Linking forestry, land use, and energy models for climate change mitigation assessment

Transcription

1 Linking forestry, land use, and energy models for climate change mitigation assessment Petr Havlík 1, Mykola Gusti 1, Nicklas Forsell 1, Tatiana Ermolieva 1, Georg Kindermann 1, Hannes Bötcher 1, Pekka Lauri 1, Oliver Fricko 2, Manfred Strubegger 2, Keywan Riahi 2, Florian Kraxner 1, Michael Obersteiner 1 1 ESM Ecosystem Services and Management 2 ENE Energy

2 Climate change mitigation and land use Studies of biomass resource have indicated large scale biomass potentials Increasing biomass can be provided from: Harvesting residues Forest management intensification Short rotation crops and perennial crops Byproducts/residues from industries and agricultural sector Woody biomass resource estimates are also often performed without explicit linkage to the agricultural sector Climate change mitigation studies have often been performed without linkage to the land use sector 2

3 Global Future Energy portfolios, Source: Modified after Azar et al

4 Aim of the study Provide the means for integrating the land use sector into energy system models and mitigation potential estimations Link a detailed biophysical forest (G4M) and agricultural (EPIC) models with a bottom-up partial equilibrium model of the forest and agricultural sector (GLOBIOM). Use the GLOBIOM model to develop look-up-tables that consistently covers the land use sector, land use change emissions and biomass demand implications. Incorporate the tables into the MESSAGE energy system model to estimate cross sectorial mitigation potentials and energy portfolios. 4

5 Land cover Land use Production Markets Demand Rain, Snow, Chemicals Below Root Zone EPIC Surface Flow 18 crops (FAO + SPAM) Wheat, Rice, Maize, Soybean, Barley, Sorghum, Millet, Cotton, Dry beans, Rapeseed, Groundnut, Sugarcane, Potatoes, Cassava, Sunflower, Chickpeas, Palm Fruit, Sweet potatoes 3 different systems Cropland Evaporation and Transpiration Subsurface Flow Population, GDP, preferences Food Fibers Energy ECONOMIC MARKET + Spatial equilibrium trade PRICES RUMINANT Digestibility model Feed intake Animal production GHG emissions 7 animals (FAO + Gridded livestock) Cattle & Buffalo Sheep & Goat Pig Poultry 8 different systems Grassland BIOENERGY Processing MJ biofuel MJ bioelectric Coproducts Land suitable for Poplar Pillow Eucalyptus Productivity from literature Short rotation plantations Global Land Cover 2000 Industry G4M Global Forest model Harvestable wood Harvesting costs Downscaled FAO FRA at grid level Area Carbon stock Age Tree size Species Rotation time Thinning Managed forest Natural forest Other natural land

6 Spatial resolution Homogeneous response units (HRU) clusters of 5 arcmin pixels HRU = Altitude & Slope & Soil PX5 Altitude class, Slope class, Soil Class PX5 Altitude class (m): 0 300, , , and > 2500; Slope class (deg): 0 3, 3 6, 6 10, 10 15, 15 30, and > 50; Soil texture class: coarse, medium, fine, stony and peat; Source: Skalský et al. (2008) 6

7 Spatial resolution Simulation Units (SimU) = HRU & PX30 & Country zone > SimU LC&LUstat Country HRU*PX30 SimU delineation related statistics on LC classes and Cropland management systems PX5 reference for geo-coded data on crop management; input statistical data for LC/LU economic optimization; Source: Skalský et al. (2008) 7

8 Forests G4M Estimates afforestation and deforestation by comparing the income of different land uses Is calibrated to historic data ( ) reported by Member States on afforestation and deforestation Management: Planting/Regeneration Thinning Final Harvest Calamities Management Major outputs: Mean annual increment Tree size Sawn wood suitability Harvesting cost (Full Carbon Accounting) 8

9 Crops - EPIC Processes Weather Hydrology Erosion Carbon sequestration Crop growth Crop rotations Fertilization Tillage Irrigation Drainage Pesticide Grazing Manure Rain, Snow, Chemicals Below Root Zone EPIC Surface Flow Evaporation and Transpiration Subsurface Flow Major outputs: Crop yields, Environmental effects (e.g. soil carbon, nitrogen leaching) 20 crops (>75% of harvested area) 4 management systems: High input, Low input, Irrigated, Subsistence 9

10 GLOBIOM - Livestock Global production system map FAO/ILRI 14 livestock production systems 6 animal types: Buffalo Cattle Sheep Goat Pig Poultry 10

11 GLOBIOM supply chain LAND USE CHANGE Natural Forests Managed Forests Short Rotation Tree Plantations Cropland Grassland Other natural land Wood Processing Bioenergy- Processing Livestock Feeding Bioenergy Bioethanol Biodiesel Methanol Heat Electricity Biogas Wood products Sawn wood Chemical pulp Mechanical pulp Fiberboard Play wood Crops Corn Wheat Cassava Potatoes Rapeseed etc Livestock products Beef Lamb Pork Poultry Eggs Milk 11

12 Look-up-tables The model is solved for a range of global biomass consumer prices and global carbon prices. The GLOBIOM solution scape is represented by incorporated into a look-up-table. The look-up-tables provides a consistent representation of information such as: Land use development Forest development Biomass availability Land use related GHG emissions (C02, CH4, N2O) Calorie consumptions Forest industrial developments Etc... 12

13 Preliminary scenario runs: Biomass availability 13

14 Preliminary scenario runs: Mitigation 14

15 Preliminary scenario runs: Mitigation 15

16 Preliminary scenario runs: Food consumption 16

17 Preliminary scenario runs: Food consumption 17

18 Forest industrial implication 18

19 MESSAGE energy system model (ENE) INPUT OUTPUT Energy system structure (including vintage of plant and equipment) Base-year energy flows and prices Energy demand projections Technology and resource options & their technoeconomic performance parameters Technical and policy constraints MESSAGE Primary Energy [EJ/yr] Biomass Coal Gas Geothermal Hydro Nuclear Oil Solar Wind Primary and final-energy mix Emissions and waste streams Health and environmental impacts (externalities) Resource use Land use Import dependence Investment requirements 19

20 Integration of the look-up-tables (ENE) 300 Biomass Usage by MESSAGE [EJ/yr] Range from GLOBIOM Reference 6 W/m2 4.5 W/m2 3.7 W/m2 2.6W/m2 20

21 Preliminary scenario runs (ENE): Energy sector development SSP2 Ref. Primary Energy [EJ/yr] % 90 % 80 % 70 % 60 % 50 % 40 % 30 % 20 % 10 % SSP2 Ref. Primary Energy Shares [%] 0 % Biomass Coal Gas Geothermal Hydro Nuclear Oil Solar Wind SSP2 2.6W/m2 Primary Energy [EJ/yr] Biomass Coal Gas Geothermal Hydro Nuclear Oil Solar Wind Biomass Coal Gas Geothermal Hydro Nuclear Oil Solar Wind SSP2 2.6W/m2 Primary Energy Shares [%] 100 % 90 % 80 % 70 % 60 % 50 % 40 % 30 % 20 % 10 % 0 % Biomass Coal Gas Geothermal Hydro Nuclear Oil Solar Wind 21

22 Preliminary scenario runs (ENE): Mitigation SSP2 Ref GHG Development [MtCO2e/yr] CH4 Energy CH4 Other CH4 Landuse CO2 Fossils and Industry CO2 Landuse N20 Energy N20 Other N20 Landuse SF SSP2 2.6W/m2 GHG Development [MtCO2e/yr] CH4 Energy CH4 Other CH4 Landuse CO2 Fossils and Industry CO2 Landuse N20 Energy N20 Other N20 Landuse SF6 22

23 Conclusions and future work The approach present a way of computing a set of land use scenarios that covers both the forest and agricultural sectors. The look-up-tables provide a consistent representation of the solution space that can be integrated into a variety of energy system models. We are currently in the process of setting up a web page for freely accessing the look-up-tables. Further work will be carried out in terms of updating the forest sector representation in the GLOBIOM model. 23

24 Questions and Answers Petr Havlik Nicklas Forsell Acknowledgement: FP7 LIMITS Project

25 Forests G4M Downscaling FAO country level information and forest growth functions estimated from yield tables Source: Kindermann et al. (2008) 25