New approaches to the statistical analysis of air quality network data: insights from application to national and regional UK networks

Every hour, ambient concentration data for dozens of air pollutants is collected from hundreds of monitoring sites across the UK, adding to a repository consisting of more than 370 million observations going back 47 years. And yet, due to the difficulty of extracting meaningful information from this data, it is principally used for monitoring compliance with air pollution limits. This thesis aims to develop new statistical techniques and apply them to the air quality network data to derive additional insights concerning changes in air quality in the UK over the last twenty years. The rolling change method is a new way of conducting robust long term trend analysis across multiple sites within monitoring networks that are subject to biases caused by site flux. It is used to analyse the long term trends in NOx and NO2 concentration, and in NO2/NOx ratio in London, Scotland, and the UK between 2000 and 2017. At each scale, the results are consistent, showing declines in NOx and NO2 concentration, and a peak in NO2/NOx around 2010, followed by a fall. The 'meteorological normalisation' method using random forest is applied to remove the effect of meteorology from air pollutant concentrations at London sites to enable clearer visualisation of the trend due to changes in emissions. The method is also used to evaluate the efficacy of the London Low Emission Zone through the generation of counterfactual scenarios that are compared to the true normalised trend. The results suggest a mild improvement in air quality. The influence of inter-annual meteorological variation on annual average concentrations of NOx , NO2 and O3 is estimated for a large number of UK sites using the novel tools of heatmaps and cumulative sum plots. This influence is shown to be considerable: the range of the annual average concentration due to meteorological variation is 2.9 μg m −3 (8.2%) for NO2 , 9.9 μg m −3 (12.6%) for NOx and 3.3 μg m −3 (7.5%) for O3 . The implications of these findings for the use of the annual average metric in compliance monitoring within the EU are considered.