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Christopher Andersen

PhD Student

Christopher Andersen



PhD project: High-resolution modelling of air pollution in Denmark

University: Aarhus University

Department: Department of Environmental Science

Supervisor:  Ole Hertel

Co-supervisors: Jørgen Brandt & Matthias Ketzel

Project term: 01.05.2020 – 30.04.2023

Master’s degree:  MSc in physics, specialization in astrophysics, University of Copenhagen, Denmark



According to WHO, air pollution is now the world’s largest single environmental health risk (WHO, 2016). WHO estimates there were 4.2 million premature deaths in 2016 from urban and rural sources worldwide due to exposure to outdoor air pollution. In Europe, recent results (Brandt et al., 2013a; 2013b) show that outdoor air pollution caused 570.000 premature deaths in 2011. According to Danish Center for Environment and Energy (DCE), the similar figures for Denmark show that about 4.200 premature deaths as a mean over the years 2016-2018 can be linked to air pollution (Ellermann et al., 2020). 


The aim of this project is to significantly advance methodologies for human air pollution exposure and thereby improve health impact assessments. More specifically, the focus is on developing a new model for the assessment of local background pollutant levels in Denmark and use these in human air pollution exposure assessments. The latter will be obtained by revising the Aarhus University’s Urban Background Model (UBM) with a newly developed high-resolution air pollution model for Denmark using the most comprehensive methodologies available with respect to physics, chemistry and numerical methods, and still applicable for performing long simulations e.g. for use in the assessment of lifetime exposure. 


The model development in the PhD project will focus on the description of atmospheric transport for high-resolution modelling, the description of the planetary boundary layer (PBL) physics with focus on mixing heights and horizontal and vertical dispersion, the description of chemistry in the model, including the development of a chemical scheme and a deposition scheme optimal for local scale modelling, the assessment and inclusion of relevant processes for resuspension of atmospheric particles, and the development of suitable time variation of relevant local emissions, e.g. wood stoves and road traffic. In each of the five focus points of the PhD project, different methodologies will be developed, inter-compared and evaluated with respect to measurements. It is anticipated that the model developed within the present project will incorporate a combination of Lagrangian and Eulerian principles.


Big Data Center for Environment and Health (BERTHA)

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