Comparative Analysis of Spatial Distribution and Mechanism Differences Between Public Electric Vehicle Charging Stations and Traditional Gas Stations: A Case Study from Wenzhou, China

With the impact of fossil energy on the climate environment and the development of energy technologies, new energy vehicles, represented by electric cars, have begun to receive increasing attention and emphasis. The rapid proliferation of public charging infrastructure for NEVs has concurrently influenced traditional petrol station networks, creating measurable disparities in their spatial distributions that warrant systematic investigation. This research examines Wenzhou City, China, as a representative case area, employing multi-source Point of Interest (POI) data and spatial analysis models to analyse differential characteristics in spatial layout accessibility, service equity, and underlying driving mechanisms between public electric vehicle charging stations (EV) and traditional gas stations (GS). The findings reveal that public electric vehicle charging stations exhibit a pronounced “single-centre concentration with weak multi-centre linkage” spatial configuration, heavily reliant on dual-core drivers of population density and economic activity. This results in marked service accessibility declines in peripheral areas, resembling a cliff-like drop, and a relatively low spatial equity index. In contrast, traditional gas stations demonstrate a “core-axis linkage” diffusion pattern with strong coupling to urban road networks, showing gradient attenuation in service coverage efficiency along transportation arteries, fewer suburban service gaps, and more gradual accessibility reductions. Location entropy analysis further indicates that charging station deployment shows significant capital-oriented tendencies, with certain areas exhibiting paradoxical “excess facilities” phenomena, while gas station distribution aligns more closely with road network topology and transportation demand dynamics. Furthermore, the layout characteristics of public charging stations feature a more complex and diverse range of land use types, while traditional gas stations have a strong dependence on industrial land. This research elucidates the spatial distribution patterns of emerging and legacy energy infrastructure in the survey regions, providing critical empirical evidence for optimising energy infrastructure allocation and facilitating coordinated transportation system transitions. The findings also offer practical insights for the construction of energy supply facilities in urban development frameworks, holding substantial reference value for achieving sustainable urban spatial governance.

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Publication Details

Journal
Sustainability
Published
2025-09-05
DOI
https://doi.org/10.3390/su17178009
Citations
2
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
4.35
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article

Comparative Analysis of Spatial Distribution and Mechanism Differences Between Public Electric Vehicle Charging Stations and Traditional Gas Stations: A Case Study from Wenzhou, China

Wangyu Wu, Bo Tang, Aoyang Li, Bingcai Wei et al.
2 citations
Sustainability
Urban Transport and Accessibility
4.35
article

Comparative Analysis of Spatial Distribution and Mechanism Differences Between Public Electric Vehicle Charging Stations and Traditional Gas Stations: A Case Study from Wenzhou, China

Wangyu Wu, Bo Tang, Aoyang Li, Bingcai Wei, Chao Chen, Fei Wang, Jingmin Pan
article en
2 citations

Abstract

With the impact of fossil energy on the climate environment and the development of energy technologies, new energy vehicles, represented by electric cars, have begun to receive increasing attention and emphasis. The rapid proliferation of public charging infrastructure for NEVs has concurrently influenced traditional petrol station networks, creating measurable disparities in their spatial distributions that warrant systematic investigation. This research examines Wenzhou City, China, as a representative case area, employing multi-source Point of Interest (POI) data and spatial analysis models to analyse differential characteristics in spatial layout accessibility, service equity, and underlying driving mechanisms between public electric vehicle charging stations (EV) and traditional gas stations (GS). The findings reveal that public electric vehicle charging stations exhibit a pronounced “single-centre concentration with weak multi-centre linkage” spatial configuration, heavily reliant on dual-core drivers of population density and economic activity. This results in marked service accessibility declines in peripheral areas, resembling a cliff-like drop, and a relatively low spatial equity index. In contrast, traditional gas stations demonstrate a “core-axis linkage” diffusion pattern with strong coupling to urban road networks, showing gradient attenuation in service coverage efficiency along transportation arteries, fewer suburban service gaps, and more gradual accessibility reductions. Location entropy analysis further indicates that charging station deployment shows significant capital-oriented tendencies, with certain areas exhibiting paradoxical “excess facilities” phenomena, while gas station distribution aligns more closely with road network topology and transportation demand dynamics. Furthermore, the layout characteristics of public charging stations feature a more complex and diverse range of land use types, while traditional gas stations have a strong dependence on industrial land. This research elucidates the spatial distribution patterns of emerging and legacy energy infrastructure in the survey regions, providing critical empirical evidence for optimising energy infrastructure allocation and facilitating coordinated transportation system transitions. The findings also offer practical insights for the construction of energy supply facilities in urban development frameworks, holding substantial reference value for achieving sustainable urban spatial governance.

SustainabilityVol. 17(17)
University of Liverpool (GB), Sun Yat-sen University (CN), Wuhan University (CN), Wenzhou Vocational College of Science and Technology (CN), Anhui Xinhua University (CN), Guangzhou Xinhua University, Taiyuan University of Technology (CN)
Openalex Percentile: Top 6%
Urban Transport and Accessibility
4.35
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