Literature DB >> 33401639

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

Wilmar Hernandez1, Alfredo Mendez2, Vicente González-Posadas3, José Luis Jiménez-Martín3, Iván Menes Camejo4.   

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.

Entities:  

Keywords:  categorization of ozone measurements; central tendency and scale estimates; robust analysis; robust and nonrobust confidence intervals

Year:  2021        PMID: 33401639      PMCID: PMC7795081          DOI: 10.3390/s21010277

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  26 in total

1.  Photolysis of atmospheric ozone in the ultraviolet region.

Authors:  Yutaka Matsumi; Masahiro Kawasaki
Journal:  Chem Rev       Date:  2003-12       Impact factor: 60.622

2.  Bias in meta-analysis detected by a simple, graphical test.

Authors:  M Egger; G Davey Smith; M Schneider; C Minder
Journal:  BMJ       Date:  1997-09-13

Review 3.  Effects of ambient ozone concentrations with different averaging times on asthma exacerbations: A meta-analysis.

Authors:  Xing Li; Qing Chen; Xueyan Zheng; Yongzhi Li; Min Han; Tao Liu; Jianpeng Xiao; Lingchuan Guo; Weilin Zeng; Junfeng Zhang; Wenjun Ma
Journal:  Sci Total Environ       Date:  2019-07-04       Impact factor: 7.963

4.  Causes of ozone pollution in summer in Wuhan, Central China.

Authors:  P Zeng; X P Lyu; H Guo; H R Cheng; F Jiang; W Z Pan; Z W Wang; S W Liang; Y Q Hu
Journal:  Environ Pollut       Date:  2018-06-15       Impact factor: 8.071

5.  Development of Low-Cost Air Quality Stations for Next Generation Monitoring Networks: Calibration and Validation of PM2.5 and PM10 Sensors.

Authors:  Alice Cavaliere; Federico Carotenuto; Filippo Di Gennaro; Beniamino Gioli; Giovanni Gualtieri; Francesca Martelli; Alessandro Matese; Piero Toscano; Carolina Vagnoli; Alessandro Zaldei
Journal:  Sensors (Basel)       Date:  2018-08-28       Impact factor: 3.576

6.  Ozone Therapy as a Possible Option in COVID-19 Management.

Authors:  Alessandra Gavazza; Andrea Marchegiani; Giacomo Rossi; Marianno Franzini; Andrea Spaterna; Sara Mangiaterra; Matteo Cerquetella
Journal:  Front Public Health       Date:  2020-08-25

7.  Development of a Network of Accurate Ozone Sensing Nodes for Parallel Monitoring in a Site Relocation Study.

Authors:  Brandon Feenstra; Vasileios Papapostolou; Berj Der Boghossian; David Cocker; Andrea Polidori
Journal:  Sensors (Basel)       Date:  2019-12-18       Impact factor: 3.576

8.  Input-Adaptive Proxy for Black Carbon as a Virtual Sensor.

Authors:  Pak Lun Fung; Martha A Zaidan; Salla Sillanpää; Anu Kousa; Jarkko V Niemi; Hilkka Timonen; Joel Kuula; Erkka Saukko; Krista Luoma; Tuukka Petäjä; Sasu Tarkoma; Markku Kulmala; Tareq Hussein
Journal:  Sensors (Basel)       Date:  2019-12-28       Impact factor: 3.576

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