Preliminary Considerations for Carbon Emission Factors in LCFS Indirect Land Use Change Analysis

1. LCFS Indirect Land Use Change Expert WorkgroupCarbon Emission Factors Subworkgroup Presentation to California Air Resources BoardSacramento, CAOctober 14, 2010

2. Objective • Provide a summary of our preliminary considerations of most recent GTAP analysis (Tyner et al. 2010) and the appropriateness of the assumption/changes • Biomass and soil carbon stock • Biomass and soil carbon EF • assumption of 25 percent of forest biomass is indefinitely sequestered in wood products CARB ILUC EWG Emission Factors

3. Our Preliminary Considerations and Suggestions #1. Evaluate the spatially-explicit Winrock database as a basis for estimating biomass C stock by AEZ #2. Supplement with databases to improve the accuracy of certain regions/eco-system types (such as peatlands), or to include the consideration of certain factors (e.g. forest degradation and fire) #3. Provide clear justification for the consideration of C stored in harvested wood product (HWP) CARB ILUC EWG Emission Factors

4. Our Preliminary Considerations and Suggestions -Cont’d #4. Provide clear justification for the consideration of other non-land conversion emissions • Livestock emissions • Rice production emissions • Crop switching • Differences in on-farm energy and agrichemical use #5. Conduct sensitivity analysis on the effects of non-Kyoto climate forcing gases and particles #6. Perform uncertainty analysis, including uncertainty propagation and uncertainty importance analysis CARB ILUC EWG Emission Factors

5. #1. GTAP, Woods Hole and Winrock Regions * Winrock data is divided into countries and for some a further breakdown by administrative unit. The quantity given is the number of regions for each given GTAP region (Note: Some values are different because the regions are not exactly the same) CARB ILUC EWG Emission Factors

6. GTAP 18 Regions + AEZs Map by Sahoko Yui, UC-Davis Use GIS data to estimate C stocks for GTAP region / AEZs CARB ILUC EWG Emission Factors

7. Winrock Biomass Database • Uses a range of geographically explicit data of varying quality • Some based on field data + GIS modeling • Others based on radar • Relies on best available

8. Alternative Approach to Forest Biomass Compiled by OSU, funded by EPA Climate Analysis Branch Data for all GTAP Regions, by AEZ, & Accessible vs. Inaccessible Land; Mix of different Inventory Source Data (FAO, USDA, others) Partially Reviewed Model and Methodology Example: 8

9. Accessible vs. Inaccessible Forest Area • Methodology dependent on region • For Europe: All Forest Area Deemed Accessible • For USA: Accessibility is a function of timber demand / timber price • For Tropics (China, Russia): Accessibility is based on proximity of forestland to roadways

10. Alternative Approach to Forest Biomass • Need to ultimately create data set by AEZ & by Accessibility • Can adopt OSU data since it is available or create new data set and compare to OSU

11. Harmonized World Soil Database (HWSD) • 0-100 cm soil C concentration can be calculated. • Last updated March 2009 though lots of missing data especially for subsoil (30-100 cm), see following slides. (t C/ha) Map by Sahoko Yui, UC-Davis

12. HWSD by AEZ (t C/ha) Map by Sahoko Yui, UC-Davis CARB ILUC EWG Emission Factors

13. HWSD Missing information topsoil (0-30 cm) subsoil (30-100 cm) CARB ILUC EWG Emission Factors

14. Forest EF

15. Pasture EF

16. Biomass & Soil C Recommendations • Use best available spatially-explicit, published datasets to provide estimates by GTAP regions and AEZ combinations • Rely on largely datasets underlying Winrock biomass analysis with improved data in a few locations • Use GIS to estimate soil C for region / AEZ using global datasets; STATSGO for U.S. • Use satellite-based land cover maps to pull out carbon estimates for grassland, forest, cropland etc • Supplement with literature values for peatlands CARB ILUC EWG Emission Factors

17. #2. Include Peatland Emissions • Peatland stores large amount of carbon stock and is a large sink for atmospheric carbon • Tropical peatland is ~11% of global peatland area and 15% of global peat carbon pool • 75% is in Southeast Asia (65% in Indonesia and 10% in Malaysia). CARB ILUC EWG Emission Factors CARB ILUC EWG Emission Factors 17

18. Tropical Peatland Emission Factors • Winrock • Peatlands cover 2-44% and 2-22% in some of the corresponding administrative regions in Indonesia and Malaysia, respectively. • Assume cumulative emissions of 600 or 1600 t C/ha for 30 or 80 yrs, respectively (EF = 20t C/ha/yr assuming 80 cm drainage depth) • Fargione et al. (2008) assumes 941 t C/ha (EF = 18.8 t C/ha/yr for 50 yrs) • Both studies noted that these assumptions lack rigor, especially the duration of emissions CARB ILUC EWG Emission Factors

19. Peatland Drainage and Carbon Emissions Schematic illustration of progressive subsidence of the peat surface in drained peatland, due to peat decomposition resulting in CO2 emission, as well as compaction. Source: Hooijer et al. (2010): CO2 emissions from drained peat in Southeast Asia CARB ILUC EWG Emission Factors

20. EF Based on Land Conversion Types Unit CO2 emission is a linear function of groundwater depth and % area drained in converted land • Greater drainage is needed for large cropland/palm plantation • Cropland/palm plantation keeps average water tables always below 0.7 m, but they are often as deep as 1.2m on average Source: Hooijer et al. (2010): CO2 emissions from drained peat in Southeast Asia CARB ILUC EWG Emission Factors

21. Peatland EF Recommendations • Use best available spatially-explicit, published literature data to provide estimates • Emission factor should be weighted by peatland (conversion) area by GTAP regions and AEZ combinations, such information should come from Land Conversion Type subgroup • To the extend possible, use EF by land use conversion type such as the table shown in the previous slide. Source: Hooijer et al. (2010): CO2 emissions from drained peat in Southeast Asia

22. Peatland Emissions from Fossil Fuel Land Use Though not directly related to biofuel land use, the topic may be relevant to Other Indirect Emissions subgroup. • Boreal peatlands store 85% of global peat, contain ~ 6 times more carbon than tropical peatlands • LU GHG emissions (t CO2e/ha) from oil sands surface mining development can be comparable or higher than biofuels, primarily due to peatland disturbance and CH4 emissions from tailings pond (see next slide) CARB ILUC EWG Emission Factors Source: Yeh et al. (2010)

23. Peatland Emissions from Fossil Fuel Land Use • Fossil fuel LU EF (t C/ha) is significantly lower than for biofuels due to higher fossil fuel yield. CARB ILUC EWG Emission Factors Source: Yeh, Jordaan, Brandt et al. (2010) ES&T, in press

24. #3. Long-term C Storage in Harvested Wood Products (HWPs) • When wood is taken out of forest systems, C is either stored in product-in-use and landfill; or emitted, combusted, or decomposed and recycle back to the atmosphere. • Fraction of C stored in HWP depends on • How much (and what type of wood) is removed from the forest system; • Types of end-use products; and • Lifetime of C remains in end-use products and landfills CARB ILUC EWG Emission Factors

25. Fraction of C Remaining in End Use by Enduse Category, US Source: U.S. Department of Energy, 2006. Guidelines for Voluntary Greenhouse Gas Reporting. Source: Mueller et al (2010) manuscript CARB ILUC EWG Emission Factors

26. #3. Long-term C Storage in HWP in the US • In the US, on average 23 percent of the aboveground biomass removed from forest stands has been sequestered after 30 years (Mueller et al.)(see previous slide) • In the US and Canada, only roughly 50% of harvested biomass is removed from forest system • Need adjustment to account for belowground biomass and the fraction left on the ground (eventually decompose and is incorporated into soil or released as CO2) • This calculation does not take into account fossil emissions displaced by wood product for energy production and by displacing energy intensive materials such as concrete and steel. • The C storage factor may be even smaller for developing countries due to lower removal and mill efficiency, faster decomposition, etc. CARB ILUC EWG Emission Factors 26

27. HWP EF Recommendations • Based on our examination, there is sufficient data to consider C storage HWP in the US and other developed countries. • However, data of global HWP disposition by country and long-term carbon storage factor by wood-type and end-product (preferably by region) is difficult to obtain. • Short-term: include sensitivity analysis of C storage in HWP (30 yrs, 50 yrs, 100 yrs) • Long-term: global calculation of HWP and include uncertainty in HWP disposition • Potential consideration of energy displacement, construction material displacement, and price effects (demand reduction). CARB ILUC EWG Emission Factors

28. #4. Summary of Emission Factors of Other Indirect Effects • There are other indirect impacts beyond changes in carbon stocks (biomass + Soil C). • Livestock emissions • Rice production emissions • Crop switching and changes in energy and chem. use • The changes can be positive or negative. • For some pathways the other emissions are significant (~25% of ILUC for soybean biodiesel). • See August subgroup presentation for details CARB ILUC EWG Emission Factors

29. Fertilizer Use and N2O Emissions • Yields (bushels/acre) of two primary crops (corn and soybeans) grown in the U.S. have increased dramatically over the past approximately 30 years for the same amount of fertilizer applied • Further studies are needed to determine whether the observed decrease in fertilizer use should be applied to reference case, or ILUC scenarios (e.g. increase yield with no changes in fertilizer use?) Source: Nelson et al.

30. Other Indirect EF Recommendations • This whole issue of fertilizer vs. yield needs to be thought through as to how much is covered in the direct emission calculation and what the incremental emissions/unit of production might be for the indirect emissions. • N2O emissions and N2 application rate have significant implications for GHG emissions. Better regional data would be useful in considering fertilizer use and N2O emissions in the reference case and ILUC scenarios. CARB ILUC EWG Emission Factors

31. #5. Non-Kyoto Climate Forcing Gases and Particles Source: Courtesy of Richard Plevin a Delmas et al. 1995; b IPCC AR4; c Brakkee et al 2008; d Bond and Sun 2005; e Sanhueza 2009

32. Savanna Burning Emission Factor 32

33. Non-Kyoto Climate Forcing Gases and Particles Recommendations • Non-Kyoto climate forcing gases and particles can contribute to large uncertainties and significantly increase the estimated impacts of biofuel LUC emissions. • The use of these Non-Kyoto gases would also require that the gasoline and diesel reference fuels would need to be re-done. • Sensitivity analysis (short-term) and uncertainty analysis (long-term) should be performed to explicitly consider the effects of non-Kyoto climate forcing gases and particles CARB ILUC EWG Emission Factors

34. Recommendations on Treatment of Uncertainty Short-term: • Incorporate range of uncertainties reported in the datasets/literature for biomass and soil C. • Use sensitivity analysis or scenario analysis to illustrate the importance of the consideration of certain parameters , such as HWP, other non-land conversion emissions, non-Kyoto climate forcing gases and particles. • Use parametric analysis to estimate effect of specific time profile to examine emissions over time or scenario analysis to consider different approaches to handling time, (e.g., simple amortization, cumulative radiative forcing, discounting). Long-term: • Include probability distributions for all estimates. • Propagate uncertainty using Monte Carlo simulation. • Use global SA to estimate uncertainty importance to identify which parameters drive overall variance. CARB ILUC EWG Emission Factors

35. Remaining Important Issues • This subgroup has not had a chance to provide a comprehensive review of the following issues: • EF related to changes in biomass C stock • Fire emissions • Forest categories (disturbed vs undisturbed, maturity, degradation, drought) • EF of soil C emissions after LU conversion • Dynamic modeling of LU emission changes (stock + flow) vs. categorical modeling (percent changes in stock) • Albedo effect • Some of these issues may be included in the final report. However, CARB should conduct independent studies to determine the effect of these issues (long-term). CARB ILUC EWG Emission Factors