Abstract
Ground level concentrations of nitrogen oxide (NOx) can act as an indicator of air quality in the urban environment. In cities with relatively good air quality, and where NOx concentrations rarely exceed legal limits, adverse health effects on the population may still occur. Therefore, detecting small deviations in air quality and deriving methods of controlling air pollution are challenging. This study presents different data analytical methods which can be used to monitor and effectively evaluate policies or measures to reduce nitrogen oxide (NOx) emissions through the detection of pollution episodes and the removal of outliers. This method helps to identify the sources of pollution more effectively, and enhances the value of monitoring data and exceedances of limit values. It will detect outliers, changes and trend deviations in NO2 concentrations at ground level, and consists of four main steps: classical statistical description techniques, statistical process control techniques, functional analysis and a functional control process. To demonstrate the effectiveness of the outlier detection methodology proposed, it was applied to a complete one-year NO2 dataset for a sub-urban site in Dublin, Ireland in 2013. The findings demonstrate how the functional data approach improves the classical techniques for detecting outliers, and in addition, how this new methodology can facilitate a more thorough approach to defining effect air pollution control measures.
Highlights
IntroductionMost cities have an increasing environmental problem related to air pollution [1,2,3,4].This specific pollution is a continuing threat to human health and welfare, with a range of different sources generating different pollutants which have distinct health effects on urban populations [5,6,7].Detailed air quality monitoring data for pollutants, such as carbon monoxide (CO), nitrogen oxides (NO and NO2 ), sulphur dioxide (SO2 ), ozone (O3 ) and particulate matter (PM10 and PM2.5 ), are becoming more important because of the health problems said pollutants can cause in living beings [6].The measurements of pollutants provide real-time data to inform the public and provide a mechanism of alerting local residents of a possible hazard
The data used come from a sub-urban air quality monitoring site in Dublin, Ireland, and cover the whole year 2013 with hourly measurements
A statistical process control was adopted to study the data grouped by days or hours, and with different control charts (Xbar-chart, S-chart)
Summary
Most cities have an increasing environmental problem related to air pollution [1,2,3,4].This specific pollution is a continuing threat to human health and welfare, with a range of different sources generating different pollutants which have distinct health effects on urban populations [5,6,7].Detailed air quality monitoring data for pollutants, such as carbon monoxide (CO), nitrogen oxides (NO and NO2 ), sulphur dioxide (SO2 ), ozone (O3 ) and particulate matter (PM10 and PM2.5 ), are becoming more important because of the health problems said pollutants can cause in living beings [6].The measurements of pollutants provide real-time data to inform the public and provide a mechanism of alerting local residents of a possible hazard. Most cities have an increasing environmental problem related to air pollution [1,2,3,4]. This specific pollution is a continuing threat to human health and welfare, with a range of different sources generating different pollutants which have distinct health effects on urban populations [5,6,7]. Detailed air quality monitoring data for pollutants, such as carbon monoxide (CO), nitrogen oxides (NO and NO2 ), sulphur dioxide (SO2 ), ozone (O3 ) and particulate matter (PM10 and PM2.5 ), are becoming more important because of the health problems said pollutants can cause in living beings [6]. Pollutant sources from traffic emissions, such as NOx, which represents a combination of nitrogen oxide (NO) and nitrogen dioxide (NO2 ), are typically emitted at ground level from vehicles and are associated with health-related problems [8].
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