Long-Term Transport Energy Demand and Climate Policy: Alternative Visions on Transport Decarbonization in Energy-Economy Models

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Arlene Dawson
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University, Chen Wenying Tsinghua University Page Kyle PNNL, Gunnar Luderer PIK, Elmar Kriegler PIK

1 Long-Term Transport Energy Demand and Climate Policy: Alternative Visions on Transport Decarbonization in Energy-Economy Models Robert Pietzcker PIK, Thomas Longden FFEM Fu Sha Renmin University, Chen Wenying Tsinghua University Page Kyle PNNL, Gunnar Luderer PIK, Elmar Kriegler PIK Climate Policy Outreach Project (CPO) IEW 2013, Paris March 22, 2013 FEEM working paper, currently under review at ENERGY

2 Contents Model & Analysis Setup General Scenario Results Analysis and Discussion Main Messages 2

3 Research Questions Is transport more difficult to decarbonize than other sectors? What are possible decarbonization pathways for transport? How do different IAMs model transport? Answered with energy-economy models by Running four scenarios with a global carbon tax rising at 5%/year, starting in 2020 with 0/10/30/50 $/tco2 Analyzing the mitigation levers along the chain of causality from mobility demand to primary energy Discussing the structural differences between mitigation in the transport sector and the non-transport sectors 3

4 Overview over the Transport Paper Participating Models: Two partial equilibrium models (focus on China) : PECE, CHN-TIMES Three general equilibrium models (World): WITCH, REMIND, GCAM New Research due to CPO project : Impressive improvement of transport modeling First in-depth analysis of embedded transport decarbonization across several IAMs 4

5 Chain of Causality in the Transport Sector 5

6 Model specs: Which transport modes are modeled Transport Sector Passenger Freight LDV Rail Bus Aviation Truck Rail Aviation Navigation CHN-T y y y y y y y y GCAM y y y y y y y y PECE y y y y y y y y REMIND y y aggregated aggregated WITCH-T y y n n* y y n* n *: the energy used for aviation is included in a fossil-fuel-heavy non-electricity sector 6

7 Model specs: Energy carriers used LDVs use Fuels used for freight Fuels used for aviation CHN-T GCAM PECE REMIND WITCH-T Liquids y y y y y Liquids (efficient) y n y n y Gas y y y n n Power y y y y y H2 y y y y n Liquids y y y y y Gas y n n n y Power y n y n y H2 n n n n n Liquids y y y y Gas n n n n Power n n n n N/A H2 n n n n 7

8 Model specs: PE types used for liquid fuels CHN-T GCAM PECE REMIND WITCH-T Crude Oil y y y y y PE usable for liquid transport fuels Biofuel y y y y y Bio+CCS n y y y n Coal y y y y N Coal+CCS y y y y N Gas y y y n N 8

9 Contents Model & Analysis Setup General Scenario Results Analysis and Discussion Main Messages 9

10 Transport Final Energy Demand China, REF Very different projections factor of 2 in 205 WITCH: strong reduction of transport FE use due to electrification Local models consistently see very high transport FE demand 10

11 Transport emissions - China WITCH decarbonizes already in REF due to electrification REMIND has strong emissions increase in REF due to Coal2Liquid Tax Scenarios well-behaved 11

12 Transport decarbonization relative to REF Emission reductions Tax30 China, rel. to Ref In the long term >90% emission reduction in Transport 12

13 Contents Model & Analysis Setup General Scenario Results Analysis and Discussion Main Messages 13

14 Chain of Causality in the Transport Sector 14

15 What happens to Energy Service demand? Passenger Freight China Very different demand projections factor 3 in 2050 No reaction to prices in WITCH-T, PECE and CHN-T, not 130 $/tco2 in 2050 (0.35 $/liter of 1500 $/tco2 in 2100 (3.5 $/ liter of gasoline) 15

16 What happens to Final Energy use? : All models but WITCH-T keep share of liquid fuels above 87% All models reduce FE demand PECE and CHN-T with eff. vehicles 2100: Strong shift to electricity and H2 16

17 Where do strong reductions come from? % FE coming from PE Biomass Fossil 2050: >80% Fossil, a bit Bio Liq 2100: GCAM: BioCCS Liq // Nuc Elec REMIND: BioCCS H2 // REN Elec WITCH: Nuc Elec // REN Elec 17

18 Direction of sectoral mitigation Transport Non-Transport Tax30 China, relative to Reference Transport until 2030: main action on FE efficiency then continue on both dimensions Non-Transport 4 models go to -20/-20, then mainly CO2 intens. reduction The dots mark the years 2010, 2020, 2030, 2050,

19 Timing of sectoral mitigation Transport Non-Transport Emission reductions Tax30 China, rel. to Ref transport lags years behind non-transport 19

20 Contents Model & Analysis Setup General Scenario Results Analysis and Discussion Main Messages 20

21 Main Messages 1. Very different long-term decarbonization pathways for transport across IAMs 2. Transport decarbonization delayed by years compared to non-transportation 3. Transport relies strongly on liquid fuels until 2050 (>85%): The models see final energy reduction as the main cost-efficient mitigation measure until Transport decarbonization reaches >90% in 2100: deep reductions achieved through EV/H2 plus BiomassCCS/RE/Nuc 6. National models quite unflexible in the transport sector: - No reduction of Energy Service demand - Very little use of alternative vehicles (Electricity, H2) - Little use of Bioliquids, no BioCCS 21

22 Discussion Models say normal CO2 prices will not lead to large near-term changes to transport BUT Substantial literature on other policies that target consumer behavior and infrastructure: Can have major influence on travel behavior Studies: Soft mobility measures could reduce emisssions by 20-60% Not included: local air pollution benefits (Creutzig et al) heterogenous consumers buy more expensive new LDV 22

23 Thank you! 23

24 CO2 Intensity of FE Transport Non-Transport Strong decarbonization happens through CO2 intensity - BioCCS CHN-M and PECE don t use this option in Transport stiffness 24

25 Long-term dependence on fossils? Transport Non-Transport All models stay above 25% share of Transp energy coming from fossils GCAM and REMIND reduce fossil use in nontransp much lower, 5-15% It seems very difficult to get the transport sector fossil-free 25

26 Further research 1. Need to check REMIND numbers for FE Transportation in China 2. Maybe possible to extract Energy services from REMIND 3. Need to check WITCH Transport emissions from electricity for model comparability 4. CHN-Markal: possible to get disaggregated FE variables? 5. PECE has the technology BioCCS liquids included what is the reason it is not really used for transport? 6. No H2 used in PECE? 26

27 Final Energy demand Reference run China USA World Transport FF&I CHN strong growth, US stabilizing US/world numbers more similar accross models Total FF&I numbers more similar than transport numbers 27

28 Final Energy demand Reference run China USA World LDV Transport FF&I CHN strong growth, US stabilizing US numbers quite similar accross models 28

29 Emissions China USA World Non-Transp Transport FF&I Very different baselines accross models Very different assumptions about Transport in China 29

Transport s Role in the Decarbonization Process

Transport s Role in the Decarbonization Process Implications of Paris Research and Workshop Series Trondheim, Norway March 5-6, 2017 David McCollum (IIASA) Mitigation burden of transport sector impacts,