Framework for rapid country-level analysis of AFOLU mitigation options

Abstract

Mitigation in the agricultural sector is critical to meeting the 2 ̊C target set by the Paris Agreement. Recent analysis indicates that land-based mitigation can potentially contribute about 30% of the reduction is needed to reach the 2030 target. However, action to reduce emissions from the agricultural sector has lagged behind other sectors. Action and investment in agriculture have been constrained by a lack of policy-relevant and science-based methods estimating GHG emissions and mitigation potential that contribute to decision making. In this paper, we present a framework for a rapid country-level scientific assessment of emissions and mitigation potential from the agricultural, forestry and other land-use (AFOLU) sector. The framework sets targets for AFOLU mitigation based on local agro- environmental conditions, mitigation options best fitted for those conditions and stakeholder input. It relies on the use of simple models or tools to estimate emissions at the farm gate using a mix of Tier 1, Tier 2 and simple Tier 3 methods under baseline, business-as-usual (BAU) and mitigation scenarios. The mitigation potential of low-emissions agriculture options is determined relative to a baseline or BAU scenario. The framework also enables examining the likely level of implementation of low-emission options. This includes assessing the cost and additional benefits of applying the identified low- emission options across different jurisdictions of interest. The feasibility of these options, assessment of institutional capacity for scaling and identification of barriers and risks of adoption to identify priorities are also determined. This information is used by stakeholders and experts to develop a road map for implementation. Rapid assessment of national mitigation potentials can help countries to assess their Nationally Determined Contributions’ (NDC) targets and prioritize mitigation options for achieving the targets and monitor progress towards their achievement. Spatially explicit information helps countries plan implementation at subnational levels