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Baseline time accounting

Baseline time accounting. CARB expert workgroup meeting Time accounting subgroup – Interim report Jesper Hedal Kløverpris, PhD – Novozymes Steffen Mueller, PhD – University of Illinois. Estimating GHG emissions from ILUC. The four main steps Determine -

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Baseline time accounting

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  1. Baseline time accounting CARB expert workgroup meeting Time accounting subgroup – Interim report Jesper Hedal Kløverpris, PhD – Novozymes Steffen Mueller, PhD – University of Illinois

  2. Estimating GHG emissions from ILUC The four main steps Determine - …amount of land affected (in relation to baseline) …types of land affected (grassland, forest etc.) …carbon stocks/sequestration of land affected …how to deal with time accounting Although the ‘land use baseline’ is usually considered in step 1, it is most often not considered in step 4.

  3. Current time accounting approach ILUC contribution based on 30 year production period: 30 g CO2e/MJ Source: CARB (2009), Fig. C4-3 Result dependent on assumed biofuels production period What would have happened to this land in the baseline?

  4. Baseline land use change Arable land and land under permanent crops (only food and feed) Developing world: Arable land use mainly increasing Developed world: Arable land use mainly decreasing Source: Bruinsma (2009), Fig. 6

  5. Accelerated expansion ILUC taking place in a region where land use is already expanding (baseline) Baseline Biofuels scenario (1 y prod.) Year 1 Year 1 Year 0 Year 0 Human land use Human land use Human land use Human land use Land for biofuel Land for biofuel Year 2 Year 2 Baseline Biofuels scenario (2 y prod.) The figures on this slides are for illustrative purposes only and do not indicate any sizes or proportions of indirect land use change

  6. Delayed reversion ILUC taking place in a region where land use is ‘contracting’ (baseline) Baseline Biofuels scenario (1 y prod.) Human land use Human land use Year 1 Year 1 Year 2 Year 2 Land for biofuel Land for biofuel Year 0 Year 0 Baseline Biofuels scenario (2 y prod.) Human land use Human land use The figures on this slides are for illustrative purposes only and do not indicate any sizes or proportions of indirect land use change

  7. Baseline implications for time accounting ILUC: Accelerated expansion Baseline Regional baseline: Expansion of land use Direct (avoided) fossil emissions Cumulative GHG emissions (g CO2e) Induced Saved Direct ethanol emissions Time (y) TA Analytical time horizon Baseline One year ILUC: Delayed reversion Regional baseline: Contraction of land use Areas indicated equivalent to ton·years of carbon No GHG decay assumed above – graphs for illustrative purposes only and not meant to indicate proportions of GHG emissions

  8. Land use projections literature review Current trends in agricultural land use (sources) Developing world • Cropland area expanding, forest area decreasing Developed world • Cropland area contracting, forest area increasing Sources: FAOSTAT (2010) and Global Forest Resources Assessment 2010 – Key findings (FAO 2010)

  9. Land use projections literature review Future trends in agricultural land use (references) • Climate change and agricultural vulnerability(Fischer et al. 2002) • World Agriculture Towards 2015/2030 (Bruinsma 2003) • The resource Outlook to 2050 (Bruinsma 2009) • World Food and Agriculture to 2030/50 (Fischer 2009) • Millennium Ecosystem Assessment (Alder et al. 2005) • Climate benefits of changing diet (Stehfest et al. 2009) • Background report to the OECD Environmental Outlook to 2030 (Bakkes et al. 2008) Full references given at the end of the slideshow

  10. Land use projections literature review • The studies mentioned on the previous slide differ in several aspects such as temporal scope, yield assumptions, modeling framework, land use type(s) considered, regional disaggregation, drivers etc. • The studies come out with different results but all of them predict a steady increase in global agricultural land use up to 2030 and, except for Stehfest et al. (2009); this increase is expected to continue until 2050 • The conditions for ’baseline time accounting’ thereby seem to be in place for decades ahead

  11. Converting ‘accelerated expansion’ and ‘delayed reversion’ into a GWP(100) Following the definition of the GWP(100): • Take the cumulative radiative forcing (CRF) during 100 years caused by the emissions from the land conversion taking place as an indirect effect of biofuels production • Take the CRF within the same period of time for the same land area but for the emissions that would have occurred in the baseline (a shift in emissions by one year) • Divide the difference in CRF between these two situations by the CRF of a pulse emission of one unit of CO2 seen over 100 years This procedure will result in an ILUC factor equivalent to the GWP(100) – consistent with the unit used for direct emissions

  12. Preliminary results 1 GTAP-WH, only accelerated expansion assumed (no regional disaggregation) 2 Only accelerated expansion assumed The preliminary results have been derived by use of a climate model kindly made available by Martin Persson, University of Gothenburg, Sweden. Additional refinement of data input and quality control is still required.

  13. Conclusions • The ILUC factor must be consistent with direct emissions • Under current and near term baseline conditions, indirect land use change (ILUC) will likely be constituted by • Accelerated expansion (typical for the developing world) • Delayed reversion (typical for the developed world) • Under those conditions, assumptions about the biofuels production period are unnecessary – however: • If a 30 year biofuels program is considered, projections of the land use baseline 30 years into the future is required • Global agricultural land use is expected to increase at least to 2030 and most likely also to 2050

  14. Conclusions (continued, input from K. Kline) • Interacting with baseline conditions, the ILUC could also be constituted by use of previously cleared lands and - • Reduced fire and avoided (decreased) expansion (developing world) • Avoided reversion to urban/commercial/industrial and other uses that (in absence of ILUC) is representing loss of productive capacity and carbon carrying capacity (developed world) Thank you

  15. Extra slides and references

  16. Graphs for discussion Legend Ha Baseline Biofuels Acc. exp. Del. rev. Acc. exp.: Accelerated expansion Del. rev.: Delayed reversion Time Additional expansion Ha Ha Additional expansion Acc. exp. Del. rev. Acc. exp. Del. rev. Time Time

  17. Hertel et al. (2010) • Not straight forward to apply ’baseline time accounting’ to this study because it has partly been considered already: • ‘It may be […] that technological change will increase maize yields so much […] that total maize acreage actually falls, but our analysis is directed (in that case) to how much more it would fall without the biofuel increase.’ • In Europe, we use a lower emission factor for deforestation because cropland is already reverting to forest and biofuel cropland demand merely slows this process. The result is avoided [slow] sequestration rather than [rapid] release of aboveground carbon. • Baseline not considered in time accounting Delayed reversion! Delayed reversion

  18. Land quality (Kløverpris et al. 2010)

  19. Sustainable development and time accounting In 1987, The Brundtland Commission defined sustainable development as: …development that meets the needs of the present without compromising the ability of future generations to meet their own needs. Do we only care about the next 30 years?

  20. GWP values for CO2, CH4, and N2O Source: IPCC’s Fourth Assessment Report

  21. References • Alder et al. (2005): Changes in Ecosystem Services and Their Drivers across the Scenarios. Chapter 9 in: Carpenter SR, Pingali PL, Bennett EM, Zurek MB (eds) (2005): Ecosystems and Human Well-being: Scenarios, Volume 2. 2005 Millennium Ecosystem Assessment, Island Press, Washington·Covelo·London • Bakkes et al. (2008): Background report to the OECD environmental outlook to 2030. Overviews, details, and methodology of model-based analysis. MNP Report 500113001/ 2008, ISBN 978-90-6960-196-0, available at www.pbl.nl/en • Bruinsma J (ed) (2003): World Agriculture: towards 2015/2030. An FAO Perspective. FAO, Earthscan, London • Bruinsma J (2009): The resource Outlook to 2050. By how much do land, water and crop yields need to increase by 2050?, FAO Expert meeting on how to feed the world in 2050, 24-26 June 2009. • CARB (2009): Proposed Regulation to Implement the Low Carbon Fuel Standard – Vol. 1, California EPA • FAO (2010): Global Forest Resources Assessment 2010 – Key findings. Food and Agriculture Organization of the United Nations, Rome, available at www.fao.org/forestry/fra2010 • FAOSTAT (2010): http://faostat.fao.org, United Nations Food and Agricultural Organisation • Fischer G, Shah M, van Velthuizen H (2002): Climate Change and Agricultural Vulnerability, IIASA, Remaprint, Vienna • Fischer (2009): World Food and Agriculture to 2030/50: How do climate change and bioenergy alter the long-term outlook for food, agriculture and resource availability? FAO Expert meeting on how to feed the world in 2050, 24-26 June 2009. • Hertel TW, Golub AA, Jones AD, O’Hare M, Plevin RJ, Kammen DM (2010): Global Land Use and Greenhouse Gas Emissions Impacts of U.S. Maize Ethanol: Estimating Market-Mediated Responses, BioScience 60 (3) 223-231 • Kløverpris JH, Baltzer K, Nielsen PH (2010): Life cycle inventory modelling of land use induced by crop consumption Part 2: Example of wheat consumption in Brazil, China, Denmark and the USA, International Journal of Life Cycle Assessment 15:90-103 • Searchinger et al. (2008): Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land Use Change, Science 319: 1238–1240 • Stehfest E, Bouwman L, van Vuuren DP, den Elzen MGJ, Eickhout B, Kabat P (2009): Climate benefits of changing diet. Climatic Change 95:83–102

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