Automated Screening of Spatio-Temporal Anomalies in Long Term / Large Scale Air Quality Observation Time Series

We are presenting the closer evaluation of a consolidated screening tool for the automatized recognition of anomalies in air quality monitoring data, which considers both attribute values and spatio-temporal relationships. Application examples for the identification of anomalies within the AirBase 2001-to-2010 time series of PM10 background station datasets are demonstrated. Furthermore, sensitivity analyses and validation approaches using synthetic datasets are being discussed. The implemented method is of significant interest as the basis of a data quality screening system.JRC.H.2-Air and Climat