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Alison Eagle and Lydia Olander, Nicholas Institute, Duke University M-AGG Workshop, Carbon Markets and Agriculture June 10, 2010 – Davis, CA. The intersection of science, policy, and markets .

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Alison Eagle and Lydia Olander, Nicholas Institute, Duke University

M-AGG Workshop, Carbon Markets and Agriculture

June 10, 2010 – Davis, CA

The intersection of science, policy, and markets

“Agricultural land management practices in the United States have the technical potential to contribute about 230 Mt  CO2e/yr of GHG mitigation by 2030 “

-Smith et al., 2008

…private or 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

What if.....?

Lay the scientific and analytical foundation necessary for building a suite of methodologies for high-quality greenhouse gas (GHG) mitigation for the agricultural sector

T-AGG Purpose

  • 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)

Collaborative and transparent

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, N2O)

Outreach and engagement

Similar process for international opportunities

T-AGG Process

Gather expert and user input

Mitigation Activities Considered

Over 800 papers (mostly peer reviewed)

Soil carbon, N20 and CH4

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…

Methods: literature

Biophysical GHG Mitigation Potential

Note: negative means storage or emission reduction

Biophysical GHG Mitigation Potential

Note: negative means storage or emission reduction

Quantify valid comparisons in research

Highlights where research is missing

Methods: Data Availability and gaps

  • Usually use area metrics CO2e/acre

  • Intensity metrics based on productivity/output

    • 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

    • Intensity approach, allows overall emissions to continue to increase

    • Positive(good) leakage is an imperfect approach adding uncertainty regarding overall environmental impact

    • Financial additionality? Would farmers do it anyway if it increases yield?

    • Yield volatility adds uncertainty to crediting

Intensity Based metrics

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)

Modeling for economic response

Net GHG Mitigation by Source (Mt CO2e)

Source: FASOMGHG economic model

Note: negative means storage or emission reduction

Regional Variation: For C and N2O

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

  • 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

Implementation and Accounting

  • Buyer 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

Sampling and measurement

Minimum # of samples needed to detect difference (95% confidence)

Biogeochemical models

Current Practices (crop, rotation, tillage…)

Scale models to address variability

Land use history

  • Working with wide range of research experts and modelers to develop detailed information

  • Draft reports – Synthesis this summer and C and N2O this fall

  • Coordinating meetings for feedback on the reports

  • Initiating international assessments

Next Steps

Thank you

Website and email list

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

Relevant references

Significant Co-benefits?

May consider activity with lower GHG potential if it provides other social, economic or environmental co-benefits

Number of samples needed to detect SOC change, 0-30 cm depth [7–14 g carbon/kg, 1.4 g/cm3 (~140 t C/ha)]

VandenBygaart, A.J., E.G. Gregorich, D.A. Angers and B.G. McConkey (2007). "Assessment of the lateral and vertical variability of soil organic carbon." Canadian Journal of Soil Science 87(4): 433–44.

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