Prospective Environmental Assessments Introduction to Scenario Analysis Techniques (Part 3)

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1 Prospective Environmental Assessments Introduction to Scenario Analysis Techniques (Part 3) Dr. Andy Spörri Ernst Basler + Partner AG, Resources, Energy + Climate, Zollikerstrasse 65, 8702 Zollikon March 7, 2017; HCI J7

2 Schedule of today (Lecture 3)» Short wrap-up of lecture 2» FSA Focus B» Phase 3: Projection» Phase 4: Scenario selection and interpretation» Linking FSA to modeling and assessment» Material flow analysis ()» Life Cycle Assessment ()» Multi-Attribute Utility Theory ()» Typology & of scenarios Scenarios, modeling & assessment Scenario typology &»» Functions of scenario analysis in strategic planning and decision making

3 Scenarios, modeling & assessment Scenario typology &

4 Phase 3 & 4 of FSA Scenarios, modeling & assessment Scenario typology &

5 Phase 3: Projection (step 3.1 & 3.2)» Future level definition (step 3.1), e.g.:» 1: Minimum extreme» 2: Trend extrapolation» 3: Maximum extreme» Consistency assessment (step 3.2)» 2: conditional» 1: supportive» 0: independent» -1: obstructive» -2: inconsistent Scenarios, modeling & assessment Scenario typology &

6 Phase 3: Projection (step 3.3)» Scenario construction (step 3.3)» Scenario as combination of different future levels of all impact factors used to describe and analyze a system» Calculation scenario indices of all possible scenarios (used for the selection)» Additive and/or multiplicative consistency» Number of inconsistencies» Local efficiency (neighborhood )» Pre-filter during scenario construction:» Number of tolerated inconsistency» Threshold value for additive and/or multiplicative consistency Significant reduction of original number of scenarios Scenarios, modeling & assessment Scenario typology &

7 Phase 4: Selection & interpretation (step 4.1)» Goal» Selection of a small (4-8) set of consistent, diverse and representative scenarios (cf. Tietje, 2005; Spoerri et al., 2009)» Two fundamentally different procedures» Data driven (bottom up, inductive) selection» Based on algorithms relying on calculated scenario indices» Local efficiency selection» Tietje selection» Distance-to-selected selection» Concept driven (top down, deductive) selection» Applied if the study team has conceptual ideas about the future of the investigated system ( representative scenarios) Scenarios, modeling & assessment Scenario typology &

2)» Synthesis of the final scenarios to a comprehensive and accessible picture

8 Phase 4: Selection & interpretation (step 4.2) Illustrative results» Description & Interpretation (step 4.2)» Synthesis of the final scenarios to a comprehensive and accessible picture based on all insights gained in the analysis» Scenario A-2 Recycling as a self-runner Scenarios, modeling & assessment Scenario typology &

2)» Synthesis of the final scenarios to a comprehensive and accessible picture based on

9 Phase 4: Selection & interpretation (step 4.2) Illustrative results» Description & Interpretation (step 4.2)» Synthesis of the final scenarios to a comprehensive and accessible picture based on all insights gained in the analysis» Scenario A-2: Monopoly of gravel suppliers breakdown of recycling Scenarios, modeling & assessment Scenario typology &

10 Summary FSA Reality Concept Model Scenarios Pictures 1 Goal formation 2 System analysis 3 Projection 4 Selection & interpretation Scenarios, modeling & assessment Scenario typology &

12 FSA, modeling» Goal» Assessment of environmental/sustainability performance of developed future states of a system (prospective assessment)» Relevance» Decisions of today determine impacts over long time periods (e.g., urban infrastructures)» Example from thermal waste management:» Investment in thermal treatment facility determine environmental performance for several decades (±30 years)» Environmental performance of specific technology depends on various future developments, such as:» Future waste compositions» Energy price developments» Changes in legal standards» Efficiency of landfill mining (technology learning curve)

13 FSA & (e.g., emission models) Case Study Waste Scenarios for the European Union in 2050» Goal: Prospective analysis of future emissions from municipal solid waste incineration in the European Union» Scenario analysis» Development of scenarios to determine waste amounts of the European Union in 2050» Based on the analysis of impacts of EU Directives on future waste amounts Amounts of household, commercial & medical waste, sewage sludge going into: (i) Recycling, (ii) Incineration, (iii) Landfill» Linking scenarios to emission model» From waste amounts to material composition as inputs to WM model

FSA & Life Cycle Assessment ()» General procedure (principle):» Translate scenarios into future state specific Life Cycle Inventory (LCI)» Depending on

14 FSA & Life Cycle Assessment ()» General procedure (principle):» Translate scenarios into future state specific Life Cycle Inventory (LCI)» Depending on constructed scenarios more or less concretization steps are required to link scenarios to LCI Scenario analysis Life Cycle Inventory Life Cycle Impact Assessment

15 FSA & Life Cycle Assessment () Examples:» Waste scenarios for the European Union in 2050» Elementary compositions could also be used for the environmental impact assessment of different thermal treatment or waste management options, e.g.:» Grate-incineration with additional metal recovery from residues» Waste gasification» Waste gasification combined with ash melting» Pre-treatment, sensor-based separation techniques» Prospective of transport systems in 2020» Spielmann, M., Scholz, R.W., Tietje, O. & de Haan, P. (2005). Scenario modeling in prospective of transport systems. Application of Formative Scenario Analysis. International Journal of Life Cycle Assessment, 10(5),

16 Prospective of transport systems 1 Framing of the study» Goals» Methodological» Conceptualization of uncertainties in prospective environmental assessment by the application of Formative Scenario Analysis» Case study» Prospective assessment of environmental performance of regional passenger transport alternatives in 2020 taking into account different cornerstone scenarios» Transport alternatives» Rail transport» low cost» comfort» ultra-light» Bus» Private car

17 Prospective of transport systems 2 Basic Procedure LCI based on future levels of technology variables LCI of transport systems - Train - Bus - Car LCIA Time dependent Environmentally relevant FSA Technological factors Embedding Socio-economic factors Projection & Selection Scenarios Scenario specific, prospective environmental impacts of different regional transport systems in 2020

18 Prospective of transport systems Unit process scenarios Technology factors Socio-economic factors Factor identification Impact assessment & analysis Future level def. & consistency assessment Linking technology factors to LCI

19 Prospective of transport systems Impact factors for unit process Operation Bus

20 Prospective of transport systems Impact factors for unit process Operation Bus Energy mix 100% Natural gas no change 60% NG & 40% LFO Manufacturing low cost train

21 Prospective of transport systems Results Greenhouse gas emissions

22 Prospective of transport systems Results NO x emissions

23 FSA & Multi-Attribute Utility Theory ()» Goal» Assessment of utility (attractiveness) of impacts/outcomes of a set of alternatives (e.g., scenarios)» Identification of best alternative based on a set of performance attributes (i.e., criteria)» Procedure a) Determine assessment perspective b) Define utility criteria and respective indicators c) Perform criteria-specific judgments for each alternative d) Define utility function to translate judgment into criteriaspecific utility e) Aggregate criteria-specific utilities and standardize overall utility

24 : Illustration of general procedure a) Assessment persp. b) Criteria set c) Judgments e) Overall utility Aggregation d) Utility functions Figuera, J., Greco, S., Ehrgott, M. (2005). Multiple criteria decision analysis. State of the art. New York: Springer.

25 FSA & Multi-Attribute Utility Theory ()» I vs. II» I» Evidence- and data-based, objective utility assessment» Classical scientific assessment» II» Stakeholder- and preference-based, subjective utility assessment» Intuitive assessment» Assessment foci» Different and case-specific sets of criteria applicable depending on the assessment perspective, e.g.,» Environmental performance» Eco-efficiency (e.g., environmental performance related to costs)» Sustainability performance» Desirability» Probability

Exploration parcours ( II)» Structured procedure to reveal and record the interests and evaluations of stakeholders Loukopoulos, P. & Scholz, R.W. (2004).

26 Exploration parcours ( II)» Structured procedure to reveal and record the interests and evaluations of stakeholders Loukopoulos, P. & Scholz, R.W. (2004). Sustainable future urban mobility: using area development negotiation for scenario assessment and participatory strategic planning. Environment and Planning A, 36,

27 Typology & Characteristics of Scenarios

28 Future analysis» Various /approaches available to analyze future system developments» From quantitative system modeling to qualitative exploration of system developments and future states» Appropriate depends on various of the investigated system a) Degree of complexity and uncertainty b) Considered time horizon c) Scope of the future analysis (focus) t 0 time

29 Degree of complexity & uncertainty» Facets of complexity» Multi-dimensional (highly interdisciplinary)» Multi-scale (processes interact at various scales)» Nature/character of interactions Wicked, ill-defined problem (vs. well-defined vs. task) Van Asselt, M.B.A. (2000). Perspectives on uncertainty and risk: The PRIMA approach to decision support. Dordrecht: Kluver. Scholz, R.W. & Tietje, O. (2002). Embedded case study. Integrating quantitative and qualitative. Thousand Oaks: Sage.

30 Degree of complexity & uncertainty Graphical illustration System boundary Context A System A World economy International law Policy Context B System B Direct impact (linear & non-linear, fuzzy) Indirect impact (1-3 via 2) Nature 3 2 Feedback 3 loop 2 (1-1 via 2 & 3) Behavior

A typology of scenarios Scenarios Predictive Explorative Normative Forecasts What-if External Strategic» Combination of scenario types often done, e.g. IPCC emission scenarios:» Predictive scenarios for well-understood systems (e.

31 A typology of scenarios Scenarios Predictive Explorative Normative Forecasts What-if External Strategic» Combination of scenario types often done, e.g. IPCC emission scenarios:» Predictive scenarios for well-understood systems (e.g., energy consumption and GHG emissions, embedded in socioeconomic/political contexts (explorative) Preserving Transformin g Höjer, M., Ahlroth, S., Dreborg, K-H., Ekvall, T., Finnveden, G. et al. (2008). Scenarios in selected tools for environmental system analysis. Journal of Cleaner Production, 16,

32 Scopes of scenario types» Predictive: What will happen?» Forecasts: What will happen provided that the most likely development unfolds?» What-if: What will happen on the condition of some specified events?» Explorative: What can happen?» External: What can happen to the development of external factors?» Strategic: What can happen if we act in a certain way?» Normative: How can a specific target be reached?» Preserving: How can the target be met by adjustments to current situation?» Transforming: How can a target be met, when prevailing structure blocks necessary changes?

33 Analyzing the future of a system From prediction to exploration of the future Degree of complexity high low» From parameter variations to explorations of new systems Real scenario techniques Normative Explorative Quantitative modeling/ simulation Predictive short-term Time horizon long-term Swart, R.J., Raskin, P. & Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14,

34 Probability Possibility Further categorization of scenarios Prediction Quantitative system modeling Quantitative Cross-impact analysis FSA Exploration Normative Storytelling Qualitative

35 Categorization of FSA» Methodology for construction of explorative scenarios» Both external and strategic scenarios» Methodology for construction of normative scenarios» Backward planning approach in FSA» Start from defined goals (scenarios)» Perform system analysis» Perform projection with consistency assessment

36 Scenarios in strategic planning

38 Functions of scenarios (result-related) Results (scenarios/future states) Basis for assessment of scenarios ( I & II) Input for modeling (e.g., SFA) and prospective assessment (e.g., ) Initial step for strategy development Counseling decision-makers

39 Functions of scenarios (procedural)» Procedural functions are linked to collaboration between science and practice (i.e., transdisciplinarity) Mutual learning between science and practice Capacity building for system transformations

40 CU next week

Student exercise 3: Prospective Environmental Assessment

Student exercise 3: Prospective Environmental Assessment Objectives The goal in the first two exercises was to determine scenarios for future e-bike mobility in Europe until 2050 and quantify implications