Abi Riley: ‘A Bayesian Spatio-temporal Multisource Air Pollution Exposure Model’

Biography and overview:

2^nd Year PhD Student on the MRC Centre for Environment and Health PhD Studentship in the Department of Epidemiology and Biostatistics, supervised by Dr Monica Pirani, Professor Marta Blangiardo, Dr Fred Piel, and Professor James Kirkbride (UCL). With a background in mathematics and statistics, I am particularly interested in the development of Bayesian statistical models for assessing the effects of environmental exposures on human health, more specifically, for this project, I am looking at the robust causal effects of air pollution exposure on a variety of mental health outcomes in large cohort studies. The first objective of my PhD is to develop a Bayesian spatiotemporal exposure model for PM_2.5 and NO₂ covering the UK at a 1km x 1km monthly resolution for the years 2005-2020, using ground-monitored data, satellite-derived measurements, and physical models as sources of air pollution data, and predictive covariates such as temperature, precipitation, population density, and spatial location.