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.

Año de publicación:

2020

Keywords:

  • Classification and categorization of NO2 concentration measurements
  • Nonparametric confidence interval
  • Nonparametric analysis
  • Bootstrap confidence interval
  • Robust analysis
  • Classic confidence interval
  • Classic analysis
  • Robust confidence interval
  • statistical inference

Fuente:

scopusscopus
googlegoogle

Tipo de documento:

Article

Estado:

Acceso abierto

Áreas de conocimiento:

  • Ciencia atmosférica
  • Inferencia estadística

Áreas temáticas:

  • Miscelánea
  • Ciencias de la tierra
  • Tecnología (Ciencias aplicadas)