Reconciling climate objectives with an efficient bio-economy.

Transcription

1 Reconciling climate objectives with an efficient bio-economy. FEDIOL Conference: Critical challenges for EU vegetable oil processors. Brussels, 8th June Prof. Dr. André P.C. Faaij Academic Director - Energy Academy Europe Distinguished Professor Energy System Analysis University of Groningen

2 IPCC: Energy demand, GHG emissions and climate change 2

3 Energy system transformation [GEA/van Vuuren et al CoSust, 2012]

4 Global biomass deployment in relation to GHG mitigation (IPCC AR 5, 2014)

5 Advancing markets pushed by technological progress and pulled by high/volatile oil prices Advanced biofuels (strong economic perspective) Biorefining, biochemicals, biomaterials Aviation and shipping [IEA Biofuels Roadmap]

6 GHG emissions per km driven No CCS CCS [Van Vliet et al., 2009]

7 But, BBE faces key hurdles Negative perception on biomass use for energy (and materials) in key markets (including EC; RED to EXCLUDE iluc mitigation ). Policy arena is divided and fails to combine key priorities (agri, energy, climate, development). Uncertain investment climate stalls essential technological learning of advanced BBE-options. Too limited attention for synergy between sustainable agriculture, forestry, land use and biomass production. 7

8 Bioenergy potentials [2050] (colors based on expert opinion). (IPCC AR5 WGIII, 2014)

9 (O Neill et al., 2014) Different scenario s for: Energy, land use, agriculture Scenarios SSP1: Optimistic world (low challenges to mitigation and adaptation) SSP2: Middle of the road SSP3: Pessimistic world (high challenges to mitigation and adaptation) 9 Vassilis Daioglou - The role of biomass in climate change mitigation

10 Supply biomass Residues Theoretical Potential: Driven by increased demand of agriculture & forestry products Ecological Potential: Follows similar trend, but less pronounced SSP1 SSP2 SSP3 Available Potential: Opposite trend, very small differences Explanation: competing uses grow significantly from SSP1 to SSP3. Different drivers across scenarios cancel eachother out. 10 Vassilis Daioglou - The role of biomass in climate change mitigation

11 Supply Energy crops potential future supply of modern biomass from residues and energy crops accounting for the drivers and constraints in a spatially explicit manner (IMAGE) SSP1: Lots of natural lands are protected High abandonement of productive lands 11 Vassilis Daioglou - The role of biomass in climate change mitigation

12 Supply Energy crops SSP3: Expansion of land for food Low protection of natural lands 12 Vassilis Daioglou - The role of biomass in climate change mitigation

13 Supply Curves 2100 Residue supply-curves consistent Availability of high quality lands in SSP1 leads to extremely high and low cost availability of biomass 13 Vassilis Daioglou - The role of biomass in climate change mitigation

14 Demand System demand for biomass for different energy and chemical purposes in a dynamic energy system model (TIMER) SSP1 SSP2 SSP3 Base Mitig Base Mitig Base Mitig Baseline Scenarios - Liquid bioenergy very important, especially in SSP1 - Also some solids and chemicals, especially in SSP3 Mitigation Scenarios - Increased (but not exclusive) use of BECCS. H 2 in SSP1 increased technological development Vassilis Daioglou - The role of biomass in climate change mitigation

15 Emissions Integrated overall greenhouse gas impact of biomass deployment for bioenergy and biochemicals, taking the potential dynamics of future land use and the energy system into account SSP1 SSP2 SSP3 Base Mitig Base Mitig Base Mitig Availability of high quality lands for biomass and protection of carbon stocks in SSP1 leads to high biomass deploymend and land based mitigation! In SSP2, about 10% of mitigation is due to biomass use, largest contribution from BECCS - Higher in SSP1 (lower LUC, better bioenergy technologies) - Lower in SSP3 15 Vassilis Daioglou - The role of biomass in climate change mitigation

16 BBE Strategies What is the future role of biomass, bioenergy and biochemicals in various climate change mitigation scenarios when accounting for the land and energy-systems in an integrated manner? Biomass has an important role - Residues: low cost source, similar across scenarios - Energy crops (lignocellulosic), important at higher demand levels Conditions for its effective use - Land use scenarios and Protection of carbon stocks High biomass production with mitigation vs. Low biomass production in high LUC - Multiple energy and non-energy uses - Highest mitigation: transport and power - Advanced technologies a must: 2 nd gen. Biofuels, BECCS - Competing uses: Improve efficiency and alternate technologies 16 Vassilis Daioglou - The role of biomass in climate change mitigation

17 The role of biomass Strategies Supply Regions: - Residues: - Asia - OECD Energy crops: - Latin America - OECD - Asia - Africa -... Mitigation scenarios SSP1 2.6 SSP2 2.6 SSP3 3.4 Primary Production (EJ Prim /yr) Residues Energy Crops Total Land Use(MHa) Secondary Bioenergy (EJ Sec /yr) w/o CCS w CCS % Total Final Consumption 35% 25% 21% 17 Vassilis Daioglou - The role of biomass in climate change mitigation

18 Yield (t/(ha.yr)) Yield (t/(ha.yr)) Yield (t/(ha.yr)) Yield (t/(ha.yr)) Yield (t/(ha.yr)) Further investigations yield gaps Maize Rice, paddy Livestock footprint per unit of meat of milk may Improve a factor depending on setting USA China Wheat Sugar cane Brazil India Zambia & Zimbabwe Australia Soybeans Australia Brazil Legend: Countries assessed in this study Countries assessed by De Wit et al. [1] Maize Rice Soybean Wheat Sugarcane Beef and milk Key options such as intercropping, agroforestry and multiple harvests poorly included (e.g Camelina) [Gerssen-Gondelach, et al., Food & Energy Security, 2015] China India United States of America Zambia Zimbabwe

19 Potential biomass production on saline soils. [Wicke et al, Energy & Environmental Science, 2011]

20 Confrontation bottom-up vs. top down iluc modelling Key steps iluc modelling efforts: CGE; historic data basis Model shock, short term, BAU, current technology. Quantify LUC Quantify GHG implications (carbon stocks) Bottom-up insights: Coverage of BBE options, advancements in agriculture, verification of changes (land, production) Gradual, sustainability driven, longer term, technological change (BBE, Agriculture LUC depends on zoning, productivity, socio-economic drivers Governing of forest, agriculture, identification of best lands. [IEA & other workshops, ; Wicke et al, GCB-Bioenergy 2014]

21 Example: Corn ethanol Results from PE & CGE models B: Ethanol LUC-related GHG emissions (g CO2e/MJ) Corn Searchinger et al. [3] CARB [13] EPA [18] Hertel et al. [14] Tyner et al. [15] Group 1 Tyner et al. [15] Group 2 Tyner et al. [15] Group 3 Al-Riffai et al. [16] Laborde [17] [Wicke et al., Biofuels, Lywood 2012] et al. [25]

22 General approach iluc mitigation From economic models Baseline: developments in food, feed and fibres Biomass target: the amount required to meet targets such as RED. [Brinkman, et al., 2015] 22

23 Full impact analysis TOTAL AND NET ANNUAL GHG EMISSIONS FOR 2010 AND THE BASELINE AND ILUC MITIGATION SCENARIOS IN EMISSIONS FROM THE MISCANTHUS-ETHANOL VALUE CHAIN. THE EQUILIBRIUM TIME FOR SOIL CARBON STOCK CHANGES IS 20 YEARS. ILUC PREVENTION SCENARIOS: L, LOW; M, MEDIUM; H, HIGH. INTENSIFICATION PATHWAYS: CI, CONVENTIONAL INTENSIFICATION; II, INTERMEDIATE SUSTAINABLE INTENSIFICATION; SI, SUSTAINABLE INTENSIFICATION. [Gerssen-Gondelach et al., GCB Bioenergy, 2016]

24 [IPCC-SRREN, 2011]

25 LUC in Indonesia Land area (Mha) Rest degraded land immature palm oil mature palm oil permanent pastures permanent crops w/o palm oil arable land grassland shrubland and savannah Forest plantation forest cover [Wicke, et al., 2010, Land use policy]

26 Land are (Mha) LUC until 2020 Indonesia Business as Usual Provincial plans (base) Land are (Mha) Land area (Mha) Land are (Mha) Sustainability Past trends (improved) forest cover Projection Forest plantation Projection shrubland and savannah forest grassland cover Forest forest plantation cover Forest plantation agricultural land mature palm oil immature palm oil shrubland degraded and land savannah grassland shrubland and savannah [Wicke, grassland et al., 2010 rest agricultural land mature agricultural palm oil land (land mature use policy)] palm oil immature palm oil degraded immature land palm oil degraded land rest rest

27 Example: Palm-oilbased vs. fossil electricity GHG emissions (g CO 2 eq/ kwh) Peatland forest Natural rain forest Coal Base case CPO electricity Fossil electricity PFAD electricity [Wicke et al., Biomass and Bioenergy, 2008] Average Dutch Claus power plant Average EU Logged-over forest Modern natural gas PFAD Degraded land Improvement

28 Summary BBE deployment ~300 EJ required post 2050 (mix of advanced fuels, power, heat, biomaterials + bio-ccs) for essential GHG mitigation effort (BBE may take up to 40%). Potentials (technical, economic, sustainable) suffice when combined with modernization of agriculture and good land management. Realize the synergies with more resilient food production, more efficient use of natural resources, increased carbon stocks. and rural development + (shift of fossil fuel expenditures to rural areas can amount several trillion U$/yr). Logical and efficient pathways and gradual development of (biomass) markets, infrastructure and technologies; intersectoral approaches.

29 No time to waste (to cite Greenpeace) & Thank you very much for your attention / sciencedirect/scopus/google scholar

30 Yield projections Europe Observed yield CEEC and WEC Linear extrapolation of historic trends Widening yield gap Applied scenarios Yield [ton/ha] Low, baseline and high 0 Observed historic yields Projections Source FAOSTAT [Wit & Faaij, Biomass & Bioenergy, 2010]

31 Results - spatial production potential Arable land available for dedicated bio-energy crops divided by the total land Potential Low potential < 6,5% Countries NL, BE, LU, AT, CH, NO, SE and FI Moderate potential 6,5% - 17% FR, ES, PT, GE, UK, DK, IE, IT and GR High potential > 17% PL, LT, LV, HU, SL, SK, CZ, EST, RO, BU and UKR [Wit & Faaij, Biomass & Bioenergy, 2010]

32 [Wit & Faaij, Biomass & Bioenergy, 2010] Results - spatial cost distribution Production cost ( GJ -1 ) for Grassy crops Potential Low Cost Moderate Cost < 2,00 2,00 3,20 Countries PL, PT, CZ, LT, LV, UK, RO, BU, HU, SL, SK, EST, UKR FR, ES, GE, IT, SE, FI, NO, IE High Cost > 3,20 NL, BE, LU, UK, GR, DK, CH, AT

33 Total energy potential under three different crop schemes. Low yielding crops : all arable land available planted with oil crops. High yielding crops : all available land planted with grass crops. [Wit & Faaij, Biomass & Bioenergy, 2010]

34 Example: GHG balance of combined agricultural intensification + bioenergy production in Europe + Ukraine [Wit et al., BioFPR, 2014]