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Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD
The air pollution in China currently is characterized by high fine particulate matter (PM(2.5)) and ozone (O(3)) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM(2.5) and O(3) are above the National Ambient Air Quality Standards (NAAQS)) po...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10127971/ https://www.ncbi.nlm.nih.gov/pubmed/37097531 http://dx.doi.org/10.1007/s10661-023-11213-w |
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author | Bao, Bingyi Li, Youping Liu, Chunqiong Wen, Ye Shi, Kai |
author_facet | Bao, Bingyi Li, Youping Liu, Chunqiong Wen, Ye Shi, Kai |
author_sort | Bao, Bingyi |
collection | PubMed |
description | The air pollution in China currently is characterized by high fine particulate matter (PM(2.5)) and ozone (O(3)) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM(2.5) and O(3) are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM(2.5) and O(3). Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM(2.5) and O(3) in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM(2.5) decreased while O(3) increased in most cities due to the effect of COVID-19, and the increase in O(3) is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM(2.5)-O(3) DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM(2.5)-O(3) VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM(2.5) and O(3) are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM(2.5)-O(3) DHP coordinated control strategies. |
format | Online Article Text |
id | pubmed-10127971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-101279712023-04-27 Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD Bao, Bingyi Li, Youping Liu, Chunqiong Wen, Ye Shi, Kai Environ Monit Assess Research The air pollution in China currently is characterized by high fine particulate matter (PM(2.5)) and ozone (O(3)) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM(2.5) and O(3) are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM(2.5) and O(3). Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM(2.5) and O(3) in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM(2.5) decreased while O(3) increased in most cities due to the effect of COVID-19, and the increase in O(3) is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM(2.5)-O(3) DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM(2.5)-O(3) VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM(2.5) and O(3) are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM(2.5)-O(3) DHP coordinated control strategies. Springer International Publishing 2023-04-25 2023 /pmc/articles/PMC10127971/ /pubmed/37097531 http://dx.doi.org/10.1007/s10661-023-11213-w Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Bao, Bingyi Li, Youping Liu, Chunqiong Wen, Ye Shi, Kai Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD |
title | Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD |
title_full | Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD |
title_fullStr | Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD |
title_full_unstemmed | Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD |
title_short | Response of cross-correlations between high PM(2.5) and O(3) with increasing time scales to the COVID-19: different trends in BTH and PRD |
title_sort | response of cross-correlations between high pm(2.5) and o(3) with increasing time scales to the covid-19: different trends in bth and prd |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10127971/ https://www.ncbi.nlm.nih.gov/pubmed/37097531 http://dx.doi.org/10.1007/s10661-023-11213-w |
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