Air pollution is a major problem in many parts of the world, and is particularly acute in countries with rapidly developing economies such as China. Urban air pollution has a major impact on human health, but small-scale variability in pollutant sources makes assessment of human exposure difficult. Understanding this variability is important for quantifying the impacts on human health and for the source attribution required to inform mitigation and control of air pollution. Air quality models typically work on spatial scales of 1-3 km, far coarser than required to assess human exposure reliably, while urban monitoring networks provide measurements at specific locations but lack sufficient spatial coverage. This project addresses this through the first highresolution modelling study of air pollution in Beijing. It brings together a street-scale air quality model with an innovative air pollution sensor network for the first time. The goal is to provide new understanding of key emission sources in the city (e.g., traffic, cooking), informing future mitigation options, while providing a critical test of current understanding of chemical and meteorological processes.
The project provides the very first opportunity to estimate the exposure of urban residents in Beijing to outdoor air pollution. It will also permit optimization of urban sensor network design, informing the future establishment of air pollutant networks. The student will join the vibrant atmospheric modelling group at Lancaster, and will contribute to national and international projects addressing urban air quality. Training will be provided in atmospheric science, numerical modelling, and data analysis, and there will be a focus on using scientific results to inform air quality policy. The project will involve working with colleagues at the Chinese Academy of Sciences, and the student will spend time in Beijing learning first-hand about the challenges of measuring, modelling and mitigating urban air pollution.
Applicants should hold a minimum of a UK Honours degree at 2:1 level or equivalent in Chemistry, Physics, Mathematics, Natural or Environmental Science, or a related discipline.
For further details please contact Prof. Oliver Wild (firstname.lastname@example.org).