Ozone and temperature in Europe
Project: Modelling of combined tropospheric ozone and temperature events relevant for human health in Europe
Start date: 15.10.2018
End date: 14.10.2021
Duration: 3 years
Funded by: Augsburg University
Project leader: M.Sc. Sally Jahn, Prof. Dr. Elke Hertig
Air pollution is the single largest environmental health risk in Europe (EEA Report No 10/2019). One of the most harmful air pollutants is tropospheric ozone, its concentration highly depending on prevailing air chemical and meteorological conditions. In addition to ozone, high summer air temperatures pose a high risk to human health, with strong persistent heat events being of particular significance. Since elevated air temperatures combined with intense solar radiation favor the formation of ground-level ozone, high ozone concentrations often co-occur with high air temperatures. The resulting synergistic effects pose an intensified threat to human health resulting in an even greater health burden for the European population.
The aim of this PhD project is to investigate and statistically model the combined occurrence of health-relevant ozone and temperature events.
A strong focus is set to assess the relationship between recent as well as future meteorological conditions and air quality in Europe.
The analysis of the influence of meteorological conditions on the occurrence of combined ground-level ozone and temperature events along with the identification of primary key factors (e.g. ozone persistence or larger-scale air temperature and wind conditions) using various statistical modelling techniques forms the starting point of the study. Recent and future climatological conditions based on their anticipated changes in the scope of global warming are analysed by integrating projections of general circulation models into the statistical modelling process.
The exploration of meteorological variables and their change is complemented by an increased regional to local approach. Different weather pattern and circulation type classifications, in particular their specific conditions and characteristics relevant for ozone-temperature events are investigated. The realistic and coherent assessment of health-relevant air-hygienic and climatological events is conducted by also taking into account medical health data, socio-economic factors and local vulnerabilities on different scales.
The methodological focus is primary on statistical modelling, the application and comparison of varying multivariate statistical approaches and different machine learning methods. For example, various regression analyses using shrinkage methods, random forests and neural networks are subject of research.