Monitoring Air Pollutants To Detect Anomalies
With Applications To The Ozone Concentrations
Author(s)
S. Bordignon & M. Scagliarini
Abstract
The quality of data collected by air pollution monitoring networks is often affected by
inaccuracies and missing data problems, mainly due to breakdowns and/or biases of the
measurement instruments. In this paper we propose a statistical method to detect, as soon as
possible, biases in the measurement devices, in order to improve the quality of collected data
on line. The technique is based on the joint use of stochastic modelling and statistical process
control algorithms. This methodology is applied to the mean hourly ozone concentrations
recorded from one monitoring site of the Bologna urban area network. We set up the
monitoring algorithm (t
Keywords
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