Application of the new scenario approach in the ReMIND-MAgPIE integrated assessment framework

Transcription

1 Application of the new scenario approach in the ReMIND-MAgPIE integrated assessment framework, Alexander Popp, David Klein Lena Reuster, Jana Schwanitz, Nico Bauer Gunnar Luderer, Marian Leimbach, Franziska Piontek Workshop on new SMA/ SSP approach July 2011, Changwon, Korea Research Domain Sustainable Solutions

2 Overview 1. An overview of ReMIND-MAgPIE model capabilities 2. Which narrative to choose? 3. Tentative implementation of narratives in ReMIND-MAgPIE 4. SSP1 vs. SSP5: An example from EMF24 5. Outlook

3 Quick introduction to the models: ReMIND Macro Economy Welfare Investments Consumption Energy system costs Energy system Trade Output Fuel costs Investment costs Operation and Maintenance costs Capital Labour Final energy Energy transformations and conversion technologies Learning by doing Labour efficiency Energy efficiency Ressource and potential constraints Emissions Trade Exogenous Data Climate module 3 Leimbach,Bauer, Baumstark, Edenhofer, O. (2009) Trade

4 Quick introduction to the models used: ReMIND ReMIND regions USA - USA EUR - EU27 JAP - Japan CHN - China IND - India RUS - Russia AFR - Sub-Saharan Africa (excl. Republic of South Africa) MEA - Middle East, North Africa, central Asian countries OAS - Other Asia (mostly South East Asia) LAM - Latin America ROW - Rest of the World (Canada, Australia, New Zealand, Republic of South Africa, Rest of Europe).

5 Climate Demography Income vs. Food consumption Billion Kcal / Cap / Day kcal = 802 * gdp^( ) [R^2 = 0.66] Income and diet ECHAM4 Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001) GDP / Cap / Year kcal_cap (105 countries, 1990/2000) kcal_cap (fitted values) Socioeconomic inputs CCSR mm Food demand, production costs Crop yields Land & Water constraints Cereals Sugar beets Oilseeds Pulses LPJ (50x50 km grid) Bioenergy Biophysical inputs Lotze-Campen, Popp et Elmar al. (2008), Kriegler Agricultural Economics MAgPIE a global land use optimisation model spatially explicit (0.5 ), 10 economic regions 30 production activities (13 crops, livestock, irrigation, bioenergy, land conversion) internal feed balances, international trade endogenous land expansion endogenous technological change

6 Climate change (GCM) Demography Income vs. Food consumption Billion Kcal / Cap / Day kcal = 802 * gdp^( ) [R^2 = 0.66] Income and diet ECHAM4 Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001) GDP / Cap / Year kcal_cap (105 countries, 1990/2000) kcal_cap (fitted values) Socioeconomic inputs CCSR mm Food demand, production costs Crop yields Land & Water constraints Cereals Sugar beets Oilseeds Pulses LPJ (50x50 km grid) Bioenergy Biophysical inputs Land use dynamics 2035 Land use pattern Lotze-Campen et al. (2008), Agricultural Economics

7 Climate change (GCM) Demography Income vs. Food consumption Billion Kcal / Cap / Day kcal = 802 * gdp^( ) [R^2 = 0.66] Income and diet ECHAM4 Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001) GDP / Cap / Year kcal_cap (105 countries, 1990/2000) kcal_cap (fitted values) Socioeconomic inputs CCSR mm Food demand, production costs Crop yields Land & Water constraints Cereals Sugar beets Oilseeds Pulses Bioenergy LPJ (50x50 km grid) Biophysical inputs Potsdam Institute for Lotze-Campen Climate Impact and Research Popp, World Development Report 2010

8 Climate change (GCM) Demography Income vs. Food consumption Billion Kcal / Cap / Day kcal = 802 * gdp^( ) [R^2 = 0.66] Income and diet ECHAM4 Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001) GDP / Cap / Year kcal_cap (105 countries, 1990/2000) kcal_cap (fitted values) Socioeconomic inputs CCSR mm Food demand, production costs Crop yields Land & Water constraints Cereals Sugar beets Oilseeds Pulses Bioenergy LPJ (50x50 km grid) Biophysical inputs 2055 Agricultural N2O [Mt CO2-e] Popp et al. 2010, GEC

9 Influence of diets Combination A Pop. growth & diet shifts C Technological mitigation B Less livestock products D Combination of B & C

10 LPJmL Input: climate, CO 2, soil, land-use Natural vegetation Managed grasland Cropland Bondeau et al. 2007, GCB

11 LPJmL Agricultural yields Carbon content Gumpenberg, Popp et al. 2010, ERL Bondeau et al. 2006, GCB Run-off Müller, Bondeau, Popp et al. WDR 2010 Füssel, Popp, Heinke (2010)

12 Model coupling Objective: Model framework to explore potential contribution of bioenergy to climate change mitigation, including its costs and trade-offs LPJmL - global vegetation and hydrology model MAgPIE - global land use optimization model REMIND- global energy-economy-climate model

13 Which storylines to choose?

14 Which storylines to choose? Increasing socio-economic mitigation challenges SSP 5 Coal & gas powered growth SSP 1 Sustainable development SSP 2 SSP 3 Fragmented world SSP 4 Divided in rich & poor Increasing socio-economic adaptation challenges

15 Established scenarios often span the diagonal Increasing socio-economic mitigation challenges SSP 5 Coal & gas powered growth SSP 1 Sustainable development SSP 2 SSP 3 Fragmented world SSP 4 Divided in rich & poor Increasing socio-economic adaptation challenges

16 Off-diagonal scenarios far less considered Increasing socio-economic mitigation challenges SSP 5 Coal & gas powered growth SSP 1 Sustainable development SSP 2 SSP 3 Fragmented world SSP 4 Divided in rich & poor Increasing socio-economic adaptation challenges

17 Tentative implementation of narratives in ReMIND and MAgPIE

18 Contrasting SSPs: : High vs low adaptive capacity Increasing socio-economic mitigation challenges SSP 5 High adapative capacity SSP 1 SSP 3 Low adapative capacity SSP 4 Increasing socio-economic adaptation challenges

19 Contrasting SSPs: : High vs low adaptive capacity High adaptative capacity Low adaptative capacity low to medium population growth well-functioning markets and institutions globalized and cooperative world High inter-/ intraregional convergence rapid technological progress high population growth distorted markets and institutions fragmented world prone to conflicts Low inter-/ intraregional convergence slow technological progress Narrative matches ReMIND default assumptions

20 How to differentiate between the two verticals Increasing socio-economic mitigation challenges High adapative capacity Low exogenous population scenario High exogenous labour productivity with fast convergence between regions free capital and commodity trade technology spill-overs Convergence of energy service and food demand Low adapative capacity High exogenous population scenario Low exogenous labour productivity with slow convergence between regions regionally differentiated trade costs and capital taxes reducing the rate of return on capital, import / export quotas on capital and commodities No technology spill-overs Persisting regional differences in energy service and food demand Increasing socio-economic adaptation challenges

21 RoSE GDP Scenarios Basic methodology Based on Methodology by PricewaterhouseCoopers Hawksworth, J. (2006), The World in 2050 How big will the major emerging market economies get and how can the OECD compete.

22 Quality adjusted input of labor L = h(s) ( e 1 N(15-64 yr) + e 2 N(65+ yr) ) s = average years of school (data from Barro and Lee, 2001; Scenario after 2010) e 1 = labor particapation rate working age population (Varies from 55% 75% across regions. Cultural factors dominating? Assumed constant after 2010) e 2 = labor participation rate of population 65+ years old (Varies from 3% 50% across regions. Dominated by per capita income. 3%-20% in developed countries. Scenario assumed after 2010)

23 RoSE GDP per capita scenarios - World Preliminary results

24 RoSE GDP per capita scenarios - China Preliminary results

25 Contrasting narratives: SSP1 vs. SSP5 Increasing socio-economic mitigation challenges SSP 5 Low mitigative capacity High mitigative capacity SSP 1 Increasing socio-economic adaptation challenges

26 Contrasting narratives: SSP1 vs. SSP5 SSP 1 Environment: lifecycle perspective and closed-loop industries, high external costs of fossil energy, fossil fuel availability limited Technology: rapid technological progress on RE, high TC in agricultural sector Behaviour: sustainable consumption patterns SSP 5 Environment: problem-oriented environmental regulation (end-of pipe approach), external costs of fossil fuels well controlled, gasification world, NIMBY perpective with RE Technology: strong reliance on fossil fuels, broad access to cheap fossil energy, maximization of resource extraction Behaviour: energy intensive consumption patterns (buildings, cars, ), meat rich diet

27 How to differentiate between the two horizontals Low mitigative capacity High mitigative capacity Increasing socio-economic mitigation challenges large fossil fuel availability, no fossil resource extraction constraints high energy intensity/ end energy demand scenario for high calory demand, high lifestock share, high consumer waste share high exogenous scenarios for RE investment costs, efficiencies, adjustment costs and expansion constraints low fossil fuel availability, fossil resource extraction constraints low final energy intensity/ end energy demand scenario for low calory demand, low lifestock share, low consumer waste share low exogenous scenarios for RE investment costs, efficiencies and adjustment costs, and no expansion constraints Increasing socio-economic adaptation challenges

28 EMF24 example: : Low vs. high mitigative capacity with unchanged adaptive capacity SSP1 SSP5 EMF24 run R2G2, low energy intensity EMF24 run R2G6, high energy intensity, pessimistic RE, low biomass

29 Summary and conclusions Fun work to try to translate SSP narratives in model assumptions Hard work to implement it and ensure that model results are reasonable and reflective of the narrative Need guidance and coordination: Where would it best to focus, where are other groups focusing Need dialogue and cooperation with a range of non-iam groups: demography, growth accounting, institutional analysis, human development, IAV Concern about lock-in in low, medium, high UN population scenarios (e.g. divided world scenarios)

30 Thank you!

31 Backup Slides

32 Crucial indicators for SSPs Category Indicators Population: Economy: Environment: Equity: Technology: Governance: Globalisation: total population, age structure, urbanization GDP, sectoral structure, investment rate, income convergence, labor participation rates external costs (fossils, RE), energy intensity of consumption patterns, pollution, land use footprints intra- and interregional income distribution, energy and food prices energy resources and technologies, agricultural productivity, diffusion rates, direction of technological change rule of law, political stability, international regimes, market regimes trade patterns / limitations, knowledge transfer, capital markets Behaviour: consumption patterns, health indicators