Big Data Analysis for Effects of the COVID-19 Outbreak on Ambient PM2.5 in Areas that Were Not Locked Down

被引:6
|
作者
Yu, Tai-Yi [1 ]
Chao, How-Ran [2 ,3 ,4 ,5 ]
Tsai, Ming-Hsien [6 ]
Lin, Chih-Chung [2 ]
Lu, I-Cheng [2 ]
Chang, Wei-Hsiang [7 ]
Chen, Chih-Cheng [8 ,9 ]
Wang, Liang-Jen [9 ,10 ]
Lin, En-Tzu [2 ]
Chang, Ching-Tzu [3 ]
Chen, Chunneng [11 ]
Kao, Cheng-Chih [12 ]
Mansor, Wan Nurdiyana Wan [13 ,14 ]
Yu, Kwong-Leung J. [12 ,15 ]
机构
[1] Ming Chuan Univ, Dept Risk Management & Insurance, Taipei 111, Taiwan
[2] Natl Pingtung Univ Sci & Technol, Coll Engn, Dept Environm Sci & Engn, Pingtung 912, Taiwan
[3] Natl Pingtung Univ Sci & Technol, Coll Agr, Inst Food Safety Management, Pingtung 912, Taiwan
[4] Natl Pingtung Univ Sci & Technol, Emerging Cpds Res Ctr, Gen Res Serv Ctr, Pingtung 912, Taiwan
[5] Kaohsiung Med Univ, Coll Dent Med, Sch Dent, Kaohsiung 80708, Taiwan
[6] Natl Pingtung Univ Sci & Technol, Coll Humanities & Social Sci, Dept Child Care, Pingtung 912, Taiwan
[7] Natl Cheng Kung Univ, Dept Food Safety Hyg & Risk Management, Tainan 70101, Taiwan
[8] Kaohsiung Chang Gung Mem Hosp, Dept Pediat, Sect Neonatol, Kaohsiung 83347, Taiwan
[9] Chang Gung Univ, Coll Med, Kaohsiung 83347, Taiwan
[10] Kaohsiung Chang Gung Mem Hosp, Dept Child & Adolescent Psychiat, Kaohsiung 83347, Taiwan
[11] JS Environm Technol & Energy Saving Co Ltd, Kaohsiung 806, Taiwan
[12] Pingtung Christian Hosp, Superintendent Off, Pingtung 90053, Taiwan
[13] Univ Malaysia Terengganu, Fac Ocean Engn Technol & Informat, Terengganu 21300, Malaysia
[14] Univ Malaysia Terengganu, Air Qual & Environm Res Grp, K Nerus 21300, Malaysia
[15] Kaohsiung Med Univ, Coll Med, Dept Anesthesiol, Kaohsiung 80708, Taiwan
关键词
COVID-19; SARS-CoV-2; PM2.5; Low-cost sensors; Domestic emission; Big data; AIR-POLLUTION; QUALITY; LOCKDOWN; CITIES; IMPACT;
D O I
10.4209/aaqr.210020
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
COVID-19, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first broke out at the end of 2019. Despite rapidly spreading around the world during the first half of 2020, it remained well controlled in Taiwan without the implementation of a nationwide lockdown. This study aimed to evaluate the PM2.5 concentrations in this country during the 2020 COVID-19 pandemic and compare them with those during the corresponding period from 2019. We obtained measurements (taken every minute or every 3 minutes) from approximately 1,500 PM2.5 sensors deployed in industrial areas of northern and southern Taiwan for the first quarters (January-March) of both years. Our big data analysis revealed that the median hourly PM2.5 levels decreased by 3.70% (from 16.3 to 15.7 mu g m(-3)) and 10.6% (from 32.4 to 29.3 mu g m(-3)) in the north and south, respectively, between these periods owing to lower domestic emissions of PM2.5 precursors (viz., nitrogen dioxide and sulfur dioxide) and, to a lesser degree, smaller transported emissions of PM2.5, e.g., from China. Additionally, the spatial patterns of the PM2.5 in both northern and southern Taiwan during 2020 resembled those from the previous year. Finally, controlling local PM2.5 emission sources critically contributes to reducing the number of COVID-19 cases.
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页数:17
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