Integrated technological and computational tools to capture detailed personal exposure for improved health models

A key challenge in modern epidemiology is understanding the source-related effects of air pollution on health. Large-scale studies traditionally use measurements of outdoor reference monitoring stations as metrics of exposure. However, these measurements are often poorly correlated with personal exposure levels due to varying local sources, microenvironmental settings, attenuation effects of the building envelops and individual behavioural patterns. My research expands the capabilities of low-cost sensors by developing analytical techniques to maximise extracted information: 

• A time-activity model to classify major exposure-related microenvironments using as input readily gathered parameters from smartphone technologies. to provide a comprehensive picture of environmental health risks during daily life.
• A novel source apportionment method to characterise local and regional emission sources, and review how the low-cost sensor measurements can be used as proxies for more detailed measurements.

This integrated technological and analytical framework can revolutionise the fields of indoor exposure, building science and epidemiology. Health models using improved exposure metrics indicate the strong influence of source-related exposure on health.