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Cities, soil and sustainability: Integrating soil microbiomes, AI and life cycle assessment for climate-resilient urban green infrastructure
Secondary Supervisor(s): Professor Helen Onyeaka
University of Registration: University of Birmingham
BBSRC Research Themes:
Project Outline
Cities contribute to 80% of gross domestic product, and house 55% of the global population projected to reach 68% by 2050. Using Birmingham as a case study, this research will explore how soil microbial community impact nutrient cycling, carbon sequestration, and crop productivity. Resilient urban agro-ecosystems and functional green spaces are crucial nature-based solutions for urban cooling and sustainable food supply, to advance sustainable agriculture and net zero transitions.
The main aim is to investigate the biological mechanisms underpinning urban soil functionality and embed bioscience data into life cycle assessment (LCA) models for place-based climate adaptation in Birmingham. The objectives are: (1) Assess urban soil properties and microbiome functionality to determine biological suitability and resilience for urban agriculture and food security; (2) Conduct cradle-to-grave LCA of diverse green infrastructure typologies to quantify environmental impacts; and (3) Develop spatial 'what-if' scenarios integrating remote sensing data with LCA outputs to evaluate variations in heat island mitigation and carbon dynamics.
This interdisciplinary methodology combines soil bioscience, environmental systems, and spatial data analysis. Urban soils will undergo physicochemical profiling (carbon %, organic matter %, pH, texture) and biological analysis (microbial biomass carbon, extracellular enzyme activity, community profiling) to identify indicators of yield stability and nutrient-use efficiency. Attributable biological emission and sequestration fluxes will be embedded into LCA models to refine biological inventories. Spatial information will be used from remote sensing data using computer vision algorithms. Trade-offs between food production and urban heat island mitigation will be assessed by machine learning/AI models across varying spatiotemporal scales.
This PhD is supervised by Dr Neha Mehta, Prof Helen Onyeaka, Dr Jiarui Zhou at the University of Birmingham.