Time Accounting Sub-Group

1. Time Accounting Sub-Group Jeremy Martin (Chair), Jesper Hedal Kløverpris (Co-Chair) Keith Kline Steffen Mueller Michael O’Hare, 1

2. Hertel 2010 Land Use Change Numbers, 13.52 billion gallons corn ethanol production Results Based on Hertel 2010 for illustration purposes only 2

3. Emissions Factors, Woods Hole Derived Results Based on Hertel 2010 for illustration purposes only 3

4. Emissions = Land Use Change * Emissions Factors Results Based on Hertel 2010 for illustration purposes only 4

5. Total Emissions from Biofuels Program Note: Foregone Sequestration is an annual value Results Based on Hertel 2010 for illustration purposes only 5

6. Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) Included in GREET 1.8d as supplemental spreadsheet Current land use datasets include GTAP 2010 runs (“Appendix C1-C3”) Per working group/CARB requests modified with Hertel 2010 land use and emissions factor data 6

7. Time Horizons For direct emissions (measured by their GWP100), the accounting period runs from the time of emission and 100 years ahead (rolling time horizon) 7

8. Annualized Method Simply averages of emissions over production years Land Use after Biofuels Production Reversion to Native State – Carbon Recovery Other Harvested Corn Products - HCP (bioplastics, food, etc.) Discounting: Social Discount Rate (SDR): Reflects a society’s relative valuation of today’s well-being versus well-being in the future. Assigning an SDR to carbon emissions is a proxy but it would generally recognize that early emissions get more weight than later emissions Social Cost of Carbon (SCC): Offsetting to the SDR is the SCC, which may include an increasing cost of carbon as damages get more severe over time Effective Discount Rate: The effective discount rate is a combination of both and it can be positive or negative (for example, if the SDR is 2% and the SCC is 1% a year, the effective discount rate is: 2%-1%=1%) 8

9. Results Results Based on Hertel 2010 for illustration purposes only 9

10. Basic Assumptions (from Hertel et al. for illustration, not debate) 777 g CO2e/MJ Fuel production, + 0.8 g/MJ per year foregone sequestration Assume 30 years production, 70 years regrowth of 35% of original above+below ground carbon Results Based on Hertel 2010 for illustration purposes only 10

11. Basic Assumptions (from Hertel et al. for illustration, not debate) 777 g CO2e/MJ Fuel production, + 0.8 g/MJ per year foregone sequestration Assume 30 years production, 70 years regrowth of 35% of original above+below ground carbon • Highly simplified forecast based on static GTAP results. • More dynamic trajectories also possible • e.g., changes in direct carbon emissions for all fuels, Carbon flows to and from plants and soil, etc. Results Based on Hertel 2010 for illustration purposes only 11

12. Simple Amortization (Current CARB and EPA practice) Simply averaging over 30 years ILUC = 27 g/MJ Averaging over 100 years, including regrowth, ILUC = 18 g/MJ Results Based on Hertel 2010 for illustration purposes only 12

13. Carbon in Atmosphere(from ILUC, no direct emissions) Carbon releases during land use change accumulate as below ground carbon is released into the atmosphere and then gradually abates (following Bern model) Results Based on Hertel 2010 for illustration purposes only 13

14. How to convert CO2 to Carbon Intensity Many methods possible Fuel Warming Potential Compare ethanol scenario to gasoline scenario Baseline Time Accounting using GWP Compare temporal shift in land use emissions to the warming effect of 1 unit CO2 Time Shift Discounting Score 1 year time shift using explicit measure of time preference (discounting) 14

15. Global Warming Potential GWP is the ratio of Cumulative Radiative Forcing (CRF), which is essentially the cumulative amount of warming the earth has experienced in the analytical timeframe 15

16. By analogy, Fuel Warming Potential Ratio of warming from biofuels policy case (b)to reference gasoline case (g) is the cumulative radiative forcing, or the amount of warming the earth has sustained during the analytical timeframe 16

17. CO2 in Atmosphere for Ethanol and Gasoline Case Results Based on Hertel 2010 for illustration purposes only

18. CO2 in Atmosphere for Ethanol and Gasoline Case Ratio of CO2 concentration at any time in the future Results Based on Hertel 2010 for illustration purposes only

19. CO2 in Atmosphere for Ethanol and Gasoline Case Ratio of CO2 concentration at any time in the future Ratio of Cumulative Radiative Forcing Results Based on Hertel 2010 for illustration purposes only

20. Fuel Warming Potential (comparing ethanol to gasoline baseline) 30 years FWP = 1.1 CI = 106 g/MJ ILUC = 46 g/MJ 100 years FWP = 0.9 CI = 86 g/MJ ILUC = 26 g/MJ Results Based on Hertel 2010 for illustration purposes only

21. Baseline time accounting • Baseline trend in agricultural area • Developing world: Increasing • Developed world: Decreasing • ILUC from one year of biofuels production will cause a temporal shift in land use emissions, which can take two forms: • Accelerated expansion in the developing world:Above- and below-ground carbon emissions happening sooner than in the baseline • Delayed reversion in the developed world: Carbon sequestration being postponed

22. Accelerated expansion Baseline Biofuels scenario (2 y prod.) Year 2 Year 1 Human land use Human land use Land for biofuel Land for biofuel Delayed reversion Year 3 Baseline Biofuels scenario (2 y prod.) Human land use Human land use Year 1 Year 0 Year 2 Year 3 The figures on this slides are for illustrative purposes only and do not indicate any sizes or proportions of indirect land use change

23. Baseline Time Accounting and GWP • Direct emissions measured by their GWP100 • Same approach used for indirect emissions • GWP100 = ΔCRF(100 y) / CRF(CO2) (100 y) • CRF: Cumulative radiative forcing • Graphicalexplanationonnext slide (acceleratedexpansion)

24. Accelerated expansion and GWP Illustration (not to scale) of CRF from accelerated expansion and baseline emissions

25. Accelerated expansion and GWP B A Illustration (not to scale) of CRF from accelerated expansion and baseline emissions ΔCRF(100 y) = A – B

26. Accelerated expansion and GWP B A C 101 Illustration (not to scale) of CRF from accelerated expansion and baseline emissions ΔCRF(100 y) = A – B = C Same principle for delayed reversion

27. Developing world*: Accelerated expansion • Net change in cropland area: 1.2 MHa (32%) • Above- and below-ground C: 110 g CO2e/MJ • Emissions profiles: • Contribution to ILUC factor: 0.8 g CO2e/MJ (GWP100) Results Based on Hertel 2010 for illustration purposes only * Loosely defined as Africa, Asia, and Latin America

28. Developed world*: Delayed reversion • Net increase in cropland (ILUC): 2.6 MHa (68%) • Assumption: Reverting land will re-sequester the carbon that was originally lost upon conversion within 100 years.→ Average annual C sequestration: 3.9 t CO2e/Ha** • Emissions profiles: • Contribution to ILUC factor: 10.1 g CO2e/MJ(GWP100) * Loosely defined as Europe, North America, and Oceania ** Average for grassland and forest Results Based on Hertel 2010 for illustration purposes only

29. ILUC factor (Baseline Time Accounting) • Developing world (acc. exp.): 0.8 g CO2e/MJ • Developed world (del. rev.): 10.1 g CO2e/MJ • Total (GWP100): 10.9 g CO2e/MJ • GWP20: (4.6 + 10.1) g CO2e/MJ = 14.0 g CO2e/MJ • GWP30: (3.0 + 10.1) g CO2e/MJ = 12.3 g CO2e/MJ NB: Average C seq. rate assumed to be the same for the 20 and 30 y accounting period as in the 100 y period Results Based on Hertel 2010 for illustration purposes only All results are preliminary

30. Conclusions (Baseline time accounting) Baseline time accounting • is independent of production period assumptions • takes global land use dynamics into account • relies on annual expansion/reversion rates and results must therefore be updated regularly (as many other carbon intensities, e.g. that of gasoline) Full description of methodology to be submitted to peer-reviewed journal shortly

31. Simplified time accounting for ILUC Michael O’Hare University of California, Berkeley October 2010

32. Variables • Gv = “direct” – variable emissions from one MJ production • Gc = Gcd – Gcs = ILUC – capital investment emissions for one MJ production capacity Gcd = ILUC discharge from conversion to crops Gcs = annual ILUC sequestration on land converted from crops ≈ 0.1% of Gcd EWG X-10 O'Hare 32

33. Challenge • Amortizing Gc into a variable cost • requires knowing production period • Ignores atmospheric persistence & cumulative warming • Should include a discount rate • combine Gv and Gc with minimal assumptions to generate a per-MJ GHG intensity EWG X-10 O'Hare 33

34. EWG X-10 O'Hare 34

35. ILUC accelerates conversion, delays sequestration EWG X-10 O'Hare 35

36. Implication of K-M model Using our example values, Example: US corn ethanol, Hertel et al Gtotal = 60 + (776 x .05/1.05) = 97 A single year of biofuel production, if cropland is overall increasing for other reasons, displaces + ILUC that would occur anyway to one year earlier, -ILUC to one year later. EWG X-10 O'Hare 36

37. Note that: All discharges in this model occur within a year of each other, so residence time, analytic horizon, etc. don’t matter There is no avoiding a discount rate, for any action with a time delay component EWG X-10 O'Hare 37

38. Comparison of Results Results Based on Hertel 2010 for illustration purposes only 38

39. Consensus Findings & Recommendations • The production period is an especially uncertain parameter and time accounting methodologies that can ignore it are attractive • Any time accounting methodology is only as good as the modeling results that go into it. • Choice of discount rate in a regulation is a policy choice that combines value judgments and inferences with technical factors • It is possible to consider the impact of a biofuels policy as a temporal shift of the complex dynamics which drive land use change and vary widely at local scales: • In regions with an expanding agricultural area (typical for the developing world) , ILUC could cause land to come into production sooner than it otherwise would. • In regions with a contracting agricultural area (typical for the developed world) , ILUC could cause land to stay in production longer than it otherwise would. • The timing of emissions are important and, as a general goal, policy should differentiate based on timing where possible

40. Individual Sub-Group Member Input

41. O’Hare - What we have learned It is analytically unacceptable to treat a unit discharge as having the same effect, cost, or importance no matter when it occurrs Fuels with different time profiles of discharge must be scored recognizing time effects More robust (fewer assumptions) models of the effect of time are better, OTBE There is no escape from discounting!

42. Kline Comments/Conclusions Time matters: • Choice of temporal scale influences all aspects of analysis • Initial conversion is often determined by factors set in motion decades before change is detected • Understanding how biofuel policy interacts with LUC drivers over time is essential to reduce risks of unintended policy consequences • Baseline time accounting offers advantages (adaptability, simplicity) • A long-term monitoring plan is recommended to develop more accurate emission profiles for land use and LUC over time Assess empirical evidence: • ILUC from biofuel policy can cause temporal shifts in baseline land emission dynamics: • Expansion in “developing world” can be delayed as LUC – driven by under-valued land, poverty, legal non-compliance and use of fire – is mitigated by markets, employment, increased environmental compliance and incentives to better manage previously cleared lands • Delayed reversion in developed nations maintains productive ecosystem services and postpones emissions from conversion to “developed” uses (chart) • Same time accounting questions apply

43. Kline Comments/Conclusions • Recommendations: • Apply scientific approaches to assess policy impacts • Conduct iterative analyses, use best available data, improve baselines and projections • Plan to review data (and adjust policy) over manageable time horizons • Consider LUC theory and land transition models based upon empirical evidence • Policy goals over time should aim to improve land management and accelerate forest recovery • Improved approaches to account for emissions over time should be measurable and verifiable • Don’t let “scoring” and time accounting distract from policy goals: reduce actual emissions, today and tomorrow FIRE is a low-cost, common, tool to maintain previously cleared, under-utilized lands. Between 330 and 430 million hectares burned each year, 1997 to 2008 (Giglio et al. 2010)

44. Kløverpris Recommendations 1. Make sure the ILUC factor is consistent with the metric for direct emissions, i.e. the GWP100 (you cannot add apples and pears) 2. Use baseline time accounting to avoid the production period assumption required by the annualization and the FWP method 3. Obtain better understanding of long-term C seq. 4. Update the ILUC factor on a regular basis to consider changes in global land use dynamics

45. Kløverpris Recommendations (cont.) 5. If CARB does not adopt baseline time accounting, acknowledge that crop yields, gasoline CI, and efficiency in biofuels production are not constant over the next 30 years (data issue) Kløverpris Comments Re. reversion: Two options after biofuels production 1. Land can go into another use (Baseline TA) 2. Land can revert Assuming neither 1 nor 2 is inconsistent with reality Sustainable development is …development that meets the needs of the present without compromising the ability of future generations to meet their own needs 45

46. J. Martin - What have we learned…. Much of our work revisited earlier CARB and EPA reviews No breakthroughs, the hard parts remain: (1) predicting the future (the inputs to time accounting) (2) scoring the future (choice of timeframe and/or discount rate) Time Shift Accounting • Not yet reviewed in detail by the sub-group or anyone else • Converts a prediction problem into a time shift problem • How to score time preference is the central point • Low ILUC scores rest largely on using GWP100 as the sole measure of time preference (equivalent to r = 0.76%) The use of GWP100 to compare simultaneous emissions of methane and carbon dioxide does not imply that a discount rate of 0.76% is “scientific,” consistent, or otherwise appropriate • Other important details also need work • Treatment of foregone sequestration from delayed reversion • Accelerating deforestation and delaying reversion are likely to have important secondary impacts beyond those considered

47. J. Martin’s Conclusions • Don’t lose the forest for the trees: amortization periods, “payback times,” or time shift accounting are different justifications for the same decision • 20-30 year amortization period ~ 3-5% discount rate • Appropriate discount rates from cost benefit analysis would be 5-7% • 15-20 years would be more appropriate timeframe than 30 • Current 30 year timeframe is too long, independent of forecast duration of corn ethanol production or lifetime of a facility • Fundamentally Kløverpris and Mueller are proposing an effective timeframe of >100 years or discount rates <1%. • Tropical deforestation would not factor significantly in lifecycle carbon intensity • Time Shift accounting may eventually provide useful insights. But first the methodology requires more work, sensitivity analysis, peer review, and must include a credible representation of time preference/discounting • Common sense: does accounting methodology support policy goals? • Land use is a fundamental constraint on the expansion of biofuels • Accounting treatment of land use change should send a clear market signal that rewards the efficient use of land

48. Time 20 Year Corn Harvests to Bioplastics/Food 30 Year Corn Harvests to Biofuels 50 Analytical Horizon S. Mueller - Time Accounting General Notes • Choosing a Biofuels Production Period is subjective – Many scenarios are equally logical including: -- Harvested Corn Products Scenario: • For example assumes biofuels produced for 30 years followed by 20 years of additional corn production (in line with Bruinsma 2009 and Fischer 2009). • Sum up corn harvests over 50 years, allocate 3/5 of the upfront emissions to biofuels and 2/5 to bioplastics/food production • Effect: Indirect Land Use Factor drops from 26.6 g/MJ to 16 g/MJ • Biorefinery Useful Life May be a Measure but it is at least 30 years • Dry grind plants built in early 80s are still around and have been retrofitted to match energy efficiency of current plants (Mueller, Biotechnology Letters, May 2010). • Baseline Time Accounting • Allows assessment independent of Production Period • Takes actual global land use into account • More Complex but only method that reduces Subjectivity

49. S. Mueller - Discount Rate • Applying discount rates to biofuels produces anomalies • 7% as proposed by OMB would implicitly mean that we assume that: • Gasoline has current emissions of 95gCO2/MJ but only 13.35 gCO2/MJ at the end of 30 years • Biofuels do not get this large discounting benefits because all emissions occur upfront (less effect of compounded discounting)