Real-time monitoring of carbon monoxide using value-at-risk measure and control charting

Abstract

One of the most important environmental health issues is air pollution, causing the deterioration of the population's quality of life, principally in cities where the urbanization level seems limitless. Among ambient pollutants, carbon monoxide (CO) is well known for its biological toxicity. Many studies report associations between exposure to CO and excess mortality. In this context, the present work provides an advanced modelling scheme for real time monitoring of pollution data and especially of carbon monoxide pollution in city level. The real time monitoring is based on an appropriately adjusted multivariate time series model that is used in finance and gives accurate one-step-ahead forecasts. On the output of the time series, we apply an empirical monitoring scheme that is used for the early detection of abnormal increases of CO levels. The proposed methodology is applied in the city of Athens and as the analysis revealed has a valuable performance.

The use of length-biased distributions in statistical monitoring

“…Examples of applications of SPM to non-industrial processes can be found in Woodall (2006), Shmueli & Fienberg (2006), Woodall et al (2008), Shmueli & Burkom (2010), Frisén, Andersson & Schiöler (2010), Schiöler & Frisén (2012), , Sparks, Keighley & Muscatello (2010, 2011, Tsui et al (2008), Bersimis, Sgora & Psarakis (2016), Anderson & Thompson (2004), and Bersimis, Degiannakis & Georgakellos (2017).…”