Published on

presentation on the Workshop on Biomass resources and bioenergy in Norway and other Nordic countries

Published in: Education, Technology, Business
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
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.
  • 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
  • We will now be presenting some results on EUFASOM investigations on biomass and bioenergy potentials and the costs related to its production. The objectives of this specific study is to investigate and analyze the…
  • Economic Potentials = Fraction of Technical Potentials (Biophysically maximum impact of a given technology)
  • Externalities are internalized through introduction of policy analysis in terms of taxes, subisidies, incentives in the model.
  • ** databases used for the food crops data Farm budgets: Yields – yield per hectare, production quantity Inputs – weather, soil, topography, land management (e.g. crop rotations) Costs – producer prices
  • Engineering – data taken from other models – ex: crop growth models (EPIC, MISCANMOD, etc) or results from studies done by project partner institutions and from other literatures, extrapolation are also done when needed.
  • Through a bottom up optimization approach, EUFASOM maximizes the net present value of the sum of the producer and consumer surplus of each sector (agriculture, forest). The producer surplus are interpreted as net returns from the sectors (as resource rents).
  • Bioethanol market price between 450-500 EUR/tonne (source: Ethanol production cost in Europe is around 50 EUR/hl ( *Assumptions: the price of petrol fuel is half the bioethanol price (before tax) - * and and *At the beginning of 2006, the European Commission published their document “Biofuel strategy” *and pointing out that “with current technology, bioethanol is only competitive when oil is at €90/barrel” (in 2005 it reached $70/barrel). *However, at the beginning of 2008, the oil barrel passed the $100 barrier, likewise the price of cereals significatively increased in the same period and some cereals even doubled their price. - It is estimated that the cost of producing biodiesel is twice that of conventional diesel. And just to meet the 5.75 percent target, more than 9 percent of the EU’s agricultural area will be needed. ( Biogas to electricity price in Germany (at Jundhe , one of the first German biomass powered villages. It started up at the end of 2005. 140 houses, about 600 people, fed by 4 farmers making silage. They make enough gas to run a 700kw electricity plant continuously, and feed most of that into the National grid at 0.18Euros/kwhr).
  • As of 2007, biomass is 65.2% of the renewable energy sources which in total contributes to about 7.5% of the total primary energy consumption in 2007.
  • Current trend: 75-80 Mtoe in 2010 ( - European Biomass Industry Association)
  • In Europe, grassland is one of the dominant forms of land use covering 80 million hectares or 22% of the EU-25 land area (EEA, 2005).
  • Existing wetland data from SWEDI model in the EU25 amounts to around 16 m ha (current).
  • EC4MACS – European Consortium for Modeling of Air Pollution and Climate Strategies - to build and maintain a network of well established modelling tools for a comprehensive integrated assessment of the policy effectiveness of emission control strategies for air pollutants and greenhouse gases. NEEDS – New Energy Externalities Development for Sustainability - To evaluate the full costs and benefits (i.e. direct + external) of energy policies and of future energy systems , both at the level of individual countries and for the enlarged EU as a whole. ENFA - To develop a dynamic agricultural and forest sector model for the integrated economic and environmental assessment of non-food alternatives. TRANSUST.SCAN - Scanning Policy Scenarios for the Transition to Sustainable Economic Structures - to scan a wide range of policy scenarios as to their relevance to the European Sustainable Development Strategy in view of Extended Impact Assessment. The project linked and expanded an extensive set of existing/available models to reflect the multi-functionality aspect of sustainability policies and their trade-offs with other policies. Global Earth Observation – Benefit Estimation: Now, Next and Emerging” ( GEOBENE ) is to develop methodologies and analytical tools to assess societal benefits of GEO in the domains of: Disasters, Health, Energy, Climate, Water, Weather, Ecosystems, Agriculture and Biodiversity. BEE - to harmonize biomass resource assessments, focusing on the availability of biomass for energy in Europe and its neighboring countries. This harmonization will improve consistency, accuracy and reliability of biomass assessments, which can serve the planning of a transition to renewable energy in the European Union. EuroGEOSS: a European approach to the Global Earth Observation System of Systems. – to develop, link, and make globally available the EU information systems addressing forests, droughts, and biodiversity. CCTAME - Climate Change - Terrestrial Adaptation and Mitigation in Europe (CCTAME) – to assess the impacts of agricultural, climate, energy, forestry and other associated land-use policies, considering the resulting feed-backs on the climate system. Geographically explicit biophysical models together with an integrated cluster of economic land-use models will be coupled with regional climate models to assess and identify mitigation and adaptation strategies in European agriculture and forestry. The role of distribution and pressures from socio-economic drivers will be assessed in a geographically nested fashion. Crop/trees growth models operating on the plot level as well as on continental scales will quantify a rich set of mitigation and adaptation strategies focusing on climatic extreme events. The robustness of response strategies to extreme events will further be assessed with risk and uncertainty augmented farm/forest enterprise models. Bioenergy sources and pathways will be assessed with grid level models in combination with economic energy-land-use models. The results from the integrated CC-TAME model cluster will be used to provide: quantitative assessments in terms of cost efficiency and environmental effectiveness of individual land-use practices; competitive LULUCF mitigation potentials taking into account ancillary benefits, trade-offs and welfare impacts, and policy implications in terms of instrument design and international negotiations. LULUCF Projections - (Land Use, Land Use Change, and Forestry ) - integrated treatment of assumptions on biomass/biofuels/biogas use between energy projections and agriculture/forestry is needed.
  • BioPotentials_Oslo2009

    1. 1. Biomass Potential and Cost Assessment through the European Forest and Agricultural Sector Optimization Model Workshop on Biomass Resources and Bioenergy in Norway and other Nordic Countries Oslo, Norway, 23-25 September 2009 Research Unit Sustainability and Global Change Centre for Marine and Atmospheric Sciences Hamburg University, Germany Chrystalyn Ivie S. Ramos Uwe A. Schneider Christine Schleupner
    2. 2. 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>
    3. 3. The EUFASOM Model <ul><li>General Objective </li></ul><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><ul><li>Specific Objective </li></ul><ul><li>EUFASOM aims at integrated assessments of food, climate, biodiversity, bioenergy and water issues from different land use options. </li></ul>
    4. 4. Biomass and Bioenergy Investigations in EUFASOM <ul><li>Objectives </li></ul><ul><ul><li>investigate biomass and bioenergy technical and competitive economic potentials in Europe </li></ul></ul><ul><ul><li>analyze the impacts of biomass and bioenergy production on food sustainability, biodiversity, regional and international trade and its related marginal costs </li></ul></ul><ul><ul><li>assess CO 2 mitigation potentials in Europe </li></ul></ul>
    5. 5. Economic Potentials of Biomass and Bioenergy <ul><li>Direct Production Costs </li></ul><ul><li>Opportunity Costs (land scarcity, markets) </li></ul><ul><li>External Costs (Non-market impacts) </li></ul><ul><ul><li>GHG Emissions (Offsets, Leakage) </li></ul></ul><ul><ul><li>Biodiversity and Ecosystems </li></ul></ul><ul><ul><li>Soil Quality </li></ul></ul><ul><ul><li>Food Security </li></ul></ul><ul><ul><li>Landscape </li></ul></ul>
    6. 6. Biomass and Bioenergy Economics in EUFASOM <ul><li>Farm and Processing Plant level economics - Microeconomics </li></ul><ul><li>Economics of international agricultural and forest markets – Macroeconomics </li></ul><ul><li>Externalities – Policy Analysis </li></ul>
    7. 7. Microeconomic Data 1: Conventional Technologies <ul><li>Sources: </li></ul><ul><ul><li>Farm Accountancy Data Network Database </li></ul></ul><ul><ul><li>Food and Agriculture Organization of the United Nations Statistical Databases & Data-sets </li></ul></ul><ul><li>Farm budgets </li></ul><ul><ul><li>Yields </li></ul></ul><ul><ul><li>Inputs </li></ul></ul><ul><ul><li>Costs </li></ul></ul><ul><li>Automated Data Processing & Integration </li></ul>
    8. 8. Microeconomic Data 2: Adaptation Technologies <ul><li>New Technologies </li></ul><ul><ul><li>New agricultural production methods </li></ul></ul><ul><ul><li>New bioenergy processes </li></ul></ul><ul><li>Existing Technologies without data </li></ul><ul><ul><li>Crop management adaptations </li></ul></ul><ul><ul><li>Processing plants </li></ul></ul>Engineering
    9. 9. Macroeconomics in EUFASOM Demand Supply Price Quantity P* Q* Producer Surplus Consumer Surplus
    10. 10. EUFASOM Model Structure Resources Land Use Technologies Processing Technologies Products Markets Inputs Limits Supply Functions Limits Demand Functions, Trade Limits Environmental Impacts
    11. 11. Technological Data: Biomass <ul><li>Indicative producer prices </li></ul>Sources: Defra/DTI (2007), UK Biomass Strategy Statistics Austria (2008), ENFA Consortium (2008) ~ 100 Timber ~ 50 Pulp ~ 70 Willow ~ 40 RCG ~ 53 Miscanthus Average Cost (EUR/tonne) Biomass Type
    12. 12. Technological Data: Bioenergy <ul><li>Indicative market prices </li></ul>Sources:   ENFA Consortium (2008) E UR/hL ~ 100 Biogas for transport 15-20 50-70 10-20 30-40 Price E UR/MWh Biogas for electricity E UR/hL Biofuels E UR/MWh Bioheat E UR/MWh Bioelectricity Unit Sector
    13. 13. European Biomass Resources <ul><li>EU Consumption (2006): </li></ul><ul><li> Source: </li></ul><ul><li>- Primary energy: > 2000 mtoe </li></ul><ul><li>- Solid biomass*: ~ 62.4 mtoe (3.7%) </li></ul><ul><li> </li></ul><ul><li>EU guideline on biomass use (EU25): </li></ul><ul><li> Sources: EUROSTAT, and </li></ul><ul><li>- by 2010 ^ : ~ 150 mtoe ~ 360 M dry ton biomass </li></ul><ul><li>- by 2020: ~ 217 mtoe ~ 520 M dry ton biomass </li></ul>* Includes biomass to heat, electricity, biofuels ^ Conversion: 1 toe ~ 2.4 dry ton biomass
    14. 14. Bioenergy Indicative Targets by 2010 <ul><li>Sources: B. Kavalov (2004); EC (2006) </li></ul><ul><li>15% ~ 62 mtoe for heat/electricity </li></ul><ul><li>5.75% ~ 18 mtoe for biofuels </li></ul>Source: EU Biomass Action Plan (2006),
    15. 15. Scenario Analysis Results <ul><li>Economic Potentials </li></ul><ul><li>Technical Potentials </li></ul><ul><li>Impact on Food, Consumption and Trade </li></ul><ul><li>Impact on Biodiversity </li></ul><ul><ul><li>Grasslands </li></ul></ul><ul><ul><li>Wetlands </li></ul></ul>
    16. 16. Scenario: Biomass Potential Assessment * 1 toe ~ 2.4 dry ton biomass * Broek van den et al (2003) Technical Potential* By 2010 Biomass Price in Euro/ton EU25 Biomass Demand in million dry tons 0 250 500 750 1000 0 100 200 300 400 500 600 Competitive Economic Potential Technical Potential (simulated) * 2006 consumption ~150 M dry tons 2006 consumption
    17. 17. Scenario: Bioenergy Potential Assessment Bioenergy Price in Euro/MWh EU25 Bioenergy Demand in 1000 MWh (all sectors) 0 500 1000 0 10 20 30 40 50 60 Competitive Economic Potential Technical Potential 250 750
    18. 18. Scenario: Biofuel Cost-Supply Functions 0 50 100 150 200 250 300 350 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Marginal Biofuel Cost in Euro/hl EU25 Biofuel Production in mill hl Bioethanol Biodiesel Biofuel
    19. 19. 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 EU25 Bioenergy Demand in million MWh Price Consumption Net Export
    20. 20. Impact on Biodiversity: Grassland 0 50 100 150 200 250 300 350 400 0 500 1000 1500 2000 2500 3000 3500 Bioenergy Subsidy in Euro/MWh EU 25 Bioenergy Demand in 1000 MWh KeepGrassland_Biofuel KeepGrassland_Biogas KeepGrassland_BioElec KeepGrassland_AllBioEn ConvertGrassland_AllBioEn
    21. 21. Protect existing grassland areas Impact on Biodiversity: Grassland 0 5 10 15 20 25 30 35 40 45 0 50 100 150 200 250 300 350 400 450 500 EU25 Energy crop area in million ha Bioenergy Subsidy in Euro/ha Northern Europe Western Europe Central Europe Eastern Europe Southern Europe EU25 Countries
    22. 22. Unprotect existing grassland areas Impact on Biodiversity: Grassland 0 5 10 15 20 25 30 35 40 45 50 0 50 100 150 200 250 300 350 400 450 500 EU25 Energy crop area in million ha Bioenergy Subsidy in Euro/ha Northern Europe Western Europe Central Europe Eastern Europe Southern Europe EU25 Countries
    23. 23. Scenario: Bioenergy and Wetlands 0 100 200 300 400 500 600 0 50 100 150 200 250 300 350 400 Marginal Biomass Cost in Euro/ton EU25 Biomass Production in million wet tons 10 Mha 30 Mha Wetlands = 40 Mha
    24. 24. Impact on Biodiversity: Wetlands Protect existing wetland areas 18 20 22 24 26 28 30 32 0 100 200 300 400 500 600 700 800 EU25 Wetland area in Million ha Incentive in Euro/ha Biomass Target 0% Biomass Target 25% Biomass Target 50% Biomass Target 75% Biomass Target 100%
    25. 25. Impact on Biodiversity: Wetlands Unprotect existing wetland areas 8 10 12 14 16 18 20 22 24 26 28 0 100 200 300 400 500 600 700 800 EU25 Wetland area in Million ha Incentive in Euro/ha Biomass Target 0% Biomass Target 25% Biomass Target 50% Biomass Target 75% Biomass Target 100%
    26. 26. References <ul><li>Ramos, C. I. S. and U.A. Schneider (2009). “The European Forest and Agricultural Sector Optimization Model (EUFASOM)”. 3rd Project Meeting, Skopje, Macedonia, 10-11 September 2009. </li></ul><ul><li>Link, P.M., C.I. Ramos, U.A. Schneider, E. Schmid, J. Balkovic and R. Skalsky (2008). “The interdependencies between food and biofuel production in European agriculture - an application of EUFASOM”. FNU-165, Hamburg University and Centre for Marine and Atmospheric Science, Hamburg. </li></ul><ul><li>Schleupner, C. and U.A. Schneider (2008). “Evaluation of European wetland restoration potentials by considering economic costs under different policy options”. FNU-158, Hamburg University and Centre for Marine and Atmospheric Science, Hamburg. </li></ul><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>Schneider, U.A., C. Schleupner, K. Jantke, E. Schmid, C. I. Ramos (2008). “Biofuel consequences for European wetland species”. Workshop on Linking Biophysical and Economic Models of Biofuel Production and Environmental Impacts. Chicago, November 13-15, 2008. </li></ul><ul><li>Smit, H.J., M.J. Metzger, F. Ewert (1998). “Spatial distribution of grassland productivity and land use in Europe”. Agricultural Systems, Volume 98, Issue 3, October 2008, Pages 208-219. </li></ul>
    27. 27. EUFASOM Applications <ul><li>Applied in a number of EU Projects </li></ul><ul><ul><li>EC4MACS (EU-LIFE Program) </li></ul></ul><ul><ul><li>FP6 </li></ul></ul><ul><ul><ul><li>NEEDS </li></ul></ul></ul><ul><ul><ul><li>European Non-Food Agriculture </li></ul></ul></ul><ul><ul><ul><li>TranSust.Scan </li></ul></ul></ul><ul><ul><ul><li>GEO-BENE </li></ul></ul></ul><ul><ul><li>FP7 </li></ul></ul><ul><ul><ul><li>Biomass Energy Europe </li></ul></ul></ul><ul><ul><ul><li>EuroGEOSS </li></ul></ul></ul><ul><ul><ul><li>CCTAME </li></ul></ul></ul><ul><ul><ul><li>LULUCF Projections (in cooperation with EC-JRC) </li></ul></ul></ul>
    28. 28. Thank you! Chrystalyn Ivie S. Ramos [email_address]