Work

Spatiotemporal associations between the built environment and carbon emission reduction potential of shared on-demand transit

Year: 2026

Type: article

Abstract: Shared on-demand transit has emerged as a promising mobility solution for reducing transport-related carbon emissions and supporting more sustainable urban environments. However, limited evidence exists on how built environment characteristics are associated with its carbon emission reduction potential across space and time. This study aimed to quantify the maximum carbon emission reduction achievable through ODT and identify the built environment factors associated with its spatial variation. An integer linear programming model combined with a multi-passenger travel optimization framework was developed to estimate achievable carbon emission reductions using travel demand data. An XGBoost model was then used to examine their relationships with built environment characteristics, while SHAP and partial dependence analyses were employed to interpret nonlinear, threshold, and spatially heterogeneous relationships. The results showed that ODT could reduce carbon emissions by up to 17.67% in the morning and 14.48% in the evening. Built environment characteristics exhibited pronounced spatiotemporal heterogeneity, with employment- and education-related land uses showing higher nonlinear thresholds in the evening than in the morning. Local interpretation further revealed substantial spatial variation in feature contributions, with areas surrounding educational facilities, employment centers, and suburban metro stations associated with greater carbon emission reduction potential. These findings provide spatial evidence for targeted ODT implementation and highlight the potential of built environment characteristics to inform low-carbon mobility strategies and sustainable urban transport planning.

Source: Frontiers in Public Health

DOI: 10.3389/fpubh.2026.1927997

Authors: Xiaofan Wei, Zhe Zhang, Chao Li, Meigen Xue, Hongdi He

Institutions: Shanghai Jiao Tong University, State Key Laboratory of Ocean Engineering, Tsinghua University, Chang'an University, Shanghai Urban Construction Design and Research Institute (Group)

Language: English

Topic: Transportation and Mobility Innovations

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $3,801