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I am a PhD candidate at University College Dublin (UCD) and Teagasc Walsh Scholar in Ireland.
As a dedicated Agricultural and Environmental Economist passionate about addressing pressing issues in modern farming, I invite you to explore my research and professional journey. With a solid foundation in econometrics and statistics, my focus is on production and productivity while mitigating greenhouse gas (GHG) emissions on farms. Additionally, I am interested in various economic topics, including income, salaries, poverty, rural areas, and climate change.
Through this platform, you'll discover my research projects, publications, and conference presentations, offering insight into my expertise and contributions to the field.
Furthermore, my CV highlights my academic achievements, teaching experience, grants received, and professional work as a consultant.
Whether you're a fellow researcher, industry professional, or intrigued by the intersection of agriculture and sustainability, I trust that this website will be a valuable resource. Thank you for dropping by, and don't hesitate to reach out for collaboration opportunities or further discussion!
Additionally, you can review my profiles on Google Scholar, LinkedIn and ResearchGate.
Recent work
Estimating Nitrous Oxide (N2O) emissions from managed soils at higher spatial resolution in the Republic of Ireland (with Cathal Buckley, James Breen and Gary Lanigan)
This paper aims to define a high spatial resolution model for estimating nitrous oxide (N2O) emissions from agricultural soils in Ireland. In 2020, N2O emissions from the management of agricultural soils represented 10% of the total national agricultural Greenhouse Gas (GHG) emissions. The high spatial resolution model employed here takes account of environmental factors that influence N2O emissions at a more disaggregated spatial scale than the Intergovernmental Panel on Climate Change (IPCC) national inventory-reporting framework. Results indicate that N2O emissions are 5% lower by applying this high spatial resolution modelling approach at the farm level compared to the baseline model (Tier 2). Nevertheless, 25% of the farms in the sample analysed had an overestimation in their N2O emissions of 20%, and another 25% of the farm sample had an average underestimation in their N2O emissions by 19%, a consequence of the variation of environmental factors among farms. Using a data panel regression, results confirm that the environmental factors examined are statistically significant within the model proposed, and with a simulation, we assessed the switching of 20% of CAN fertiliser for protected urea. According to the high spatial model, this mitigation measure can reduce N2O emissions from inorganic fertilisers by up to 15%. However, the reduction is conditioned by local factors and environmental conditions.
Work in progress
Economic and Environmental Impacts of Mitigation Technologies.
Environmental variability, farm characteristics, and N2O Emissions.
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