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GHG projections in Norway

GHG projections in Norway. Peer Stiansen Ministry of Environment. Main characteristics of the Norwegian model. Emissions projections are consistent with overall macroeconomic projections Combination of a top down and a bottom up approach

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GHG projections in Norway

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  1. GHG projections in Norway Peer Stiansen Ministry of Environment

  2. Main characteristics of the Norwegian model • Emissions projections are consistent with overall macroeconomic projections • Combination of a top down and a bottom up approach • Macro driver for emissions mainly energy use (CO2); offshore, transport, onshore energy use • Micro approach: • non CO2 emissions • processing industry • road traffic • petroleum sector • Micro level and micro information possibly more relevant and available for 2010 than 2020

  3. Methodology in use • CO2 projections are based on a macroeconomic general equilibrium model called MSG • An emission calculation model is included in MSG • Projections for non-CO2 emissions are based on information from relevant sectors and consistent with macroeconomic projections • Emission projections are (as a rule) fully updated every 4 years News • Updated projections (2010/ 2020) will be published in a White paper in Nov. 2004

  4. Emission calculation model • Different pollutants (CO2, NOX, SO2 and VOC) are disaggregated by source and sector and specified in the model • Emission are projected as a function of activity data and emission coeffisients. • Emission coeffisients are calibrated to a base year, and emissions are projected by taking into account effects of environmental instruments or policies that are already implemented or decided • Microinformation is used as guidance to adjust or overrule model projections • Statistics Norway develop and update the Emission calculation model in collaboration with The Norwegian State Pollution Control

  5. Authorities involved • Ministry of Finance are responsible for the production and publishing of the official emission projections, and activity data fed into the MSG ( including energy data) • The Norwegian State Pollution control are responsible for the production of emission projections of non-CO2 gases, and also for publishing emissions by source for alle GHG- gases • Ministry of Petroleum and Energy is responsible for the annual projections of emissions from the Petroleum sector • Ministry of Agriculture and The Norwegian State Pollution Control Agency are responsible for the LULUCF projections

  6. Policy reflection – do shifts matter ? • Taxes (energy/transport emissions, waste) • Emissions trading (energy,other ghgs) – Price ? • Agreements (industrial, F-gases) • Direct regulations (waste, some industry) • Grant schemes, labelling etc. (energy) • Planning measures (energy, transport, housing)

  7. CERs EUA, 05-07 EUA, 08-12 AAU 18 Towards 2012 (scenario from PointCarbon) 16 CERs trace highest EUA price EUAs fall because 14 of increased supplies 12 Price rise because of banking to 2013 10 EUAs rise due to NAPs for 08-12 8 6 4 EUAs collapse due to oversupply and limited banking to 2008 International post-2012 2 agreement enters into force 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 2004 2005 2006 2007 2008 2009 2010 2011 2012

  8. Challenges • Intersection between macro and micro level • How to ensure consistensy with macrolevel and activity data fed into the macro model, and emission projections when relying on a large degree of micro information and information gathered within sectors ? • How to deal with ”voluntary agreements” in projections and scenarios when measures and emisson reductions would be achieved anyway? • How to interprete the different scenarios in the reporting guidelines ?

  9. LUCF projections • In Norway there are no permanent institutional arrangement for making projection on GHG emission/removals from LUCF sector • Ministry of Agriculture and The Norwegian State Pollution are responsible for the LUCF projections • Norwegian forest has a long rotation period (70-120 years), thus the projection is mainly driven by past forest management practice which will result in continuing gross increment the next 10-20 years • The projection is based on following assumptions: - continuation of increase in gross increment - continuation of current harvesting rate - no changes in natural dieoff - no change in forest policy - soil carbon and non-CO2 GHGs not included

  10. Challenges:Land-Use Change and Forestry • Difficult to project harvesting rate, since this is mainly driven by the international prices on timber • Difficult to predict eventually increased in the natural dieoff (decay) when the rate of old forests increase due to reduces harvesting rate • Difficult to predict changes in soil carbon stock due to changed harvesting rate • Difficult to project effect of past measures (improved forest management) • Difficult to predict carbon changes in marginal forests (forest in mountain areas and in northern parts of Norway)

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