Eufasom_BiomassPotentials_Skopje2009

366 views

Published on

Biomass Energy Europe meeting presentation by UniHH

Published in: Education, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
366
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • spatially explicit information such as road layouts, existing land uses, population densities and growth rates, distributions of endangered species, archeologically significant areas, etc. to inform planning and policy development related to biomass energy at a regional or national level.
  • Supply functions: implicit meaning there are no direct supply functions for crops for example but we have inputs of resources, labor, technologies which in the end brings about yields as an output for example. Demand functions: changing prices, ex. decreasing prices
  • Policies: energy taxes, carbon taxes, tariffs and subsidies, standards Technical change: example – 20% increase in crop productivitiy, agricultural mechanization, etc. Environmental change: introduction of environmental policies, etc. Socioeconomic change: Population, Low income population effects, high-income population; inequalities; land tenure; standard of living
  • Sealed lands include lands used for roads, railroads, lands where buildings were erected, etc.
  • It is a small static model which marginally represents the bioenergy module in EUFASOM but does not possess all the advantages and characteristics of EUFASOM which is dynamic. It is also a stand alone model – runs outside EUFASOM.
  • Inputs: Resource constraints: (Land) - fixed total quantity and/or increasing resource supply functions Outputs: production Q = land use, water use, environment (CO2 emissions) consumption Q = undernourishment indicators trade flows = net exports or net imports
  • 1 km2 = 100 ha. The EU27 has a total land area of 433.2 Mha, of which 196.6 Mha is agricultural and 113.5 Mha arable. Forest area is around 150.85 million has. Data from Institute of Science and Society, 2008. (other data as of 2006 from Europe Statistical Pocketbook). According from EURURALIS, for the EU27 about 4% of total land and about 8% of agricultural land will be used to grow first generation bio-energy crops. As of 2003, availability of biomass resources for EU25 according to a fact finding study done by Broek van den et al (biofuels in the dutch market) shows a potential of around 165 mtoe including electricity, heat and biofuels. From this study, it is around 214 mtoe (500 million tons biomass).
  • Eufasom_BiomassPotentials_Skopje2009

    1. 1. The European Forest and Agricultural Sector Optimization Model (EUFASOM) Chrystalyn Ivie S. Ramos and Uwe A. Schneider, Hamburg University 3 rd Project Meeting, Skopje, Macedonia, 10-11 September 2009 BEE project is funded by the European Commission under the Framework Programme 7 FP7 GRANT AGREEMENT N˚: 213417
    2. 2. Presentation Summary <ul><li>Part I: The EUFASOM Model </li></ul><ul><li>Part II: Policy Scenario Analysis </li></ul>
    3. 3. Part I: The EUFASOM Model
    4. 4. EUFASOM Model Presentation <ul><li>Partial equilibrium model (endogenous prices) </li></ul><ul><li>Bottom-up approach </li></ul><ul><li>Computes agricultural and forest market equilibrium (optimization model) </li></ul><ul><li>Constrained by resource endowments, technologies, policies </li></ul><ul><li>Spatially explicit, dynamic </li></ul><ul><li>Data intensive, comprehensive </li></ul><ul><li>Integrates environmental effects </li></ul><ul><li>Programmed in GAMS, Solved as LP </li></ul>
    5. 5. EUFASOM Model Presentation <ul><li>Supply functions </li></ul><ul><ul><li>implicit: </li></ul></ul><ul><ul><ul><li>technology1 (RfCvSt) yield1 </li></ul></ul></ul><ul><ul><ul><li>technology2 (IrZeSt) yield2 </li></ul></ul></ul><ul><li>Demand functions </li></ul><ul><ul><li>explicit: changing prices </li></ul></ul><ul><li>Temporal resolution: 5-year time periods, regional or national aggregation levels </li></ul>
    6. 6. Purpose and Objectives <ul><li>To advice policy makers about the agricultural and forestry sector response to structural changes based on: </li></ul><ul><li>Policies </li></ul><ul><li>Environmental change </li></ul><ul><li>Technical change </li></ul><ul><li>Socioeconomic change </li></ul>
    7. 7. Food Timber Fiber Bioenergy Biomaterial Carbon Sinks Land use competition Nature Reserves Sealed Lands
    8. 8. EUFASOM Structure Resources Land Use Technologies Processing Technologies Products Markets Inputs Limits Supply Functions Limits Demand Functions, Trade Limits Enviro nmental Impacts
    9. 9. EUFASOM Model Structure Processing Markets Feed mixing Labor Pasture Other Inputs Cropland Water Livestock production Forestry, Nature, Crop production Export Domestic demand Import Forest Inventory
    10. 10. EUFASOM Modeling System EUFASOM Crop & Tree Simulation Models Spatial Analysis Tools Farm level & GIS Data Viable Population Analysis Systematic Wetland Conservation Planning Engineering Equations Other Economic Models Climate Models Aggregated Agricultural Statistics
    11. 11. EUFASOM Model Clusters AROPAj Model: Farm type models, CAP reform and GHG management FORMICA Model: Regional forest management, GHG budget at forestry sector level, case studies Bio-Tech Model: Product chains of bioenergy and biomaterials, GHG balance of options EPIC Model: Agriculture, crop production, environmental factors, biogeochemistry supply curves OSKAR: Forest biomass growth, Afforestation, Deforestation, Forest Management EUFASOM Model: Trade and competition between regions, competition between sectors optima biomass supply chemistry technology and costs BEWHERE Model: Optimal location of plants according to supply and demand, competition between biomass production types Geography Case studies Technology Production technology and costs Trade and competition
    12. 12. EUFASOM Simulated Projections <ul><li>Projections = Scenario Results </li></ul><ul><li>≠ Predictions (Baselines) </li></ul>Scenarios  Assumptions, Policies, Society, Technologies, Environment
    13. 13. Challenges <ul><li>Scales, Scopes, Data Consistency </li></ul><ul><li>Computing Power </li></ul><ul><li>Validation </li></ul><ul><li>Efficient Adaptation under Multiple Objectives </li></ul>
    14. 14. Reference <ul><li>Schneider U.A., J. Balkovic, S. De Cara, O. Franklin, S. Fritz, P. Havlik, I. Huck, K. Jantke, A.M.I. Kallio, F. Kraxner, A. Moiseyev, M. Obersteiner, C.I. Ramos, C. Schleupner, E. Schmid, D. Schwab, R. Skalsky (2008), “The European Forest and Agricultural Sector Optimization Model – EUFASOM”, FNU-156 , Hamburg University and Centre for Marine and Atmospheric Sciences, Hamburg. </li></ul><ul><li>http://www.fnu.zmaw.de/ </li></ul>
    15. 15. Part II: Policy Scenario Analysis (Bioenergy Illustration Case)
    16. 16. Illustration Case: Bioenergy <ul><li>Model characteristics </li></ul><ul><ul><li>National and regional levels (EU25 wide) </li></ul></ul><ul><ul><li>Scenarios done for the agricultural sector only </li></ul></ul><ul><ul><ul><li>conventional food crops </li></ul></ul></ul><ul><ul><ul><li>biomass from dedicated energy crops (willow, miscanthus and reed canary grass) </li></ul></ul></ul><ul><ul><li>Regional trade included </li></ul></ul><ul><ul><li>Bioenergy scope: biomass, biopower, biofuels, biogas </li></ul></ul><ul><ul><li>Subjected to bioenergy policy, ie: subsidies </li></ul></ul>
    17. 17. Illustration Case: Bioenergy <ul><li>Inputs </li></ul><ul><ul><li>resource quantities, crop yields, production costs </li></ul></ul><ul><ul><li>Bioenergy processes: technologies, biomass input, processing costs, unit bioenergy output </li></ul></ul><ul><ul><li>Market data: base prices </li></ul></ul><ul><li>Outputs </li></ul><ul><ul><li>Production/Consumption quantities </li></ul></ul><ul><ul><li>Economic and technical potentials </li></ul></ul><ul><ul><li>Prices </li></ul></ul><ul><ul><li>Trade flows </li></ul></ul><ul><li>Assumptions: </li></ul><ul><ul><li>For the EU27, about 4% of total land and about 8% of agricultural land were used to grow first generation bio-energy crops (EURURALIS,2008). </li></ul></ul><ul><ul><li>Only minimum demand for biomass, everything else used for the production of bioenergy (in scenario runs) </li></ul></ul>
    18. 18. Scenarios: Economic and Technical Potentials 0 250 500 750 1000 1250 1500 1750 2000 0 100 200 300 400 500 600 Biomass Incentive in Euro/ton Biomass Demand in million dry tons Competitive Economic Potential Technical Potential Current Consumption* * Consumption, 385 M dry tons (fact-finding study by Broek van den et al, 2003)
    19. 19. Scenarios: Economic and Technical Potentials Incentive in Euro/MWh Sectoral Demand in billion MWh 0 500 1000 1500 2000 0 5 10 15 20 25 30 35 40 45 50 Biogas BioPower Biofuel 60
    20. 20. Scenarios: Economic and Technical Potentials 0 500 1000 1500 2000 0 10 20 30 40 50 60 Incentive in Euro/MWh Bioenergy Demand in billion MWh Competitive Economic Potential Technical Potential
    21. 21. Impact on Food Price, Consumption and Trade Net Export Volume in Billion Euros -1000 -500 0 500 0 2000 4000 6000 8000 10000 12000 14000 16000 -10000 -5000 0 5000 Fisher Index for Food Price and Consumption Biofuel Demand in million MWh Price Consumption Net Export
    22. 22. Policies <ul><li>Greenhouse gas taxes (climate, environment) </li></ul><ul><li>Other policies (agriculture, trade, etc) </li></ul>
    23. 23. Forest Policy: Crop Emissions Emissions (kg C/ha) Carbon price (Euro/tce) -15 -10 -5 0 5 10 15 0 50 100 150 200 250 300 Nitrogen Fertilizer Ag-Soil Carbon Irrigation Use Fossil Fuel Use
    24. 25. Power Plant Biomass Supply 0 10 20 30 40 50 60 70 80 0 20 40 60 80 100 Energy Crops (million tons) Carbon tax on energy (EUR/ton of carbon) 2010 Capacity 2030 Capacity 2050 Capacity Unrestricted Capacity
    25. 26. Thank you! <ul><li>Chrystalyn Ivie S. Ramos </li></ul><ul><li>Hamburg University </li></ul><ul><li>+49 40 42838 4830 </li></ul><ul><li>[email_address] </li></ul>BEE project is funded by the European Commission under the Framework Programme 7 FP7 GRANT AGREEMENT N˚: 213417

    ×