IA-SCENARIOS AND IA-MODELS A CROSS-FERTILIZATION

1. SUMMERSCHOOL IA-SCENARIOS AND IA-MODELS A CROSS-FERTILIZATION Jan Rotmans September 3rd 1999

2. SCENARIOS Characteristics: • Hypothetical • Dynamic • Links of states, driving forces, events, consequences and actions • Fixed time horizon

3. Scenarios are NOTimages of the future BUTmovies of the future (sequence of future images) Scenarios are NOTpredictions or forecasts of the future BUTprojections of the future (what …. if projections)

4. REMEMBER THE DUALITY BETWEEN ‘DOERS’ AND ‘THINKERS’! Most scenarios have been developed by ‘doers’ instead of ‘thinkers’ Domination of engineers, economists and planners Rare contributions from social sciences No poets, painters, philosophers and free thinkers

5. DEFICIENCIES OF CURRENT SCENARIOS • narrow-based (one disciplinary, one perspective) • extrapolative (business-as-usual) • boring (not imaginative) • opaque (not transparent) • inconsistent (assumptions do not match)

6. SCENARIO CLASSIFICATION • forecasting versus backcasting • descriptive versus normative • model-based versus narrative • participative versus desk-study • multiple-issue versus single-issue • multiple-scale versus single-scale

7. WHAT ARE IA-SCENARIOS? Integrated Assessment scenarios are: Participative (stakeholder-based) Consistent (key assumptions checked among different sectors, actors and factors) Coherent (inclusion of relevant linkages and dimensions) Multiple scale (cover various scales in space and time)

8. EUROPEAN SCENARIOS IN HISTORICAL PERSPECTIVE: • about 40 European scenario studies have been considered • 10 European scenario studies have been studied in-depth • social, economic, environmental and institutional dimensions have been analysed • scenario exercises have been classified into: • model-based, narrative, participatory/single area, single issue • scenarios have been clustered (comparable trends)

9. CLASSES OF INDICATORS Indicators Social Economic Environmental Institutional WRR (1992) * * * Button (1993) * EFILWC (1994) * ECN (1995) * McRae (1995) * * EC DGXII (1996) * * * EC DGXVII (1996) * * * CPB (1997) * Smith (1997) * * Table: The classes of indicators used in the various studies

10. WHAT DID THE EUROPEAN SCENARIOS HAVE IN COMMON? • Limited variety (look similar) • Descriptive rather than normative • Almost no surprises • Forecasting rather than backcasting • Hardly any concrete policy recommendations

11. GENERAL CONCLUSION There are no scenarios available that discuss sustainable development in Europe in a balanced and integrated manner

12. CLUSTERING OF EUROPEAN SCENARIOS • Money maker • high economic growth as binding element • Think green • environmental protection as binding element • Wait and see • with limited policy action as binding element • Doom monger • with pessimistic character as binding element

13. Integration scenario Opening Opportunities Free market free trade Global Competition Hypermarket Money maker Conventional Wisdom Guiding Change Plus ça change Nature and landscape Thord scenario McRae scenario Wait & See Transport ECOTEC European Coordination Battlefield Fragmentation Environmental protection Energy ECOTEC Divided Europe Transforming Communities The Apocalypse Think Green Forum Doom monger Clustered scenarios Dark ages Regional development

14. INTEGRATED ASSESSMENT MODELS Computer simulation models that describe: the cause-effect relations of a specific problem and the interlinkages with other problems

15. IA MODELS First generation on resource depletion and pollution Second generation on international environmental problems Third generation on sustainable development on intangible issues

16. TWO TYPES OF IA-MODELS • economic-oriented • parameterised • neo-classical/equilibrium • optimisation • poor representation of environment • e.g. DICE • environment-oriented • process-based • complex • evaluation • poor representation of economics • e.g. IMAGE • TARGETS

17. ESSENTIAL COMPLEX  COMPLICATED Complex models contain many interactions and feedbacks between processes Complicated models contain many processes SIMPLE = BEAUTIFUL

18. STRENGHTS OF IA-MODELS • Exploration of feedbacks • Flexible and rapid tools • Exploration of critical uncertainties • Communication tools

19. WEAKNESSES OF IA-MODELS • High abstraction level • Inadequate treatment of uncertainties • Deterministic • Limited calibration and validation

20. GENERAL STRUCTURE IA-MODEL CLIMATE CHANGE Demographic module Economic/Energy module Atmospheric Chemistry module Terrestrial and Aquatic Biosphere module Climate module Sea level rise module Socio-economic impacts Ecological impact module

21. META CLIMATE INTEGRATED ASSESSMENT MODEL A simple Integrated Assessment Model for Climate Change contains mathematical equations that represent the cause-effect chain from emissions to impacts of climate change. Here, only the greenhouse gas CO2 is taken into account.

22. META CLIMATE INTEGRATED ASSESSMENT MODEL continued Human activities - Emissions of CO2EmCO2(t) = pop(t) * {En(t)/pop(t)}*{Em(t)/En(t)} Emission CO2 - Concentration CO2pCO2(t) = pCO2(t-1) + rf(t-1) * atmc * EmCO2(t-1) Concentration CO2 - Radiative forcing QCO2 = {Q2*CO2(t)/Ln(2)}/{Ln[pCO2(t)/pCO2in(t)]}

23. META CLIMATE INTEGRATED ASSESSMENT MODEL continued Radiative forcing - Emission of CO2 Teq(t) = {QCO2(t)/} Equilibrium Temperature Change - Transient Temperature ChangeTtranssa(t) = {f *Teq + kToc}/{f + k} Global-Mean Transient Temperature Change - Regional Temperature Change Tregt(t) = 1/n  {[Tregi(t)/Teq(t)] * Ttrans(t)} n=1 Tregt(t) ={ Treg(t)/Teq(t)} * Ttrans(t) n i = 1

24. META CLIMATE INTEGRATED ASSESSMENT MODEL continued Transient Temperature Change - Sea level Change  Seaglac(t) =  * Ttrans (t) * e- Ttrans(t)/ Transient Temperature Change - Malaria Incidence Change Nmal(t) = k * {-log(p)/a2p2} Sea level Change - Adaptation Costs Cadap(t) = Cdikes (t) + Cdunes(t) + Cwater(t) f(safety-index) f(coastal retreat)