GHG-TransPoRD: 2020: Linking R&D, transport policies and reduction targets. Project overview -

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1 GHG-TransPoRD: reducing greenhouse gas emissions of transport beyond 2020: Linking R&D, transport policies and reduction targets Project overview - Dr. Wolfgang Schade Fraunhofer-ISI Coordinator of GHG-TransPoRD w.schade@isi.fraunhofer.de i h f d Seite 2

2 Objective of GHG-TransPoRD Suggestion of an integrated strategy for the EU that links R&D policy for transport with a transport policy strategy such that the European GHG reduction targets for 2020 and 2050 can be met also for transport. Expected results: Reduction targets for transport R&D strategy Transport policy strategy Project framework Funded by European 7 th Research Framework Programme (~950 k ) Project duration 27 months (Oct. 1 st 2009 to Dec. 31 st 2011) Five project partners from five European countries Seite 3

3 Structure of activities of GHG-TransPoRD (work pack ages) WP5: Hig gh-level policy con ntext WP1 : R&D eff forts in th he transpo ort sector WP2 WP3 WP4 Scoping of GHG reduction measures Short listing of promising measures Estimation of potential CO2 reductions Economic impact of GHG reduction measures Linking R&D and learning curves to measures Estimation of abatement cost of measures Bundling of measures to scenarios Simulation of scenarios with models Impact assessment of scenarios WP6 6: Commu unication with stak keholders => GHG reduction scenarios and targets for transport Seite 4

4 Step 1: Estimating GHG reduction potentials WP2 Scoping of GHG reduction measures Short listing of promising measures Estimation of potential CO2 reductions Result tco 2 saved by measure WP3 Economics of GHG reduction measures Linking R&D and learning curves to measures Estimation of abatement cost of measures Bundling of measures to scenarios Simulation of scenarios with models WP4 Impact assessment of scenarios Seite 5

5 Reference energy demand trend up to 2050 ( b y f uel t ype i n PJ/year) GHG TransPoRD Energy Framework 30,000 25,000 20,000 15,000 10,000 5,000 [PJ] Biofuel (road) Hydrogen Electricity (rail) Kerosene (air) CNG (car) LPG (car) Diesel (ship) Diesel (road & rail) Gasoline (road) Source: GHG-TransPoRD D Seite 6

6 Theoretical GHG reduction potentials of measures E xampl e for cars for the year 2020(s h ort list) Injection Technology Electrical System Energy Supply Heat/Cooling Management Lightweight Construction Engine Control System Hybrid Vehicles Aerodynamics/Resistance CNG/LPG Battery Electric Vehicles Electrical l System Energy Demand Drive and Transmission Hydrogen Fuel Cell Vehicles [Mt CO2] Source: GHG-TransPoRD D2, Remark: usage of biofuels was subject to separate analyses Seite 7

7 Technical theoretical GHG reduction potentials by mode Mode [%-relative reduction to reference] Road Technical cars* -40 to -45% -60 to -68% Technical trucks -30 to -36% -57 to -63% Urban measures** -43% -70% National policies*** -40% -70% Rail Technology non-urban traffic -10% -42% Technology urban traffic -8% -55% Air Technology & policy -15% -41% Shipping Technology ogy & policy -5% -20to -25% Biofuels Technology**** -16% n.a. Source: GHG-TransPoRD D2 Seite 8

8 Step 2: Estimating costs of single measures WP2 Scoping of GHG reduction measures Short listing of promising measures Estimation of potential CO2 reductions Result tco 2 saved by measure WP3 Economics of GHG reduction measures Linking R&D and learning curves to measures Estimation of abatement cost of measures /t CO 2 t 1, t 2, t 3 saved by measure Bundling of measures to scenarios Simulation of scenarios with models WP4 Impact assessment of scenarios Seite 9

9 Cluster 1: Aerodynamics and Resistance Technology Potentials Cost ( 2005 ) Reference Improved aerodynamics 2% 103 AEA 2009 Low rolling resistance tyres 2% 39 AEA 2009 Tyre pressure monitoring system 1% 62 TNO 2006 Low viscosity lubricants 2% 19 TNO 2006 Reduced mechanical friction components 4% 64 AEA 2009 Total 10% 288 First market entry: % diffusion: Cum. Prod.(2010): 2 Mio 0.4 Market size: 50 Mio/a Learning rate: 5%,10%,15% ket Penetration] [Mar Technology Diffusion Aerodynamics and Resistance [Year] Seite 10

10 Cluster 1: Classical 1-Factor Learning Curve Factor Learning Curve Aerodynamics and Resistance price incl. Ta ax in 2005] [Retail Learning Rate 5% Learning Rate 10% Learning Rate 15% [Cumulated Production in Mio Units] Source: GHG-TransPoRD D3 Seite 11

11 Step 3: Estimating impacts of scenarios WP2 Scoping of GHG reduction measures Short listing of promising measures Estimation of potential CO2 reductions Result tco 2 saved by measure WP3 Economics of GHG reduction measures Linking R&D and learning curves to measures Estimation of abatement cost of measures /t CO 2 t 1, t 2, t 3 saved by measure Bundling of measures to scenarios Simulation of scenarios with models WP4 Impact assessment of scenarios t CO 2 saved GDP change Etc. by EU27 Seite 12

12 Models applied for the scenario analysis ASTRA: integrated transport-environment-economy assessment model scenario design and quantification model, policy analysis model. POLES: world energy system model transport as one of the covered final energy demand sectors. TREMOVE: transport fleet and environmental assessment model policy analysis model. MARS: urban simulation model covering the urban transport sector urban case study. Seite 13

13 Linkages between the applied models R eference scenari o PRIMES Reference Scenario GDP Population Demand for Energy, Transport Measures as part of the Reference Scenario Energy prices Biofuel supply Energy prices ASTRA Integrated economytransport-environment model POLES World energy model TREMOVE Environmental impact model and vehicle fleet model White Paper 2011 Impact assessment Energy prices Vehicle fleet composition MARS GDP Transport (energy) demand Urban land use and transport model Seite 14

14 Linkages between the applied models P olicy scenari os of GHG-TransP ord Policy scenario Technology by mode Investment in R&D and new production National policies Urban policies Energy prices Biofuel supply Energy investment ASTRA Integrated economytransport-environment model POLES World energy model Energy prices TREMOVE Environmental impact model and vehicle fleet model Energy prices Vehicle fleet composition MARS GDP Transport demand Transport energy demand Urban land use and transport model Seite 15

15 Agenda of day 1 ASTRA model POLES model TREMOVE model MARS model Seite 16

16 Contact Dr. Wolfgang Schade Coordinator of GHG-TransPoRD project Fraunhofer Institute Systems and Innovation Research (ISI) Breslauerstr. 48, Karlsruhe, Germany Phone: Fax: Project website: Seite 17

GHG-TransPoRD: 2020: Linking R&D, transport policies and reduction targets. Economic impacts of the scenarios

GHG-TransPoRD: 2020: Linking R&D, transport policies and reduction targets. Economic impacts of the scenarios GHG-TransPoRD: reducing greenhouse gas emissions of transport beyond 2020: Linking R&D, transport policies and reduction targets Economic impacts of the scenarios Dr. Wolfgang Schade Fraunhofer-ISI Karlsruhe,