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On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China
Due to the COVID-19 pandemic, human activities are largely restricted in Shanghai, China and it is a valuable experiment to testify the correlation of air quality and human activities. In consideration of the complexity of air pollution, this study aims to compare the multifractal characteristics of...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681039/ https://www.ncbi.nlm.nih.gov/pubmed/33250563 http://dx.doi.org/10.1016/j.physa.2020.125551 |
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author | Li, Xing |
author_facet | Li, Xing |
author_sort | Li, Xing |
collection | PubMed |
description | Due to the COVID-19 pandemic, human activities are largely restricted in Shanghai, China and it is a valuable experiment to testify the correlation of air quality and human activities. In consideration of the complexity of air pollution, this study aims to compare the multifractal characteristics of air quality index (AQI) time series before and during COVID-19 partial lockdown, and analyze the correlations between multifractal parameters of AQI time series and human activities in Shanghai, China. The hourly AQI series in Shanghai from November 27, 2019 to March 23, 2020 is used for this study. Firstly, using the MF-DFA method, the multifractal characteristics of the AQI series are explored. Secondly, the causes of the multifractality of the AQI series are determined. Finally, the correlations between multifractal parameters of AQI time series and human activities are investigated. The multifractal analysis results reveal that the AQI series during COVID-19 partial lockdown also has multifractal characteristics, and the slightly weaker multifractal characteristics and marginally smaller multifractal degree are obtained in comparison with the pre-lockdown phase. However, the contribution of the effective or intrinsic multifractality before and during COVID-19 partial lockdown are very close. The results via the sliding window procedure indicate that the multifractal parameters ([Formula: see text]) show the similar fluctuations along with the fluctuations of passenger volume in Shanghai Metro. Furthermore, it is found that [Formula: see text] and [Formula: see text] and adjusted passenger volume in Shanghai Metro are positively correlated. The possible trend is that the higher adjusted passenger volume is, the larger the value of [Formula: see text] , [Formula: see text] becomes, which means the stronger multifractal characteristics and larger multifractal degree of air quality system. |
format | Online Article Text |
id | pubmed-7681039 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76810392020-11-23 On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China Li, Xing Physica A Article Due to the COVID-19 pandemic, human activities are largely restricted in Shanghai, China and it is a valuable experiment to testify the correlation of air quality and human activities. In consideration of the complexity of air pollution, this study aims to compare the multifractal characteristics of air quality index (AQI) time series before and during COVID-19 partial lockdown, and analyze the correlations between multifractal parameters of AQI time series and human activities in Shanghai, China. The hourly AQI series in Shanghai from November 27, 2019 to March 23, 2020 is used for this study. Firstly, using the MF-DFA method, the multifractal characteristics of the AQI series are explored. Secondly, the causes of the multifractality of the AQI series are determined. Finally, the correlations between multifractal parameters of AQI time series and human activities are investigated. The multifractal analysis results reveal that the AQI series during COVID-19 partial lockdown also has multifractal characteristics, and the slightly weaker multifractal characteristics and marginally smaller multifractal degree are obtained in comparison with the pre-lockdown phase. However, the contribution of the effective or intrinsic multifractality before and during COVID-19 partial lockdown are very close. The results via the sliding window procedure indicate that the multifractal parameters ([Formula: see text]) show the similar fluctuations along with the fluctuations of passenger volume in Shanghai Metro. Furthermore, it is found that [Formula: see text] and [Formula: see text] and adjusted passenger volume in Shanghai Metro are positively correlated. The possible trend is that the higher adjusted passenger volume is, the larger the value of [Formula: see text] , [Formula: see text] becomes, which means the stronger multifractal characteristics and larger multifractal degree of air quality system. Elsevier B.V. 2021-03-01 2020-11-23 /pmc/articles/PMC7681039/ /pubmed/33250563 http://dx.doi.org/10.1016/j.physa.2020.125551 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Li, Xing On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China |
title | On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China |
title_full | On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China |
title_fullStr | On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China |
title_full_unstemmed | On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China |
title_short | On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China |
title_sort | on the multifractal analysis of air quality index time series before and during covid-19 partial lockdown: a case study of shanghai, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681039/ https://www.ncbi.nlm.nih.gov/pubmed/33250563 http://dx.doi.org/10.1016/j.physa.2020.125551 |
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