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Spatial and temporal patterns of impact of transportation informatization on transportation carbon emissions in provinces along the Belt and Road in China |
SHI Jing-jing1, ZHAO Hong-xing1, NIE Jiang-long2, HE Rui-chun1, LIU Ping3 |
1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China; 2. Construction Division of State Grid Gansu Province Electric Power Company, Lanzhou 730000, China; 3. Troop 69245, Urumqi 830000, China |
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Abstract The administrative units of 17provinces along the Belt and Road in China were selected as basic spatial units. Firstly, the evaluation index system for transportation informatization along the Belt and Road from 2012 to 2022 was established. Secondly, a bivariate spatial correlation analysis was conducted to explore the relationship between transportation informatization and transportation carbon emissions. Lastly, a geographical detector was employed to investigate the spatial-temporal heterogeneity of the impact of transportation informatization on transportation carbon emissions. The results indicated varying levels of transportation informatization development among provinces along the Belt and Road, with more mature developments observed in external window regions and pioneering open areas, while relatively lagging in the Silk Road core area and strategic fulcrum regions. The bivariate spatial autocorrelation index ranged from 0.1917 to 0.4001, exhibiting an overall downward trend, with significance levels ranging from 0.008 to 0.060. High-high clusters were primarily distributed in pioneering open areas, low-low clusters in the Silk Road core area, and high-low clusters in external window regions and strategic fulcrum regions, with an increasing number of provinces falling into the latter category over time. The application of transportation informatization systems emerged as the dominant driving factor influencing the spatial differentiation pattern of overall transportation carbon emissions along the Belt and Road, with a maximum average determinant power of 0.53. Differences existed in the driving factors influencing spatial differentiation of transportation carbon emissions among different provinces, and there was strong synergy among these factors.
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Received: 22 February 2024
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