Impacts of multi-scale built environment on transportation carbon emissions: A Guangzhou case

Document Type

Journal Article

Publication Date

2026

Subject Area

place - asia, place - urban, mode - subway/metro, mode - bus, mode - car, technology - emissions, policy - environment, land use - impacts, land use - planning, ridership - behaviour, ridership - commuting, ridership - mode choice, planning - environmental impact

Keywords

public transportation, accessibility, transportation carbon emissions (TCE)

Abstract

While the built environment is recognized as a key driver of transportation carbon emissions (TCE), the multi-scale mechanisms linking urban spatial structures to TCE variations across different travel purposes remain underexplored. Clarifying these relationships is critical for designing targeted low-carbon policies at appropriate spatial scales. Through the implementation of spatial analysis and regression models, this study examined the spatial distribution patterns of TCE across diverse travel purposes and temporal spans, considering multiple living circles. Encompassing 30 community samples in Guangzhou, the findings revealed that residents' TCE showed a multicentre agglomeration with hotspots converging towards the city centre across various travel purposes and time spans. High TCE levels were mainly found in commercial, premium commercial, and unit housing communities on both sides of the Pearl River. In contrast, low TCE levels were in core areas (traditional neighbourhoods) or urban peripheries (urban villages). Accessibility and public transportation significantly influenced TCE more than other built environment factors. At the community scale, a positive relationship existed between the distance to the nearest bus stop and TCE. Differences emerged based on scale and travel purpose, such as a negative significance between the number of subway stations and TCE within a 5 - and 10-minute living circle for weekend travel but not for other scales. Sociodemographic factors, including marital status, employment, education, income, homeownership, driver’s licence, and vehicle ownership significantly influenced TCE.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

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