Title: First evaluation of a novel screening tool for outlier detection in large scale ambient air quality datasets
Authors: Oliver Kracht; Michel Gerboles; Hannes I. Reuter
Addresses: European Commission – Joint Research Centre, Institute for Environment and Sustainability, Air and Climate Unit, Via E. Fermi 2749, I-21027 Ispra, Italy ' European Commission – Joint Research Centre, Institute for Environment and Sustainability, Air and Climate Unit, Via E. Fermi 2749, I-21027 Ispra, Italy ' GISxperts GbR, Eichenweg 42, 06849 Dessau, Germany
Abstract: Systematic collection of long term meso- to large-scale datasets of ambient air quality provides an indispensible means for air pollution monitoring. However, the quality of these monitoring data depends on the chosen method of measurements and the QA/QC procedures applied. We present the first version of a prototyped screening tool for the automatic detection of outliers in large data volume air quality monitoring records. The method is based on an adaption of the existing Smooth Spatial Attribute Method, which considers both attribute values and spatio-temporal relationships. An application example of the method is demonstrated by computing warnings on abnormal records in the 2006A/2007 time series of PM10 daily values of background stations reported in the European air quality database AirBase.
Keywords: air pollution; air quality; pollution monitoring; spatial statistics; screening tools; spatio-temporal outliers; quality control; harmonisation; outlier detection; PM10.
International Journal of Environment and Pollution, 2014 Vol.55 No.1/2/3/4, pp.120 - 128
Available online: 29 Nov 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article