SPATIO-TEMPORAL MODELLING OF URBAN SENSOR NETWORK DATA - MAPPING AIR QUALITY RISKS IN EINDHOVEN, THE NETHERLANDS
Vera van Zoest is a PhD student in the department of Earth Observation Science (EOS). Her supervisor is prof.dr.ir. A. Stein from the Faculty of Geo-Information Science and Earth Observation (ITC).
Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. This thesis aims to evaluate the data quality and usability of an air quality sensor network in Eindhoven. The first objective addresses outlier detection based on a spatio-temporal classification. The second objective addresses calibration of the sensors, evaluating different methods in terms of temporal stability, spatial transferability and sensor specificity. The third research objective addresses prediction of air pollutant concentrations using a spatio-temporal regression kriging framework. Prediction maps are created at fine spatio-temporal resolution, which can be used in infrastructural decision-making and epidemiological studies. The final research objective addresses health risk mapping. A panel study is set up to collect daily data on symptoms in asthmatic children. In a Bayesian analysis, these are combined with a priori information from literature to obtain accurate health effect estimates and subsequent burden of disease maps.