STEPS Transportation Transition Scenarios for California

Transcription

1 NextSTEPS (Sustainable Transportation Energy Pathways) STEPS Transportation Transition Scenarios for California Christopher Yang, Marshall Miller, Lew Fulton, Joan Ogden, Rosa Dominguez-Faus, Dominique Meroux STEPS Symposium June 2, 216

2 STEPS Decarbonization Scenarios for Transportation Critical Transition Dynamics Develop scenarios for transportation to analyze future vehicle mixes, fuel usage, emissions and costs Integrate ongoing STEPS research on vehicles and fuels Focus on the cost and emissions impacts of a transition to decarbonized transportation system (vehicles and fuels) Analyze with particular focus on Explore detailed vehicle/fuel scenarios across many transport sectors Project goals Develop scenario modeling framework Produce realistic scenarios that help contribute to meeting climate change goals in transportation Assess technology/fuel/resource mix and emissions Assess incremental costs (and potential subsidies required) Scenarios enable what-if analyses and improve understanding of sensitivities of the system to inputs

3 Decarbonization Scenarios for Transportation Analyze reference (BAU) and decarbonization (GHG) scenarios Look across transportation sectors Light-duty, medium and heavy-duty/medium-duty trucks initially Additional sectors to be included later Start with focus on California to build up modeling capabilities but plan to develop US scenarios Similar approach (technology specifications, modeling framework) Differences (additional data collection, infrastructure and resource Cars availability and cost) 21 CA Transportation Emissions Ex: Aviation HDV Ex: Marine Cars Light Trucks Unspecified Avia on Intrastate Avia on Other Avia on Light-duty Cars Light-duty Trucks & SUVs Heavy-duty Trucks, Buses Motorcycles Water - borne Port Water borne Transit Water borne Harbor Cra Off-road Industrial Off-road Oil Drilling Interna onal Avia on Interstate Avia on Interna onal Marine

4 Transition Scenario Modeling Framework Spreadsheet-based model Specify vehicle technologies (sales mix, fuel consumption, cost) Specify fuel supply (production/delivery pathways, carbon intensity, cost) Vehicle Input Data Fuels Input Data Vehicle stock turnover model for each vehicle type/technology Fuel Consump on Fuel Infrastructure accoun ng model for each fuel type/ pathway Not yet completed Model Outputs Vehicle Costs Infrastructure Costs Incremental Costs GHG emissions Fuel consump on Total Resource Usage

5 CA Scenarios Progress and Results Work is ongoing and we have completed the light-duty vehicle sector and several heavy-duty and medium-duty truck applications California data and scenarios Stock turnover model based upon VISION model Vehicle component cost model Currently assume trajectory for component costs, but will incorporate learning for batteries, fuel cells and other key components as a function of adoption Simple representation of fuel pathways and fuel costs More detailed infrastructure (resource supply, production, transport, refueling) representation will be developed Lots of assumptions about fuel blends, carbon intensity, and costs across BAU and GHG scenarios The results shown in the following slides are preliminary scenarios examples from this first stage scenario model

6 LDVs scenarios compared Reference scenario (BAU): ZEV compliant scenario ~16% of vehicles in 225 are ZEVs or TZEVs No additional growth in adoption after that Low Carbon scenario (GHG): Aggressive uptake of ZEVs by 23: 46% of cars/light trucks sold in 23 are EVs and PHEVs, and ~9% in 24 Scenarios are identical to 215 BAU 3, LDV Fleet Mix 3, GHG LDV Fleet Mix 25, 25, LDV Fleet (Thousands of Vehicles) 2, 15, 1, 5, LDV Fleet (Thousands of Vehicles) 2, FCV BEV 15, PHEV HEV 1, CNG Conv+FFV 5, FCV BEV PHEV HEV CNG Conv+FFV

7 Reference (BAU) HD and MD Trucks scenarios LH Fleet (Thousands of Vehicles) Conservative adoption of alternative vehicle technologies in LH and SH. CNG is adopted fairly substantially in MD delivery Long-Haul Fleet Mix SH Fleet (Thousands of Vehicles) BEV Fuel 8 Cell CNG SI LNG 6 SI LNG CI 4 Hybrid Diesel 2 Short-Haul Fleet Mix BEV 2 BEV 1 Fuel Cell CNG Si LNG Si LNG CI Hybrid Diesel MD Delivery Fleet (Thousands of Vehicles) Medium-Duty Delivery Fleet Mix BEV 2 BEV 1 Fuel Cell CNG Hybrid Gasoline Diesel

8 Decarbonized (GHG) HD and MD scenarios LH Fleet (Thousands of Vehicles) Sales of 5% FCVs in LH and SH by 25. B5 Diesel blend. MD has substantial CNG, Fuel Cell and BEVs by 25 Long-Haul Fleet Mix SH Fleet (Thousands of Vehicles) BEV Fuel 8 Cell CNG SI LNG 6 SI LNG CI 4 Hybrid Diesel 2 Short-Haul Fleet Mix BEV 2 BEV 1 Fuel Cell CNG Si LNG Si LNG CI Hybrid Diesel MD Delivery Fleet (Thousands of Vehicles) Medium-Duty Delivery Fleet Mix BEV 2 BEV 1 Fuel Cell CNG Hybrid Gasoline Diesel

9 LDV Results 14 BAU - has significant increase in fuel economy so fuel consumption drops by 21% (23) and 33% (25) GHG - even larger reduction in fuel consumption, 33% in 23 and 57% in 25 Fuel Consumption (Million GGE) H2 Electricity CNG Biodiesel Diesel Ethanol Gasoline BAU GHG 8 16, LDV Fuel Economy (MPGGE) BAU GHG Annual LDV GHG Emissions (ktco2/yr) 14, 12, 1, 8, 6, 4, 2, BAU

10 HD and MD Results Fuel economy improvements lead to substantial reduction in fuel consumption: 25% (23) and 2% (25) in BAU, 26% (23) to 32% (25) in GHG scenario Fuel Consumption (Million GGE) BAU GHG H2 Electricity CNG Biodiesel Diesel Ethanol Gasoline Annual GHG Emissions (ktco2/yr) 45, 4, 35, 3, 25, 2, BAU 15, 1, 5,

11 GHG emissions comparison Greater emissions reduction from LDVs due to greater adoption of advanced and zero-emission vehicles LDV HD+MD Total LDV HD+MD Total BAU 22.4% 26.1% 23.2% 35.5% 22.6% 32.7% reduction from 21 levels GHG 33.7% 28.7% 32.6% 73.3% 55.% 69.3% reduction below BAU GHG 14.5% 3.6% 12.2% 58.6% 41.9% 54.4% GHG Emissions (MtCO2e) HDV Reductions LDV Reductions HDV Emissions LDV Emissions BAU GHG

12 LDV Cost Comparison Annual expenditures- Fuel: $26 billion Vehicles: $46 billion in 215 Incremental vehicle cost: up to $4 billion/yr Fuel savings grows over time Fuel savings balance incremental vehicle cost in 23 Total incremental cost to 23: $13 billion Large savings after , Fuel Fuel Vehicle 1, F+V Vehicle Cumulative F+V Annual Costs ($Millions) 5, -5, PV Cumulative F+V , -15,

13 HDV + MDV Cost Comparison Annual expenditures- Fuel: $7 billion Vehicles: $3 billion in 215 Incremental vehicle cost: up to $3 million/yr Fuel savings balance incremental vehicle cost in 237 Total incremental cost to 237: $1.7 billion Large savings after 24 2, Fuel Vehicle Fuel 1,5 F+V Vehicle 1, Cumulative F+V Annual Costs ($Millions) , PV F+V Cumulative ,5-2,

14 Abatement Cost Comparison The cost of CO2 reduction ($/tonne CO2) is comparable between light-duty vehicles and trucks LDVs have higher emissions reduction potential Greater total costs ($/tonne x tonnes reduced) CO2 Reduction Cost ($/tco2e) 'LDV' 'HDV + MDV' Annual Emissions Reduction (MtCO2e) GHG Mitigation Cost ($/tco2e) 1,6 1,4 Annual LDV 1,2 Cumulative LDV Annual HD/MD 1, Cumulative HD/MD

15 Initial Findings We built a spreadsheet framework for our transition scenarios modeling and incorporated largest/most important transportation sectors LDVs Most HDVs (Long-Haul, Short-Haul and MD Delivery) We developed two preliminary scenarios, a Reference and GHG reduction scenario to analyze emissions, fuel and cost impacts of the transition to a low-carbon transport system LDVs can achieve a 73% GHG reduction from 21 levels by 25, ultimately at negative cost of abatement substantial incremental cost in the medium-term ($13 billion by 23) HDVs and MDVs achieve 55% reduction from 21 levels by 25, also with negative cost of abatement. Incremental cost of $1.7 billion by 238 Abatement costs ($/tonne CO2) are high initially (at low levels of GHG reduction), but decline substantially, becoming negative, as GHG reduction quantity increases

16 Next Steps Add additional transportation sectors/segments Other truck sectors (vocational, light-heavy duty) Bus, Rail, Air, Marine, Off-road Improve representation of fuel resource supply, production and infrastructure Continue to refine cost and vehicle performance assumptions Explore other scenarios of interest