Shopping mobility and travel carbon emissions among suburban residents: lessons from Shenyang city, China

Jing Li; Kevin Lo; Pingyu Zhang

doi:10.1080/14498596.2018.1453883

Shopping mobility and travel carbon emissions among suburban residents: lessons from Shenyang city, China

Jing Li^*
, Kevin Lo
, Pingyu Zhang

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

1 Citation (Scopus)

Abstract

This research examined the link between shopping mobility and travel CO₂ emissions among suburban residents in Shenyang, China. We found suburban residents travelled 14.33 km and produced 1111.32 g of CO₂ per shopping trip. The high emitters are mostly located at the urban fringe, travelling long distances and having a stronger dependency on cars. Furthermore, we used a binary logistic regression model to discover the main factors statistically significant in explaining private car usage. Evidence from this research indicates the need to formulate sustainable transport policies and reduce carbon emissions through compact urban forms and transit-oriented development.

Original language	English
Pages (from-to)	311-323
Number of pages	13
Journal	Journal of Spatial Science
Volume	63
Issue number	2
DOIs	https://doi.org/10.1080/14498596.2018.1453883
Publication status	Published - 3 Jul 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities
SDG 13 Climate Action

User-Defined Keywords

shopping mobility
suburban residents
Transport carbon emission
travel behaviour

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10.1080/14498596.2018.1453883

Cite this

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title = "Shopping mobility and travel carbon emissions among suburban residents: lessons from Shenyang city, China",

abstract = "This research examined the link between shopping mobility and travel CO2 emissions among suburban residents in Shenyang, China. We found suburban residents travelled 14.33 km and produced 1111.32 g of CO2 per shopping trip. The high emitters are mostly located at the urban fringe, travelling long distances and having a stronger dependency on cars. Furthermore, we used a binary logistic regression model to discover the main factors statistically significant in explaining private car usage. Evidence from this research indicates the need to formulate sustainable transport policies and reduce carbon emissions through compact urban forms and transit-oriented development.",

keywords = "shopping mobility, suburban residents, Transport carbon emission, travel behaviour",

author = "Jing Li and Kevin Lo and Pingyu Zhang",

note = "Funding Information: This work was supported by grants from the National Natural Science Foundation of China [grant number 41771179], [grant number 41571152], [grant number 41401478], [grant number 41201159], Strategic Planning Project from the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences [grant number Y6H2091001]; Key Research Program of the Chinese Academy of Sciences [grant number KSZD-EW-Z-021-03].",

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doi = "10.1080/14498596.2018.1453883",

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T1 - Shopping mobility and travel carbon emissions among suburban residents

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AU - Lo, Kevin

AU - Zhang, Pingyu

N1 - Funding Information: This work was supported by grants from the National Natural Science Foundation of China [grant number 41771179], [grant number 41571152], [grant number 41401478], [grant number 41201159], Strategic Planning Project from the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences [grant number Y6H2091001]; Key Research Program of the Chinese Academy of Sciences [grant number KSZD-EW-Z-021-03].

PY - 2018/7/3

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N2 - This research examined the link between shopping mobility and travel CO2 emissions among suburban residents in Shenyang, China. We found suburban residents travelled 14.33 km and produced 1111.32 g of CO2 per shopping trip. The high emitters are mostly located at the urban fringe, travelling long distances and having a stronger dependency on cars. Furthermore, we used a binary logistic regression model to discover the main factors statistically significant in explaining private car usage. Evidence from this research indicates the need to formulate sustainable transport policies and reduce carbon emissions through compact urban forms and transit-oriented development.

AB - This research examined the link between shopping mobility and travel CO2 emissions among suburban residents in Shenyang, China. We found suburban residents travelled 14.33 km and produced 1111.32 g of CO2 per shopping trip. The high emitters are mostly located at the urban fringe, travelling long distances and having a stronger dependency on cars. Furthermore, we used a binary logistic regression model to discover the main factors statistically significant in explaining private car usage. Evidence from this research indicates the need to formulate sustainable transport policies and reduce carbon emissions through compact urban forms and transit-oriented development.

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KW - suburban residents

KW - Transport carbon emission

KW - travel behaviour

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DO - 10.1080/14498596.2018.1453883

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JF - Journal of Spatial Science

IS - 2

ER -

Shopping mobility and travel carbon emissions among suburban residents: lessons from Shenyang city, China

Abstract

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