Dr Duncan Lee and Prof Marian Scott have won a NERC CASE PhD studentship (with SEPA) on “High resolution air quality modelling and prediction”. The details are as follows:

The impact of air pollution on human health and on the environment is well recognised.  In the UK, health impacts of poor air quality have been calculated to cost between £9 and £19 billion per year, with transport contributing around half of this total. Statistical models play an important role in describing, explaining and predicting local and regional air quality and ultimately contribute to better air quality management by local councils.  Statistical models are required to provide accurate spatio-temporal predictions of air pollution concentrations at small spatial scales, and to also integrate the routine but sparse monitoring undertaken within our cities and the increasingly detailed physico-chemical models being developed.

Low Emission Zones (LEZs) are regarded by many councils as a potentially effective management measure that could help to improve local air quality but they need to be supported by statistical modelling and data analysis.  Assessment of measures to improve air quality often requires a detailed modelling study and while there are many different air quality modelling tools, one of the key challenges concerns the integration of models with differing spatial and temporal resolution and routine monitoring data.

The objectives of this research proposal are to:

  • develop and apply a suite of functional data analysis tools for air quality modelling;
  • develop and apply functional data models and tools to calibrate and ground-truth air pollution models;
  • develop visualisation tools for the model and data outputs.

Congratulations Marian and Duncan!

First published: 22 January 2016

<< February 16