1. Lydia Olander and Alison Eagle, Nicholas Institute, Duke University M-AGG Workshop, Carbon Markets and Agriculture June 17, 2010 – Washington, DC

2. “Agricultural land management practices in the United States have the technical potential to contribute about 230 Mt CO 2 e/yr of GHG mitigation by 2030 “ -Smith et al., 2008

3.  …voluntary GHG market  …cap & trade legislation  …incentive program to mitigate GHGs  …corporate-driven supply chain requirements  …low carbon biofuels  All require technical and background scientific information to ensure environmental progress is achieved and farmers are fairly compensated  Information needs are context-specific

4. Lay the scientific and analytical foundation necessary for building a suite of methodologies for high-quality greenhouse gas (GHG) mitigation for the agricultural sector Identify agricultural practices that reduce GHGs Assess biophysical potential, economic, technical and social feasibility Evaluate approaches for implementing mitigation policy or program (measurement, verification, additionality, baseline, etc.)

5.  Advisory board and Science advisors  researchers, government agencies, agriculture & agri- business, NGOs  Many years of experience in carbon & other GHGs  Broader network  Email list and website  Information gathering meeting, Nov ’09, Expert meeting Apr ‘10  Frequent interaction with protocol developers, policy makers and others working in this space  Open review process and outreach meetings  C-AGG/M-AGG (policy; market mechanisms)

6.  Review of agricultural GHG mitigation opportunities in the U.S.  Side-by-side assessment of biophysical and economic potential; barriers and co-effects  Produce technical reports with executive summaries for stakeholders and decision makers (Synthesis, Carbon, N 2 O)  Outreach and engagement  Similar process for international opportunities Gather expert and user input

7. Cropland Management.Grazing Land ManagementLand Use Change Conservation till and no-tillImproved grazing land managementCropland  grazing land Fallow managementChange species compositionCropland  natural landscape Increase cropping intensityImprove fertilizer NUEAvoid draining wetlands Shift between annual cropsEnteric fermentation managementRestore degraded lands Application of organic soil amendments (incl. biochar) Fire managementConvert pasture to natural (cease grazing) Include more perennial cropsFertilization Irrigation managementAgroforestry Improve fertilizer NUE and reduce N rateIrrigation management Rice water management and cultivars Irrigation improvements Reduce chemical inputs Improved organic soil management Agroforestry Herbaceous buffers Improved manure application Drain agricultural land in humid areas

8.  Over 800 papers (mostly peer reviewed)  Soil carbon, N 2 0 and CH 4  Upstream and process emissions  Compared and enhanced with model results (Century and DayCENT)  Showing range of values  Scaled up to national using weighted averages  Separate review of co-effects, barriers…

9. Soil CN 2 O& CH 4 Emissions Upstream & Process TotalNational ---- t CO 2 e/ha/yr ------Mt CO 2 e/yr No-till, modeled (-5.61–0.43) -0.04-0.59-1.63-129.4 No-till, literature -1.15 (-2.60–0.26) 0.15 (-0.84–1.81) -0.14 (-0.18–0.07) -1.13-115.0 Note: negative means storage or emission reduction

10. Soil CN 2 O& CH 4 Emissions Upstream & Process TotalNational ---- t CO 2 e/ha/yr ------Mt CO 2 e/yr No-till, modeled (-5.61–0.43) -0.04-0.59-1.63-129.4 No-till, literature -1.15 (-2.60–0.26) 0.15 (-0.84–1.81) -0.14 (-0.18–0.07) -1.13-115.0 Reduce N fertilizer0.00 -0.46 (-1.42 – -0.14) -0.22 (-0.30 – -0.15) -0.68-86.4 Winter cover crops -1.44 (-3.06–-0.37) -0.25 (-1.05–0.00) -1.82 (-3.10–-0.55) -3.51-166.6 Eliminate summer fallow -0.82 (-2.35–0.88) 0.05 (-0.07–0.30) 0.13 (0.07–0.24) -0.64-12.6 Diversify annual crop rotations -0.59 (-3.01–1.10) -0.04 (-0.33–0.11) 0.00 -0.63-98.1 Improved rangeland management -1.01 (-4.99–0.10) -0.28 (-0.31–0.227) 0.00 -1.29-172.4 Note: negative means storage or emission reduction

11.  Quantify valid comparisons in research  Highlights where research is missing Mitigation PracticeNumber of Comparisons Regional Representation No-till200All U.S. regions, best data for Southeast, Great Plains, Corn Belt Winter Cover Crops160Only regions with sufficient growing season Reduce N fertilizer rate 277Corn Belt, Lake States, Rocky Mountains, Great Plains Change N source to slow release 14Lake States, Rocky Mountains – no data found for other regions

12.  Usually use area metrics CO2e/acre  Output metrics based on productivity and efficiency  CO2e/tons of crop produced (yield)  Positives  Encourages increasing efficiency aligning with food security  Expand ag practices that would count for mitigation programs  Internalizing the yield impacts on the broader system (good and bad leakage)  Concerns  Yield volatility adds uncertainty and complexity  Intensity approach, allows overall emissions to continue to increase  Discomfort paying for it if farmers would do it anyway if it increases yield or reduces costs http://www.nicholasinstitute.duke.edu/t-agg

13.  Land use competition & implementation costs – not all practices can achieve full biophysical potential  Responses to carbon prices – efficiency gained when least costly mitigation practice is first target  Full GHG accounting – assumes that all sources and sinks are counted in the market (somehow)

14. Carbon price $5/tCO 2 e$15/tCO 2 e$30/tCO 2 e$50/tCO 2 e Forestry, Afforestation and Bioenergy Mitigation Activities -210.42-463.2-639.76-846.11 Other Land-Based Agricultural Mitigation Activities -12.13-37.74-70.56-99.25 Example Agricultural Opportunities Reduced Fossil Fuel Use-0.39-2.15-5.37-9.34 Changing Tillage Practices-1.97-8.67-18.12-26.68 Reduced N Use-0.20-0.33-4.75-10.48 Manure Management-1.10-3.15-5.08-6.61 Source: FASOMGHG economic model Note: negative means storage or emission reduction

15. Figure 2. Representative map of FASOMGHG regions and sub-regions

16.  What emissions or sinks are counted?  Depends on the policy or market context  Measurement, additionality and baseline  Field Sampling alone (difficult)  Modeling with site data/field sampling (preferable)  Agricultural Systems/ mix of practices  Accounting for multiple practices in combination  Verification and monitoring  Practice based with variable level of detail depending on measurement choice  Leakage  Intensity metrics  Modeling/look up tables  Reversals  Understand GHG impacts, tools to evaluate risks

17.  Regulator wants to ensure there is a difference  Protect against Type I error (false positive)  Type II error (false negative) is more important to seller (farmer)  Can need 2 to 3 times more samples to have confidence (95%) that a real difference is detected # of Samples at given CV % changeCV 10%CV 15%CV 20% 1061525 5 5075 2.575150250 1200400700 0.6160025004000 Minimum # of samples needed to detect difference (95% confidence)

18. Land use history Current Practices (crop, rotation, tillage…) BGC Models Century/Daycent; DNDC; RothC; EPIC/APEX Based on empirical research Tested and updated regularly Decision support tools Range of input required Min: location, crop system, area, practice, (yield) Max: land use history, fert Baseline and Measurement Baseline from default info Change in GHG for practices that can be modeled Scale models to address variability

19.  Working with wide range of research experts and modelers to develop detailed information  Draft reports – Synthesis this summer and C and N 2 O this fall  Coordinating meetings for feedback on the reports  Initiating international assessments

20. Thank you Website and email list http://www.nicholasinstitute.duke.edu/t-agg

21.  Baker, J.S., B.A. McCarl, B.C. Murray, S.K. Rose, R.J. Alig, D.M. Adams, G. Latta, R. Beach and A. Daigneault (2010). "Net farm income and land use under a U.S. greenhouse gas cap and trade." Policy Issues, PI7 - April 2010: 1-5  Output based paper coming soon – with examples

22. May consider activity with lower GHG potential if it provides other social, economic or environmental co- benefits Net GHG/ha, total ha available, and over what time frame Costs for management shifts (opportunity costs, capital costs, …) Physical and Economic Potential – High/Med/Low? Is information (measurement and modeling) sufficient by practice, crop, and geography? Does directional certainty exist for net GHGs? Scientific Certainty – High/Med/Low? Yield decline (affects production elsewhere and economic impact) Economic cost – break-even price too high? Technical barriers – monitoring, adoption, or production barriers Social barriers or negative community or farmer impacts Negative ecological impact Life cycle analysis – significant negative upstream or downstream GHGs Possible Barriers – Addressable? Measurement, monitoring and verification – Are there good methods for measuring or modeling GHG outcomes on a project scale? and for verifying projects? Additionality – Can it be assessed sufficiently? Baseline – Are there viable approaches for setting baseline? Sufficient data? Leakage risk – Is there leakage risk (life cycle analysis)? Can it be accounted for? Reversal risk – Can risk be estimated? Can it be accounted for? Is it too high? Implementation & Accounting Barriers – Addressable? Significant Co- benefits?