Break-out session Uncertainty, assumptions and value commitments

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Break-out session Uncertainty, assumptions and
value commitments

• Jeroen van der Sluijs (Chair)
• Naomi Oreskes (key-note)
• Barbara Regeer (young researcher)
• Anne Myhr (rapporteur)

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Towards multi-dimensional uncertainty assessment
for complex environmental problems

• Jeroen van der Sluijs (UU Copernicus Institute)
• j.p.vandersluijs_at_chem.uu.nl

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Insights on uncertainty

• Uncertainty is partly socially constructed and
  its assessment always involves subjective
  judgement
• Omitting uncertainty management can lead to
  scandals and crisis undermines trust in the
  science
• More research does not necessarily reduce
  uncertainty
• may reveal unforeseen complexities
• irreducible uncertainty (intrinsic or
  practically)
• High quality ? low uncertainty
• Shift in focus needed from reducing uncertainty
  towards a systematic management of uncertainty
  and value loadings
• Uncertainty is a multi-dimensional concept and
  can manifest itself at different locations

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Locations of uncertainty

• Sociopolitical and institutional context
• System boundary problem framing
• Model
• Model structure
• Assumptions
• Parameters
• Inputs
• Scenarios
• Data

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Dimensions of uncertainty

• Technical (inexactness)
• Methodological (unreliability)
• Epistemological (ignorance)
• Societal (limited social robustness)

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NUSAP Qualified Quantities Example pedigree
matrix
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NUSAP Diagnostic Diagram
high
Danger zone
Sensitivity
Safe zone
low
weak
strong
Pedigree
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Method for analysis of assumptions

• Applied to
• EO5 Environmental Indicators
• (Penny Kloprogge)

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(No Transcript)
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Calculation chain ozone deaths hospital
admittances

• Societal/demographical developments
• VOC and NOx emissions in the Netherlands and
  abroad
• Ozone concentrations
• Potential exposure to ozone
• Number of deaths/hospital admittances due to
  exposure
• What are key-assumptions in this calculation and
  what is their pedigree?

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Value loading can be in practical / disciplinary
/ epistemic / socio-political sense

• Pedigree criteria for reviewing assumptions
• Plausibility
• Inter-subjectivity peers
• Inter-subjectivity stakeholders
• Choice space
• Influence of situational restrictions (time,
  money)
• Sensitivity to view and preferences of analyst
• Estimated influence on results

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Workshop reviewing assumptions

• Completion of list of key assumptions
• Rank assumptions according to importance
• Elicit pedigree scores
• Evaluate method

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Key assumptions ozonedeaths and hospital
admittances

• Uncertainty mainly determined by uncertainty in
  Relative Risk (RR)
• No differences in emissions abroad between the
  two scenarios
• Ozone concentration homogeneously distributed in
  50 x 50 km grid cells
• Worst case meteo now worst case future
• RR constant over time (while air pollution
  mixture may change!)
• Linear dose-effect relationship

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Example traffic light graph
Assumption that there is a linear dose-effect
relationship
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Conclusions

• NUSAP system
• Can address all locations and dimensions of
  uncertainty
• Provides framework for synthesising qualitative
  and quantitative assessments of uncertainty
• Structures in depth review of strengths and
  weaknesses of knowledge bases and of assumptions
• Helps to focus research efforts on most
  problematic model components
• Can be used interactively in extended peer
  processes to structure the critical appraisal of
  knowledge bases for (sustainability) policies.