Narratives of low-carbon futures in land transport

Felix CreutzigMercator Research Institute on Global Commons and Climate Change

Lead Author, IPCC

Disclaimer: NOT representing the IPCC

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?

Ottmar Edenhofer, Martin Kowarsch: A Pragmatist Approach to the Science-Policy Interface, MCC-Working Paper 2012-1

Decomposing GHG emissions of transport

Total emissions

Carbon intensity

Energy intensity= x xActivity

A SI FActivity

Modal

Structure

Energy Intensity

Fuels

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

The short-term perspective

Total emissions =

Fuel producers

Car producersCar drivers

10% reduction 2020 in EU regulation, but doubtful due to LUC effects of biofuels

ca. 40% reduction in 2030 in EU/US due to 2020/2025 regulation

15-20% reduction by congestion charge (Stockholm, London)

Carbon intensity

Energy intensityx xActivity

Two narratives of mitigation

A SI FActivity

Modal

Structure

Energy Intensity

Fuels

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

pessimistoptimiststructuralbehavioral

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

Federal Ministry of Transport(Dr. Andreas Scheuer):

“everyone shall be mobile according to their facon”

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

Creutzig et al., (Nature Climate Change, 2012), based on Wise et al., 2009; Melillo et al., 2009; Meinshausen et al., 2010)

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.

Qualifying technological optimism: the bioenergy case

A Copernican-welfarist view

• Copernican in starting with observations on ground.

• Welfarist in 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.

Key messages World Bank Report

1. Embed low-carbon policies into a co-benefit framework

2. Synergies in policies: Mode shift along with demand measures

3. Explicitly consider infrastructure lock-ins4. Technical AND behavioral change is needed

Bill. RMB Creutzig, F. and He, D., Climate Change Mitigation and Co-Benefits of Feasible Transport Demand Policies in Beijing Transportation Research D 14, 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, Ancha Srinivasan, and Shobhakar Dhakal (Earthscan, London, 2009)

Net accounting of car traffic in Beijing 2005: Costs are at least 7.7% of Beijng‘s GDP

1. Embed into co-benefit framework

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

Pareto gain 13.2 to 16.2

billion Y

Elast: 0.61.0

Synergy between public transit supply and congestion charges in Beijing

Creutzig, F. and He, D., Climate Change Mitigation and Co-Benefits of Feasible Transport Demand Policies in Beijing Transportation Research D 14, 120 (2009)

Adding public transit capacity increases the efficiency of a congestion charge.

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”.

Modeling scenarios: policy packages of

increasing ambition

Example: Barcelona

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

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.

Co-benefits are high enough to motivate policies

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

Narratives and their norms

Promethian-liberal• 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

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

Weak Copernican-welfarist

Two narratives of mitigation

A SI FActivity

Modal

Structure

Energy Intensity

Fuels

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

pessimistoptimiststructuralbehavioral