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Examining the long-term reduction in commuting emissions from working from home
Södertörn University, School of Social Sciences, Sociology. University of Dublin, Ireland.ORCID iD: 0000-0003-2366-7740
University of Dublin, Ireland; National Transport Authority of Ireland, Ireland.
University of Dublin, Ireland; National Transport Authority of Ireland, Ireland.
National Transport Authority of Ireland, Ireland.
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2024 (English)In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 127, article id 104063Article in journal (Refereed) Published
Abstract [en]

To develop effective climate strategies, it is necessary to model the long-term impacts of combined policy measures. This study examines how an increase in working-from-home (WFH) practices, coupled with higher private car fleet penetration of electric vehicles (EVs), could change commuting patterns and associated emissions. Simulations for the Dublin Region show that if half of white-collar workers were WFH and EVs made up one-third of the fleet as forecasted for 2030, emissions from travel activities could be reduced by up to 35% for carbon dioxide (CO2) and 25% for particulate matter (PM). However, transitioning from a moderate to a high WFH scenario may not deliver significant benefits in terms of travel length, modal shift, and emissions reduction. In addition, a decrease in commuter trips can lead to an increase in other trips. This suggests that there is a need for additional measures to discourage car usage when commuter trips decline.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 127, article id 104063
Keywords [en]
COVID-19, Electric vehicle, Greenhouse gas emissions, Scenario analysis, Telecommuting, Transport modelling, Working from home, Carbon dioxide, Climate models, Electric vehicles, Emission control, Fleet operations, Gas emissions, Greenhouse gases, % reductions, Long-term impacts, Policy measures, Private cars, Scenarios analysis, Travel activities, Workers'
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:sh:diva-53331DOI: 10.1016/j.trd.2024.104063ISI: 001163606100001Scopus ID: 2-s2.0-85182508036OAI: oai:DiVA.org:sh-53331DiVA, id: diva2:1830584
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-06-26Bibliographically approved

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Stefaniec, Agnieszka

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • sodertorns-hogskola-harvard.csl
  • sodertorns-hogskola-oxford.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf