Do Vehicle Restrictions on Urban Expressways Reduce Carbon Emissions Across the Urban Road Network? Short-Run and Longer-Run Evidence from Shanghai

Vehicle restrictions on urban expressways are widely used to relieve traffic congestion and reduce traffic emissions. However, the effects of such restrictions should be assessed over the wider urban road network rather than on expressways alone, and over both short-run and longer-run periods. This study empirically investigates the impacts of vehicle restriction policies on network-level emissions in Shanghai. The network-level vehicle emissions are dynamically estimated using a carbon-emissions macroscopic fundamental diagram (CE-MFD) model based on taxi trajectory data and loop detector data. The effects are then identified using a spatial difference-in-differences (SDID) framework, while geographically weighted regression (GWR) is used to examine spatial heterogeneity in the associated factors. The results show that extending the restriction periods reduced carbon emissions across the urban road network by 9.96% after one month and by 17.93% after one year. The effects are spatially heterogeneous and are associated with population, road-network characteristics, parking supply, and ramp configuration. These findings suggest that the sustainability impacts depend not only on the restrictions themselves, but also on traffic redistribution and local network conditions. Findings provide empirical evidence for designing sustainability-oriented traffic strategies, underscoring the importance of evaluating emissions outcomes across the urban road network over both short-run and longer-run horizons.

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Publication Details

Journal
Sustainability
Published
2026-06-24
DOI
https://doi.org/10.3390/su18136455
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
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article

Do Vehicle Restrictions on Urban Expressways Reduce Carbon Emissions Across the Urban Road Network? Short-Run and Longer-Run Evidence from Shanghai

Yizhe Huang, Shuichao Zhang, Chaomin Liu, Alica Kalašová et al.
Sustainability
Vehicle emissions and performance
article

Do Vehicle Restrictions on Urban Expressways Reduce Carbon Emissions Across the Urban Road Network? Short-Run and Longer-Run Evidence from Shanghai

Yizhe Huang, Shuichao Zhang, Chaomin Liu, Alica Kalašová, Chengying Hua, Yibin Zhang
article en

Abstract

Vehicle restrictions on urban expressways are widely used to relieve traffic congestion and reduce traffic emissions. However, the effects of such restrictions should be assessed over the wider urban road network rather than on expressways alone, and over both short-run and longer-run periods. This study empirically investigates the impacts of vehicle restriction policies on network-level emissions in Shanghai. The network-level vehicle emissions are dynamically estimated using a carbon-emissions macroscopic fundamental diagram (CE-MFD) model based on taxi trajectory data and loop detector data. The effects are then identified using a spatial difference-in-differences (SDID) framework, while geographically weighted regression (GWR) is used to examine spatial heterogeneity in the associated factors. The results show that extending the restriction periods reduced carbon emissions across the urban road network by 9.96% after one month and by 17.93% after one year. The effects are spatially heterogeneous and are associated with population, road-network characteristics, parking supply, and ramp configuration. These findings suggest that the sustainability impacts depend not only on the restrictions themselves, but also on traffic redistribution and local network conditions. Findings provide empirical evidence for designing sustainability-oriented traffic strategies, underscoring the importance of evaluating emissions outcomes across the urban road network over both short-run and longer-run horizons.

SustainabilityVol. 18(13)
Ningbo University of Technology (CN), University of Žilina (SK), Vyskumny Ústav Dopravny (SK)
Openalex Percentile: Top 10%
Vehicle emissions and performance
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