1. 1. International Open Nomiracle workshop, June 2006 Application of multi criteria methods in scenario selection Peter B Sørensen Application of multi-criteria methods in scenario selection What is a scenario in this context ? What is a criteria in this context ? Why is the work prior to the application of multi-criteria methods critical ? The best way from the problem towards the answer The hidden uncertainty of risk assessment

2. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Definition of a scenario Risk problem boundary includes the elements: Target The target that may be subject to harmful effects. The environmental target can be defined as a single organism, a group of organisms or a specific eco-system. Condition for exposure The condition of exposure covers all the aspects other that the substance that has an influence on the exposure level. This include mixtures. Substances to be considered The space of substance needs to be clarified. Is the problem about a special group of chemicals based on their usage like e.g. pesticides or a chemical class like organophosphates or a single component? Other stressors To what extend will other stressors like temperature, UV radiation etc. be included as a part of the risk problem? The risk scenario quantifies all elements within the risk problem boundary

3. Statement 1 There are not resources for risk assessment of all possible realistic risk scenarios so the most relevant scenario for risk assessment has to be identified before the risk level can be quantified. Statement 2 A complete and thus certain identification of the most relevant risk scenario for risk assessment needs a prediction of risk levels for all possible scenarios. Thus, it is impossible to find the most relevant risk scenario with compete certainty. There is a danger that the most relevant scenario for risk assessment becomes hidden and thus risk assessment takes places on sub-optimal conditions Violating precaution and probabilistic approaches in general 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection The dilemma in complex risk assessment

4. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection The system model consists of the following sub models: Model for problem specification (Problem Specification Model, PSM). Predicts a set of sub-problems that all has relevanse for the risk estimation. Model for scenario composition (Scenario Composition Model, SCM). Predicts the set of sub-problems that are assumed mostly to govern the scenario. Model for criteria compilation (Criteria Model, CM). Compiles the set of sub-problems into a set of criteria. Model for scenario selection (Scenario Selection Model, SSM). Predicts the highest risk scenarios based on the criteria values. We need a system model for risk scenario design !!

5. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Problem Specification Model, PSM Main problem Sub problem 1 Sub problem 2 Sub problem 1.1Sub problem 1.2 Sub problem 2.1Sub problem 2.2 Not recognized but relevant sub problem: Not recognized ignorance type of uncertainty Qualitative model Human health Effects when exposed Exposure level ReleaseFateBody entranceChronicAcuteAllergy

6. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Scenario Composition Model Main problem Sub problem 1 Sub problem 2 Sub problem 1.1Sub problem 1.2 Sub problem 2.1Sub problem 2.2 Recognized ignorance type of uncertainty Increasing roughness Ordinal model: More important/Lesser important Human health Effects when exposed Exposure level ReleaseFateChronicAcute Allergy

7. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Criteria Model Ordinal model for each sub problem Risk conditionsRisk criteria Estimation byempirical dataand/or models Sub problem 1.1Criteria 1: high/low value=high/low risk Sub problem 1.2Criteria 2: high/low value=high/low risk Sub problem 2Criteria 3: high/low value=high/low risk Estimation uncertainty: condition = Criterion Chronic Acute Exposure level R48: yes/no = high/low risk level R23: yes/no = high/low risk level Production volume (tons) high/low = high/low risk level Human health

8. Criteria 1: high/low value=high/low risk Criteria 2: high/low value=high/low risk Criteria 3: high/low value=high/low risk Highest risk scenarios 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Scenario Selection Model Ordinal model for risk level Multi-criteria model R48: yes/no = high/low risk level R23: yes/no = high/low risk level Production volume (tons) high/low = high/low risk level Benzene stoddard solvent toluene 2-butoxyethanol - Risk level Value uncertainty Multi-attribute uncertainty

9. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Probability for : X 1 >X 4 =0,66 X 1 >X 2 =0,33 maximal multi-attribute uncertainty: All possible multi-criteria models will select one and only one of the three linear extensions. Multi-attribute uncertainty

10. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Id 101 Methyloxirane Cas no. 75-56-9 Multi-attribute uncertainty 10 criteria case

11. 1. International Open Nomiracle workshop, June 2006 Peter B Sørensen Application of multi criteria methods in scenario selection Statistical Learning Theory: Never solve a problem at an unnecessary high complexity level as an intermediate step !!! Conclude so much as possible before you are moving to a more detailed level Increasing complexity Problem Specification Model Scenario Composition Model Criteria Model Scenario Selection Model Risk level quantification Increasing uncertainty Only factor of uncertainty in probabilistic risk assessment Main task in risk mapping