Carbon Sequestration: Magnitude, Measurement, and Potential to Mitigate Climate Change

1. Carbon Sequestration: Magnitude, Measurement, and Potential to Mitigate Climate Change Ken Cassman, Director, Nebraska Center for Energy Sciences Research Shashi Verma, School of Natural Resources

4. http://www.epa.gov/methanetomarkets/docs/methanemarkets-factsheet.pdfhttp://www.epa.gov/methanetomarkets/docs/methanemarkets-factsheet.pdf

5. USA greenhouse gas emissions by economic sector, 2004 Kyoto 1990 target = 4,200 MMT CO2E

6. 0 200 400 600 800 Potential Annual Carbon Sequestration (Tg) in USA Crop, Forest, and range lands. Adapted from Metting FB, Smith JL, Amthor JS. 1998.

7. UNL Carbon Sequestration Program: Goals • Quantify the annual amounts of carbon (C) sequestered in major rainfed and irrigated agroecosystems in the north-central USA. • Improve our basic understanding of the biophysical processes that govern C exchange in these ecosystems.

8. University of Nebraska Ecological Intensification Project What is the potential for maximizing yield, carbon sequestration, greenhouse gas mitigation, and nutrient use efficiency concomitantly with progressive management that achieves high yields and high input efficiencies? N fertigation and precise N and water management, Bt hybrids, Round-up Ready soybeans, higher plant densities, no tillage

9. Annually Integrated NEE (g C m-2 y-1)

10. Carbon Sequestration Program Co-Principal Investigators Shashi B. Verma. . . . . . . . . . . . . . School of Natural Resources Kenneth G. Cassman. . . . . . . . . . . Agronomy and Horticulture Co-Investigators Timothy J. Arkebauer. . . . . . . . . . .Agronomy and Horticulture Achim Dobermann. . . . . . . . . . . . . Agronomy and Horticulture Anatoly A. Gitelson . . . . . . . . . . . School of Natural Resources Kenneth G. Hubbard . . . . . . . . . . School of Natural Resources Johannes M. Knops. . . . . . . . . . . School or Biological Sciences Gary D. Lynne. . . . . . . . . . . . . . . Agricultural Economics Madhavan Soundararajan. . . . . . . Biochemistry Andrew E. Suyker . . . . . . . . . . . . . School of Natural Resources Elizabeth A. Walter-Shea . . . . . . . School of Natural Resources Daniel T. Walters . . . . . . . . . . . . . Agronomy and Horticulture Haishun Yang. . . . . . . . . . . . . . . . Agronomy and Horticulture

11. Dryland C-S Site 3 Rainfed maize – soybean Site 1 Irrigated continuous maize Site 2 Irrigated maize – soybean Irrigated C-C Irrigated C-S Carbon Sequestration Program Field Sites

12. Research Components • Tower eddy covariance fluxes of CO2, water vapor and energy: Verma, Suyker • Monitoring and mapping soil C stocks: Dobermann, Walters • Litter decomposition: Knops • Above biomass and leaf area index: Arkebauer • Leaf gas exchange: Arkebauer • Soil surface fluxes of CO2, N2O and CH4: Arkebauer • Belowground processes: Walters • Monitoring soil water: Hubbard, Schimelfenig • Ecosystem modeling: Yang, Cassman • Remote sensing: Gitelson, Walter-Shea • Life-cycle GHG emissions analysis for both the cropping system and when crops are used for biofuel production: Walters, Cassman, Liska

13. Tower Flux Studies Close-up of Eddy Covariance Flux Sensors Landscape-level (Eddy Covariance) Measurement of CO2 and Other Fluxes Measuring Components of Solar Radiation Verma, Suyker, & the team

14. Seasonal and Interannual Variability:Net Ecosystem CO2 Exchange (NEE) Mead, Nebraska

17. Extrapolation to Regional Scales Tower CO2 Flux vs Remotely Sensed Data Maize-Soybean, Mead, Nebraska Chlorophyll Index, CIgreen = [(RNIR/Rgreen)-1], where Rgreen and RNIR are reflectances in TM Landsat bands 2 (520-600 nm) and 4 (760-900 nm), respectively. (Gitelson et al., 2005)

18. GPP distribution retrieved from Landsat ETM+ imagery 1 2 3 1- Irrigated Continuous maize 2- Irrigated Maize-Soybean Rotation 3- Dryland Maize-Soybean Rotation

19. Scaling Process Leaf/plot level Landscape level Regional Remote Sensing Studies: Gitelson et al.; Walter-Shea et al.

20. Biomass and Leaf Area Index Arkebauer et al.

21. Leaf Gas Exchange Arkebauer et al.

22. Soil Surface Fluxes Arkebauer et al.

23. Below Ground Processes Walters et al.

24. Monitoring Soil Water Hubbard, Schimelfenig & the team

25. Litter Decomposition Knops et al.

26. Mapping Soil Carbon Stocks Dobermann et al.

27. Site 1: Irrigated Continuous Maize Fuzzy soil classes, intensive measurement zones for scaling to the whole field

28. Initial soil C profiles at CSP site 3, 2001 Rainfed site: soil cores representative of the six soil types within the 150 acre production field.

29. Average annual change in soil carbon stocks in a four-year period that included two complete rotation cycles for the corn-soybean rotation treatments: based on eddy tower CO2 flux measurements or direct measurement of changes in soil carbon content. BOTTOM LINE: no detectable C sequestration! ¶Negative value indicates net loss of soil C.

30. Modified Century Soil Carbon Model: overpredicts C sequestration potential of our CSP sites; we find no net sequestration, i.e. C neutral

31. What are reasons for over-predition of soil C sequestration? • Ecosystem C models calibrated to long-term field experiments that: • Only evaluated soil C changes in upper foot of soil; ignored full active root zone profile • Did not account for the decrease in soil bulk density that occurs when soil organic matter content increases • While soil C turnover model components were mechanistic, crop productivity components were empirical and not robust • Points to critical role of detailed measurements to validate ecosystem models, especially those used to inform lawmakers and guide policy

32. Expansion of USA Maize-Ethanol Production 42% 34% Percentage of projected USA maize production, assuming 34 Mha area harvested and trend- line yield increase 20%

33. Greenhouse Gas Mitigation and Net Energy Yield of USA Maize-Ethanol • While there are many life-cycle analysis (LCA) studies of maize-ethanol systems • Includes crop production, ethanol conversion, co-product processing and utilization • Results vary depending on selection of system boundaries, energy content of crop inputs, crop yields and input levels, energy use in ethanol plant

34. Backward-looking vs forward-looking LIFE-CYCLE ANALYSES • Previous studies use aggregate data from the recent past • But efficiencies of maize production and ethanol conversion are continually improving • More relevant question: what is the energy efficiency and greenhouse gas mitigation potential of current and future maize-ethanol systems?

35. Biofuel Energy Systems Simulator (BESS) • Recently released life-cycle assessment software available at: www.bess.unl.edu • Uses updated input values for maize yields and production practices, energy requirements for ethanol fermentation-distillation, and co-product processing and utilization • Estimates much higher net energy efficiency and greenhouse gas mitigation potential than previous estimates

37. BESS LCA Analysis: GHG Emissions Reduction (%, Mt CO2eq*) -----Corn Production System----- Based on a 378 ML/yr maize-ethanol plant: from www.bess.unl.edu

38. Bottom line: Energy Efficiency and GHG Mitigation Current state-of-the-art USA maize ethanol systems • Large net energy yield, 30-75% net energy surplus, 25-90% GHG reduction when corn-ethanol replaces gasoline

39. NPPD Generation CO2 Projections Potential C-credits from 1 billion gallons of NE ethanol production (BESS software estimate:www.bess.unl.edu)

40. Annually Integrated NEE (g C m-2 y-1)

42. Contribution of other biomes to GHG emissions or mitigation, and impact on water quality? • CRP land and parks • Prairie grass biofuel systems • Nutrient storage and fluxes • Biological diversity