In order to improve national GHG reporting and reduce the emissions profile of the agricultural sector, more refined emission factors and flexible inventories are urgently required. AGRI-I has adopted a twin measurement and modelling approach which will facilitate a move towards Tier 2 and Tier 3 country-specific methodologies rather than using Tier 1 default values for GHG emissions. This project will use process models, such as DNDC, Daycent and ECOSSE, to constrain data from N2O and C sequestration measurements in AGRI-I and extend the analysis to the regional/national scale using GIS and land-use databases. The aim will be to assess the efficiency of mitigation strategies across a range of representative soil types and under future climate scenarios. The information generated will be invaluable for scenario-testing and GHG and land-use policy development.
Large volumes of data from both measurement and modelling activities will be generated within AGRI-I. To allow for exchange of data between partners and correct data use and interpretation, datasets need to be standardised and quality-controlled. A dedicated database will therefore be established to archive flux, soil, metadata (climate, management/activity data) and modelling output data from AGRI-I. The data infrastructure will be based on existing international databases such as the Carbo Europe IP database and use standard methods to flag inconsistencies in the quality of the data. Future expansion of the database to include datasets from other Department of Agriculture, Food and the Marine Stimulus funded projects is envisaged. The overall project objectives are to:
- quantify and model the effect of management and climate on C sequestration and N2O emissions in Irish grassland and spring barley
- generate modelled estimates of C and N emissions at a site and regional scale which can be used as a tool for scenario-testing and policy development
- establish a database for AGRI-I measurement and modelling outputs.