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

Abstract

This paper analyzes 12 years of tropospheric ozone (O3) concentration measurements using robust techniques. The measurements were taken at an air quality monitoring station called Belisario, which is in Quito, Ecuador; the data collection time period was 1 January 2008 to 31 December 2019, and the measurements were carried out using photometric O3 analyzers. Here, the measurement results were used to build variables that represented hours, days, months, and years, and were then classified and categorized. The index of air quality (IAQ) of the city was used to make the classifications, and robust and nonrobust confidence intervals were used to make the categorizations. Furthermore, robust analysis methods were compared with classical methods, nonparametric methods, and bootstrap-based methods. The results showed that the analysis using robust methods is better than the analysis using nonrobust methods, which are not immune to the influence of extreme observations. Using all of the aforementioned methods, confidence intervals were used to both establish and quantify differences between categories of the groups of variables under study. In addition, the central tendency and variability of the O3 concentration at Belisario station were exhaustively analyzed, concluding that said concentration was stable for years, highly variable for months and hours, and slightly changing between the days of the week. Additionally, according to the criteria established by the IAQ, it was shown that in Quito, the O3 concentration levels during the study period were not harmful to human health.

Smart and Portable Air-Quality Monitoring IoT Low-Cost Devices in Ibarra City, Ecuador

“…This section presents the data analysis scheme used to locally implement the ML algorithm. It is essential to consider that, in Ibarra, it is known from previous studies that the air quality is acceptable [1,4,10]. However, it shows punctual peaks that generate risk for people.…”

“…Traditionally, countries obtain air-pollution data daily and create a relationship between the maximum and minimum concentration to establish the AQI between good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, and hazardous. The gases taken into account are Sulfur Dioxide (SO 2 ), Nitrogen Dioxide (NO x ), Ozone (O 3 ), and Carbon Monoxide (CO) [1,10,[19][20][21]. However, as has been witnessed in several papers [14,22,23], there is no metric of ambient air pollution that includes related factors such as temperature, relative humidity, and ultraviolet (UV) exposure.…”

“…Therefore, to obtain R S , it is necessary to use the voltage supply (V C ) and the voltage that the sensor receives (V RL ). The equation used is (1).…”

“…Environmental pollution is an issue that has undeniably attracted our full attention. The problem of air pollution affects people's physical and mental health, and long-term exposure increases the risk of cardiovascular and respiratory diseases [1]. In addition, the World Health Organization (WHO) forecasts that 4.2 million people die every year because of exposure to air pollutants.…”

Statistical Analysis of the Impact of COVID-19 on PM2.5 Concentrations in Downtown Quito during the Lockdowns in 2020

“…To begin the study of the data, a preliminary analysis of the available observations was made [1,2,[59][60][61][62]. This study was carried out through an exploratory analysis of the data.…”