Low Carbon Transport Futures

David Banister

Director of the Transport Studies Unit School of Geography and the Environment

Oxford University

ESRC Seminar Series – Modelling on the Move: Towards Sustainable Transport Systems

St Anne’s College Oxford 7th December 2012

1. The Global Transport Imperative

1. Transport brings enormous benefits – globalisation, travel and trade

2. Totally dependent on oil – uses 61% global oil

3. Major contributor to CO2 emissions – about 24% IPCC 2007: Figure 5.4: Historical and projected CO2 emission from

transport by modes, 1970–2050 Source: IEA, 2005; WBCSD, 2004b.

Estimates of about 400 CO2 ppmv 2011 – and CO2e = 440

The Facts – tCO2 2008 Total Transport Global 4.38 1.00

EU27 7.72 1.89

US 18.35 5.54

Target 2.00 0.75

China 4.91 0.34

India 1.25 0.12

Energy + Carbon in Transport

Global Transport in 2050: The potential for reduction

2008 2050 Land transport Air transport Shipping Global Total

6.6 Gt CO2 (22%) 0.730 Gt CO2 (2.2%) 1 Gt CO2 (3.1%)

29.381 Gt CO2

3.2 – 3.6 Gt CO2 (20-22%) 2.4 – 3.2 Gt CO2 (15-20%) 2.4 – 3.6 Gt CO2 (15-22%)

16 Gt CO2 (100%)

The 2050 figure is 50% of 2005 figure.

This means that nearly 65% of all carbon emissions could come from transport – see figures above.

Air transport figures from IEA (2008) and shipping from the second IMO GHG CO2 study (2009).

2. Looking into the Future

Scenarios: innovation, reflexivity, framing in analysing change in socio economic systems

1. Forecasting - Projective a) Probable futures and possible futures b) Where current trends are stable c) Time horizon about 10 years d) American tradition – cautious no

regrets strategy is taken e) Regional in scale – promoted by

metropolitan planning authorities – sprawl and urban form

f) Quantitative and some evaluation – conventional futures being considered

2. Exploratory - Prospective a) Most widely used – two dimensions

and four scenarios b) Possible and plausible futures –

challenging and designed to promote new thinking

c) French Tradition or La Prospective – present the possibility space and uncertainty explicit

d) Interactive and participatory e) Peter Schwartz – 10 steps f) Mixed quantitative and qualitative -

workshops

Good Intentions Carbon points, energy efficient and monitored society, but still not really responded to climate change imperative

Perpetual Motion Constant information, globalisation, consumption and competition, and a high demand for travel

Tribal Trading Energy shock, global recession, high unemployment, poor quality infrastructure and local travel

Urban Colonies Minimum environmental impacts, good environmental practice, sustainable cities and clean transport

Impact of transport systems

Acceptability of intelligent infrastructure

UK Foresight Project 2006

Global Visions

Fukuyama

Globalisation

Material intensive

The End of History

Brundtland

Globalisation

Material extensive

Sustainable Development

Huntington

Regional

Material intensive

Clashes of Civilisation

Schumacher

Regional

Material extensive

Small is Beautiful

Globalisation

Localisation

Environment and Equity

Econ

omic

Effi

cien

cy

3. Visioning - Backcasting

a) Longer term (20-30 years) trend breaking b) More normative view of the future c) Desirable futures – visioning – pathways d) Swedish tradition – participatory e) John Robinson f) Flexibility, adaptability and robustness g) Quantitative and qualitative

1. Baseline and projection 2. Alternative image(s) of the

future 3. Policy measures and

packages available 4. Appraisal, costing, optimum

pathways 5. Conclusions – policy

recommendations

5 Stages

Backcasting : Study Method

Key elements in Backcasting

1. Uncertainty explicit – energy costs $100 a barrel ++

2. Differential economic growth rates, population growth, migration and ageing all treated as external elements

3. Changes in activities – work to leisure based society, differential levels of development, role of technology

4. Different Images of the Future – to encompass views on sustainable development, consumption, pricing, technology and behavioural change

5. Reviews the full range of policy options – then puts them together in mutually supporting packages

6. Identifies pathways from the present to the future – to determine what actions should be taken now, where the ‘quick hits’ are, and the scale of change needed

7. Appraisal of policy packages through multicriteria analysis

8. Extensive participation throughout the Backcasting process.

Backcasting Studies in Transport

Jinan - China

Delhi - India

London - UK

Oxfordshire - UK

Auckland - NZ

Victoria - Canada

UK Transport Policy

www.vibat.org

Comparing Forecasting and Backcasting

Measure Forecasting Backcasting Philosophy Justification as the context

Causality determinism Discovery as the context Causality and intentions

Perspective Dominant trends Likely futures Possible marginal adjustments Focus on adapting to trends

Societal problem in need of a solution Desirable futures Scope of human choice Strategic decisions Retain freedom of action

Approach Extrapolate trends into future Sensitivity analysis

Define interesting futures Analyse consequences and conditions for these futures to materialise

Method and technique

Various econometric models Mathematical algorithms

Partial and conditional extrapolations Normative models, system dynamic models, Delphi methods, expert judgement

Based on Geurs and Van Wee, 2000, 2004; and adapted from Dreborg, 1996. See also Banister, Hickman and Stead (2007) and Åkerman and Höjer (2006).

3. Modelling on the Move – Future Agendas and Low

Carbon Transport 1. Shaping and adapting – specific issues; inclusive of all interested

parties; role of experts; keeping options open; direction of shaping

2. Single futures or multiple futures – simple images good for building coalitions and setting agenda; multiple options allow greater flexibility and allow more space for thinking

3. Normative or exploratory – vision driven helpful where there is a clear imperative; exploratory better for situations of greater uncertainty

4. Robustness and adaptability of policy portfolios – flexibility in approaches important; robustness relates to whether measures are appropriate under all situations and adaptability links with accommodating the unexpected – risks, opportunities and resilience