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Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions

The unprecedented outbreak of COVID-19 significantly improved the atmospheric environment for lockdown-imposed regions; however, scant evidence exists on its impacts on regions without lockdown. A novel research framework is proposed to evaluate the long-term monthly spatiotemporal impact of COVID-1...

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Autores principales: Wong, Yong Jie, Shiu, Huan-Yu, Chang, Jackson Hian-Hui, Ooi, Maggie Chel Gee, Li, Hsueh-Hsun, Homma, Ryosuke, Shimizu, Yoshihisa, Chiueh, Pei-Te, Maneechot, Luksanaree, Nik Sulaiman, Nik Meriam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234473/
https://www.ncbi.nlm.nih.gov/pubmed/35781986
http://dx.doi.org/10.1016/j.jclepro.2022.132893
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author Wong, Yong Jie
Shiu, Huan-Yu
Chang, Jackson Hian-Hui
Ooi, Maggie Chel Gee
Li, Hsueh-Hsun
Homma, Ryosuke
Shimizu, Yoshihisa
Chiueh, Pei-Te
Maneechot, Luksanaree
Nik Sulaiman, Nik Meriam
author_facet Wong, Yong Jie
Shiu, Huan-Yu
Chang, Jackson Hian-Hui
Ooi, Maggie Chel Gee
Li, Hsueh-Hsun
Homma, Ryosuke
Shimizu, Yoshihisa
Chiueh, Pei-Te
Maneechot, Luksanaree
Nik Sulaiman, Nik Meriam
author_sort Wong, Yong Jie
collection PubMed
description The unprecedented outbreak of COVID-19 significantly improved the atmospheric environment for lockdown-imposed regions; however, scant evidence exists on its impacts on regions without lockdown. A novel research framework is proposed to evaluate the long-term monthly spatiotemporal impact of COVID-19 on Taiwan air quality through different statistical analyses, including geostatistical analysis, change detection analysis and identification of nonattainment pollutant occurrence between the average mean air pollutant concentrations from 2018–2019 and 2020, considering both meteorological and public transportation impacts. Contrary to lockdown-imposed regions, insignificant or worsened air quality conditions were observed at the beginning of COVID-19, but a delayed improvement occurred after April in Taiwan. The annual mean concentrations of PM(10), PM(2.5), SO(2), NO(2), CO and O(3) in 2020 were reduced by 24%, 18%, 15%, 9.6%, 7.4% and 1.3%, respectively (relative to 2018–2019), and the overall occurrence frequency of nonattainment air pollutants declined by over 30%. Backward stepwise regression models for each air pollutant were successfully constructed utilizing 12 meteorological parameters (R(2) > 0.8 except for SO(2)) to simulate the meteorological normalized business-as-usual concentration. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model simulated the fate of air pollutants (e.g., local emissions or transboundary pollution) for anomalous months. The changes in different public transportation usage volumes (e.g., roadway, railway, air, and waterway) moderately reduced air pollution, particularly CO and NO(2). Reduced public transportation use had a more significant impact than meteorology on air quality improvement in Taiwan, highlighting the importance of proper public transportation management for air pollution control and paving a new path for sustainable air quality management even in the absence of a lockdown.
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spelling pubmed-92344732022-06-27 Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions Wong, Yong Jie Shiu, Huan-Yu Chang, Jackson Hian-Hui Ooi, Maggie Chel Gee Li, Hsueh-Hsun Homma, Ryosuke Shimizu, Yoshihisa Chiueh, Pei-Te Maneechot, Luksanaree Nik Sulaiman, Nik Meriam J Clean Prod Article The unprecedented outbreak of COVID-19 significantly improved the atmospheric environment for lockdown-imposed regions; however, scant evidence exists on its impacts on regions without lockdown. A novel research framework is proposed to evaluate the long-term monthly spatiotemporal impact of COVID-19 on Taiwan air quality through different statistical analyses, including geostatistical analysis, change detection analysis and identification of nonattainment pollutant occurrence between the average mean air pollutant concentrations from 2018–2019 and 2020, considering both meteorological and public transportation impacts. Contrary to lockdown-imposed regions, insignificant or worsened air quality conditions were observed at the beginning of COVID-19, but a delayed improvement occurred after April in Taiwan. The annual mean concentrations of PM(10), PM(2.5), SO(2), NO(2), CO and O(3) in 2020 were reduced by 24%, 18%, 15%, 9.6%, 7.4% and 1.3%, respectively (relative to 2018–2019), and the overall occurrence frequency of nonattainment air pollutants declined by over 30%. Backward stepwise regression models for each air pollutant were successfully constructed utilizing 12 meteorological parameters (R(2) > 0.8 except for SO(2)) to simulate the meteorological normalized business-as-usual concentration. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model simulated the fate of air pollutants (e.g., local emissions or transboundary pollution) for anomalous months. The changes in different public transportation usage volumes (e.g., roadway, railway, air, and waterway) moderately reduced air pollution, particularly CO and NO(2). Reduced public transportation use had a more significant impact than meteorology on air quality improvement in Taiwan, highlighting the importance of proper public transportation management for air pollution control and paving a new path for sustainable air quality management even in the absence of a lockdown. Elsevier Ltd. 2022-09-10 2022-06-27 /pmc/articles/PMC9234473/ /pubmed/35781986 http://dx.doi.org/10.1016/j.jclepro.2022.132893 Text en © 2022 Elsevier Ltd. 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
Wong, Yong Jie
Shiu, Huan-Yu
Chang, Jackson Hian-Hui
Ooi, Maggie Chel Gee
Li, Hsueh-Hsun
Homma, Ryosuke
Shimizu, Yoshihisa
Chiueh, Pei-Te
Maneechot, Luksanaree
Nik Sulaiman, Nik Meriam
Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions
title Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions
title_full Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions
title_fullStr Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions
title_full_unstemmed Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions
title_short Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions
title_sort spatiotemporal impact of covid-19 on taiwan air quality in the absence of a lockdown: influence of urban public transportation use and meteorological conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234473/
https://www.ncbi.nlm.nih.gov/pubmed/35781986
http://dx.doi.org/10.1016/j.jclepro.2022.132893
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