| 经济同质性城市群交通碳排放驱动机制与空间格局异质性 |
| 摘要点击 260 全文点击 8 投稿时间：2025-04-18 修订日期：2025-08-06 |
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| 中文关键词 交通碳排放 城市群 对数平均迪氏指数（LMDI）分解模型 多尺度地理加权回归模型（MGWR） 标准差椭圆方法（SDE） |
| 英文关键词 transportation carbon emissions urban agglomerations logarithmic mean Divisia index（LMDI）model multiscale geographically weighted regression model（MGWR） standard deviation ellipse（SDE） |
| DOI 10.13227/j.hjkx.202504234 |
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| 中文摘要 |
| 在“双碳”战略目标推动下，交通作为典型的高能耗和高排放行业，其碳排放的区域差异性成为关注焦点. 现有研究多聚焦于城市尺度或单一城市群，对经济发展水平相近但区位结构不同的城市群之间的交通碳排放差异缺乏系统性比较分析. 鉴于此，选取长三角城市群与粤闽浙城市群为代表，构建了“时间-空间-机制”三维分析框架，从经济同质性背景出发，探讨其交通碳排放的演化特征与驱动机制的空间异质性. 首先，基于标准差椭圆法（SDE）识别两大城市群2010~2022年交通碳排放的时空格局演变；其次，运用对数平均迪氏指数（LMDI）分解模型量化多维驱动因素的贡献，并引入多尺度地理加权回归模型（MGWR）揭示其空间异质性. 结果表明：① 经济发展水平与单位货物经济效益在两地均表现为主要促进作用，而能源强度与交通运输强度则普遍抑制碳排放增长；② 长三角城市群碳排放重心集中在江苏无锡；粤闽浙城市群重心稳定在福建龙岩；③ 能源结构和能源强度对碳排放的影响在地理空间上趋于局部化. 研究结果可为经济发展同质性的城市群制定区域差异化减排策略提供实证支持与空间决策依据. |
| 英文摘要 |
| Under the impetus of the “dual carbon” strategic goals， traffic， as a typical high-energy-consumption and high-emission industry， has seen its regional differences in carbon emissions become a focal point of attention. Existing research predominantly focuses on the urban scale or single urban agglomerations， lacking systematic comparative analysis of transportation carbon emission differences between urban agglomerations with similar economic development levels but different locational structures. In light of this， this study selects the Yangtze River Delta and the Guangdong-Fujian-Zhejiang urban agglomerations as representatives， constructing a “time-space-mechanism” three-dimensional analytical framework. From the perspective of economic homogeneity， it explores the evolutionary characteristics of their transportation carbon emissions and the spatial heterogeneity of driving mechanisms. Firstly， based on the standard deviation ellipse （SDE） method， the spatiotemporal pattern evolution of transportation carbon emissions in the two urban agglomerations from 2010 to 2022 was identified. Secondly， the logarithmic mean Divisia index （LMDI） decomposition method was used to quantify the contributions of multidimensional driving factors， and the multiscale geographically weighted regression （MGWR） model was introduced to reveal their spatial heterogeneity. The study found that： ① Economic development level and unit cargo economic efficiency were the main promoting factors in both regions， while energy intensity and transportation intensity generally inhibited carbon emission growth. ② The center of carbon emissions in the Yangtze River Delta urban agglomeration was concentrated in Wuxi， Jiangsu， and the center in the Guangdong-Fujian-Zhejiang urban agglomeration remained stable in Longyan， Fujian. ③ The impact of energy structure and energy intensity on carbon emissions tended to be localized and refined in geographical space. This study provides empirical support and a spatial decision-making basis for formulating regionally differentiated emission reduction strategies among different urban agglomerations. |
