A Dynamic Spatial Microsimulation Model for Irish Agricultural Emissions

This thesis describes the development of a dynamic spatial microsimulation model for Irish agriculture and its use in providing a spatially disaggregated profile of resultant emissions. Following the establishment of a baseline spatial agricultural emissions inventory, a dynamic microsimulation model is developed and is used to simulate agricultural activity forward in time to provide an estimation of future emissions outcomes based on previous historical trends. Finally, in the context of potentially conflicting economic and environmental policies for Irish Agriculture a scenario analysis is undertaken in order to assess the potential emissions impact of achieving the expansionary targets outlined for the dairy sector in the Food Harvest 2020 programme. An adaptation of the SMILE (Simulated Model of the Irish Local Economy) quota sampling procedure involving the incorporation of a novel stocking rate ranking methodology was found to dramatically improve results for the preservation of spatial heterogeneity of stocking levels and associated agri-emissions. Results from a dynamic spatial microsimulation model based on the Teagasc National Farm Survey project a gradual decline in agricultural activity based on historical trends over a ten year simulation period with a concomitant marginal reduction in associated emissions. Results from a multi-scenario analysis in the post-quota era reveal the potential future spatial locations of new dairy farms required to enter in order to meet target. For three alternative dairy expansion scenarios, total emissions from agriculture are projected to fall by between 2-5% by 2020. Information on the potential future spatial disaggregation of emissions related activities provides an opportunity for the advanced planning and design of novel mitigation strategies at the sub-national level. This thesis offers a solution to this information deficit for Irish agriculture, the largest contributor to non-Emissions Trading Scheme emissions. It also provides a unique contribution to knowledge by establishing a framework under which economic and environmental policies for the agricultural sector can be assessed in tandem in terms of their future consequences for national emissions