Publication detail

Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour

Jiang, P., Fu, X., Fan, Y.V., Klemeš, J.J., Chen, P., Ma, S., Zhang, W.

Original Title

Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour

Type

journal article in Web of Science

Language

English

Original Abstract

Coronavirus disease-2019 (COVID-19) poses a significant threat to the population and urban sustainability worldwide. The surge mitigation is complicated and associates many factors, including the pandemic status, policy, socioeconomics and resident behaviours. Modelling and analytics with spatial-temporal big urban data are required to assist the mitigation of the pandemic. This study proposes a novel perspective to analyse the spatial-temporal potential exposure risk of residents by capturing human behaviours based on spatial-temporal car park availability data. Near real-time data from 1,904 residential car parks in Singapore, a classical megacity, are collected to analyse car mobility and its spatial-temporal heat map. The implementation of the circuit breaker, a COVID-19 measure, in Singapore has reduced the mobility and heat (daily frequency of mobility) significantly at about 30.0%. It contributes to a 44.3%–55.4% reduction in the transportation-related air emissions under two scenarios of travelling distance reductions. Urban sustainability impacts in both environment and economy are discussed. The spatial-temporal potential exposure risk mapping with space-time interactions is further investigated via an extended Bayesian spatial-temporal regression model. The maximal reduction rate of the defined potential exposure risk lowers to 37.6% by comparison with its peak value. The big data analytics of changes in car mobility behaviour and the resultant potential exposure risks can provide insights to assist in (a) designing a flexible circuit breaker exit strategy, (b) precise management via identifying and tracing hotspots on the mobility heat map, and (c) making timely decisions by fitting curves dynamically in different phases of COVID-19 mitigation. The proposed method has the potential to be used by decision-makers worldwide with available data to make flexible regulations and planning. © 2020 Elsevier Ltd

Keywords

Air-emission reduction; Car mobility behaviour; COVID-19; Flexible lockdown strategy; Risk mitigation; Spatial-temporal analysis

Authors

Jiang, P., Fu, X., Fan, Y.V., Klemeš, J.J., Chen, P., Ma, S., Zhang, W.

Released

10. 1. 2021

Publisher

Elsevier Ltd

ISBN

0959-6526

Periodical

Journal of Cleaner Production

Number

279

State

United Kingdom of Great Britain and Northern Ireland

Pages from

123673

Pages to

123673

Pages count

13

URL

https://www.sciencedirect.com/science/article/pii/S0959652620337185?via%3Dihub

BibTex

@article{BUT167964,
  author="Yee Van {Fan} and Jiří {Klemeš}",
  title="Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour",
  journal="Journal of Cleaner Production",
  year="2021",
  number="279",
  pages="123673--123673",
  doi="10.1016/j.jclepro.2020.123673",
  issn="0959-6526",
  url="https://www.sciencedirect.com/science/article/pii/S0959652620337185?via%3Dihub"
}