1. Workshop on the Criteria to establish projections scenarios Selected items from EU workshop on projections of November 2011 Mario Contaldi, TASK-GHG Ankara, 15-17 March 2016

2. EU Reporting requirements Development of draft GHG projection guidelines Parameters, assumptions indicators etc. QA/QC procedures The general ideas behind the tiered guidance. The 1st order draft guidance per sector (to be discussed again in sectoral workshops) 2

3. Outline - 1 Background Modeling projections Variables, Parameters and Indicators Tiers QA/QC issues: 3

4. Outline- 2 Further improved quality of data related to: – the completeness in terms of gases and sources – the comparability in terms of assumptions – the consistency related to the impacts of policies and measures historic GHG inventories and verified emissions from EU ETS the accuracy and quality of methodologies, data and assumptions used for the projections. the transparency of data and information on methodologies and assumptions 4

5. What consider in projections 5

6. Modelling projections an economy module, estimating projected activity data for all years in the projection (economic scenarios). a policy module, providing the information on what policies and measures are assumed to be in place in the years of the projection (policy scenarios) a technology module, performing the actual emission calculations, based on the projected activity rates for one or more economic scenario translating the assumed policies in into emission factors (technology scenarios) 6

7. Variables, parameters and indicators 7 are values that may change within the scope of the application of a model in a given projection. There are input variables: the entities on which the value of the output variable in the model depends output variables: the entity that is to reflect the result of the model and communicate it to the model user; define the behavior of a relation (mathematical function) between the input variables and the output variables. They are basically constants, although in some applications a parameter might be given a different value for different times (Manipulations of) output variables that are used to communicate the results of the projections exercise to the out side world Model variables Model parameters Projection indicators:

8. Variables- technology module 8

9. From historic emissions to projected emissions We aim at full consistency of the projections with the latest historic inventory: – Activity data Activity projections are needed in the same detail Emission factors need to be developed in the same detail Both should show an explainable development from the historic values: – Historic - Projection time series consistency!. 9

10. Reference models in EU framework Where you have country specific projection models available, use these! Projections of energy consumption / supply can be obtained from the following models: – PRIMES http://www.e3mlab.ntua.gr/ – POLES http://www.enerdata.fr/enerdatauk/tools/Model_POLES.html – WEO – TIMES http://www.etsap.org/Tools.asp Agricultural forecasts can be obtained from – The CAPRI model http://www.ilr1.uni- bonn.de/agpo/rsrch/capri/caprifp4_e.htm – The Food and Agriculture Organisation http://www.fao.org/ – The European Fertilizer Manufacturer Association (www.efma.org) and, – The International Fertilizer Industry Association www.fertlizer.org Transport projections can be obtained from: – The TREMOVE model www.tremove.org/. 10

11. PRIMES Energy system model Energy system model by country of Europe, including all sectors and markets and interconnections among countries for electricity and gas Modular system with individual sub-models for demand sectors including industrial processes and energy supply sectors including detailed electricity, CHP, gas, and RES models Core model integrates two detailed sub-models: PRIMES-TREMOVE transport model and PRIMES biomass model Formulation of actors’ behaviours in each sector influenced by market prices, technology dynamics and policies. The PRIMES integrating module simultaneously clears all markets for energy and allowances by projecting explicitly all prices. The prices influence demand and supply behaviours. The model can handle market imperfections, price and non price barriers A rich set of policy instruments is included in the model The formulations allow mainly medium and long term projections, but not short term forecasting. The PRIMES model suite projects dynamically to the future detailed energy balances, investments, costs, prices, CO2 emissions per country, as well as gas and electricity flows between countries 11

12. Times Energy system model The JRC-EU-TIMES model is a linear optimisation bottom-up technology model generated with the TIMES model generator from ETSAP1 of the International Energy Agency The equilibrium is driven by the maximization (via linear programming) of the discounted present value of total surplus, representing the sum of surplus of producers and consumers, which acts as a proxy for welfare in each region of the model. The model is supported by a detailed database, with the following main exogenous inputs: – (1) end-use energy services and materials demand, such as residential lighting, demand for machine drive or steel; – (2) characteristics of the existing and future energy related technologies, such as efficiency, stock, availability, investment costs, operation and maintenance costs, and discount rate; – (3) present and future sources of primary energy supply and their potentials; and – (4) policy constraints and assumptions. 12

13. CAPRI model Economic model with full coverage of agriculture and the Common Agricultural Policy and related environmental policies. Two major components are a set of regional programming models (approx. 280 regions, 60 activities) that iterate with a global, spatial multi-commodity model for about 50 products and 77 world regions in 40 trade blocks Purpose for Reference scenario quantification: Provide agricultural outlook for Reference scenario, in particular on livestock and fertiliser use Cross check with GLOBIOM on overlapping variables, in particular in crop sector Provide the impacts on the agricultural sector from changed biofuel demand 13

14. TREMOVE transport model New development of econometric transport activity projections for the Reference scenario Detailed sectoral model which projects the fuel consumption, CO2 emissions, pollutant emissions, the stock of vehicles and provides detailed transport sector costs as well the external costs (congestion, accidents, noise, air pollution) The model includes features aiming at simulating consumer behaviour and capturing the generalised price of transportation influencing decision making TREMOVE features also a spatial infrastructure tool linking in an integrated manner the density of infrastructure of refuelling/recharging stations in different areas (urban/inter-urban/short/long distance) with the different consumer travelling habits (represented through stylised histograms of trips) Purpose for Reference scenario quantification: Provide detailed projections for the evolution of the entire transport sector in terms of transport activity, energy consumption, emissions, fleet development, new technologies and alternative fuels 14

15. Improved Tier methodology Tier 1 Fall back option; Simple method with default parameters or centrally modelled data sets Cannot be used for “important” sectors Tier 2 – Same method with country specific parameters and/or higher stratification Tier 3 – Anything more complex than this – Decision tree Guides user step by step through the procedure Supports methodology choice (Tier 1, 2 or 3) Proposes data to be looked for. 15

16. Components of QA/QC for emissions Projections 16 QA/QC plan with objectives: goals for the quality of the projection output QA/QC activities: specific tests to determine if the quality objectives are met. Roles to be assigned to independent reviewers QA/QC implementation: record of QA/QC activities undertaken and whether objectives were met

17. Roles and responsabilities for QA/QC QA/QC Manager: maintains the QA/QC plan, sets quality objectives and defines, co-ordinates QA/QC activities and undertakes cross cutting QA/QC activities. Sectoral Experts: Perform sector specific QA/QC activities and report to the QA/QC Manager. Sector Experts should also collaborate with Data suppliers and other key stakeholders to review estimates and perform QA/QC on supplied material. External Review Teams: Provide expert/peer review of projections for specific sectors and report to the QA/QC Manager. 17