TY - JOUR
T1 - The impact of high-speed rail on urban carbon emissions
T2 - Evidence from the Yangtze River Delta
AU - Tang, Zhaopei
AU - Wang, Liehui
AU - Wu, Wei
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/6
Y1 - 2023/6
N2 - Clarifying the relationship between high-speed rail (HSR) and a city's carbon emissions is the critical premise behind transportation decarbonization and China's carbon target. Based on HSR's operational data, total carbon emissions data, and socio-economic statistics, this study examines how HSR affects a city's carbon emissions and the varying effects among different categories of cities using the Spatial Difference-In-Difference model from both static and dynamic perspectives. HSR would decrease a city's carbon emissions through the scale effect under the influence of the complex external and internal environment and the resulting uncertainty, with both substitution and stimulation. We find that, at the static level, the operation of HSR in cities with HSR stations, can statistically reduce carbon emissions by 0.58% at the 1% level. It also reduces the carbon emissions of neighboring cities' to a greater extent through the spillover effect, which is characterized by being multi-directional and multi-processed. The dynamic effect of HSR is related to its three-stage phase development, including the start-up phase, the expansion phase, and the intensification phase, which is characterized by a significant time lag. The intensity of HSR's carbon reduction effect on cities tends to increase initially and then decrease, as the HSR network improves and gradually reaches saturation. The impact of HSR on a city's carbon emissions varies with city characteristics, including economic growth, industrial structure, and city population. These findings can theoretically and empirically support the carbon reduction effect of HSR, and provide important decision-making reference for HSR construction driven by China's carbon target.
AB - Clarifying the relationship between high-speed rail (HSR) and a city's carbon emissions is the critical premise behind transportation decarbonization and China's carbon target. Based on HSR's operational data, total carbon emissions data, and socio-economic statistics, this study examines how HSR affects a city's carbon emissions and the varying effects among different categories of cities using the Spatial Difference-In-Difference model from both static and dynamic perspectives. HSR would decrease a city's carbon emissions through the scale effect under the influence of the complex external and internal environment and the resulting uncertainty, with both substitution and stimulation. We find that, at the static level, the operation of HSR in cities with HSR stations, can statistically reduce carbon emissions by 0.58% at the 1% level. It also reduces the carbon emissions of neighboring cities' to a greater extent through the spillover effect, which is characterized by being multi-directional and multi-processed. The dynamic effect of HSR is related to its three-stage phase development, including the start-up phase, the expansion phase, and the intensification phase, which is characterized by a significant time lag. The intensity of HSR's carbon reduction effect on cities tends to increase initially and then decrease, as the HSR network improves and gradually reaches saturation. The impact of HSR on a city's carbon emissions varies with city characteristics, including economic growth, industrial structure, and city population. These findings can theoretically and empirically support the carbon reduction effect of HSR, and provide important decision-making reference for HSR construction driven by China's carbon target.
KW - Carbon emission
KW - Climate change
KW - High-speed rail
KW - Spatial difference-in-difference model
KW - The Yangtze River Delta
UR - https://www.scopus.com/pages/publications/85163969044
U2 - 10.1016/j.jtrangeo.2023.103641
DO - 10.1016/j.jtrangeo.2023.103641
M3 - 文章
AN - SCOPUS:85163969044
SN - 0966-6923
VL - 110
JO - Journal of Transport Geography
JF - Journal of Transport Geography
M1 - 103641
ER -