File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Quantifying the spillover elasticities of urban built environment configurations on the adjacent traffic CO2 emissions in mainland China

TitleQuantifying the spillover elasticities of urban built environment configurations on the adjacent traffic CO<inf>2</inf> emissions in mainland China
Authors
KeywordsBuilt environment configurations
Spatial autoregressive model
Traffic CO emission 2
Issue Date2021
Citation
Applied Energy, 2021, v. 283, article no. 116271 How to Cite?
AbstractUrban built environment regulations can effectively mitigate traffic CO2 emissions. Thus, it is critical to quantify the elasticities of altering built environment configurations. To address this issue, we have built nationwide spatial autoregressive models to differentiate between localized and spillover effects across 325 Chinese cities in the years of 2005 and 2015. Our results indicate that a 1% increase in built-up areas’ size, compactness, and isolation is associated with increases of 0.35%, −0.14%, and 0.13%, respectively, in adjacent traffic CO2 emissions. The underlying reason is that the spatial configurations of built environment do not only systemically affect the probability, frequency, speed, and distance of intracity motorised travels, but also have impacts on the intercity transboundary mobility of motor vehicles. In addition, the built-up areas’ compactness effect has an antagonistic relation with the per capita GDP effect. Thus, our findings provide evidence that the built environment configuration-related measures can benefit traffic CO2 emission reductions in adjacent cities. It is therefore necessary for policymakers to make a traffic CO2 mitigation strategy at the city agglomeration level.
Persistent Identifierhttp://hdl.handle.net/10722/333482
ISSN
2021 Impact Factor: 11.446
2020 SCImago Journal Rankings: 3.035

 

DC FieldValueLanguage
dc.contributor.authorSong, Weize-
dc.contributor.authorZhang, Xiaoling-
dc.contributor.authorAn, Kangxin-
dc.contributor.authorYang, Tao-
dc.contributor.authorLi, Heng-
dc.contributor.authorWang, Can-
dc.date.accessioned2023-10-06T05:19:42Z-
dc.date.available2023-10-06T05:19:42Z-
dc.date.issued2021-
dc.identifier.citationApplied Energy, 2021, v. 283, article no. 116271-
dc.identifier.issn0306-2619-
dc.identifier.urihttp://hdl.handle.net/10722/333482-
dc.description.abstractUrban built environment regulations can effectively mitigate traffic CO2 emissions. Thus, it is critical to quantify the elasticities of altering built environment configurations. To address this issue, we have built nationwide spatial autoregressive models to differentiate between localized and spillover effects across 325 Chinese cities in the years of 2005 and 2015. Our results indicate that a 1% increase in built-up areas’ size, compactness, and isolation is associated with increases of 0.35%, −0.14%, and 0.13%, respectively, in adjacent traffic CO2 emissions. The underlying reason is that the spatial configurations of built environment do not only systemically affect the probability, frequency, speed, and distance of intracity motorised travels, but also have impacts on the intercity transboundary mobility of motor vehicles. In addition, the built-up areas’ compactness effect has an antagonistic relation with the per capita GDP effect. Thus, our findings provide evidence that the built environment configuration-related measures can benefit traffic CO2 emission reductions in adjacent cities. It is therefore necessary for policymakers to make a traffic CO2 mitigation strategy at the city agglomeration level.-
dc.languageeng-
dc.relation.ispartofApplied Energy-
dc.subjectBuilt environment configurations-
dc.subjectSpatial autoregressive model-
dc.subjectTraffic CO emission 2-
dc.titleQuantifying the spillover elasticities of urban built environment configurations on the adjacent traffic CO<inf>2</inf> emissions in mainland China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.apenergy.2020.116271-
dc.identifier.scopuseid_2-s2.0-85097090037-
dc.identifier.volume283-
dc.identifier.spagearticle no. 116271-
dc.identifier.epagearticle no. 116271-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats