Abstract

In this study, we assessed air quality (AQ) and urban climate during the mobility restrictions implemented in the Greater Tokyo Area, Japan, the world’s most populated region, in response to the COVID-19 pandemic. Observations from dense surface networks were analyzed using an interpretable machine learning approach. In parallel with a ∼50% reduction in mobility and an altered lifestyle of the population, we found limited reductions in nitrogen dioxide; decreases in fine particulate matter not entirely driven by local mobility; minor variations in ozone, with a positive (negative) tendency in areas with high (low) emissions; a decrease in air temperature consistent with mobility; and pollution levels and air temperature changes with well-defined, common spatiotemporal patterns. Specifically, cooling mainly occurred in urbanized areas with an improved AQ. Overall, although reductions in mobility were moderately effective in improving the typical indicators of urban AQ, including those known to negatively impact human health, the reductions in waste heat had a stronger impact on Tokyo’s urban heat island, suggestive of a strategy to minimize exposure to heat stress. These findings can help guide urban planning strategies and policies aimed at addressing climate change.

Details

Title
Air quality and urban climate improvements in the world’s most populated region during the COVID-19 pandemic
Author
Damiani, Alessandro 1 ; Irie, Hitoshi 2 ; Belikov, Dmitry 2   VIAFID ORCID Logo  ; Cordero, Raul R 3   VIAFID ORCID Logo  ; Feron, Sarah 4   VIAFID ORCID Logo  ; Ishizaki, Noriko N 1 

 Center for Climate Change Adaptation, National Institute for Environmental Studies , Tsukuba, Japan 
 Center for Environmental Remote Sensing, Chiba University , Chiba, Japan 
 Universidad de Santiago de Chile , Santiago, Chile 
 Universidad de Santiago de Chile , Santiago, Chile; University of Groningen , Leeuwarden, The Netherlands 
First page
034023
Publication year
2024
Publication date
Mar 2024
Publisher
IOP Publishing
e-ISSN
17489326
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2929137514
Copyright
© 2024 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.