Download Now! Actions to Transform Food Systems under Climate Change

Robust data on greenhouse gas emissions and emissions reductions and practical methods for monitoring, reporting and verification (MRV) are required to transition to low emissions development in agriculture. To meet these needs, CCAFS works across the CGIAR and with research and implementation partners to support better data, innovative estimation methods, quantification of uncertainty, and a shared database of emission factors representing tropical, developing countries. The refined data and methods increase confidence in emissions figures and include analysis of uncertainties.

Key research questions are: 

  • What are the potential net reductions of emissions and emission intensities from smallholder farms in priority sectors?
  • What are the most cost-effective methods of quantifying GHG emissions of smallholder food systems?
  • What are generalizable metrics for measuring progress on low-emissions agriculture and assessing trade-offs?
  • What MRV procedures are appropriate to national needs and best achieve accountability for agricultural systems?

CCAFS supports information sharing and capacity building among partner countries and global scientists through collaborative research initiatives, meetings and events and by facilitating the Standard Assessment of Agricultural Mitigation Potential and Livelihoods (SAMPLES) project. SAMPLES is a global research programme that promotes robust and comparable data on greenhouse gas emissions and livelihood indicators for smallholder farming systems through sharing measurement methods, compiling emission factors and bringing together research and findings about quantification of greenhouse gas emissions and mitigation. Visit the SAMPLES website.

Key outputs are:

  • Data and methods for quantifying emissions and mitigation in smallholder systems to support LED plans and other agricultural development initiatives. Will be appropriate to and affordable for developing countries, increase confidence, and include analysis of uncertainties. E.g., improved emission factors, activity data, models, tools, "big data" sets, platforms, MRV/accounting systems.
  • Strengthened capacity of national research organizations, young scientists, and decision-makers to quantify LED emissions and identify and prioritize technical LED options.  (50% of individuals will be women.)