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

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 stu...

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Bibliographic Details
Published in:Aerosol and air quality research 2021-08, Vol.21 (8), p.210020
Main Authors: Yu, Tai-Yi, Chao, How-Ran, Tsai, Ming-Hsien, Lin, Chih-Chung, Lu, I-Cheng, Chang, Wei-Hsiang, Chen, Chih-Cheng, Wang, Liang-Jen, Lin, En-Tzu, Chang, Ching-Tzu, Chen, Chunneng, Kao, Cheng-Chih, Wan Mansor, Wan Nurdiyana, Yu, Kwong-Leung J.
Format: Article
Language:English
Subjects:
Air pollution
Big Data
Coronaviruses
COVID-19
Data analysis
Disease transmission
Emissions
Industrial areas
Industrial plant emissions
Mortality
Nitrogen dioxide
Pandemics
Particulate matter
Population density
Quarantine
Segregation
Sensors
Severe acute respiratory syndrome
Severe acute respiratory syndrome coronavirus 2
Social distancing
Socioeconomic factors
Sulfur
Sulfur dioxide
Viral diseases
VOCs
Volatile organic compounds
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Summary: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 µg m–3) and 10.6% (from 32.4 to 29.3 µg 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.
ISSN:1680-8584
2071-1409
DOI:10.4209/aaqr.210020