IIASA Markus Amann, Chris Heyes, Wolfgang Schöpp International Institute for Applied Systems Analysis Uncertainty treatment in the integrated assessment modelling for the Gothenburg Protocol - a review

IIASA Standard uncertainty analysis “ Uncertainty analysis lacks a tool kit to address salient uncertainties in an adequate manner as a central activity in IAM” (Rotmans & van Asselt, 2001) E.g., empirical (Monte Carlo) approach: –Complex and time consuming to perform an overall uncertainty analysis for the RAINS calculations –Does it answer the critical policy questions?

IIASA Critical question in the policy context Not: What is the confidence range of the model results? But: Given all the shortcomings, imperfections and the goals, how can we safeguard the robustness of the model results? For practical reasons alternative approach required

IIASA Uncertainties addressed through (1) Model construction (2) Identification of potential biases (3) Target setting (4) Sensitivity analyses

IIASA Model construction Cost curves –Applicability rates –Filtering/smoothing Atmospheric transfer matrices –11-year mean matrices –Small elements ignored Reduced-form ozone model –Calculation of AOT values (integral measure) –Regressor selection based on information criteria –Continuous comparisons with full EMEP model Optimization –Relative emissions (scaling) –Reference point –3 different solvers

IIASA Potential biases Critical loads could be stricter... –dynamic effects, limited spatial resolution Critical levels (ozone) could be too strict... Population exposure (ozone) … –overestimated in city centers/underestimated in suburbs Constant background ozone …. Emission control costs too high … –‘Pre-Kyoto’ energy projections, no structural changes Emission control potential too small … –technological progress ignored, no structural changes considered

IIASA Target setting Potential influence of uncertainties minimized by –Use of ‘gap closure’ targets (relative improvements) –Compensation mechanism with soft targets –Integral functions for environmental exposure –Explicit model confidence intervals –Excluding extreme situations

IIASA Sensitivity analyses Analysis of alternative of exogenous assumptions: ‘Post-Kyoto’ energy projections ‘Low NH 3 ’ agriculture ‘High SO 2 ’ energy scenario ‘High NH 3 ’ agriculture

IIASA Conclusions and questions Despite no formal uncertainty analysis conducted, concern about uncertainties guided model construction, model use and interpretation of results Uncertainties could not be quantified, but answers to concerns of decision makers provided. Interactive and iterative process between scientists, decision makers and IA modelers Will this be sufficient for the next round of policy application? Where/how can we improve? Can formal methods help?