1. 15 July 2010 Baseline time accounting CARB expert workgroup meeting Time accounting subgroup – Interim report Jesper Hedal Kløverpris, PhD – Novozymes Steffen Mueller, PhD – University of Illinois

2. 2 The four main steps Determine - 1.…amount of land affected (in relation to baseline) 2.…types of land affected (grassland, forest etc.) 3.…carbon stocks/sequestration of land affected 4.…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. Estimating GHG emissions from ILUC

3. Current time accounting approach 3 ILUC contribution based on 30 year production period: 30 g CO 2 e/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 4 Source: Bruinsma (2009), Fig. 6 Developing world: Arable land use mainly increasing Developed world: Arable land use mainly decreasing Arable land and land under permanent crops (only food and feed)

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

6. Delayed reversion 6 Baseline Human land use Biofuels scenario (1 y prod.) Human land use Land for biofuel Year 1 Year 2 Year 0 BaselineBiofuels 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 ILUC taking place in a region where land use is ‘contracting’ (baseline) Human land use Land for biofuel Year 1 Year 2 Year 0

7. 7 Cumulative GHG emissions (g CO 2 e) Time (y) Baseline implications for time accounting Baseline One year ILUC: Accelerated expansion ILUC: Delayed reversion Regional baseline: Expansion of land use Regional baseline: Contraction of land use Direct (avoided) fossil emissions Direct ethanol emissions No GHG decay assumed above – graphs for illustrative purposes only and not meant to indicate proportions of GHG emissions Areas indicated equivalent to ton·years of carbon TATA Analytical time horizon Saved Induced

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 8 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) 9 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 10

11. Converting ‘accelerated expansion’ and ‘delayed reversion’ into a GWP(100) 11 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 CO 2 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 ”30 year method” Baseline time accounting BTIME numbers 1 30 g CO 2 e/MJ10 g CO 2 e/MJ Searchinger et al. (2008) 2 104 g CO 2 e/MJ23 g CO 2 e/MJ 12 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 13

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) 14 Thank you

15. 15 Extra slides and references

16. Graphs for discussion 16 Baseline Biofuels Acc. exp.: Accelerated expansion Del. rev.: Delayed reversion Legend Acc. exp.Del. rev. Ha Time Acc. exp. Del. rev. Additional expansion Ha Time Del. rev.Acc. exp. Ha Additional expansion 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 17 Delayed reversion! Delayed reversion

18. Land quality (Kløverpris et al. 2010) 18

19. 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 CO 2, CH 4, and N 2 O 20 20 years100 years500 years CO 2 111 CH 4 72258 N2ON2O289298153 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 21