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