PhD Studentship - Modelling and Monitoring Greenhouse Gas Emissions with Robots

PhD Studentship: Modelling and Monitoring Greenhouse Gas Emissions with Robots
Precise and representative quantification of greenhouse gas (GHG) emissions is essential for evaluating the effectiveness of mitigation strategies aimed at achieving net-zero targets. This project focuses on the accurate and representative monitoring of GHGs in farmland, water, and forest environments, which are major producers/absorbers of these gases. However, their realistic monitoring is greatly undermined by the substantial spatial and temporal variability of emissions, which conventional methods, despite their precision, fail to capture comprehensively. Current monitoring techniques use expensive techniques for acquiring precise measurements only representative of a small footprint (e.g. closed chambers, optical sensors). Eddy covariance towers have a much larger sensing footprint (roughly 200m diameter) and provide continuous measurements in time. However, these are pieces of costly capital infrastructure, requiring complex operation and maintenance, and their representativeness is
quite limited by their height and static position.
We propose the deployment of a robotic flux tower system, comprising low-cost sensor arrays tethered to a ground robot by an aerodynamic balloon. The adaptable sensing altitude of the platform will allow spatially representative measures over complex natural environments. Being tethered to a robot, the flux tower can be easily transported to sites where GHG measurements are needed. The system will allow emissions data collection in a way that is scalable and transferable to any site where GHG emissions are a concern.
By combining cutting edge sensing and robotics innovation with modern techniques in data science, the project's datasets and collection techniques will become a platform for further development of robotic environmental monitoring which can support sustainable development and will ultimately help to ensure emissions targets can be reached in the UK.
Supervisors: and

We are seeking a highly motivated candidate with degrees in a relevant engineering field (e.g., aeronautics, environmental, civil, mechanical), as well as physical sciences or applied mathematics. Candidates should have excellent communication skills and a strong inclination towards multidisciplinary research. Students holding a first-class degree (or a good 2:1) in the aforementioned disciplines and a background in aerial robotics are encouraged to apply. Previous experience with Matlab/Python and/or with experimental work would be beneficial.