Direct and indirect measurements of on-road vehicle emissions in the UK: Implications for outdoor and within-vehicle air quality and human health

Urban air quality and particularly human exposure to traffic related emissions is one of the biggest problems in modern societies. This thesis is dedicated to advancing understanding of human exposure to traffic related air pollution in developed cities. The conceptual framework covers aspects of exposure spanning from roadside to within-vehicle exposure, while focusing on providing new modelling tools and methods that can be used to assist and better manage air quality. To investigate roadside exposure, a trend analysis of nitric oxide, nitrogen dioxide, ozone and temperature was performed across the UK for the period 2009 - 2016 and a new methodology was introduced to quantify for the first time the impact of cold weather-related vehicle primary nitrogen dioxide emissions on urban air quality. To study within-vehicle exposure, a set of field experiments were conducted, where four vehicles were driven on a consistent route encompassing contrasting road types, measuring, under different ventilation options, simultaneous within-vehicle and ambient levels of particulate matter, aerosol lung surface deposited area, nitric oxide and nitrogen dioxide. The data from these experiments were used to build a mass balance model to estimate personal exposure to air pollution within vehicle cabins, while state-of-the-art machine learning algorithms were also used to introduce new predictive capabilities for air pollution exposure.