This dissertation develops brain-charting methods to support precision psychiatry and neurology by measuring how an individual’s brain differs from population norms. Using normative modelling, it replaces conventional case-control averages with personalised deviation scores across age and disease progression. The research introduces warped normative models for non-Gaussian imaging data and multivariate extreme-value methods for identifying unusual patterns across brain regions. Applications to rare copy-number variants and Parkinson’s disease reveal individual differences obscured by group averages. The defence also examines longitudinal monitoring, environmental influences, resilience, ethics, stigma and clinical implementation, while emphasising that brain deviations alone cannot define pathology or determine treatment.

Microplastics and nanoplastics pose growing environmental and health concerns, yet their formation pathways remain unclear. This research compiles data from nearly 300 studies to model plastic degradation and identifies key roles of plastic type and weathering process. Lab experiments reveal mechanical wear can directly generate nanoplastics, improving risk assessment and mitigation strategies.

Sunny-day flooding is becoming common in coastal North Carolina. Sensors revealed 65 flood days per year, and water-quality tests showed fecal contamination up to 100× above closure standards. A new computer model tracks how contaminated floodwaters move, helping identify hotspots and supporting safer water-quality advisories and flood-defense planning.