ENFA Model ENFA Kick-off Meeting Hamburg, 10 May 2005 ENFA Model • Simulates land use decisions in the EU agricultural and forest sectors • Represents markets and computes market equilibrium • Portrays trade on a global level • Accounts for environmental impacts of land use decisions • Spatially explicit, dynamic Non-Food Food Land use competition Biodiversity ENFA Model Structure Limits Limits Resources Inputs Supply Functions Land Use Products Markets Processing Technologies Demand Functions, Trade Technologies ENFA Optimization Model determines the "optimal" use to which each individual technology should be used in each region and time period • Maximize welfare • Obey restrictions Product prices are endogenous ENFA Spatial Resolution • • • • • Political regions (NUTS 2) Soil types Farm types Altitude levels Slopes ENFA Dynamics • 5 to 10 year steps from 2005 to 2030 (2100?) • Technical progress • Demand & industry growth • Resource change • Policy scenarios Data • Resource data – Climate, Soil, Water, Existing Forests, Population, Labor • Technological data – Inputs / outputs for crop, livestock, forest management, and product processing and transportation options • Market data – Observed prices, production, trade, and income levels – Supply Demand function parameters • Environmental impact data – Emissions, Sequestration, Erosion, Biodiversity ENFA Technologies • Traditional agriculture – major crops – major livestock • • • • Forestry Non-food agriculture Processing (Wildlife preservation) Non-market Impacts • • • • • Greenhouse gas emissions Air, water, soil quality Income distribution Rural development / employment Wildlife Simultaneity • Technologies • Non-Market Impacts • Current and Potential Policies … resource competition … multiple impacts Crop Technology Data Base Region Altitud Soil Farm Rotation Water Tillage Fertilz Residue Item Unit Value Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Wheat dt/ha/y 50 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic S-Beat dt/ha/y 200 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Straw dt/ha/y 50 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Labor hr/ha/y 30 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Land ha/ha/y 1 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Diesel l/ha/y 40 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic ... ... ... Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Soil-C kg/ha/y 50 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic Erosion kg/ha/y 15 Poland 0-300 Sand ES3 W-W-S Irrig Conv. Basic Basic NO3-L kg/ha/y 20 Inputs Outputs Technology Adoption Non-Market Impacts Consistency • Representative yields not maximum yields on experimental plots • Representative input quantities on labor and energy intensive inputs • Representative and complete variable costs on remaining inputs • Environmental Impacts (from EPIC) Technical Details • Programmed in GAMS • Non-linear functions are linearly approximated • Solved with CPLEX • Variables and equations are aggregated to blocks Constrained Optimization Max f (x) subject to g(x) 0 Max y p DD d y r r,y y pc EX j,r,c d j,c r Objective Function p c IM j,r,c d j,c r L L dL p Lr,s a r,c,t,w L a LIVE a dL d s r ,s,s r,s,s ,n,s,u r,c,t,w ,n,s,u r,k,i r,k,i r,s c,t,w ,n,u k,i LB LB LB p r a r,c,t,w ,n,s,u Lr,c,t,w ,n,s,u a r,k,i LIVE r,k,i d r k,i c,t,w ,n,s,u W p rW a r,c,t,w L d ,n,s,u r,c,t,w ,n,s,u r c,t,w ,n,s,u AU p AU a LIVE d r r,k,i r,k,i r k,i inp inp pinp a inp L a LIVE a PR h r,h r ,h r,c,t,w ,n,s,u r,c,t,w ,n,s,u r,k,i r,k,i r,inp c,t,w ,n,s,u k,i US p r,r USr,r,y USr,r,y p IM / EX EX j,r,c IM j,r,c r r y j,c pCE EM g ER g g Resource Limits a ED r,c,t,w,n,s,u c,t,w,n,s,u ED L r,c,t,w,n,s,u a r,k,i LIVE r,k,i k,i a ED r,h PR r,h h Limits exist on • Land • Water • Family labor • Public grazing land b ED r Balance Equations LIVE a CROP L a r,k,i,y LIVEr,k,i r,c,t,w ,n,s,u,y r,c,t,w ,n,s,u t,w ,n,s,u,c k,i a PR r,c,h PR r,h DD r,y h USr,r,y USr,r,y IM j,r,y EX j,r,y 0 r r j j International Trade EX j,r,y EX j, j,y FD j,y 0 r IM r j j,r,y IM j, j,y FSj,y 0 j Emission Accounts EM g e r,c,t,w,n,s,u,g Lr,c,t,w,n,s,u r,c,t,w,n,s,u e r,f ,g dL r,s,s r,s,s er ,f ,g 0 e r,k,i,g LIVE r,k,i r,k,i e r,h,g PR r,h r,h er ,k ,i ,g 0 er ,h ,g 0 er ,c ,t ,w ,n ,s ,u ,g 0 Basic Results Technology Potentials Measures of potential – Technical – Economic • single strategy • multiple strategy U.S. Ag-Soil Carbon Potentials 500 Carbon price ($/tce) 400 Economic Potential 300 Competitive Economic Potential 200 100 Technical Potential 0 0 20 40 60 80 100 120 Soil carbon sequestration (mmtce) 140 160 U.S. Afforestation Potentials 500 Carbon price ($/tce) 400 300 Competitive Economic Potential 200 Economic Potential 100 Technical Potential 0 0 50 100 150 200 Emission reduction (mmtce) 250 300 U.S. Biofuel Potentials 500 Economic Potential Carbon price ($/tce) 400 300 Competitive Economic Potential 200 Technical Potential 100 0 0 50 100 150 200 250 Emission reduction (mmtce) 300 350 Land Allocation Pasture Traditional Crops Biomass for Power Plants Afforestation Carbon Tax Energy Crop Area Bioenergy use None 2010 Limit 2030 Limit 2050 Limit Unrestricted Subsidy A Simple Example Rainfed Corn Yield (bu/acre) Irrigated Corn Yield (bu/acre) Irrigation Emission (tce/acre) Irrigation Cost ($/acre) Other Cost ($/acre) Biofuel Crop Market Revenue ($/acre) Biofuel Net Carbon Emission Offset (tce/acre) 140 180 0.5 35 220 35 1.7 Constant Corn Price Rainfed Corn Irrigated Corn Biofuel Revenue in $/Acre 250 200 150 100 50 0 0 25 50 Carbon Price in $/tce 100 Endogenous Corn Price Rainfed Corn Irrigated Corn Biofuel Revenue in $/Acre 250 200 150 100 50 0 0 (1.80) 25 (1.98) 50 (2.16) 100 (2.88) Carbon Price in $/tce (Corn price in $/bu)
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