Abstract
The lockdown measures enacted to control the COVID-19 pandemic in Wuhan, China, resulted in a suspension of nearly all non-essential human activities on January 23, 2020. Nevertheless, the lockdown provided a natural experiment to understand the consistency of the relationship between the urban form and air pollution with different compositions of locally or regionally transported sources. This study investigated the variations in six air pollutants (PM2.5, PM10, NO2, CO, O3, and SO2) in Wuhan before and during the lockdown and in the two same time spans in 2021. Moreover, a hierarchical agglomerative cluster analysis was conducted to differentiate the relative levels of pollutants and to detect the relationships between the air pollutants and the urban form during these four periods. Several features depicting the urban physical structures delivered consistent impacts. A lower building density and plot ratio, and a higher porosity always mitigated the concentrations of NO2 and PM2.5. However, they had inverse effects on O3 during the non-lockdown periods. PM10, CO, and SO2 concentrations have little correlation with the urban form. This study improves the comprehensive understanding of the effect of the urban form on ambient air pollution and suggests practical strategies for mitigating air pollution in Wuhan. © 2022 Elsevier Ltd.
| Original language | English |
|---|---|
| Article number | 103972 |
| Journal | Sustainable Cities and Society |
| Volume | 83 |
| Online published | 30 May 2022 |
| DOIs | |
| Publication status | Published - Aug 2022 |
| Externally published | Yes |
Funding
This study was supported by the National Natural Science Foundation of China (No. 51778251 & 51538004), and the Fundamental Research Funds for the Central Universities, HUST (No. 2021JYCXJJ009).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
Research Keywords
- COVID-19
- Air pollution
- Urban form
- Cluster analysis
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