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[中国运输碳排放相关联网络的时空动力学和驱动机制]

Chen Zhang¹, Xiu-Ting Wang², Qing Yang¹

¹School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China.

Huan jing ke xue= Huanjing kexue

|January 14, 2026

概括

中国的运输碳排放网络显示出强大的历史影响和空间聚类,核心省份占主导地位. 经济差异和时空相互作用显著推动了这些模式,需要协调的区域碳减排战略.

科学领域:

环境科学与政策环境科学与政策
运输地理交通地理
网络分析网络分析

背景情况:

了解省际运输碳排放网络对于有效的碳减排和中国协调的区域战略至关重要.
之前的研究还没有完全捕捉到中国运输碳排放网络中复杂的时空动态和驱动机制.

研究的目的:

探索2003年至2021年中国省际运输碳排放相关联网络的时空动态演变,相互作用特征和驱动机制.
确定关键的省份,空间模式和影响因素,以告知协调的碳减排政策.

主要方法:

员工使用二次性分配程序 (QAP) 和社交网络分析 (SNA) 来分析网络结构和演变.
利用探索性时空数据分析 (ESTDA) 和多重回归二次赋值程序 (MRQAP) 来调查驱动机制和空间依赖.

主要成果:

网络结构表现出显著的"时间惯性",未来模式受到历史趋势的严重影响,并显示出明显的空间异质性和集群.
核心省份 (山东,江苏,广东,上海) 发挥了主导作用,而强大的省际合作关系 (84.6%) 与特定地区的显著竞争并存.
经济差异和时空相互作用对网络产生了积极的影响,而工业和交通结构的差异则对网络产生了负面影响.

结论:

中国的运输碳排放网络的特点是结构锁定,过渡惯性和显著的时空依赖.
有效的区域碳减排需要区域间协调,差异化政策和战略运输网络规划.
解决经济差异和优化时空相互作用是减轻运输碳排放的关键.

关键词:

驱动机制的驱动机制探索空间时间数据分析 (ESTDA)多重回归二次赋值程序 (MRQAP) 模型空间和时间的动态.运输碳排放运输碳排放

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