# Presentation: 036344

## DOE/NRCan Study of North American Transportation Energy Futures

**DOE/NRCan Study of North American Transportation Energy Futures**

**Elyse Steiner, *****National Renewable Energy Laboratory***** **
**Philip Patterson, *****US Department of Energy***
**David Greene, *****Oak Ridge National Laboratory***
**Steve Plotkin, Margaret Singh, Anant Vyas,**
**   ****Marianne Mintz, Dan Santini, Steve Folga,**
**   *****Argonne National Laboratory***
**Jim Moore, *****TA Engineering, Inc.***
**Peter Reilly-Roe, Kevin Cliffe, Ruth Talbot, Paul Khanna, Vernel Stanciulescu, *****Natural Resources Canada***

## Outline of This Presentation

**Background**
- Models
- Scenarios
- Analytical Results
- Fuel Cost Modeling (Ethanol & Biodiesel)
- Concluding Remarks

## Background for This Study

- In April 2000, DOE Undersecretary asked the Transportation office in DOE to undertake a study of transportation long-term futures.
- “Future U.S. Highway Energy Use: A Fifty Year Perspective”(dated May 3, 2001 and called Phase 1) is available at:  www.ott.doe.gov/future_highway.shtml
- The Phase 1 study had a limited scope, so a Phase 2 was undertaken to address costs and resource limitations. Natural Resources Canada asked to be a part of Phase 2.  Focus expanded to North America.

**Notes:**
Ernie Monez, Undersecretary of Energy asked Tom Gross (the head of the Office of Transportation Technologies) to conduct this study.

## Phase 2:  Tools of This Study

- _Scenarios_ of possible futures using (1) rate of innovation, (2) environmental responsiveness, and (3) degree of North American energy market integration as drivers.
- DOE needs to have a robust R&D portfolio that has benefit to the Nation under many plausible scenarios.
- _Models_ for analysis of energy demand, greenhouse gas emissions, oil markets and costs.
- _Resource Papers_ on key topics to provide context, technical detail and cost data.

## Structure of the Analysis

**Scenario Development**

**Resource Papers**

**Natural gas resources**
** ****& price functions**

**Vehicle stock &**
** ****GHG models**

** ****GHG**
** ****Emissions**

** ****Energy Use**
** ****by Fuel Type**

**Costs**

**World Oil**
** ****Production **

**Oil**
**Imports**

**Scenario Cost**
** ****Spreadsheet**

**World oil **
**Market model**

**  ****Oil price**

**Vehicle sales**

**Vehicle Cost functions**

**Ethanol, H2,**
**Biomass cost**

**Results**

**Analysis**

**Energy**

**Other info**

_**Legend**_

**Natural gas price**

**Notes:**
Natural gas prices are a function of scenario and cumulative production

## Outline of This Presentation

- Background
**Models**
- Scenarios
- Analytical Results
- Fuel Cost Modeling (Ethanol & Biodiesel)
- Concluding Remarks

## Models

**World Energy Scenarios Model (WESM)**
- 	Tracks remaining conventional and unconventional oil and natural gas resources over time and estimates world oil price
**Hydrogen Infrastructure (CHAIN)**
- 	Defines production and distribution paths for two H2 sources: Natural gas and Thermonuclear
**Ethanol Production** (**ELSAS)**
- 	Calculates feedstock and non-feedstock costs of cellulosic ethanol production in the U.S., and includes learning improvements. Developed by TMS.
**Ethanol Cost Spreadsheet and Resource Paper**
- 	Estimates new and converted equipment for transportation, storage, and distribution of ethanol

**Notes:**
We can provide documentation of these models. The models that are starred have use beyond this study. We would replace Champagne with our VISION model and Genius with the GREET model.

## Models

**Vehicle Cost Model and Resource Paper**
- 	Develops estimates of vehicle costs to consumer based on fuel economy vs. cost curves (NAS/CAFE work used as checkpoint) and includes innovation cost reduction assumptions
**Scenario Cost Spreadsheet**
- 	Pulls together the following estimates developed by other models and adds fuel transportation and delivery costs where necessary
**Champagne Model **
- 	Uses a stock model to estimate vehicle use and energy consumption for light vehicles, medium and heavy trucks, air, and other modes
**Genius model **
- 	Estimates fuel-cycle greenhouse gases

## Outline of This Presentation

- Background
- Models
**Scenarios**
- Analytical Results
- Fuel Cost Modeling (Ethanol & Biodiesel)
- Concluding Remarks

## The 2050 Scenarios

- Visions of what the North America and World _could_ look like
- Built from specific drivers:
- The rate of innovation
- Environmental responsiveness
- Degree of U.S./Canadian energy interdependence
- Scenarios provide the logic and context for further modeling assumptions
**Crucial point: many key scenario parameters, e.g. vehicle efficiency, are *****assumptions*****, not forecasts**

**Notes:**
NRCanada took lead on this aspect of the work because of their experience in this area.

## The 2050 Scenarios

|  | Market Interdepend-ence | Pace of Innovation | Environmental Responsive-ness | Average 
% GDP growth/year  |
| --- | --- | --- | --- | --- |
| Base (Fixed MPG) Case | Intermediate | Intermediate | Intermediate | 2.6% |
| Greening The Pump (GtP) | Full | Slow | High | 2.2% |
| Go Your Own Way (GYOW) | Limited | Rapid | High | 3.0% |
| Rollin’ On (RO) | Full | Rapid | Low | 3.0% |

## In the Base Case, energy use in North America and the developed economies grows steadily, but ROW energy use grows more rapidly.

## Different World Oil Demand Scenarios from IIASA (IPCC) Were Tied to the NA Scenarios            (Base, RO = A1, GtP = C1, and GYOW = A3)

- North American Oil Demand

- World Oil Demand

**Notes:**
Source: Conventional-unconventional oil splits US imports vs transportation energy use.xls

## Remaining recoverable natural gas resources in 2000
Base		21,000 TCF		
GtP		20,000 TCF		 	
GYOW		27,000 TCF
RO		28,000 TCF

Remaining recoverable oil resources in 2000
Base		5.4 trillion barrels
GtP		4.5 trillion barrels
GYOW		5.4 trillion barrels
RO		5.6 trillion barrels
    (based on the 2050 ultimately recoverable resource)

- Base		21,000 TCF
- GtP		20,000 TCF
- GYOW		27,000 TCF
- RO		28,000 TCF
**Remaining recoverable oil resources in 2000**
- Base		5.4 trillion barrels
- GtP		4.5 trillion barrels
- GYOW		5.4 trillion barrels
- RO		5.6 trillion barrels
**    **(based on the 2050 ultimately recoverable resource)

**Selected Scenario Assumptions About World Oil & Natural Gas Resource Bases**

- includes
- unconventional

- includes
- unconventional

**Notes:**
Note: new USGS assessment of remaining conventional resources – oil = 2.3 trillion barrels; gas = 13,650 TCF
Why is there so much more natural gas in GYOW? (GYOW assumes high rate of innovation, a crucial factor in adding to recoverable reserves.  GTP has dual hindering factors of low innovation, high environmental restrictions) Does unconventional gas include methane hydrates? (NO...commercialization of hydrates could theoretically expand recoverable resources by an order of magnitude or more)  Especially for oil. What is the conventional/unconventional split?  (need Dave Greene to answer that) Note that the difference in innovation between Base and GYOW is high for gas but is ignored for oil – primarily the effect of different analysts choosing the assumptions than actual differences between the oil and natural gas resource bases.  This calls for a revisit of assumptions in Phase 3.

Note that the resources presented here represent the difference between the ultimately recoverable resource, given the technology advances that will occur in 2000-2050, and the cumulative production to the year 2000.  In 2000, the remaining recoverable resources will appear to be less than shown here, because at that time the future growth in the resource base due to future technological advancements – included in these estimates -- will not be apparent.
RO’s remaining recoverable resources are: 28,000 TCF (natural gas) and 5.6 trillion barrels (oil)

## All scenarios, including the Base Case, assume substantial technological advances that expand the oil resource base and lower supply costs.

- 0.2-0.7%/yr reduction in unconventional and conventional oil production costs.
- 0.2-0.7%/yr rate of reserve expansion.
- 0 to 75% of speculative resources developed.
- 75-95% of unconventional resources recoverable.

**Notes:**
In all scenarios, the recoverable resource base grows over time as new technology allows formerly uneconomic or technically unrecoverable resources to become recoverable.  For GtP, a lower rate of innovation yields a smaller growth in the recoverable resource base in 2050. 

## Selected Input Assumptions for U.S. Scenarios: Light Vehicles

| Attribute | Base | GtP | GYOW |
| --- | --- | --- | --- |
| Light Vehicle VMT  | AEO 2002 rates to 2020 with further decline in rate of growth post-2020 | 15% less than Base by 2015 | Same as Base |
| Light Vehicle Sales | AEO 2002 through 2020;
2015-2020 growth rate applied through 2050 | Same as Base | Same as Base |
| New Car/Light Truck Split | 50%/50% in 2010, then constant | 62%/38% in 2050 | 42%/58% in 2050 |
| New Car MPG/ Light Truck MPG | 28.7/ 21.4 constant | 42/ 31 in 2050 | 59/ 44 in 2050 |
| % Hybrids/ FCVs of new LVs | 0%/0% | 10%/0% in 2050 | 30%/50% in 2050 |
| E10 in LVs | Continuation of current | Mandatory by 2020 | Mandatory by 2020 |
| E85 in LVs | None | 20% of LDVs sold use E85 in 2050 | 30% of LDVs sold use E85 in 2050 |
| CNG/LPG in LVs | None | 3% by 2025 | None |

| RO |
| --- |
| 10% more than Base case by 2020 |
| Same as Base |
| Same as Base |
| 40/ 29 in 2050 |
| 40%/ 0% in 2050 |
| 5% in 2050 |
| None |
| None |

**Notes:**
Only 10% Hybrids in GtP by 2050?  Only 30% Hybrids in GYOW?  Why not more?
What would bring about these assumptions, especially the VMT reduction in GtP, changes in the car/LT split, and fuel economy values?

## Fuel economy improvements start early, but then flatten out.  GYOW has greater FE improvement over a longer time.

**Fuel economy improvements start early, but then flatten out.  GYOW has greater FE improvement over a longer time.**

**Notes:**
How do you expect to achieve these fuel economies?  What is the mix of vehicle technologies?

Source:  Scenario Data - Values Only modified by Singh.xls

## VMT growth is highest in the scenario with low environmental concern and relatively low oil prices (RO).

## Selected Input Assumptions for U.S. Scenarios:  Heavy Vehicles

| Attribute | Base | GtP | GYOW |
| --- | --- | --- | --- |
| Heavy Truck VMT as % of 2000 VMT | 338% in 2050 | 269% in 2050 | 404% in 2050 |
| Medium Truck VMT as % of 2000 VMT | 247% in 2050 | 208% in 2050 | 296% in 2050 |
| New HDV MPG | 5.9 constant | 7.2 in 2050 | 11.3 in 2050 |
| New MDV MPG | 7.7 in 2010, then constant | 11.6 in 2050 | 16.5 in 2050 |
| Heavy Truck sales as % of 2000 sales | 204% in 2050 | 180% in 2050 | 340% in 2050 |
| Medium Truck sales as % of 2000 sales | 195% in 2050 | 189% in 2050 | 235% in 2050 |
| Biodiesel in diesel | None | 10% | 10% |
| Ethanol in diesel | None | 10% |  None |

| RO |
| --- |
| 129% in 2050 |
| 507% in 2050 |
| 8.1 in 2050 |
| 11.3 in 2050 |
| 55% in 2050 |
| 318% in 2050 |
| 6% |
| None |

## Outline of This Presentation

- Background
- Models
- Scenarios
**Analytical Results**
- Fuel Cost Modeling (Ethanol & Biodiesel)
- Concluding Remarks

## World conventional oil production peaks before 2050 in all scenarios. 

**World conventional oil production peaks before 2050 in all scenarios.**** **

**Base**

**Greening the Pump**

**Go Your Own Way**

**Rollin’ On**

**Notes:**
What is the difference between conventional and unconventional oil?
Is any natural gas being used to produce FT distillate?
What share is MEA? Look at the Base Case. So what if we are running out of conventional oil?  When is the peak in oil use from all sources supposed to occur?  It is not obvious that the world is close to a total oil peak in the Base Case.
What prices are tied to these production levels? (see next slide)
Note that resource depletion accounts for the peaking only for the Base Case and Go Your Own Way; in Greening the Pump, the peaking is caused by sharply reduced oil demand and the addition of oil substitutes.
Rolling On is similar to the Base Case.

## In 2050, oil prices range from $27/barrel in GYOW to $40/barrel in GtP.

**In 2050, oil prices range from $27/barrel in GYOW to $40/barrel in GtP.**

**Notes:**
Explain the different world oil prices in the scenarios.  Assumptions about resources, recovery, demand, etc.?
Source :  2050 Phase 2 costs 11-15-02.xls

## Beyond 2020, NA oil production is all about Canadian oil sands...  What level of production is feasible?

**Base Case***

**Greening the Pump**

**Go Your Own Way**

**Imports**

- North American
- Production

**Potential 10 MMBD oil sands  cap**

**Imports**

**Imports**

- * Rollin’ On production is very similar to Base Case production

**Notes:**
The key point in the first graph is that Canadian oil sands development would dominate NA production if its production were relatively unconstrained.....but this seems doubtful.  We show where a 10 MMBD cap on oil sands production would lie in the figure, but we need further analysis to establish a reliable estimate for the magnitude of a cap.  Note especially that the existence of a cap requires a rerun of the scenario, especially the WESM model, and will yield different results for the split between NA oil imports and domestic production. 
What is oil sands production right now and what are the Canadians projecting?  If such rapid escalation of oil sands production (especially in the Base Case) wasn’t feasible, what would likely happen?  Currently, a 10 mmbd cap seems reasonable....accepting this cap requires a new run of the scenario in WESM.

Potential problems with rapid oil sands expansion include uncertain availability of inexpensive natural gas and gas liquids, potential environmental problems,  potential cost escalation due to equipment and labor shortages, etc.  This is a good example of an extreme result that, properly interpreted, indicates the need for further analysis – of the feasibility of such a rapid expansion in oil sands production.  Another issue: Canada has just ratified the Kyoto treaty....huge oil sands production doesn’t seem in line with Kyoto (though it’s perhaps hard to believe Canada would give up such an important source of jobs and economic growth for Kyoto)
Rolling On is similar to the Base Case.

## Although oil-based fuels remain crucial, both H2 and E85 play major roles in GYOW, and ethanol is important in GtP.

**2000**

**2020**

**2040**

**2050**

**2030**

**2010**

**U.S. Highway Fuel Use, by Type of Fuel**

**Notes:**
Comment: Again, this is just the result of input assumptions.  If you had different assumptions, you would get different results.

This slide is somewhat inconsistent with slide #38 on oil share of total energy.  (Singh: I’m not sure that it is inconsistent.  This slide shows “highway” energy while slide #38 presents “total transportation” energy.)

Rolling On has no H2.  9 billion gals of ethanol are used in RO vs 2 billion in the Base Case and 49-50 billion in GtP and GYOW.
The “other” category includes .....

## Oil reduction can be achieved with changes in behavior and/or with technological advances.

**GTP: Includes Some Behavior Changes **

**GYOW: All Technology Changes **

**Greening the Pump**

**Go Your Own Way**

**Reduction in U.S. Transport Oil Use, %**

**Reduction in U.S. Transport Oil Use, %**

**Notes:**
Rolling On oil reductions are achieved only by technology changes.   In fact, total VMT is greater in RO than in GYOW.

## Oil reduction compared to the Base Case (Continued)

**RO: Almost all savings from efficiency improvements**** **

**Rollin On**

## GtP achieves the greatest annual GHG reductions early in the 2000-2050 time frame and GYOW later in that time period.

**U.S. Highway GHG Emissions**

**MMTCe**

**Notes:**
How did you develop these estimates?  Are they lifecycle? (They include the total fuel cycle, but don’t include vehicle cycle, e.g. GHGs emitted during vehicle manufacturing cycle) How similar would they be to what the GREET model would estimate?
State: Their cumulative GHG emissions for GtP and GYOW over the period are about the same.
In GtP, emission rates fall back to 2000 levels by 2030, then slowly rise with rising vmt.  GYOW relies on longer term technology and thus begins to push emission rates down at a later time....but basically achieves parity with GtP by 2040, then also begins to rise with vmt.
GHG emissions of Rolling On are less than in the Base case, but greater than those of GtP and GYOW.

## Total (vehicle + fuel) costs vary only moderately across scenarios with the optimistic technology price assumptions.

**2000**

**2020**

**2040**

**2050**

**2030**

**2010**

**Notes:**
What is the basis for these estimates?  (Maybe the total costs should be presented after describing the individual costs components?)
The costs displayed here are the simple total annual fuel costs for all vehicles plus annual new vehicle sales expenditures – not anything fancy like vehicle sales plus lifetime discounted fuel costs from those vehicles.  What is happening here is that we’ve assumed that GtP attains most of its fuel reductions through vmt reduction – which is “free” – and through relatively inexpensive vehicle technology.  GYOW uses relatively expensive fuel cell technology, but we’ve projected substantial cost reductions in this technology over time.  Although vehicle costs remain higher in this scenario, the very high efficiency achieved reduces fuel costs enough so that total costs become lower than the Base Case in 2040, and continue still lower (relatively).  This is a surprising result given expectations of large investments required for moving to hydrogen....but of course the results depend on strong assumed cost reductions over time.
Rolling On is most similar to GtP total costs to 2030 and then RO becomes the lowest cost scenario ($858 billion in 2050).  In the latter years. RO has the lowest total vehicle costs. The slide conclusion is still valid when RO results are included.

## Cumulative vehicle and fuel costs for the 50-year period are similar across the scenarios.

|  | Vehicles | Fuel | Total |
| --- | --- | --- | --- |
| Base Case | $27.3 | $13.5 | $40.8 |
| Greening The Pump | +$0.2 | -$3.0 | -$2.8 |
| Go Your Own Way
(Original) | +$2.6 | -$2.8 | -$0.2 |
| Go Your Own Way (Higher costs) | +$3.7 | -$2.50 | +$1.2 |
| Rollin’ On | -$0.6 | -$2.6 | -$3.2 |

**(Undiscounted***** *****Costs in Trillion 2000 $s)**

**Notes:**
If GtP had the same total VMT as the Base Case and GYOW (which are not exactly the same but very similar), the total fuel costs would be about 15% higher or ~$1.8 trillion higher.  The total scenario costs would then be $39.8 trillion.

b) The higher costs of GYOW include higher vehicle costs, natural gas prices, h2 prices and ethanol prices.

c) Vehicle costs in GYOW are not even 10% higher than the base case?  Refer back to the comments in the previous slide – the low vehicle costs in GYOW depend on assumption of sharply declining technology costs over time.  Note that fuel costs do not include government expenditures to cover tax incentives for ethanol production – which would add about $50 billion to the Base Case, $230 billion to GtP, and $140 billion to GYOW.

d) Rolling On’s cumulative vehicle cost is $26.7 trillion and its cumulative fuel cost is $10.9 trillion for a total of $37.6 trillion.

## GtP has the highest total per mile costs of all scenarios. RO has the lowest.

**GtP has the highest total per mile costs of all scenarios. RO has the lowest.**

**TOTAL**

**VEHICLE**

**FUEL**

**Cost, $/mile**

**Notes:**
RO has the lowest total cost per mile of all the scenarios for all the years presented in this slide.  By 2040, its total cost/mile is 14 cents of which 4 cents is for fuel and 10 cents is for the vehicle.  RO is the lowest cost scenario from about 2030 forward and has the highest VMT.

## High efficiency, alternative fuels, and, for GtP,

**High efficiency, alternative fuels, and, for GtP,**
**vmt reductions sharply cut oil expenditures, greatly **
**reducing NA economic and strategic vulnerability.**

**NA Oil Expenditures**

## Outline of This Presentation

- Background
- Models
- Scenarios
- Analytical Results
**Fuel Cost Modeling (Ethanol & Biodiesel)**
- Conclusions

## At high volumes, production costs start to rise because more expensive feedstocks are needed. 

- ELSAS Aggressive Case Production Costs

## Ethanol in the 2050 Study

**Greening the Pump**
-  100% of gasoline is E-10 blend by 2020
-  20% of new light vehicles consume E-85 in 2050
-  Production volume reaches 49 million gallons in 2050 and the production cost is $0.69 per gallon
**Go Your Own Way**
-  100% of gasoline is E-10 blend by 2020
-  30% of new light vehicles consume E-85 in 2050
-  Production volume reaches 50 million gallons in 2050 and the production cost is $0.61 per gallon
**Rollin On**
-  Under 10 billion gallons per year used in E-10

## Key Assumptions Used in Ethanol Production Cost Calculations 

## Capital Distribution Costs for GtP

- (Million 2000 $s)

## Capital costs for ethanol production are very high in early years relative to volume.

## In the U.S., the cost of E-85 is driven down substantially in both GtP and GYOW. 

**Market price of E-85, U.S. $/gallon (without taxes)**

**Notes:**
Primary driver of the cost reduction is the large volume of fuel demanded; GtP costs are higher mainly because innovation is lower.
RO’s E-85 costs are higher than those of GtP or GYOW.  The cost is similar in the early years and then declines to $1.36/gal by 2050.
Note: the E-85 costs are for a gasoline equivalent gallon.  All of the costs exclude taxes.

## Biodiesel in the 2050 Study

-  Assumed 50% made from soybean and 50% from yellow grease initially
-  Canola oil and mustard seed oil added when market for other feedstocks depleted
-  Market prices for commodity feedstocks subject to fluctuations.  The following 2001 prices were used:
-  Soy: $0.143/ lb.
-  Yellow grease: $0.105/ lb.
-  Canola: $0.175/ lb.
-  Mustard seed not yet commercialized; DOE program funding current R&D

## Biodiesel Cost Calculations

-  Biodiesel from vegetable oils
- (B100) = $0.366 + (8.1 * $/lb feedstock)
-  Biodiesel from yellow grease and animal fat
- (B100) = $0.35 + (8.008 * $/lb feedstock)
-  Capital and operating costs assumed to decrease gradually over time
- Spreadsheet model calculated average cost based on percentage of each feedstock type used in production
-  From NREL and Ocean Air data

## Biodiesel production costs are higher in the scenarios with greater production because expensive feedstocks are required.

## Outline of This Presentation

- Background
- Models
- Scenarios
- Analytical Results
- Fuel Cost Modeling (Ethanol & Biodiesel)
**Concluding Remarks**

## Summary of Results

- A transition from conventional to unconventional oil or to other transportation fuels beginning before 2050 appears to be necessary.  This transition raises a variety of issues about energy security, capital availability, and environmental consequences.
- For two environmentally-driven scenarios, we have illustrated similar potential for reducing NA oil use and GHG emissions at relatively similar total costs.

**Notes:**
The conclusion about a transition before 2050 is widely held.
RO would not reduce oil use or GHG emissions as much as GtP and GYOW.  While its total costs are similar to the other scenarios, its per mile costs are lower. 

## Capabilities Gained

- The 2050 project team has gained the capability to model a variety of oil, gas, and alternative fuel resource production and conservation issues.
- Specifically, we developed or used models for the following:
- Effects of increased oil and/or gas resource base and varying OPEC production behavior
- Cost of H2 production and distribution from natural gas and thermochemical processes
-  Cost of cellulosic ethanol production and distribution
- Vehicle costs across scenarios

## Analytic Limitations & Uncertainties

- World and North American energy use are basically fixed within each scenario.  There is some feedback between oil prices and world oil use, but not for gas.
- Many key input variables are highly uncertain
- Ultimate world oil and gas resources, and resource costs
- Future oil prices (depend on OPEC behavior)
- Technology costs and impacts

**Notes:**
Here you might want to talk about what this means in terms of interpreting the results of this Phase.  The key here is that our results shouldn’t be interpreted as forecasts, but as signals that certain outcomes could plausibly occur if the future developed as postulated by our scenarios.  Also, some of the results should only be used as a means to identify key issues – for example, the large volumes of oil from Canadian oil sands identifies as a key issue the plausibility of very oil sands rapid development without price surges or unacceptable environmental impacts.

## Some Identified Weaknesses

- Very sudden or rapid changes difficult to defend.  For example:
- In GYOW , H2 FCV sales increase from 5% in 2020 to 47.5% in 2030
- In GtP, VMT growth drops 15% in a short time
- Unconventional oil production in Canada nearly unlimited
- Fixed fuel economy base case
- Commonly used within EERE
- Maximizes savings, gains from technologies in other scenarios
- Possibility of modeling EIA or some other reference case

## Comments Received on Phase 2

- Separate U.S. from North American results
- Incorporate feedback loops and consumer decisions into models
- Seek additional external review
- Reevaluate base case resources and assumptions
- Use/ develop more flexible, easy-to-run models for vehicle stock, fuel use, and GHG emissions
- Likely to use the VISION model in future

## Brainstorming Ideas for “Phase 3”

- Return to U.S. focus
- Develop scenarios more aligned with U.S. concerns and interests
- Distinguish between heavy and light vehicle results
- Include analysis of effects on oil refining industry
- More in depth examination of transition to alternative fuels and technologies
- Allow input from industry experts (BP, ExxonMobil) and other groups (environmental orgs) who are interested in the same topics and have valuable insights