eCite Digital Repository
Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: implications for climate change
Citation
Su, F and Fu, D and Yan, F and Xiao, H and Pan, T and Xiao, Y and Kang, L and Zhou, C and Meadows, M and Lyne, V and Wilson, JP and Zhao, N and Yang, X and Liu, G, Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: implications for climate change, Science Advances, 7, (35) Article eabe8044. ISSN 2375-2548 (2021) [Refereed Article]
 | PDF (Published version) 4Mb |
Copyright Statement
Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons 4.0 International (CC BY 4.0) Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
DOI: doi:10.1126/sciadv.abe8044
Abstract
The 2019 novel coronavirus pandemic (COVID-19) negatively affected global public health and socioeconomic development. Lockdowns and travel restrictions to contain COVID-19 resulted in reduced human activity and decreased anthropogenic emissions. However, the secondary effects of these restrictions on the biophysical environment are uncertain. Using remotely sensed big data, we investigated how lockdowns and traffic restrictions affected China's spring vegetation in 2020. Our analyses show that travel decreased by 58% in the first 18 days following implementation of the restrictions across China. Subsequently, atmospheric optical clarity increased and radiation levels on the vegetation canopy were augmented. Furthermore, the spring of 2020 arrived 8.4 days earlier and vegetation 17.45% greener compared to 2015-2019. Reduced human activity resulting from COVID-19 restrictions contributed to a brighter, earlier, and greener 2020 spring season in China. This study shows that short-term changes in human activity can have a relatively rapid ecological impact at the regional scale.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | COVID-19, climate change, phenology, big data, atmospheric pollution |
| Research Division: | Earth Sciences |
| Research Group: | Climate change science |
| Research Field: | Climate change processes |
| Objective Division: | Environmental Management |
| Objective Group: | Air quality, atmosphere and weather |
| Objective Field: | Air quality |
| UTAS Author: | Lyne, V (Dr Vincent Lyne) |
| ID Code: | 147876 |
| Year Published: | 2021 |
| Web of Science® Times Cited: | 2 |
| Deposited By: | Fisheries and Aquaculture |
| Deposited On: | 2021-11-19 |
| Last Modified: | 2021-12-08 |
| Downloads: | 4 View Download Statistics |
Repository Staff Only: item control page