MELS builds on the Global Research Alliance DATAMAN project, which aims to improve understanding of the key variables affecting greenhouse gas emissions from livestock manure and to develop algorithms to estimate those emissions.
MELS will contribute by collating additional data on emissions from manure management and activity/ancillary data. The data will be used to generate functional relationships between emissions and activity/ancillary variables, enabling a refinement of national inventories and better assessment of the cost-effectiveness of a range of mitigation measures.
The project will assess and recommend improvements to existing farm-scale decision support systems (DSSs) in relation to greenhouse gases (GHG) emissions from livestock production systems, including grazing ruminants, by refining the calculations used to account for emissions.
A prototype farm-scale DSS will be developed for countries lacking such a tool and implemented in at least one country. This will allow the consequences of mitigation strategies on emissions and costs to be more accurately quantified and better documented, both at the national and farm scales.
Current estimates of the potential for reducing GHG emissions using existing measures are about 30% for enteric CH4 emissions and 20-30% for soil CH4 and N2O emissions. Higher emission reductions are achievable using measures applied to manure management, but depend crucially on the context under which they are implemented.
The enhancement of the DATAMAN database will provide a resource for uncertainty reduction in the generation of national inventories. At the national scale, improved emission methodologies are useful only if accompanied by appropriate and documented activity data, difficult and expensive to collect.
At the farm scale, GHG accounting can be used to support policies ranging from information campaigns, through subsidies, taxation and emission-intensity market mechanisms, to obligatory implementation of mitigation measures.
*At the time of the proposal. Please consider this data as an accurate estimate; it may vary during the project’s lifespan.
Total costs include in kind contribution by grant holders and can therefore be higher than the total requested funding.