Narratives of low-carbon futures in land transport

1. Narratives of low-carbon futures in land transport Felix Creutzig Mercator Research Institute on Global Commons and Climate Change Lead Author, IPCC Disclaimer: NOT representing the IPCC

2. Science-policy interface • Purpose of report is to give policy advice and stimulate public discussion • In technocratic, or decisionist models of policy advice normative assumptions (world views) are often underspecified, alternatives remain unexplored • A pragmatic-enlightened model of policy advice is recursive between scientific results and normative spaces, narratives • Here: What are the narratives of low-carbon policy futures? OttmarEdenhofer, Martin Kowarsch: A Pragmatist Approach to the Science-Policy Interface, MCC-Working Paper 2012-1

3. Decomposing GHG emissions of transport Total emissions Activity Energy intensity Carbon intensity = x x A S I F Schipper, L., Unander, F. and Marie-Lilliu, C. (2000) ‘The IEA Energy Indicators Effort: Increasing the understanding of the energy/emissions link’, IEA Public Information Office, Paris Creutzig, F., McGlynn, Minx, J. and Edenhofer, O. (2011) ‘Climate policies for road transport revisited (I): Evaluation of the current framework’, Energy Policy, 39(5), 2396-2406 Modal Structure Energy Intensity Activity Fuels

4. The short-term perspective Total emissions Activity Energy intensity Carbon intensity = x x Fuel producers Car drivers Car producers 15-20% reduction by congestion charge (Stockholm, London) ca. 40% reduction in 2030 in EU/US due to 2020/2025 regulation 10% reduction 2020 in EU regulation, but doubtful due to LUC effects of biofuels

5. Two narratives of mitigation A S I F Modal Structure Energy Intensity Activity Fuels structural behavioral pessimist optimist Promethian focus on technologies Behavior/ demand is not part of the game Change in mobility pattern is necessary for mitigation Technologies are insufficient on their own

6. The Promethian-liberal view • Global warming can be mitigated by technologies, result of human ingenuity and individual drive. • In transport, this translates to a focus on fuel efficiency, electric cars, hydrogen, and biofuels. • Notably, transport behavior and mobility patterns remain unchanged, or are projected as a continuation of trends. • Underlying norms: revealed preferences (“positivist”); utilitarian

7. Federal Ministry of Transport (Dr. Andreas Scheuer): “everyone shall be mobile according to their facon”

8. Pessimist and optimist view of technological change (Worldbank report) Transport is really the hardest sector to decarbonize (Clarke and Calvin, 2008) Mostly top-down view from Integrated Assessment models Fuel efficiency standards and electric car market penetration (IEA 2009) Mostly bottom-up view of transport experts IPCC AR4 also lives in technological world

9. Qualifying technological optimism: the bioenergy case IPCC (AR4, SRREN) suggests a high reliance on biofuels for mitigation. If there is no perfect forest protection, ILUC emissions can result in a catastrophic outcome of bioenergy deployment. The risk is so high that bioenergy deployment alone can eat up the remaining GHG budget. Creutzig et al., (Nature Climate Change, 2012), based on Wise et al., 2009; Melillo et al., 2009; Meinshausen et al., 2010)

10. A Copernican-welfarist view • Copernican in starting with observations on ground. • Welfaristin not equating revealed with normative preferences. • Suggesting that a system change can improve well-being, at least from a social cost perspective, perhaps even from an individual perspective.

11. Key messages World Bank Report • Embed low-carbon policies into a co-benefit framework • Synergies in policies: Mode shift along with demand measures • Explicitly consider infrastructure lock-ins • Technical AND behavioral change is needed

12. 1. Embed into co-benefit framework Bill. RMB Creutzig, F. and He, D., Climate Change Mitigation and Co-Benefits of Feasible Transport Demand Policies in Beijing Transportation Research D14, 120 (2009) Creutzig, F., Thomas, A., Kammen, D. M., and Deakin, E., in Low Carbon Transport in Asia: Capturing Climate and Development Co-benefits, edited by Eric Zusman, AnchaSrinivasan, and ShobhakarDhakal (Earthscan, London, 2009) Net accounting of cartraffic in Beijing 2005: Costsare at least 7.7% of Beijng‘s GDP

13. 2. Synergies of urban transport policies • Push policies • Car traffic restrictions • City toll • Reduce available lanes • Parking fees • Speed limits • Pull policies • Better public transport • Safe space for cycling and walking • Prioritisation of bicycles • Bicycle racks • Land use policies • Compact cities • Polycentric cities • Avoid urban sprawl • No greenfield development • Mixed use neighbourhoods Objectives - A - B - C - D Policies - 1 - 2 - 3 - 4

14. Synergy between public transit supply and congestion charges in Beijing Adding public transit capacity increases the efficiency of a congestion charge. Elast: 0.61.0 Paretogain 13.2 to 16.2 billion Y Creutzig, F. and He, D., Climate Change Mitigation and Co-Benefits of Feasible Transport Demand Policies in Beijing Transportation Research D14, 120 (2009)

15. 3. Consider infrastructure lock-ins • Marginal costs of use are smaller on existing infrastructures. • Calls for explicit infrastructure policy investment, in addition to pricing. • In the transport context: Integrate land-use and transport policies (Jose Viegas’ point). • Relatively few economic analysis of the “social optimal infrastructure investment”.

16. Modeling scenarios: policy packages of increasing ambition Example: Barcelona

17. Creutzig, Mühlhoff, Römer, Decarbonizing Urban Transport in European Cities Concurs with Possibly High Co-Benefits, submitted

18. Demand policies have a stronger marginal effect than public transit supply, but only subsequent to public transit supply. Land-use policies contribute significantly in the long run.

19. Co-benefits are high enough to motivate policies Creutzig, Mühlhoff, Römer, Decarbonizing Urban Transport in European Cities Concurs with Possibly High Co-Benefits, submitted

20. Narratives and their norms Promethian-liberal Strong Copernican-welfarist Divergence of normative and revealed preferences (Beshears et al., 2008): passive choice, complexity, limited personal experience, third-party marketing, and intertemporal choice. Consideration of status, norms, and habits for policy making • Demand is given and there is no reason to mess up with it • Utilitarian and liberal: the individual comes first • Social costs are best treated with price instruments • Revealed preferences are conditional on given infrastructures • If social costs are revealed, infrastructures should be modified to reduce costs Weak Copernican-welfarist

21. Two narratives of mitigation A S I F Modal Structure Energy Intensity Activity Fuels structural behavioral pessimist optimist Promethian focus on technologies Behavior/ demand is not part of the game Change in mobility pattern is necessary for mitigation Technologies are insufficient on their own