Abstract
In this paper, a robust analysis of SO 2 concentration measurements taken at the Belisario air quality monitoring station, Quito, Ecuador is carried out. The analyzed data contain 12 years of measurements, from January 2008 to December 2019. In addition, this set of measurements was decomposed into variables that represent each year, month, day of the week, and hour of the day in groups of two hours. For the analysis, classic, nonparametric and robust statistical methods were used, and the data were classified based on criteria established by the Quiteno Air Quality Index, taking confidence intervals into account. The results showed that the level of air pollution at the Belisario station due to the SO 2 concentration is acceptable. In addition, the trend in the level of SO 2 concentration decreased over the years studied, with a sharp drop from 2008 to 2012, then a small rise in 2013 and another fall until 2019, presenting decreasing oscillations that tend toward a desirable level of pollution. In this paper, it was shown that the air pollution at the Belisario station due to the concentration of SO 2 in the last 12 years is not harmful to humans, with the measurement precision provided by robust statistical methods. Therefore, it can be concluded that the measures that have been taken by the Quito city council over the last few years are yielding good results.
Highlights
Sulfur dioxide (SO2) is an invisible toxic gas that is dangerous to human health when inhaled [1]
In the research presented in this paper, 12 years of measurements of SO2 concentrations taken at the Belisario air-quality monitoring station (Quito, Ecuador) [20] are analyzed by using robust statistics techniques [21]–[23]
The objective of this paper was to analyze the general behavior of the SO2 concentration at the air quality monitoring station of Belisario, Quito, Ecuador over the last twelve years
Summary
Sulfur dioxide (SO2) is an invisible toxic gas that is dangerous to human health when inhaled [1]. In the research presented in this paper, 12 years of measurements of SO2 concentrations taken at the Belisario air-quality monitoring station (Quito, Ecuador) [20] are analyzed by using robust statistics techniques [21]–[23]. Other works focusing on the statistical analysis of measurements of air pollution variables that support the above work and complement the examples given in previous paragraphs include the following: In [32], to process high-dimensional data with the aim of predicting the PM2.5 concentration at 35 air quality monitoring stations in Beijing, China over the subsequent 24 hours, a LightGBM model [33] was proposed.
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