Upload
jessica-wells
View
220
Download
0
Tags:
Embed Size (px)
Citation preview
three decades of Integrated Assessment:the way forward
Jan RotmansJan RotmansEgmond aan Zee, 11-03-2009Egmond aan Zee, 11-03-2009
It would be naive to suppose that the
unsustainability problems humankind is faced
with could be solved with current tools and
methods (models!) that were applied –
or seemed to work - in the past
Rotmans, 2002
SUSTAINABILITY PARADOX
INTEGRATED ASSESSMENT
Interdisciplinary process of combining
different strands of disciplinary knowledge
to coherently represent complex societal
problems of interest to decision-makers
POLICYANALYSIS
RISK ANALYSIS
TECHNOLOGYASSESSMENT
INTEGRATEDASSESSMENT
RELEVANT RESEARCH FIELDS
HISTORY• Early Seventies Club of Rome
first global computer simulation models linking
population, pollution and resource depletion
• 1980s
IA-models for environmental issues, e.g. acid rain
• 1990s
IA-models for global climate change
• 2000-
IA-models for sustainable development
Agenda setting Strategicalpolicy making
Politicaldecision making
Implementation
IMPORTANCE of INTEGRATED ASSESSMENTim
po
rta
nce
Social and economic processes
Land coverprocesses
Atmospheric & climate processes
Processes of economic and
ecological impacts
Interventions
Pressure
State
Impact
Response
forcingfeedbackhuman interventions
IA MODEL FOR CLIMATE CHANGE
METHODS OF INTEGRATED ASSESSMENT
• modelsmodels• sscenarioscenarios• uncertainty / risk uncertainty / risk
analysisanalysis
• dialogue methoddialogue method• policy exercisespolicy exercises• mutual learningmutual learning
Analytical methods Participatory methods
natural scientific basis social-scientific basis
EVOLUTION OF IA-TOOLS
fromfrom• supply-driven supply-driven to to demand-driven demand-driven• mono-disciplinary mono-disciplinary to to inter-disciplinary inter-disciplinary• technocratic technocratic toto participatory participatory• objectiveobjective toto subjective subjective• certaintycertainty toto uncertainty uncertainty• predictivepredictive toto explorative explorative
EVOLUTION OF IA-TOOLS
Shackley & Winne (1998)Shackley & Winne (1998)
we used to build we used to build
truth machinestruth machines
but now we buildbut now we build
heuristic toolsheuristic tools
INTEGRATED ASSESSMENT
Insights from two decades of sustainability assessment:Insights from two decades of sustainability assessment:
• generic tool for integrated assessment is not possiblegeneric tool for integrated assessment is not possible• diversity of tools hinders practical use in policy-settingdiversity of tools hinders practical use in policy-setting• inter (and trans-)disciplinary approach is requiredinter (and trans-)disciplinary approach is required• subjectivity and plurality of sustainability needs to be subjectivity and plurality of sustainability needs to be
incorporated in our toolsincorporated in our tools
• current paradigm underlying integrated assessment current paradigm underlying integrated assessment
has reached its limits has reached its limits
INTEGRATED ASSESSMENT
Limits of current paradigm:Limits of current paradigm:
• rational actor paradigmrational actor paradigm
• standard equilibrium approximationstandard equilibrium approximation
• single scale representationsingle scale representation
• market failures rather than system failuresmarket failures rather than system failures
NEW PARADIGM EMERGING
• inter- and transdisciplinaryinter- and transdisciplinary
• complex systems theory as overarching mechanismcomplex systems theory as overarching mechanism
co-evolution, emergence and self-organizationco-evolution, emergence and self-organization
• evolutionary management approachevolutionary management approach
forget about command-and-controlforget about command-and-control
• co-production of knowledgeco-production of knowledge
• learning-by-doing and doing-by-learninglearning-by-doing and doing-by-learning
• system innovation rather than system optimizationsystem innovation rather than system optimization
NEXT GENERATION OF ISA-TOOLS
methodological challengesmethodological challenges
• uncertaintyuncertainty• social-cultural dimensionsocial-cultural dimension• multiple scalingmultiple scaling• stakeholder representationstakeholder representation• discontinuities and surprisesdiscontinuities and surprises• transition dynamicstransition dynamics
MULTIPLE SCALING
Various modelling approaches to multiple scaling
1. Grid-based modelssystem dynamics type of models
2. Cellular Automata modelsintelligent cell communication models
3. Multiple scale modelsland allocation regression models
Integrated
Dynamic
Model
Cellular Automata Modelling
• dynamics is more determined by macroscopic trends dynamics is more determined by macroscopic trends than by microscale dynamicsthan by microscale dynamics
• rules for determining the suitability are controversialrules for determining the suitability are controversial
• rules behind 'clustering mechanism' are not well knownrules behind 'clustering mechanism' are not well known
• reliability of CA models on macro-scale seems low, reliability of CA models on macro-scale seems low, just as reliability on the long time scale just as reliability on the long time scale
Grid-Based IA Modelling
• social, demographic, economic and technological driving forces are not represented at the grid level
• states and impacts changes are represented at the grid level (e.g. 0.5 x 0.5)
• no dynamic interactions among the grid cells
• grid cell output suggests more precision than can be fulfilled
Multiple-scale Modelling
• relatively coarse scale on which land use trends are relatively coarse scale on which land use trends are calculated and the land use driving mechanisms that calculated and the land use driving mechanisms that act over longer distanceact over longer distance
• relatively fine scale on which the local land use patterns relatively fine scale on which the local land use patterns are calculated, taking local constraints into accountare calculated, taking local constraints into account
• the dynamics of changing land use is based on the dynamics of changing land use is based on correlations and not on causal mechanismscorrelations and not on causal mechanisms
• quasi-static method which is more directed towards the quasi-static method which is more directed towards the spatial than the temporal componentspatial than the temporal component
Recommendation
Why not try combinations of system dynamics,Why not try combinations of system dynamics,
cellular automata and multiple scale models?cellular automata and multiple scale models?
Source: refers to the origin of uncertainty
Type: how uncertainty manifests itself in a particular context
UNCERTAINTY
TYPOLOGY OF UNCERTAINTIES
Societal randomness
inexactness
lack of observations/ measurements
practically immeasurable
ignorance
indeterminacy
Uncertaintydue to lack of
knowledge
Natural randomness
Value diversity
Behavioural variability Uncertainty
due to variability conflicting
evidence
unreliability
structural uncertainty
Technological surprise
SOURCES AND TYPES OF UNCERTAINTY IN IA-MODELING
Uncertainty due to variability
inexactness
uncertainequations
model structureuncertainties
uncertainties
parameter
in input data
uncertainties
Uncertainty inmodel quantities
((technical uncertainties)
uncertain levelsof confidence
uncertainty aboutmodel validity
Uncertainty aboutmodel form
(methodological uncertainties)
Uncertainty about model completeness
(epistemological uncertainties)
lack ofobservations/measurements
practicallyimmeasurable
ignorance
indeterminacy
conflictingevidence
RECOMMENDATION
Build in pluralism inBuild in pluralism intoto models models
• uncertainties can be estimated according to different uncertainties can be estimated according to different perspectivesperspectives
• perspective-based model routesperspective-based model routes
• integration of participatory processes and modelling integration of participatory processes and modelling approachesapproaches
AGENT REPRESENTATION two schools of agent representation:two schools of agent representation:
• emergent behaviouremergent behaviour
behaviour of agents ‘emerges’ primarily through behaviour of agents ‘emerges’ primarily through interaction with other agents [genetic algorithms]interaction with other agents [genetic algorithms]
• rational behaviourrational behaviour
prescribed rules for agents behaviour according to prescribed rules for agents behaviour according to
rational decision rules [neo-classical economics]rational decision rules [neo-classical economics]
SCALE REPRESENTATION OF AGENTS
Macro level (landscape)(trans-)national
authorities
Meso level (regimes)institutions/organisations
Micro level (niches)
individual agents
RECOMMENDATION
• combination of emergent behaviour & rational behaviourcombination of emergent behaviour & rational behaviour
deliberative behaviourdeliberative behaviour
• different modes of behaviour under different different modes of behaviour under different circumstancescircumstances
• automat: decision agent with a cognitive cell, linked to a automat: decision agent with a cognitive cell, linked to a memory cell, and external stimulimemory cell, and external stimuli
AGENT MODEL
Repetition
Deliberation Imitation
Social comparison
Cognitive processing
Mental map
Abilities-time
-money-age
-children
Uncertainty
Decision
Personality
Locus of control threshold
time | source | dest. | loc. | p | # visitors | conflict
Location
Peers
Peers
Intermediaries
Media
Experience
Intermediaries
Transition dynamics
• macro-meso-micro level dynamicsmacro-meso-micro level dynamics
• four different stages of transitionfour different stages of transition
• co-evolution, emergence and self-organisationco-evolution, emergence and self-organisation
• niche- and regime playersniche- and regime players
• transformative changetransformative change
Transition Model
• agent basedagent based
• market and physical infrastructure representationmarket and physical infrastructure representation
• regime, niche and empowered niche as agentsregime, niche and empowered niche as agents
regime = ICEregime = ICE
nichesniches = hybrid cars, biofuels, hydrogen cars= hybrid cars, biofuels, hydrogen cars
empowered niche = public transportempowered niche = public transport
• key concept is key concept is supportsupport for agents from consumers for agents from consumers
• landscape developments and lifestyle changes landscape developments and lifestyle changes
Fossil Fuel Signal
Ecological Signal
Economic Signal
Physical Infrastructure Signal
I
II
III
IV
Initial results
Integrated Sustainability Assessment
‘‘MATISSE’ MATISSE’ definitiondefinition
ISA is a cyclical, participatory process of ISA is a cyclical, participatory process of scopingscoping, , envisioningenvisioning,,
experimentingexperimenting and and learninglearning through which a shared interpretation through which a shared interpretation
of sustainability for a specific context is developed and appliedof sustainability for a specific context is developed and applied
in an integrated manner in order to explore solutions to persistentin an integrated manner in order to explore solutions to persistent
problems of unsustainable developmentproblems of unsustainable development
ISA conceptual framework
Envisioning stage
[sustainability vision with pathways]
Scoping stage [shared interpretation of what sustainability means]
Experimental stage[testing visions, pathways
and policy options]
Learning and
evaluating stage
[learning-by-doing and doing-by-learning]
CONCLUSIONS
• we need a new paradigm for assessing sustainable we need a new paradigm for assessing sustainable development: a transformative paradigmdevelopment: a transformative paradigm
• we need to invest more effort in improving the we need to invest more effort in improving the methodological basis of our IA-toolsmethodological basis of our IA-tools
scaling / agent representation / uncertaintyscaling / agent representation / uncertainty
• we need to invest substantially more in ISA-tools:we need to invest substantially more in ISA-tools:innovative, integrated and interactive [ triple-I ]innovative, integrated and interactive [ triple-I ]