Are we sure? UNECE-workshop on uncertainty treatment in Integrated Assessment Modelling 24-25 January 2002 Rob Maas.

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Presentation transcript:

Are we sure? UNECE-workshop on uncertainty treatment in Integrated Assessment Modelling 24-25 January 2002 Rob Maas

Learning Process 1 Denial of uncertainties 2 Acknowlegdement of uncertainties 3 Specification of types of uncertainty 4 Quantitative assessment of uncertainties 5 Specification of policy relevance 6 Uncertainty management in decision process

Types of uncertainty Lack of knowledge Variability unreliable data: inexactness lack of measurements immeasurability structural uncertainty: conflicting evidence ignorance indeterminacy Variability natural randomness value diversity behavioural variability societal randomness technological surprises

Uncertainties in NL-Projections * In 2010 50% more energy use than expected in 1990 * Surprises in societal developments: e.g lower energy prices * But also: only 70% of the policy measures were actually implemented or enforced Policy makers are an important source of uncertainty

Major open issues & bottlenecks Quality of emission data (a.o. PM10) Eulerian vs Lagrangian model Effects of climate change / policy Transcontinental fluxes (ozone) Dynamic ecosystem effects Health effects of PM-species Scenario’s for energy & agriculture Implementation of measures & costs

Aspects of uncertainty management Lack of knowledge: scenarios Variability: probability Risk: assessment

Scenario approach Scenarios raise awareness of uncertainties and can test the robustness of different policy strategies Scenarios can contribute to communicate the range of perceptions The likelihood of a scenario is subjective and differs among various scientists and policy makers Policy makers have to decide what economic and ecological risks are acceptable

Political Risk Aversion Ecologic perspective high economic growth low efficiency change low energy prices partial implementation high background level all PMs are dangerous Economic perspective low economic growth high efficiency change high energy prices full implementation low background level focus on most suspicious PMs

Policy-science interaction Political preferences are constructed during the process. Assessment and decision taking belong together. Well designed procedures include stakeholder openness, disclosure of beliefs, willingness to understand the other (to go beyond the given perspective) and procedures to manage conflicts (both legally and scientifically).

Role of science US: adversal; pluralistic; linkage with stakeholders; ‘innovative’ CLRTAP: consensus oriented; learning process within the ‘group’ possible risks: closed shop & lack of trust in science? How to remain open to dissident views?