1. Issues in the preparation of GHG projections for agriculture and land use, land-use change and forestry Summary of Discussions of Break Out Group 7 September 2004

2. Participation in Group 10 Parties and the European Community Received 4 presentations (Irl, Fin, Nz, Dk) Balance of expertise in agriculture

3. Key methodological issues for agriculture Projections of activity levels and emission factors; Use of specialized models Modelling impact of GHG-related factors – methodological problems and solutions Presentation of main drivers for GHG emissions projections

4. Projections of activity levels and emission factors (EF) Consider possible future changes in EFs Provide information on policies and measures to abate ammonia emissions Emerging importance on sensitivity analysis for projections Time frame for projections

5. Use of specialized models Data and models used in inventory should also be used in projections, if possible Focus on good scientific practice rather than specialized models or models per se Group unable to recommend use of any specialized models Multi-model approach desirable

6. Modelling impact of GHG-related factors – methodological problems and solutions Availability of data, getting statistics on specific issues Could also use bottom-up approach to include policies and measures in projection model Indirect effects of policies and measures Iteration between models to refine projections

7. Presentation of main drivers for GHG emissions projections Drivers not only related to projections but also to the inventory Recommend list of emission drivers, with reference to CRFs Textural interpretation of drivers and context What is the level of detail on information to be provided in NC ?

8. Key methodological issues for LULUCF Specific difficulties related to GHG projections for LULUCF Presentation of main drivers behind projections Exchange of information on available methods and models and sharing of solutions adopted by Parties

9. Specific difficulties related to GHG projections for LULUCF Projections in forestry – common in the industry When there is a good inventory, then projections not an issue; changes in carbon stocks very low Challenges in tracking changes in land use and changes in carbon stocks from land use change Activity data needs improvement

10. Main drivers behind projections Derive a list of variables (eg. Growth rates, tree density, biomass expansion factors) to guide better projections

11. Exchange of information on available methods and models Consider the linkage between agriculture and forestry for modelling. Existence of forest inventory Existing data sets on forest inventory, maps, remote sensing – allows simple extrapolation Consider also expert opinion in projections model GPG-LULUCF improves inventories, hence projections Group unable to elaborate further on LULUCF projections and provide solutions

12. Institutional Arrangements Importance of co-operation between institutions –to overcome methodological issues and problems –to estimate effects of policies and measures –contribute to building of projection estimates