Prof Craig Michie (University of Strathclyde), Dr Sandra Varga (University of Lincoln), Prof Michael Lengden (University of Strathclyde), Tom Gardiner (National Physical Laboratory).

Agriculture is a major source of greenhouse gases and atmospheric pollution, yet its contribution is difficult to disentangle from the pollutant mix in rural and semi-rural areas. Accurately identifying these sources is vital for designing effective mitigation strategies and supporting UK Net Zero targets. Recent advances in laser-based sensor technologies and artificial intelligence (AI) now make it possible to analyse complex, multi-gas datasets in real time—providing a timely opportunity to transform how we monitor and understand emissions.

The student will develop and deploy advanced multi-gas laser sensor systems and apply cutting-edge AI techniques to extract new insights from large, complex datasets. This will include designing and training algorithms capable of source apportionment—that is, distinguishing agricultural emissions from those of vehicles and aviation. Working across laboratory settings, field campaigns, and farm test sites, the research will integrate AI-driven data analytics with environmental metrology to ensure robust and reliable interpretation. Collaborations with the National Physical Laboratory (NPL) and Rolls-Royce will provide unique access to expertise and data from both agricultural and aviation contexts.

The student will gain hands-on experience with advanced sensors, data quality assurance, and AI methods for environmental science, alongside high-level skills in statistical modelling, machine learning, and algorithm development. They will also be trained in field deployment, project planning, and interdisciplinary collaboration. Engagement with international networks and conferences.