[影响 "一带一路 "沿线省份交通碳排放因素的时空异质性]。

Q2 Environmental Science Huanjing Kexue/Environmental Science Pub Date : 2024-08-08 DOI:10.13227/j.hjkx.202308121
Hong-Xing Zhao, Jing-Jing Shi, Rui-Chun He, Chang-Xi Ma
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引用次数: 0

摘要

选取 "一带一路 "沿线 17 个省(自治区、直辖市)的行政单位作为基本空间单元,计算 2000 年至 2021 年 "一带一路 "沿线各省交通碳排放量。选取 "一带一路 "沿线 17 个省(自治区、直辖市)的行政单元作为基本空间单元,计算 2000-2021 年 "一带一路 "沿线各省交通碳排放情况。在利用空间自相关方法分析交通碳排放时空特征的基础上,结合固定效应回归模型和地理检测器,探讨了交通碳排放影响因素的时空异质性。结果表明:①"一带一路 "沿线省份交通碳排放具有显著的空间正相关性,总体呈上升趋势。此外,交通碳排放高值和低值的集群演化在空间上呈现极化特征。高值集群区主要分布在开放引领区,低值集群区主要分布在丝绸之路核心区。开放水平和汽车保有量是交通碳排放的正向驱动因素,能源强度、交通结构、产业发展规模和政府干预是负向驱动因素。结果表明:①交通碳排放的正向驱动因素是开放水平和汽车保有量,负向驱动因素是能源强度、交通结构、产业发展规模和政府干预;②开放水平和汽车保有量是交通碳排放的正向驱动因素,能源强度、交通结构、产业发展规模和政府干预是交通碳排放的负向驱动因素;③能源强度和交通结构是交通碳排放空间变化的主要驱动因素,当它们与其他因素空间叠加时,大多会产生非线性增强,即驱动因素之间存在较强的协同作用。结果表明,"一带一路 "沿线省份交通碳排放受周边地区影响较大,影响程度呈上升趋势,交通碳排放的关键驱动因素之间存在协同作用。因此,建议 "一带一路 "沿线省份应充分考虑交通碳排放影响因素的时空异质性,制定差异化的交通碳减排政策。
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[Spatio-temporal Heterogeneity of Factors Influencing Transportation Carbon Emissions in Provinces Along the Belt and Road].

The administrative units of 17 provinces (autonomous regions and municipalities directly under the Central Government) along the "Belt and Road" were selected as basic spatial units to calculate the provincial traffic carbon emissions along the "Belt and Road" from 2000 to 2021. On the basis of analyzing the spatial and temporal characteristics of traffic carbon emissions by using the spatial autocorrelation method, the spatial and temporal heterogeneity of influencing factors of traffic carbon emissions was explored by combining a fixed-effect regression model and geographic detector. The results show that: ① The provincial traffic carbon emissions along the "Belt and Road" had significant spatial positive correlation, and the overall trend was upward. Additionally, the cluster evolution of high and low values of traffic carbon emissions presented the characteristics of polarization in space. The high value cluster area was mainly distributed in the open leading area, and the low value cluster area was mainly distributed in the core area of the silk road. ② Opening-up level and vehicle ownership were the positive driving factors of carbon emissions from transportation, whereas energy intensity, transportation structure, industry development scale, and government intervention were the negative driving factors. ③ Energy intensity and transportation structure were the main driving factors for the spatial variation of transportation carbon emissions, and most of them would produce nonlinear enhancement when they were spatially superimposed with other factors, that is, there was strong synergy among driving factors. The results showed that the provincial traffic carbon emissions along the "Belt and Road" were affected by the surrounding areas, the influence degree was increasing, and there was synergy between the key driving factors of traffic carbon emissions. Therefore, it is suggested that the provinces along the "Belt and Road" should fully consider the spatial and temporal heterogeneity of traffic carbon emission influencing factors and formulate differentiated traffic carbon emission reduction policies.

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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
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发文量
15329
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