Environmental factors like air pollution or temperature have been shown to adversely affect human health. Precise exposure modelling is essential to accurately determine people's environmental burden and assess potential effects on health. Land Use Regression (LUR) is a simple but powerful tool to estimate the spatial variability of long-term air pollution concentration. Two European-wide and one local project will be presented where we applied LUR to model annual air pollution concentration at the residences of our cohort participants. To detect potential heat islands, we also measured and modeled seasonal temperature in the Augsburg region via LUR. Further modelling approaches and the extension to spatial-temporal models will also be discussed.
Dr. Kathrin Wolf has a background in statistics and acquired her PhD in human biology from the Ludwig-Maximilians Universität in Munich, Germany, in 2009. Her main research interests include the impact of short-and long-term effects of air pollution, noise and meteorology on cardiometabolic health outcomes. She is also interested in GIS data and tools to estimate and visualize spatial concentrations of air pollutants, noise and temperature. More information can be found here:
|Veranstaltende||Lehrstuhl für Statistik|
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