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Methodologies, Technical Resources and Guidelines for Mitigation Festus LUBOYERA and Dominique REVET Programme Officers UNFCCC secretariat ([email protected] and [email protected]) 1 (1) Contents Deciding on the Methodological Approaches for mitigation analysis Steps to follow Structure of the analysis Technical Resources and Guidelines (*) Almost all Parties included information on “programmes containing measures” that could contribute to addressing climate change. Furthermore, they also provided information on methodologies, scenarios, models and criteria used for the assessment. 2 (2) Deciding on the Methodological Approaches for Mitigation Analysis Decide on the methodological approach to be adopted for the analysis “Bottom-up” or “Top-down” – check suitability, strengths and weaknesses Select the analytical tool/model to be used Consider the requirements of the analysis such as: importance of the sector considered, data availability, skills required/available, etc. 3 (2) Deciding on the Methodological Approaches for Mitigation Analysis (Cont.) Analytical structure of the Analysis Evaluation of national social and economic development framework for climate change mitigation (Slide 3) Baseline scenario projection – no policies in place on GHG reduction (Slide 4) Mitigation scenarios projections – taking into consideration the baseline scenarios (Slide 5) Macroeconomic assessment (Slide 6) Implementation issues (Slide 7) 4 (3) Evaluation of national social and economic development framework Comprehensive description of national framework for CC mitigation including: base year statistics on GDP structure, social conditions, energy balance, aggregate GHG inventory, major land use activities, population, etc. Evaluation of main national economic and social national development trends and the GHG emissions that are expected to occur as a result of economic development Overview of mitigation reports together with other climate change studies including impact, adaptation, GHG inventories 5 (4) Baseline scenario projection Select/develop modeling approach Choose base year and time horizon Define baseline scenario – baseline economic and demographic trends and assumptions Examine trends in energy consumption, production, technology, fuel prices land use change and forestry 6 (5) Mitigation scenarios projections Identification of mitigation options related to the most important future sources and sinks of GHGs Screening of mitigation options Assessment of reduction potential and the related cost of mitigation scenarios Integration of GHG reductions and costs across measures and sectors, through construction of GHG mitigation marginal cost curves 7 Sample Format for the Reporting of Mitigation Options Mitigation Option 1 Mitigation Option 2 Mitigation Option n 100,000 150,000 20,000 3.5 2.0 3.3 40 30 40 120 80 110 300,000 100,000 Uncertain Low High Medium Low Uncertain None -150 -30 No effect -200 None Reduction -75 -50 Uncertain Potential impact of implementation policies Low Medium High Sustainability of option High Uncertain Medium Consistency with national development goals High Low Medium Uncertainty of data - Technology performance and costs - Costs of implementation programs Low High Medium Low High Medium Criteria GHG saving or storage (tCeq) - Carbon (tC) - Methane (tCeq) - Other gases (tCeq) Life-cycle-cost (currency/tCeq) Capital investment (currency/tCeq) Net costs (currency/tCeq) Indirect economic impacts - Jobs created (#) - Reduced imports (US$) Equity considerations, impacts on - Low-income jobs - Low-income monthly expenditure National environmental impacts (net change) - Sulfur oxides (tonnes) - Particulates (tonnes) - Biodiversity 8 (6) Macroeconomic assessment Qualitative description of main macroeconomic impacts of national climate change mitigation strategies Assessment of key macroeconomic parameters 9 10 (7) Implementation issues Identification of main implementation requirements including financial support, technologies, institutional capacity building, regulation policies and further improvements of the national decision framework 11 (8) Some Technical Tools Examples of “Bottom–up” models COMAP (COmprehensive Mitigation Assessment Process for forestry): spreadsheet model COPATH (Carbon Pasture Agriculture Total Harvesting): spreadsheet model for the estimation of carbon flows associated with forest use ETO (Energy Technology Optimization): optimization model which compares energy supply sources to identify the lowest cost option EM (Environmental Manual for power development): tool for the inclusion of environmental and cost data into decision-making for energy projects, especially in developing countries GACMO (Greenhouse GAs Costing MOdel): a spreadsheet module for project-based mitigation analysis 12 (8) Some Technical Tools (Cont.) LEAP (Long-range Energy Alternatives Planning system): end-use accounting modeling system for energy STAIR (Services, Transport, Agriculture, Industry and Residential energy model): accounting model for long-term mitigation scenarios Examples of “Top-down” models MARKAL-MACRO (MARKet ALlocation MACRO-economic model): an energy-economy-environment optimization model (combined bottom-up and top-down approaches) ENPEP (Energy and Power Evaluation Program): iterative equilibrium model for the energy system (partial bottom-up characteristics) 13 Examples of Analytical Tools Available for Mitigation Assessments Topic Energy Sector Accounting Models Optimization Models Iterative Equilibrium Model Decision Analysis Framework Non-Energy Sectors Forestry Agriculture Rangelands Waste Management Analytical Tools LEAP, STAIR MARKAL, ETO ENPEP Analytical Hierarchy Process (AHP) COPATH, COMAP EPIC, CENTURY CENTURY Landfill Gas Model Energy-Economy Interaction LBL-CGE, MARKAL-MACRO 14 (9) Selecting a Model The model should be simple enough (i.e.: not hinder analysis process) Simple spreadsheets can be constructed for a specific analytical purpose Complex models should be supported by training Output of the model should be useful to the stakeholders (especially for national planning). 15 Key Design Features of Selected Sector Models Model Characteristics STAIR LEAP ETO MARKAL MARKALMACRO ENPEP LBL-CGE Model Type Energy Accounting Energy Accounting Engineering Optimization Engineering Optimization Iterative Equilibrium Hybrid “TopDown” Number of Non-Energy Sectors 0 0 0 0 – 1 2+ Energy Supply Representation Process Analysis Process Analysis Process Analysis Process Analysis Supply Curves Process Analysis Supply Curve Energy Demand Representation Exogenous Exogenous Exogenous Exogenous Exogenous Utility Maximization Demand Function Multi-Period No No No Yes Yes Yes Yes Not Applicable Not Applicable Perfect or Myopic Myopic Perfect or Myopic Myopic Consumer/Producer Foresight Not Applicable Accounting Accounting Linear Programming Iteration Non-Linear Optimiz. Iteration Solution Algorithm Linear Programming 16 (10) Some Useful Technical Resources IPCC Technical Paper I - Technologies, Policies and Measures for Mitigating Climate Change IPCC 3rd Assessment Report - Climate Change 2001: Working Group III: Mitigation UNEP/RISO: Economics of GHG Limitations GHG Mitigation Assessment : A Guidebook (US Country Studies Program (*) The CD-Rom of this workshop contains a number of guidelines as well as software such as LEAP and COMAP together with their manuals and some training exercises in various languages. 17 (11) For more Information EM: http://www.worldbank.org/html/fpd/em/model/em_mo del LEAP: http://forums.seib.org/leap/ COMAP: http://eetd.lbl.gov/ea/IES/iespubs/3163.pdf ENPEP: http://enpep.dis.anl.gov/mosaic/enep MARKAL: http://www.ecn.nl/unit_bs/etsap/markal 18