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Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020

In this paper, a comparative analysis between the PM [Formula: see text] concentration in downtown Quito, Ecuador, during the COVID-19 pandemic in 2020 and the previous five years (from 2015 to 2019) was carried out. Here, in order to fill in the missing data and achieve homogeneity, eight datasets...

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Autores principales: Hernandez, Wilmar, Arqués-Orobón, Francisco José, González-Posadas, Vicente, Jiménez-Martín, José Luis, Rosero-Montalvo, Paul D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697511/
https://www.ncbi.nlm.nih.gov/pubmed/36433581
http://dx.doi.org/10.3390/s22228985
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author Hernandez, Wilmar
Arqués-Orobón, Francisco José
González-Posadas, Vicente
Jiménez-Martín, José Luis
Rosero-Montalvo, Paul D.
author_facet Hernandez, Wilmar
Arqués-Orobón, Francisco José
González-Posadas, Vicente
Jiménez-Martín, José Luis
Rosero-Montalvo, Paul D.
author_sort Hernandez, Wilmar
collection PubMed
description In this paper, a comparative analysis between the PM [Formula: see text] concentration in downtown Quito, Ecuador, during the COVID-19 pandemic in 2020 and the previous five years (from 2015 to 2019) was carried out. Here, in order to fill in the missing data and achieve homogeneity, eight datasets were constructed, and 35 different estimates were used together with six interpolation methods to put in the estimated value of the missing data. Additionally, the quality of the estimations was verified by using the sum of squared residuals and the following correlation coefficients: Pearson’s r, Kendall’s [Formula: see text] , and Spearman’s [Formula: see text]. Next, feature vectors were constructed from the data under study using the wavelet transform, and the differences between feature vectors were studied by using principal component analysis and multidimensional scaling. Finally, a robust method to impute missing data in time series and characterize objects is presented. This method was used to support the hypothesis that there were significant differences between the PM [Formula: see text] concentration in downtown Quito in 2020 and 2015–2019.
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spelling pubmed-96975112022-11-26 Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020 Hernandez, Wilmar Arqués-Orobón, Francisco José González-Posadas, Vicente Jiménez-Martín, José Luis Rosero-Montalvo, Paul D. Sensors (Basel) Article In this paper, a comparative analysis between the PM [Formula: see text] concentration in downtown Quito, Ecuador, during the COVID-19 pandemic in 2020 and the previous five years (from 2015 to 2019) was carried out. Here, in order to fill in the missing data and achieve homogeneity, eight datasets were constructed, and 35 different estimates were used together with six interpolation methods to put in the estimated value of the missing data. Additionally, the quality of the estimations was verified by using the sum of squared residuals and the following correlation coefficients: Pearson’s r, Kendall’s [Formula: see text] , and Spearman’s [Formula: see text]. Next, feature vectors were constructed from the data under study using the wavelet transform, and the differences between feature vectors were studied by using principal component analysis and multidimensional scaling. Finally, a robust method to impute missing data in time series and characterize objects is presented. This method was used to support the hypothesis that there were significant differences between the PM [Formula: see text] concentration in downtown Quito in 2020 and 2015–2019. MDPI 2022-11-20 /pmc/articles/PMC9697511/ /pubmed/36433581 http://dx.doi.org/10.3390/s22228985 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hernandez, Wilmar
Arqués-Orobón, Francisco José
González-Posadas, Vicente
Jiménez-Martín, José Luis
Rosero-Montalvo, Paul D.
Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020
title Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020
title_full Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020
title_fullStr Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020
title_full_unstemmed Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020
title_short Statistical Analysis of the Impact of COVID-19 on PM(2.5) Concentrations in Downtown Quito during the Lockdowns in 2020
title_sort statistical analysis of the impact of covid-19 on pm(2.5) concentrations in downtown quito during the lockdowns in 2020
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697511/
https://www.ncbi.nlm.nih.gov/pubmed/36433581
http://dx.doi.org/10.3390/s22228985
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