Cargando…
Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China
To curb the spread of the coronavirus, China implemented lockdown policies on January 23, 2020. The resulting extreme changes in human behavior may have influenced the air pollutants concentration. However, despite these changes, hazy weather persisted in Shanghai and became a public issue. This stu...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576102/ https://www.ncbi.nlm.nih.gov/pubmed/33101538 http://dx.doi.org/10.1007/s11869-020-00956-x |
_version_ | 1783597947882045440 |
---|---|
author | Niu, Zhi Hu, Tingting Kong, Lin Zhang, Wenqi Rao, Pinhua Ge, Dafeng Zhou, Mengge Duan, Yuseng |
author_facet | Niu, Zhi Hu, Tingting Kong, Lin Zhang, Wenqi Rao, Pinhua Ge, Dafeng Zhou, Mengge Duan, Yuseng |
author_sort | Niu, Zhi |
collection | PubMed |
description | To curb the spread of the coronavirus, China implemented lockdown policies on January 23, 2020. The resulting extreme changes in human behavior may have influenced the air pollutants concentration. However, despite these changes, hazy weather persisted in Shanghai and became a public issue. This study aims to investigate air pollutant mass concentration changes during the lockdown in Shanghai. Air pollutant mass concentration data and meteorological data during the pre-lockdown period and the level I response lockdown period were analyzed by statistical analysis and a Lagrangian particle diffusion model. The data was classified in three periods: P1 (pre-lockdown: 10 days before the Spring Festival), P2 (the first 10 days after lockdown: during the Spring Festival celebration), and P3 (the second 10 days after lockdown: after the Spring Festival). Data for the same period in 2019 were used as a reference. The results indicate that the Spring Festival holiday in 2019 resulted in a reduction in energy consumption, which led to a decrease in PM(2.5) (26.4%) and NO(2) (43.41%) mass concentration, but an increase in ozone mass concentration (31.39%) in P2 compared with P1. The integrated effect of the Spring Festival holiday and lockdown in 2020 resulted in a decrease in PM(2.5) (36.5%) and NO(2) (51.9%) mass concentrations, but an increase in ozone mass concentration (43.8%) in P2 compared with P1. After the Spring Festival, the mass concentrations of PM(2.5), SO(2), and NO(2) increased by 74.41%, 5.52%, and 53.28%, respectively in P3 compared with P2 in 2019. However, PM(2.5) and SO(2) concentrations in 2020 continued to decrease, by 14.74% and 4.61%, respectively, while NO(2) mass concentration increased by 7.82% in P3 compared with P2. We also found that PM(2.5) mass concentration is susceptible to regional transmission from the surrounding cities. PM(2.5) and other gaseous pollutants show different correlations in different periods, while NO(2) and O(3) always show a strong negative correlation. The principal components before the Spring Festival in 2019 were O(3) and NO(2), and after the Spring Festival, they were PM(2.5) and CO, while the principal components before the lockdown in 2020 were PM(2.5) and CO, and during lockdown they were O(3) and NO(2). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11869-020-00956-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7576102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-75761022020-10-21 Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China Niu, Zhi Hu, Tingting Kong, Lin Zhang, Wenqi Rao, Pinhua Ge, Dafeng Zhou, Mengge Duan, Yuseng Air Qual Atmos Health Article To curb the spread of the coronavirus, China implemented lockdown policies on January 23, 2020. The resulting extreme changes in human behavior may have influenced the air pollutants concentration. However, despite these changes, hazy weather persisted in Shanghai and became a public issue. This study aims to investigate air pollutant mass concentration changes during the lockdown in Shanghai. Air pollutant mass concentration data and meteorological data during the pre-lockdown period and the level I response lockdown period were analyzed by statistical analysis and a Lagrangian particle diffusion model. The data was classified in three periods: P1 (pre-lockdown: 10 days before the Spring Festival), P2 (the first 10 days after lockdown: during the Spring Festival celebration), and P3 (the second 10 days after lockdown: after the Spring Festival). Data for the same period in 2019 were used as a reference. The results indicate that the Spring Festival holiday in 2019 resulted in a reduction in energy consumption, which led to a decrease in PM(2.5) (26.4%) and NO(2) (43.41%) mass concentration, but an increase in ozone mass concentration (31.39%) in P2 compared with P1. The integrated effect of the Spring Festival holiday and lockdown in 2020 resulted in a decrease in PM(2.5) (36.5%) and NO(2) (51.9%) mass concentrations, but an increase in ozone mass concentration (43.8%) in P2 compared with P1. After the Spring Festival, the mass concentrations of PM(2.5), SO(2), and NO(2) increased by 74.41%, 5.52%, and 53.28%, respectively in P3 compared with P2 in 2019. However, PM(2.5) and SO(2) concentrations in 2020 continued to decrease, by 14.74% and 4.61%, respectively, while NO(2) mass concentration increased by 7.82% in P3 compared with P2. We also found that PM(2.5) mass concentration is susceptible to regional transmission from the surrounding cities. PM(2.5) and other gaseous pollutants show different correlations in different periods, while NO(2) and O(3) always show a strong negative correlation. The principal components before the Spring Festival in 2019 were O(3) and NO(2), and after the Spring Festival, they were PM(2.5) and CO, while the principal components before the lockdown in 2020 were PM(2.5) and CO, and during lockdown they were O(3) and NO(2). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11869-020-00956-x) contains supplementary material, which is available to authorized users. Springer Netherlands 2020-10-21 2021 /pmc/articles/PMC7576102/ /pubmed/33101538 http://dx.doi.org/10.1007/s11869-020-00956-x Text en © Springer Nature B.V. 2020 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 | Article Niu, Zhi Hu, Tingting Kong, Lin Zhang, Wenqi Rao, Pinhua Ge, Dafeng Zhou, Mengge Duan, Yuseng Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China |
title | Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China |
title_full | Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China |
title_fullStr | Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China |
title_full_unstemmed | Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China |
title_short | Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China |
title_sort | air-pollutant mass concentration changes during covid-19 pandemic in shanghai, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576102/ https://www.ncbi.nlm.nih.gov/pubmed/33101538 http://dx.doi.org/10.1007/s11869-020-00956-x |
work_keys_str_mv | AT niuzhi airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT hutingting airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT konglin airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT zhangwenqi airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT raopinhua airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT gedafeng airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT zhoumengge airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina AT duanyuseng airpollutantmassconcentrationchangesduringcovid19pandemicinshanghaichina |