Twelve-Year Analysis of NO2 Concentration Measurements at Belisario Station (Quito, Ecuador) Using Statistical Inference Techniques

Abstract

In this paper, a robust analysis of nitrogen dioxide (NO2) concentration measurements taken at Belisario station (Quito, Ecuador) was performed. The data used for the analysis constitute a set of measurements taken from 1 January 2008 to 31 December 2019. Furthermore, the analysis was carried out in a robust way, defining variables that represent years, months, days and hours, and classifying these variables based on estimates of the central tendency and dispersion of the data. The estimators used here were classic, nonparametric, based on a bootstrap method, and robust. Additionally, confidence intervals based on these estimators were built, and these intervals were used to categorize the variables under study. The results of this research showed that the NO2 concentration at Belisario station is not harmful to humans. Moreover, it was shown that this concentration tends to be stable across the years, changes slightly during the days of the week, and varies greatly when analyzed by months and hours of the day. Here, the precision provided by both nonparametric and robust statistical methods served to comprehensively proof the aforementioned. Finally, it can be concluded that the city of Quito is progressing on the right path in terms of improving air quality, because it has been shown that there is a decreasing tendency in the NO2 concentration across the years. In addition, according to the Quito Air Quality Index, most of the observations are in either the desirable level or acceptable level of air pollution, and the number of observations that are in the desirable level of air pollution increases across the years.

Robust Inferential Techniques Applied to the Analysis of the Tropospheric Ozone Concentration in an Urban Area

“…The contribution of the present research is that it has been shown that this periodic behavior can be represented by using 95% confidence intervals, both robust and nonrobust ones. Furthermore, the range of possible values of these signals has been categorized with robust statistical precision, which is in agreement with what was discovered in [ 50 , 51 ].…”

“…The existence of maximum and minimum values in the concentration of air pollutants has also been observed in other research [ 50 , 51 , 86 ]. The reality is that anthropogenic emissions have a great influence on the levels of air pollutants in urban cities.…”

“…As has happened in previous studies [ 48 , 49 , 50 , 51 ], the variables chosen for the analysis present a large number of outliers. Therefore, this could indicate that these variables come from heavy-tailed distributions.…”

“…Other air pollution variables have been shown to have possible periodic behavior [ 50 , 51 ]. Nevertheless, everything seems to indicate that the way in which the data are represented has a great influence on either the appreciation or not of said periodic behavior.…”

“…In [ 44 ], 1000 vehicles were tested in order to find significant differences between the mean emissions of air pollutants. Other instances of authors using robust techniques to analyze the concentration of air pollutants are presented in [ 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ].…”