Professor Ben Barratt is a Professor in Environmental Exposures & Public Health and Deputy Director of the Environmental Research Group.
The early part of his career focused on the establishment of co-ordinated air quality monitoring networks, including the London Air Quality Network, which became the largest urban network in Europe. He has since utilised this foundation in measurement techniques and data handling to develop analysis methods to characterise sources, trends and behaviour in urban air pollution. He specialised in the evaluation of technological or policy driven initiatives to improve air quality, including the London Congestion Charging Scheme and Low Emission Zone, the outputs of which have been used as evidence for future national and international schemes.
The aim of more recent research is to improve the resolution of environmental exposure assessments for panel, cohort and large-scale population studies. This is linked to the development of tools to allow the public to make informed choices to reduce their own exposure to indoor and outdoor air pollution. His research is often in collaboration with international multidisciplinary teams ranging from toxicology and population health through to behavioural science and policy development.
He is head of the Exposure Science Team, currently comprising five research associates, two research assistants and up to six PhD students. The overarching aim of his team’s work is to better characterise individual and population-level exposure to environmental stress, how this relates to the health of susceptible population subgroups, and methods of public health improvement. Much of the focus of the teams work is on global air quality, primarily in China and Sub-Saharan Africa.
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et al., 2024, Microplastic emissions via air and compost from an industrial composting facility in England, Environmental Pollutants and Bioavailability, Vol:36, ISSN:2639-5932
et al., 2024, Characterising sources of PM2·5 exposure for school children with asthma: a personal exposure study across six cities in sub-Saharan Africa., Lancet Child Adolesc Health, Vol:8, Pages:17-27
Barratt B, Kolozali S, 2023, Early Detection of COPD Patients’ Symptoms with Personal Environmental Sensors: A Remote Sensing Framework using Probabilistic Latent Component Analysis with Linear Dynamic Systems, Neural Computing and Applications, ISSN:0941-0643
et al., 2023, Prenatal exposure to air pollution is associated with structural changes in the neonatal brain, Environment International, Vol:174, ISSN:0160-4120