Monitoring algorithms for detecting changes in the ozone concentrations

✍ Scribed by Silvano Bordignon; Michele Scagliarini

• Book ID: 101278737
• Publisher: John Wiley and Sons
• Year: 2000
• Tongue: English
• Weight: 170 KB
• Volume: 11
• Category: Article
• ISSN: 1180-4009
• DOI: 10.1002/(sici)1099-095x(200003/04)11:2<125::aid-env392>3.0.co;2-8

✦ Synopsis

The quality of data collected by air pollution monitoring networks is often aected 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 through Monte Carlo simulations in such a way to detect anomalies in the data within a reasonable delay. The results show several out of control signals that may be caused by problems in the measurement device.