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Climate change and the Energy-Agriculture-Climate Change nexus

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http://www.fao.org/economic/esa/esag/en/
Climate change and the Energy-Agriculture-Climate Change nexus.

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Climate change and the Energy-Agriculture-Climate Change nexus

  1. 1. Center for Global Trade Analysis Department of Agricultural Economics, Purdue University 403 West State Street, West Lafayette, IN 47907-2056 USA contactgtap@purdue.edu http://www.gtap.agecon.purdue.edu Global Trade Analysis Project Climate change and the Energy- Agriculture-Climate Change nexus Dominique van der Mensbrugghe Center for Global Trade Analysis, Purdue University Long-term scenario building for food and agriculture: A global overall model for FAO Brainstorming workshop, 19 February 2016 Global Perspectives Studies (GPS) Team, ESA FAO UN – Rome
  2. 2. • Greenhouse gas emissions • Agriculture and related land-use 25-33% • Changing atmospheric chemistry and climate • Variance perhaps more critical than mean • But climate models do not agree on either • and there are variegated changes on a regional basis • Potentially large impacts on resources and economies • Land (and capital) availability • Yields (temperature, water, pests and diseases) • Other ag and non-ag: labor productivity, health, energy demand, tourism Climate change 2
  3. 3. • Mitigation • Tax/price on carbon • REDD • Regulatory • Adaptation • Level of adaptation depends on size of climate signal • Climate smart agriculture • Changes in farming practices • Investment (e.g. irrigation) • Crop switching, crop movements • Issue: autonomous vs. exogenous Economic reactions 3
  4. 4. Climate and economic impacts -10 -8 -6 -4 -2 0 2 4 6 8 xea xlc mex idn ssa mna tur xsa bra xha usa wld ind hic jpn eur arg xec chn rus can TOU END HHE ONJ SEA WAT AGR Percent change in GDP in 2050, relative to no-damage scenario
  5. 5. • Integrated assessment • Model coupling (climate, crop models, water) • Integrated EMICs • Open loop coupling • Climate signal from GCMs • Yield/area impacts from crop models (possibly farm management practices) • Carbon taxes Modeling options 5
  6. 6. • Supply side • Energy (machinery, irrigation, heating) • Fertilizers • Down-stream (transportation, food processing, preparation & cooking) Energy-agriculture nexus 6
  7. 7. • Demand side • 1st generation biofuels • Ethanol (corn—USA, sugar—Brazil) • Biodiesel (oil crops) • Direct competition of land for food production and/or deforestation • 2nd generation biofuels • Dedicated wood crops • Wood and crop residues • Impact on land uncertain, but likely reduced • Key question: Competitiveness and substitutability with conventional technologies (and their future availability) Energy-agriculture nexus 7
  8. 8. • Largely focused on mitigation efforts • To what extent is bioenergy emission reducing? • Linked to land-use changes • Yield improvements • Source of feedstock Energy-agriculture-climate change nexus 8
  9. 9. SSP5 (Mitigation challenges dominate) Fossil-fueled Development Taking the Highway SSP3 (High challenges) Regional Rivalry A Rocky Road SSP1 (Low challenges) Sustainability Taking the Green Road SSP4 (Adaptation challenges dominate) Inequality A Road Divided SSP2 (Intermediate challenges) Middle of the Road Two-axes: adaptation & mitigation challenges 9 Socio-economic challenges for adaptation Socio-economic challengesformitigation Source: O’Neill et al. 2015
  10. 10. SSP1 SSP2 SSP3 SSP4 SSP5 RCP 8.5 REF RCP 6.0 REF REF REF REF RCP 4.5 RCP 2.6 X X Range of climate signal outcomes depends on SSPs and mitigation policies 10
  11. 11. • 3 model comparison • Significant differences in the land-use modeling across models that has implications for bioenergy deployment, feedstock composition, and GHG emissions. Land-use transition for bioenergy and climate stabilization Popp et al. 2014
  12. 12. • (All) land uses and carbon content • Bioenergy cost curves for various technologies • Prices of conventional energy technologies • ‘Share’ parameters for bioenergy technologies in energy bundles (liquid fuels, power sector, other) • Recommend looking at GCAM model • HUGE research agenda—uncertainty Data/Modeling requirements 12

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