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解析中国新冠疫情封锁期间空气污染物及健康风险变化的驱动因素。

Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China.

作者信息

Shen Fuzhen, Hegglin Michaela I, Luo Yuanfei, Yuan Yue, Wang Bing, Flemming Johannes, Wang Junfeng, Zhang Yunjiang, Chen Mindong, Yang Qiang, Ge Xinlei

机构信息

Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China.

Department of Meteorology, University of Reading, Reading, RG6 6BX UK.

出版信息

NPJ Clim Atmos Sci. 2022;5(1):54. doi: 10.1038/s41612-022-00276-0. Epub 2022 Jun 30.

DOI:10.1038/s41612-022-00276-0
PMID:35789740
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9244310/
Abstract

The COVID-19 restrictions in 2020 have led to distinct variations in NO and O concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China's 2018-2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO and O are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018-2020 to a reduction in NO by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO reductions, respectively. For O the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and -0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP's contribution highlights the effectiveness of the Chinese government's air-quality regulations on NO reduction.

摘要

2020年的新冠疫情防控措施导致中国的氮氧化物(NO)和臭氧(O)浓度出现显著变化。在此,通过综合模型测量方法,分离出人为排放变化的不同驱动因素,包括中国春节(CNY)、中国2018 - 2020年清洁空气计划(CAP)以及新冠疫情封锁措施及其对NO和O的影响。此外,应用机器学习方法评估了主要气象条件对浓度变化的贡献。对基于健康的多污染物空气质量指数(HAQI)的影响进行了量化。结果表明,春节平均每年使NO浓度降低26.7%,而2020年的新冠疫情封锁措施使NO浓度额外降低了11.6%,2018 - 2020年的清洁空气计划使NO浓度降低了15.7%。另一方面,2020年1月23日至3月7日的气象条件使NO浓度增加了7.8%。因此,忽略清洁空气计划和气象驱动因素分别导致对新冠疫情封锁措施对NO减排效果的高估和低估。对于O,发现情况相反,春节、新冠疫情封锁、清洁空气计划和气象影响分别导致O浓度变化为+23.3%、+21.0%、+4.9%和 -0.9%。这些驱动因素的总体影响表明中国与多种空气污染物相关的健康风险大幅降低,其中气象条件对中国东北地区产生了特别不利的影响。重要的是,清洁空气计划的贡献凸显了中国政府空气质量法规在减少NO方面的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f30/9244310/0a5c1b914dc0/41612_2022_276_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f30/9244310/51a29be63b5d/41612_2022_276_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f30/9244310/9912487664d6/41612_2022_276_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f30/9244310/d053f7872d7f/41612_2022_276_Fig3_HTML.jpg
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本文引用的文献

1
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Geosci Front. 2021 Sep;12(5):101189. doi: 10.1016/j.gsf.2021.101189. Epub 2021 Apr 5.
2
Four-Month Changes in Air Quality during and after the COVID-19 Lockdown in Six Megacities in China.中国六个特大城市在新冠疫情封锁期间及之后空气质量的四个月变化
Environ Sci Technol Lett. 2020 Sep 9;7(11):802-808. doi: 10.1021/acs.estlett.0c00605. eCollection 2020 Nov 10.
3
Substantial Changes in Nitrate Oxide and Ozone after Excluding Meteorological Impacts during the COVID-19 Outbreak in Mainland China.
2014 - 2021年中国济南市空气质量变化及其影响因素
Toxics. 2023 Feb 24;11(3):210. doi: 10.3390/toxics11030210.
4
Human Health Risks and Air Quality Changes Following Restrictions for the Control of the COVID-19 Pandemic in Thailand.泰国实施COVID-19疫情防控限制措施后的人类健康风险与空气质量变化
Toxics. 2022 Aug 31;10(9):520. doi: 10.3390/toxics10090520.
排除气象影响后中国大陆新冠疫情期间一氧化氮和臭氧的显著变化。
Environ Sci Technol Lett. 2020 May 18;7(6):402-408. doi: 10.1021/acs.estlett.0c00304. eCollection 2020 Jun 9.
4
An improved decomposition method to differentiate meteorological and anthropogenic effects on air pollution: A national study in China during the COVID-19 lockdown period.一种区分气象和人为因素对空气污染影响的改进分解方法:中国新冠疫情封锁期间的全国性研究
Atmos Environ (1994). 2021 Apr 1;250:118270. doi: 10.1016/j.atmosenv.2021.118270. Epub 2021 Feb 17.
5
COVID-19 mortality and exposure to airborne PM: A lag time correlation.新冠死亡率与空气中 PM 暴露:滞后时间相关性。
Sci Total Environ. 2022 Feb 1;806(Pt 3):151286. doi: 10.1016/j.scitotenv.2021.151286. Epub 2021 Oct 29.
6
Diverse response of surface ozone to COVID-19 lockdown in China.中国地表臭氧对新冠疫情封锁措施的多样响应。
Sci Total Environ. 2021 Oct 1;789:147739. doi: 10.1016/j.scitotenv.2021.147739. Epub 2021 May 15.
7
The Role of Primary Emission and Transboundary Transport in the Air Quality Changes During and After the COVID-19 Lockdown in China.一次排放和跨界传输在中国新冠疫情封锁期间及之后空气质量变化中的作用
Geophys Res Lett. 2021 Apr;48(7):e2020GL091065. doi: 10.1029/2020GL091065. Epub 2021 Apr 9.
8
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9
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Geophys Res Lett. 2021 Feb 28;48(4):e2020GL091202. doi: 10.1029/2020GL091202. Epub 2021 Feb 16.
10
Comparison of air pollutants and their health effects in two developed regions in China during the COVID-19 pandemic.比较 COVID-19 大流行期间中国两个发达地区的空气污染物及其对健康的影响。
J Environ Manage. 2021 Jun 1;287:112296. doi: 10.1016/j.jenvman.2021.112296. Epub 2021 Mar 3.