Abstract
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.
| Original language | English |
|---|---|
| Article number | 210020 |
| Journal | Aerosol and Air Quality Research |
| Volume | 21 |
| Issue number | 8 |
| DOIs | |
| State | Published - 08 2021 |
Bibliographical note
Publisher Copyright:© The Author(s).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- Big data
- COVID-19
- Domestic emission
- Low-cost sensors
- PM
- SARS-CoV-2
Fingerprint
Dive into the research topics of 'Big data analysis for effects of the covid-19 outbreak on ambient PM2.5 in areas that were not locked down'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver