Scenario Analysis, Backcasting and Sustainable Transport

Transcription

1 ADB Transport Forum, Manila 2010 Scenario Analysis, Backcasting and Sustainable Transport Visioning and Backcasting for Transport (VIBAT) Integrated Transport Decision Support and Simulation (INTRA-SIM) Dr Robin Hickman Halcrow and University of Oxford, Transport Studies Unit

2 Outline Futures methodologies London: reduced CO2 emissions scenarios Oxfordshire: sustainable transport scenarios (multi-criteria) Conclusions

3 VIBAT Series of Studies (2004-ongoing) UK (DfT, ) London (Hefce, ) Delhi, scoping (ADB, 2008) Victoria, scoping (TC, 2008) Oxfordshire (OCC, DfT, ) Swindon (SBC, DfT, 2010) Jinan (Oxford University, Future of Cities, 2010) Auckland (ACC, 2010)

4 Useful Approaches: Scenario Analysis and Backcasting Baseline and projection Alternative scenario(s) of the future Policy measures and packages available Appraisal, costing, optimum pathways

5 A Useful Approach: Backcasting Backcasting: major distinguishing characteristic is "a concern, not with what futures are likely to happen, but with how desirable futures can be attained. It is thus explicitly normative, involving working backwards from a particular desirable endpoint to the present in order to determine the physical suitability of that future and what policy measures would be required to reach that point.

6 INTRA-SIM: Policy Packaging and Scenario MCA

7 VIBAT-London

8 VIBAT London

9 VIBAT London Objective: a 60% reduction in CO2 emissions in the transport sector in London by 2025 and 80% by 2050 A range of policy packages Level of application Target achieved/ achievable?

10 London: The Baseline (Transport Only)

11 TC-SIM London Local Version 03 Web Version 03 C:\tcsim\tcsim_version_02\tcsim_65\vibat.html tcsim topgear

12 Oxfordshire INTRA-SIM

13 Broad INTRA-SIM methodology Systematic packaging of interventions/sifting, and scenario testing/optioneering: Consider likely policy interventions (OCC remit and beyond) Group interventions into packages Model impacts against multi-criteria (WebTAG): environment, economy, accessibility and safety Cluster policy packages, at various levels of application, into scenarios Systematically assess strategic policy choices and priorities Discuss and prioritise most likely strategies

14 Oxfordshire INTRA-SIM Spatial Disaggregation Oxfordshire Oxford Large town Small town Rural District

15 INTRA-SIM Policy Packages PP1 Rail PP2 Bus PP3 Walk PP4 Cycle PP5 Highway Infrastructure PP6 Traffic Demand Management PP7 Pricing PP8 Parking Management PP9 Park and Ride PP10 Land Use Planning PP11 Behavioural Change PP12 Low Emissions Vehicles PP13 Alternative Fuels PP14 Slower Speeds and Ecological Driving PP15 Freight PP16 Long Distance Travel Substitution

16 INTRA-SIM Oxfordshire Local Version 03 Web Version 03 C:\Documents and Settings\hickmanro\My Documents\oxfordshire intra-sim\bin\intrasim.html intrasim halcrow

17 Motivations for [Sustainable] Travel?

18 Emerging Findings: Towards Sustainable Transport Much debate but little action transport sector needs to URGENTLY ACCELERATE its efforts Some cities, such as London and Oxford, providing a lead Asian context a huge challenge: Dramatic projected travel growth Huge opportunity to develop the new paradigm carbon efficient travel Tailored solutions to context Wide range of policy packages available many require successful application to achieve ambitious targets Appraisal - not just CO2; wider quality of life aspects Behavioural and lifestyle changes difficult to engender need to understand the social factors Participatory elements critical people need to choose their future travel lifestyles, ideally consistent with policy goals

19 ADB Transport Forum, Manila 2010 Scenario Analysis, Backcasting and Sustainable Transport Dr Robin Hickman Halcrow and University of Oxford, Transport Studies Unit

20 ADB Transport Forum, Manila 2010 Reserve

21 Some Literature [A book on transport and climate change in preparation] Hickman, R., Ashiru, O. and Banister, D. (forthcoming 2010) Low carbon transport futures and wider multicriteria impacts. A view from Oxfordshire, UK. WCTR, Lisbon. Hickman, R., Ashiru, O. and Banister, D. (forthcoming 2010) Transitions to low carbon transport futures. Strategic conversations from London and Delhi. Hickman, R. and Banister, D. (2010) Transport and climate change: simulating the options for carbon reduction in London. Transport Policy, 17(2): Hickman, R., Ashiru, O. and Banister, D. (2009) Achieving carbon efficient transport: backcasting from London. Transportation Research Record, 2139: Woodcock, J., Banister, D., Hickman, R., et al.. (2009) Public health benefits of strategies to reduce greenhousegas emissions: urban land transport. The Lancet, 374(9705): Banister, D. and Hickman, R. (2009) Techno-optimism: progress towards CO2 reduction targets in transport: a UK and London perspective. International Journal of Sustainable Development, 12(1): Hickman, R. and Banister, D. (2009) Sustainable Cities: Transport Best Practice Guide. CABE. [ Hickman, R., Ashiru, O., Seaborn, C., Headicar, P. and Banister, D. (2009) Planning for Sustainable Travel Best practice Guide and Web manual [ Banister, D. (2008) The sustainable mobility paradigm. Transport Policy, 15: Hickman, R. and Banister, D. (2007) Looking over the horizon: transport and reduced CO2 emissions in the UK by Transport Policy, 14(5):

22 Discuss and Optimise the Strategy

23 Optimising the strategy

24 Environment (Strategic) 1. Total carbon dioxide (CO2) emissions [car, LGV, HGV, bus and rail] MCAF Indicators [WebTAG-based] Environment (Local) 1. Population and households living within 20m of the road exposed to 68db(A) or higher road traffic noise level at the point of receipt 2. Population and households perceiving road traffic noise nuisance 3. Population and households perceiving road traffic vibration nuisance 4. Total emissions of Carbon Monoxide 5. Total emissions of Hydrocarbons 6. Total emissions of Oxides of Nitrogen 7. Total emissions of Particulate Matter 8. Total emissions of Benzene 9. Total emissions of Butadiene

25 Accessibility Households within 30 minutes of Town Centres Households within 30 minutes of Hospitals Households within 30 minutes of Workplaces 4. Hansen measure of accessibility to Town Centres 5. Hansen measure of accessibility to Hospitals 6. Hansen measure of accessibility to Workplaces [highway/rail/bus/walk/cycle] MCAF Indicators Safety 1. Total number of road traffic personal injury accidents (PIAs), (observed Stats19 data, ) projected to Number of road traffic accidents resulting in slight injury 3. Number of road traffic accidents resulting in serious injury 4. Number of road traffic accidents involving fatalities Economy 1. Travel time on links 2. Junction delay 3. Journey time reliability 4. Access to jobs (Saturn/Emme2/accession)

26 Developing Scenarios (Clustered Packages)