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| 山西省公路货运碳排放时空异质性及影响因素 | |
| 引用本文： | 贺凯,宋洁,潘艺,刘敏,汪宇祥,梁雯. 山西省公路货运碳排放时空异质性及影响因素[J]. 海南师范大学学报(自然科学版), 2024, 37(2): 224-233 |
| 作者姓名： | 贺凯 宋洁 潘艺 刘敏 汪宇祥 梁雯 |
| 作者单位： | 1.太原师范学院 地理科学学院,山西 晋中 030619 2.汾河流域地表过程与资源生态安全山西省重点实验室,山西 晋中 030619 3.浙江财经大学 土地与城乡发展研究院,浙江 杭州 310018 4.江苏中图空间信息科技有限公司,江苏 南京 210000 5.运城市生态环境局,山西 运城 044031 |
| 基金项目： | 山西省高等学校科技创新项目（201802101）;山西省“1331工程”服务流域生态治理产业创新学科集群建设项目;国家自然科学基金青年项目（41901233）;教育部人文社会科学研究青年基金项目（19YJC630127） |
| 摘 要： | 采用“自下而上”法、空间自相关分析和时空地理加权回归模型,探究2001—2020年山西省公路货运碳排放时空异质性及影响因素。结果表明：（1）研究期内,山西省公路货运碳排放总量快速增长,其中2008年增幅最大,2020年增量最大;（2）山西省公路货运碳排放呈现正向的全局空间自相关性,高-高集聚和低-低集聚是主要的局部空间自相关类型,2010年后高-高集聚类型减少,低-低集聚类型增加,表明山西省公路货运碳减排工作取得一定成效;（3）整体上,人口规模和地形起伏度对公路货运碳排放具有正向影响,而国内生产总值和新能源汽车充电站数量对公路货运碳排放具有负向影响。人口稠密、地势平坦的山西省中南部地区应调整能源结构,人口稀疏、地势崎岖的西北部地区应通过调整运输结构来有效降低公路货运碳排放。 |
| 关 键 词： | 公路货运 交通碳 时空异质性 时空地理加权回归 |
Spatiotemporal Heterogeneity and Influencing Factors of Carbon Emissions From Highway Freight Transportation in Shanxi Province |
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| HE Kai,SONG Jie,PAN Yi,LIU Min,WANG Yuxiang,LIANG Wen. Spatiotemporal Heterogeneity and Influencing Factors of Carbon Emissions From Highway Freight Transportation in Shanxi Province[J]. Journal of Hainan Normal University:Natural Science, 2024, 37(2): 224-233 | |
| Authors: | HE Kai SONG Jie PAN Yi LIU Min WANG Yuxiang LIANG Wen |
| Affiliation: | 1.Institute of Geographical Science, Taiyuan Normal University, Jinzhong 030619, China 2.Shanxi Key Laboratory of Earth Surface Processes and Resource Ecological Security in Fenhe River Basin, Jinzhong 030619, China 3.Institute of Land and Urban-rural Development, Zhejiang University of Finance and Economics, Hangzhou 310018, China 4.Jiangsu Zhongtu Space Information Technology Co.,Ltd., Nanjing 210000, China 5.Yuncheng Environmental Protection Bureau, Yuncheng 044031, China |
| Abstract: | Using a bottom-up approach, spatial autocorrelation analysis, and spatio-temporal geographically weighted regression models, the spatio-temporal heterogeneity and influencing factors of carbon emissions from road freight transportation in Shanxi province from 2001 to 2020 were studied. The findings revealed that: (1) throughout the study period, carbon emissions from road freight transportation experienced rapid growth, with the most significant increase observed in 2008 and the highest increment in 2020; (2) carbon emissions from road freight transportation exhibit positive global spatial autocorrelation, with high-high clustering and low-low clustering being the predominant types of local spatial autocorrelation. After 2010, there is a decline in the high-high clustering type and an increase in the low-low clustering type, indicating some progress in carbon emission reduction efforts across various cities; (3) population size and terrain ruggedness foster carbon emissions from road freight transportation, while gross domestic product (GDP) and the number of new energy vehicle charging stations play a notable inhibitory role. Consequently, densely populated and flat areas in the central and southern regions should adjust their energy structure, while sparsely populated and rugged areas in the northwest should adapt their transportation structure to effectively mitigate carbon emissions from road freight transportation. |
| Keywords: | road freight transportation transportation carbon spatio-temporal heterogeneity GTWR |
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