An investigation into the role of aerosol emissions on the global distribution of atmospheric air pollution
Dr Lindsay Lee, Dr Carly Reddington, Prof Ken Carslaw
Particulate matter (PM) is a major component of atmospheric air pollution and inhalation of PM, specifically particles with diameters less than 2.5 m (PM2.5), is associated with adverse health effects and increased mortality. The global distribution of PM2.5 is simulated by computer models of the atmosphere, allowing investigation into regions of high PM2.5 concentrations and their contributing emission sources.
A perturbed parameter ensemble (PPE) of the UK chemistry and aerosol (UKCA) model consists of a number of model simulations designed to quantify the uncertainty in simulated global aerosol quantities with respect to aerosol emissions, lifetime and loss. The simulations provide all the necessary information to quantify the effect of these global aerosol processes on the distribution of PM2.5.
In this project, the student will use surrogate modelling and sensitivity analysis to investigate the role of aerosols emissions on the global PM2.5 distribution. The student will use readily available software and techniques developed by the supervisors along with the already available UKCA PPE model to build a surrogate model for the global aerosol simulator and carry out the required statistics.
The student will have the opportunity to choose the direction of the analysis focussing on either the choice of statistical methods used to achieve robust results or the analysis of the PM2.5 with respect to the global aerosol model emission, lifetime and loss. In either case the student will be encouraged to think about how the results can be presented to both a statistical and environmental modelling audience. To gain a wider perspective on the role of PM2.5 in human health the student will also have the opportunity to measure local PM2.5 concentrations and use existing measurements to evaluate the model results, as well as learn how these model results are used to calculate the effects of PM2.5 on human health. The student will gain a hands-on appreciation of how measurements are made and the difficulties associated with incorporating localised measurements into models.
This project is most likely to appeal to a mathematics or statistics student looking to understand how applied statistics are being used in the field of environmental science. They will learn how global aerosol is simulated using computer models, how ensembles are designed to allow uncertainty quantification and some programming skills. Successful completion of this project will provide the student with a good understanding of cutting edge statistics in environmental science and a good basis for pursuing a future career in environmental science.