenarios were run. Evaluate if possible, how sensitive the results were to assumptions Entirely dependent upon assumption. Identify topics in our study that might need to reference it The results are an important exercise in terms of examining the difficulty of reducing GHG emissions and fuel consumption in transportation LDV fuel use: 2000: 503 billion liters gasoline equivalent 2005: 565 LDV WTW GHG: 2000:1647 Mt CO2 No Change Scenario: (0% ERFC, same LDT/passenger car split, 22% on-road degradation factor) fuel use: 765 GHG: 2514 Reference Scenario: (50% ERFC, same LDT/passenger car split, 22% on-road degradation factor, S-shaped alternative vehicle penetration curve weight declines 6%) fuel use: 664 GHG: 2213 Light-Truck Shift Scenarios: (70% LDT, 55%, 30%) fuel use: 774, 765, 750 Sales Growth, VMT/Vehicle Scenarios: (halve sales growth; halve sales growth/VMT vehicle growth; 0% sales growth/halve vehicle VMT growth; 0% sales/VMT vehicle growth)…mode shifting, smart growth type developments fuel use: 699,662,605,575 Median Lifetime Scenarios: (10% lower, 20% lower) fuel use: 714,659 On-Road Degradation Scenarios: (29%, 17%) fuel use: 809,735 Turbocharged ICE Future Scenario: (2035 vehicle type mix: 10% conventional gasoline, 35% turbo gasoline, 15% HEV, 40% diesel) fuel use: 585 GHG: 1988 Market Mix Scenario: (no clear winner—37.5% conventional gasoline, 25% turbo gasoline, 15% HEV, 15% diesel, 7.5% PHEV) fuel use: 594 GHG: 2027 Mixed Market w/High Oil Sands/Low Cellulosic Ethanol: GHG: 1981 Mixed Market w/Low Oil Sands/High Cellulosic Ethanol: GHG: 1918 Hybrid Strong Scenario: (19.3% conventional gasoline, 25% turbo gasoline, 40% HEV, 0.7% diesel, 15% PHEV) fuel use: 543 GHG: 1895 Hybrid Strong/66% ERFC Scenario: (19.3% conventional gasoline, 25% turbo gasoline, 40% HEV, 0.7% diesel, 15% PHEV) fuel use: 518 GHG: 1818 Hybrid Strong/Low Oil Sand/High Ethanol Mix/66%ERFC Scenario: (19.3% conventional gasoline, 25% turbo gasoline, 40% HEV, 0.7% diesel, 15% PHEV) fuel use: 518 GHG: 1708 Hybrid Heavy Cars/Turbo Charged Trucks: (car: 25% turbo gasoline, 40% HEV, 0.7% diesel, 15% PHEV truck: 35% turbo gasoline, 15% HEV, 40% diesel) fuel use: 565 ERFC Scenarios: (100%) fuel use: 563 ERFC Scenario plus Hybrid Strong: (ERFC100%; car: 25% turbo gasoline, 40% HEV, 0.7% diesel, 15% PHEV) fuel use: 464 Market Mix Scenario plus Fuel Cell Vehicles: (25% turbo gasoline, 15% HEV, 15% diesel, 7.5% PHEV, 5% fuel cell) fuel use: 573 Delay plus Reference Scenario: (50% ERFC, 5 year delay, 10 year delay) fuel use: 692, 718 Delay plus Reference Scenario: (100% ERFC, 5 year delay, 10 year delay) fuel use: 619, 672 Travel Demand Reduction/100%ERFC Scenario: (0% vehicle/VMT growth) fuel use: 465