Low Carbon Transport Futures - Modelling on the...
Transcript of Low Carbon Transport Futures - Modelling on the...
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