The historic data from across the AgriSearch and affiliated farm platforms (BEACON FARMS, GRASSCHECK, ZERONSILE and ARCZERO) represent a wide range of actual and potential farming systems in Northern Ireland (NI) and therefore have the strong potential to offer invaluable insights into the determinants of climate impacts attributable to physical, geographical and socioeconomic characteristics of individual farms. To realise this untapped potential and establish a methodological foundation for real-time automated carbon footprinting of all NI ruminant farms, this project will develop a unified database structure and computational framework to quantify/re-quantify life cycle carbon balances and global warming potentials of all ruminant enterprises across the four platforms.
The vast majority of studies in the agricultural sustainability literature treat food commodities as homogenous goods, whereas in reality their impacts on the environment are location- and farming system-specific. Furthermore, as a farmer’s skillset and alternative land use options available to them are both diverse, the prospective economic impacts of land use transformation — and hence the likelihood of technology uptakes — also differ between individual farms. Not accounting for these heterogeneities is likely to result in unhelpful farm management recommendations and, ultimately, suboptimal interventions by the industry and policymakers alike.
Collectively, the data generated from the AgriSearch farm platforms represent a wide range of actual and potential farming systems in NI and therefore have the strong potential to offer invaluable insights into the determinants of climate impacts attributable to physical, geographical and socioeconomic characteristics of individual farms. Individually, however, each platform was conceived and evolved to address distinct research questions for different groups of audiences, and as such there is currently no streamlined data processing strategy (e.g. a standardised protocol for backfilling) to compile a cross-platform life cycle carbon inventory required to carry out such analysis.
To overcome this issue and thereby untap the previously unexplored potential of the AgriSearch farm platforms as a provider of high-value secondary data, this project will develop a unified database structure and computational framework to quantify/re-quantify life cycle carbon balances and global warming potentials of all ruminant enterprises across the four platforms. The database structure developed herein will also provide a prototype for an NI-wide ‘bottom-up’ inventory in the future, the first of its kind in the world, to be facilitated through the SOIL NUTRIENT HEALTH SCHEME (SNHS).
1. Develop an integrated life cycle greenhouse gas inventory (CO2, CH4 and N2O) to encompass all ruminant enterprises across AgriSearch farm platforms, with missing information backfilled with multiple interpolation algorithms.
2. Conduct a multi-objective sensitivity analysis to simultaneously determine the minimum set of information required to differentiate the carbon balance of NI ruminant enterprises at the farm scale and the optimal methods/degrees of backfilling.
3. Using the unified inventory thus established, quantify the carbon footprint of each enterprise under multiple functional units and multiple impact assessment methods.
4. Using the carbon footprint database thus compiled, identify physical, geographical and socioeconomic characteristics of individual farms that drive their climate performances.
5. Appraise the feasibility and accuracy of extending the proposed framework to all ruminant farms in NI, whereby detailed farm activity data are replaced by secondary information from SNHS, CEH Land Cover Map, Farm Business Survey and other sources.
Heterogeneities of farms have long been recognised, yet seldom accounted for, in the sustainability literature. This oversight has created a critically oversimplified policy and social landscapes for the ruminant sector, under which all farms are often perceived to be equally contributing to climate change. Not only is this unfair to farmers who make efforts and investments to improve their farm’s carbon balance but it is also suboptimal and thus undesirable, both economically and environmentally. Through the development of a framework to reliably quantify of farm-level carbon footprints across the NI ruminant sector, our medium- to long-term goal is to help rectify this issue and create an industry that is fairer and more rewarding for farmers and more valuable and sustainable for society.
Shorter-term, the project will provide levy payers across the AgriSearch platforms with a range of useful and thought-provoking information. This includes, amongst other examples: (i) the farm’s own carbon footprint under both standard and alternative (including nutritional value-based) functional units; (ii) multiple footprinting results based on alternative impact assessment methods and alternative time spans (including GWP*); (iii) benchmarking scores against other platform farms in NI; (iv) lay-term information on how to improve their climate performance through on-farm changes, as collated from a scenario analysis using the list of interventions recommended by the CIEL NET ZERO AND UK LIVESTOCK REPORT (2022) and developed thereafter; and (v) the cost-effectiveness table (also known as the marginal abatement cost table) to assist decision making.
The value of the project will further be enhanced through a series of industry dissemination activities, including presentations at AFBI open days, CIEL partner meetings, GrassCheck webinars, NFU/UFU events, the Balmoral Show and other opportunities. The supervisory team also has a strong track record in securing students’ appearances in popular media. Through AFBI, DAERA’s policy team and inventory team will also be kept informed.
Student Development: The successful student will join the AFBI research team, with added learning input from QUB and AgriSearch. They will receive training in a diversity of transferable skills, including, statistical analyses, scientific writing and presentation skills. There will be opportunity to present to international conferences, local farmers, breeders and industry and publish in peer reviewed journals. A study period at a centre of excellence overseas may be possible. The student will gain highly sought-after expertise and knowledge in climate change mitigation strategies.
Requirements: Any student holding/expecting a 2.1 equivalent or better degree in computer science or life sciences with a computational/modelling/data handling component or equivalent. A 2.1 primary degree plus a Master’s degree that cover the same disciplines will be equally regarded. A Master’s degree in either computational/modelling/data handling or life sciences would be an advantage.
Start Date: 1 October 2023
Duration: 4 years
How to apply: Applications must be submitted online via: https://dap.qub.ac.uk/portal/user/u_login.php