Data integration model for exposure modelling (DIMEX-UK)

Led by: Gavin Shaddick, University of Exeter

Project partners: University of Exeter, University of Manchester

This project will develop a framework in which data on concentrations of air pollution can be combined with human activity and health data. The aim of the project is to develop a modelling framework to integrate ambient and indoor concentrations with human activity to estimate personal exposures to air pollution for use in future health impact analysis and other applications. The personal exposure model developed here, for the UK, will be based on a theoretical modelling framework for estimating personal exposures stochastically with full integration of the uncertainties inherent in the process. The framework will allow these uncertainties to be propagated into final estimates of personal exposures, in a form that is suitable for further integration into assessment of health effects and the effects of interventions.