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Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais

Air pollution due to air contamination by gases, liquids, and solid particles in suspension, is a great environmental and public health concern nowadays. An important type of air pollution is particulate matter with a diameter of 10 microns or less ([Formula: see text] ) because one of the determini...

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Autores principales: da Silva, Kim Leone Souza, López-Gonzales, Javier Linkolk, Turpo-Chaparro, Josue E., Tocto-Cano, Esteban, Rodrigues, Paulo Canas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9968292/
https://www.ncbi.nlm.nih.gov/pubmed/36841859
http://dx.doi.org/10.1038/s41598-023-30365-w
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author da Silva, Kim Leone Souza
López-Gonzales, Javier Linkolk
Turpo-Chaparro, Josue E.
Tocto-Cano, Esteban
Rodrigues, Paulo Canas
author_facet da Silva, Kim Leone Souza
López-Gonzales, Javier Linkolk
Turpo-Chaparro, Josue E.
Tocto-Cano, Esteban
Rodrigues, Paulo Canas
author_sort da Silva, Kim Leone Souza
collection PubMed
description Air pollution due to air contamination by gases, liquids, and solid particles in suspension, is a great environmental and public health concern nowadays. An important type of air pollution is particulate matter with a diameter of 10 microns or less ([Formula: see text] ) because one of the determining factors that affect human health is the size of particles in the atmosphere due to the degree of permanence and penetration they have in the respiratory system. Therefore, it is extremely interesting to monitor and understand the behavior of [Formula: see text] concentrations so that they do not exceed the established critical levels. In this work, we will study the [Formula: see text] concentrations in all available monitoring stations in the Brazilian state of Minas Gerais. To better understand its behavior, we will provide a spatio-temporal visualization of the [Formula: see text] concentrations. Besides the descriptive and visualization analysis, we consider six standard and advanced time series models that will be used to fit and forecast [Formula: see text] concentrations, with application to three locations, one in Belo Horizonte, the Minas Gerais state capital, and the monitoring stations with the lowest and highest average [Formula: see text] concentration levels.
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spelling pubmed-99682922023-02-27 Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais da Silva, Kim Leone Souza López-Gonzales, Javier Linkolk Turpo-Chaparro, Josue E. Tocto-Cano, Esteban Rodrigues, Paulo Canas Sci Rep Article Air pollution due to air contamination by gases, liquids, and solid particles in suspension, is a great environmental and public health concern nowadays. An important type of air pollution is particulate matter with a diameter of 10 microns or less ([Formula: see text] ) because one of the determining factors that affect human health is the size of particles in the atmosphere due to the degree of permanence and penetration they have in the respiratory system. Therefore, it is extremely interesting to monitor and understand the behavior of [Formula: see text] concentrations so that they do not exceed the established critical levels. In this work, we will study the [Formula: see text] concentrations in all available monitoring stations in the Brazilian state of Minas Gerais. To better understand its behavior, we will provide a spatio-temporal visualization of the [Formula: see text] concentrations. Besides the descriptive and visualization analysis, we consider six standard and advanced time series models that will be used to fit and forecast [Formula: see text] concentrations, with application to three locations, one in Belo Horizonte, the Minas Gerais state capital, and the monitoring stations with the lowest and highest average [Formula: see text] concentration levels. Nature Publishing Group UK 2023-02-25 /pmc/articles/PMC9968292/ /pubmed/36841859 http://dx.doi.org/10.1038/s41598-023-30365-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
da Silva, Kim Leone Souza
López-Gonzales, Javier Linkolk
Turpo-Chaparro, Josue E.
Tocto-Cano, Esteban
Rodrigues, Paulo Canas
Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais
title Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais
title_full Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais
title_fullStr Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais
title_full_unstemmed Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais
title_short Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais
title_sort spatio-temporal visualization and forecasting of [formula: see text] in the brazilian state of minas gerais
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9968292/
https://www.ncbi.nlm.nih.gov/pubmed/36841859
http://dx.doi.org/10.1038/s41598-023-30365-w
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