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Abstract
Agriculture and forestry (including land use changes) contribute approximately 30% of anthropogenic greenhouse gas (GHG) emissions globally, but have a significant mitigation potential. Several activities to reduce GHGs at a landscape scale are under development (e.g. Reducing Emissions from Deforestation and forest Degradation activities or Clean Development Mechanism projects) but these will not be effective without improvements at the basic management scale: the farm. A number of farm-level GHG calculators have been developed; to increase farmers awareness of the GHG impacts of their management practices; to aid decision-support for mitigation actions; and to enable farmers to calculate and communicate their GHG emissions, whether for their own records, as a prerequisite to supply chain certification, or as part of larger scale mechanisms. This paper compares three farm-level GHG calculators with significant potential influence. It demonstrates how the tools differ in output when using the same input data and highlights in detail what lies behind these differences. It then discusses more generally some potential implications of using different calculators and the important considerations that must be made, thus helping future tool users or developers to interpret results and better achieve consistent and comparable results.
Notes
1. See www.coolfarmtool.org.
2. The CFT includes a reported quantity of ‘background’ GHG emissions from the farm conditions specified, that is, they are a function of the climate and soil properties, deduced from the Bouwman model (Bouwman et al., Citation2002). Without available information of the models in Bonsucro, it is not possible to detect if these ‘background’ emissions are inherent within the tool across various GHG emission sources, or not.
3. Residue N content is assumed based on the crop type. Sugarcane was modelled as Millet in the CFT because there is no option for sugarcane.