1. ARB Vision: CTP 2040 Scenarios
Historical context:
Based on ANL model inspiration
LDV GHG scenarios for ACC / ZEV Regulation
2012 Vision 1 with criteria emissions added, more sectors
Vision 2 model development in support of the SIP
Caltrans ctp tac meeting
October 23, 2014

2. Definition: “scenario planning”
Wikipedia:
“Strategic planning method…to make flexible long-term plans”
“Systems thinking…[to evaluate] surprising futures”
International Energy Agency (IEA):
“Identify technology portfolios”
U.S. Department of Energy:
“Identifying the range of possibilities of trends and policies”
“Developing a shared understanding of a problem” 2
ARB, Oct 23, 2014

3. How scenario results are used in ARB policy decisions
Long-term scenario emission results:
Are not intended to define single “path”, but rather identify “trends” of most promising (and risky) strategies
Acknowledge multiple strategy combinations exist to achieve goals; with some uncertainty
Improve understanding of transportation system impacts (e.g. fuel infrastructure, cross-sector technologies, & activity changes) 3
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4. Vision model to evaluate scenarios4
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5. Model overview: user input choices & summary results
Vehicle Efficiency
Vehicle Fuel Efficiency
Emissions of Criteria Pollutants and GHGs
Fuels (Conventional & Alternative)
Energy Consumption
Scenarios include multiple individual strategies in the areas of activity reductions, technology, and alt fuels
Activity and land-use policies
Mobile source and fuels regulations
Freight transport planning
Advanced Technology
Advanced Tech.
Vehicle
Populations
Transportation System Efficiencies
Advanced Tech.
Annually from 5
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6. Sectors in vision model 2.0
Mobile Sectors Already Included
Passenger vehicles
Heavy-duty vehicles (on-road)
Freight locomotives
Aviation
Stationary Sources Already Included
Fuel production for transportation and buildings
Residential and commercial buildings
Mobile Sectors Under Development
Cargo handling equipment
Commercial harbor craft
Commercial ships (ocean going vessels)
Construction equipment
Other off-road vehicles 6
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7. BASIC MODEL STRUCTURE
Sector In-use Fleet Population (derived from inputs)
Vehicle Emissions “Tank to Wheel” (running, evap, etc)
Example Results:
(for each veh type)
gNOx/mi
gROG/mi
gCO2e/mi
Fuel demand from each fleet
(gallons, kWh, etc)
Upstream Emissions, “Well to Tank”
Example Results:
(for each fuel type)
gNOx/gallon
gROG/gallon
gCO2e/gallon
Example Results:
Gallons gas/yr
Gallons dsl/yr
kWh elec/yr 7
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8. Model & Data coordination for ctp20408
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9. Models, data handoffs, etc
Caltrans CSTDM
MPO data, EMFAC 2011 predominantly
Alt 1 (baseline), Alt 2 (VMT strategies)
ARB EMFAC 2014
Speed bin and VMT changes – scale base EFs
ARB Vision 2.0
Already has default EMFAC 2014 embedded
Scale EF from speed bin changes, CTP VMT
Alt 3: Add new technology and alternative fuels 9
ARB, Oct 23, 2014

10. Models, data handoffs, etc
CSTDM
EMFAC
Vision 2.0
VMT aggregated into 4 veh bundles
2010, ‘20, ‘35, ’40
By county
By speed bin
Disaggregate VMT to all vehicle classes
Extrapolate all years
Result: TTW CO2e by veh class & year
EMFAC 2014 import:
VMT by veh class
EF by veh class
For all years
Statewide
Rail Plan
Aviation Plan 10
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11. Three ctp2040 alternatives
Vision results for all three alternatives
Use CTP modes; add other Vision modes for context
Alternative 1 - Baseline
CTP2040 baseline VMT
CTP2040 LDV, HDV, Passenger rail, passenger air
Alternative 2 – Caltrans VMT strategies
Only variable – reduced VMT
Alternative 3 – Advanced veh & fuel strategies
To fill GHG gap to 2050
May show various combinations to reach same GHG 11
ARB, Oct 23, 2014

12. Example results from previous vision model (public staff reports)12
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13. 2012 scenarios: Combined Results
Statewide GHG Emissions
South Coast NOx Emissions
The overall results shown here reveal the range of emission reductions identified in staff’s scenarios. The shaded area signifies that a number of scenarios were explored with a range of reductions achieved.
The “business as usual” scenario assumes all existing state policies are successful. For NOx, the graph shows the enormous reductions expected in the next ten years from existing rules.
The scenario results here show that
the 2050 GHG target is successfully met.
The 2050 South Coast NOx target is successfully met
The 2023 and 2032 NOx targets are eventually met, but not within the timeframe set in existing policy
Achieving the 2023 ozone standards by the target year requires extremely aggressive market transformation. Few samples of sector trends are highlighted below to provide context for the scale of transformation:
Passenger vehicles: Approximately 30 percent of all passenger vehicles would need to be zero emissions vehicles and approximately 40 percent would need to be near-zero emissions vehicles.
Trucks: Approximately 20 percent of all trucks operating in California would need to be zero emission trucks, 20 percent would need to be near-zero emission trucks, and more than 50 percent would need to be cleaner than the current NOx standard.
Locomotives: Approximately 30 percent of locomotives would need to be Tier 4 and 70 percent would need to be even cleaner than Tier 4
Targets
BAU = business as usual (existing policies) 13
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14. 2012 Scenario BAU: statewide ghg emissions
Emission Targets 14
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15. 2012 Scenario 2: statewide ghg emissions
~30% Below 1990 15
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16. 2012 Scenario bau: south coast nox emissions
Emission Targets 16
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17. 2012 Scenario 3: south coast nox emissions
Emission Targets 17
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18. 2009 statewide ghg scenario: LDV fleet technology mix
FCVs
ICEs
ZEV only
79%
HEVs
PHEVs
BEVs
ZEV+PHEV Sales
ZEV+ PHEV
ZEV Reg
87% 18
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19. 2012 Scenario 3: SCAB HDV fleet technology mix19
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20. 2012 scenario 3: fuel supply transformation
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21. Fuels transformation: implications for ctp204021
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22. integrated transportation systems perspective
CTP 2040
Modal Plans
Highway
Transit
Aviation
Rail
Freight
Reduce VMT
Efficient Operation of System
Approaches
Low Carbon Fuels
Advanced Vehicle Tech
Reduced VMT: Integrally tied to land use, trip pricing
Transportation system: Transportation infrastructure, facilities, Modes,
Infrastructure for ITS systems, autonomous vehicles
New Nexus / System Issue: Alt fuel infrastructure
Road network – Truck trips for feedstocks and fuel stations
VMT from adv vehicles – where they fuel, park, etc
Facilities – fuel depots for multi-modes (e.g. freight) 22
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23. Fuel transformation: regional implications
Fuel production facilities and delivery occur locally to varying degrees. Activities and land-use will change
TODAY 23
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24. Fuel transformation: regional implications
TOMORROW: Biofuels - More feedstock truck trips
TOMORROW: Hydrogen - More fuel delivery truck trips 24
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25. Fuel transformation: regional implications
TODAY
TOMORROW: Electricity
Most fueling at home, some at work
Different trip profile for fueling (work, retail) 25
ARB, Oct 23, 2014

26. Scenario results: fueling infrastructure impacts
Long-term scenario result: Expansive alternative fuel use
H2 stations for LDVs: 1,118 stations by 2030 *
Based on station size: 500 kg/day 90% utilization & 1kg/d/veh
Today: 17 H2 stations in CA (30 – 120 kg/day capacity each)
Renewable Diesel: 20 new biofuel refineries by 2030 **
Based on refinery size: 50 million gallons/yr (mgpy) capacity
Today: 3 ethanol production facilities in 50 mgpy (imported corn)
Similar needs for: Electric chargers, CNG, LNG stations
Near-term potential policy action(s):
Create infrastructure roadmap, with CEC, PUC, Caltrans
Focus on: H2, Electric chargers, CNG, LNG
* 503,000 FCVs on-road by 2030
** ~1 billion gallons RD by 2030 26
ARB, Oct 23, 2014