[中国交通运输业碳强度的时空互动特征与转换机制]。

Q2 Environmental Science Huanjing Kexue/Environmental Science Pub Date : 2024-06-08 DOI:10.13227/j.hjkx.202310194
Jian Li, Shu-Qi Liu, Xiao-Qi Wang
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引用次数: 0

摘要

本研究采用多种空间分析方法,剖析了 2002 年至 2020 年交通领域碳排放强度的时空互动特征。通过将获得的时间序列类型与面板量化模型嵌套,对其过渡机制进行了深入探讨。最后,采用与不同过渡机制相匹配的地理向量模型,研究分析了交通行业碳排放强度各影响因素之间的交互效应。结果表明:①全国 30 个省区交通运输业碳排放强度总体呈波动下降趋势,空间集聚水平相对稳定。② ESTDA 的时空交互特征显示,西北地区与相邻空间单元的关系不稳定,存在明显的变化和波动。相比之下,东部沿海城市等经济发达地区建立了成熟的交通网络,形成了相对稳定的局部空间格局,但仍有少数地区表现出时空竞争性。交通部门碳强度的时空转换可分为四种驱动或约束模式(人口经济城市化约束模式、人口经济城市化设施约束模式、技术消费产业驱动模式、技术产业规制驱动模式)。大部分省份受低量化约束模式和高量化驱动模式的影响,只有少数省份受高量化约束模式和低量化驱动模式的影响,这些省份大部分位于西北或西南地区。在此基础上,我们引入了基于交通领域碳排放强度转换机制的地理探测模型,强调多要素协调发展,加强区域间协同治理。
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[Spatiotemporal Interaction Characteristics and Transition Mechanism of Carbon Intensity in China's Transportation Industry].

This research was conducted using many spatial analysis approaches to dissect the spatiotemporal interactive characteristics of carbon emission intensity within the transportation sector from 2002 to 2020. An in-depth exploration of their transition mechanisms was conducted by nesting the obtained timewarp types with the panel quantile model. Finally, the geodetector model aligned with different transition mechanisms was employed to investigate and analyze the interaction effects among various factors influencing carbon intensity in the transportation sector. The results indicated that:① The carbon emission intensity of the transportation sector in 30 provinces and regions of China showed an overall downward trend with fluctuations, and the spatial clustering level was relatively stable. ② The spatiotemporal interactive features of ESTDA revealed that the relationship between the northwest region and its adjacent spatial units was unstable, with significant variations and fluctuations. In contrast, economically developed areas such as coastal cities in the eastern part had established mature transportation networks, resulting in a relatively stable local spatial pattern, though a few areas still exhibited spatiotemporal competitiveness. ③ The spatiotemporal transition of carbon intensity in the transportation sector could be categorized into four driving or constraining modes(the population economy urbanization constraint model, population economy urbanization facility constraint model, technology consumption industry-driven model, and technology industry regulation-driven model). Most provinces were influenced by the low quantile constraint and high quantile drive modes, with only a few affected by the high quantile constraint and low quantile drive modes, the majority of which were located in the northwest or southwest regions. ④ Further, we introduced the geographical detector model based on the identified mechanism of carbon emission intensity transition in the transportation sector, emphasizing the coordinated development of multiple factors and strengthening inter-regional collaborative governance.

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来源期刊
Huanjing Kexue/Environmental Science
Huanjing Kexue/Environmental Science Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
期刊最新文献
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