Authors: Mike G. Whitfield, Mohamed Abdalla, Giuseppe Benanti, William Burchill, Dru Marsh, Bruce Osborne, Brendan Roth, Matthew Saunders, Pete Smith and Mike Williams
Summary: This project was concerned with improving the national inventory of GHG emissions from Irish soils. The IPCC's Tier 2 and 3 methodologies were used, effectively upscaling regional data on N2O and CO2 to the national level, through a combined process-based model and geographic information system (GIS) approach.
Agricultural soils are a major source of greenhouse gas (GHG) emissions globally, but also a potential sink of carbon through appropriate land management. In Ireland, 81% of the land is devoted to agriculture, which means that there is potential for significant mitigation of agricultural GHG emissions through land-use management and land-use change. However, current tools for assessing GHG emission savings through land-use change – Intergovernmental Panel on Climate Change (IPCC) Tier 1 and Tier 2 – are limited; Tier 3 approaches, in which process-based models are used to estimate GHG emissions for given land-use and climatic scenarios, are more flexible.
The Scaling Soil Process Modelling to National Level project was concerned with improving the national inventory of GHG emissions from Irish soils by the use of Tier 2 and 3 methodologies, effectively upscaling regional data on soil N2O and CO2 fluxes to the national level through a combined process-based model and GIS approach.
A 5km x 5km GIS map framework for Ireland has been successfully developed that will allow calculation of nationwide annual emissions of N2O and CO2 from grasslands and arable soils. This has been linked to climate, land use and soil type using the Soil Information System (SIS). Upscaling process-based model outputs using the GIS map gave combined CO2 and N2O background emissions of between 0.45 and 0.5 Mt CO2eq for grassland and 0.074 and 0.08 Mt CO2eq for arable land. These are in broad agreement with inventory values considering that the effects of fertiliser additions and management were not considered. This GIS/process-based model framework provides the first stage for a workable solution for the calculation of nationwide fluxes of N2O and CO2 from grassland and arable systems. Management/activity data linked to this framework will improve the accuracy of outputs, although we recommend a simpler empirical approach for N2O determination. A similar approach for the forestry sector would allow more inclusive simulations of GHG emissions to help inform policy and identify pressures.
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