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

Authors :
Wilmar Hernandez
Alfredo Mendez
Vicente González-Posadas
José Luis Jiménez-Martín
Iván Menes Camejo
Source :
Sensors, Vol 21, Iss 1, p 277 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

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.

Details

Language :
English
ISSN :
21010277 and 14248220
Volume :
21
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.299196db5414e91ba30e86da57bc252
Document Type :
article
Full Text :
https://doi.org/10.3390/s21010277