| 赣闽粤地区交通碳排放时空演化及驱动力 |
| 摘要点击 233 全文点击 19 投稿时间：2024-04-22 修订日期：2024-07-09 |
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| 中文关键词 赣闽粤地区 交通碳排放 驱动力 LMDI模型 M-R模型 |
| 英文关键词 Jiangxi, Fujian, and Guangdong regions traffic carbon emissions driving forces LMDI model M-R model |
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| 中文摘要 |
| 赣闽粤地区紧邻东南沿海地区,是珠三角、长三角和粤闽浙等地区的腹地.随着赣闽粤地区经济发展和城市化进程加快,交通所带来的高碳排放问题日益突出.我国“十四五”规划提出深入实施区域协调发展战略,健全区域协调发展机制.长期以来,国内外学术研究和政策关注往往集中在经济发达区域,如长三角、珠三角和京津冀地区.以上区域的经济发展模式和机制已经得到了充分的研究和验证.然而,赣闽粤地区则展示出经济发展不均衡的特征,既包含经济发达的珠三角地区（广东省）,也包含相对欠发达的内陆区域（江西省）,故对于赣闽粤地区的研究有助于全面理解区域经济发展的多样性和不均衡性,并为其他欠发达地区提供参考.综上,针对赣闽粤地区交通碳排放时空差异及驱动力尚不明确的挑战,引入标准差椭圆分析法探明赣闽粤地区交通碳排放的空间分布特征（2009~2021年）,基于所构建的LMDI和M-R分解模型从时间和空间层面探明碳排放空间分异的驱动力.结果表明：①赣闽粤地区交通碳排放总量呈逐年增加趋势,其碳排放重心主要位于广东省和福建省的交界处,且持续向“东北-西南”方向转变；②经济发展水平和人口规模是交通碳排放的主要驱动力；而能源强度是关键的抑制因素；③三省碳排放与平均水平相比存在显著的空间差异.研究结论可以为制定赣闽粤地区差异化碳减排政策和联合治理措施提供重要参考. |
| 英文摘要 |
| The Jiangxi, Fujian, and Guangdong regions are located close to the southeast coastal area and serve as the hinterland for the Pearl River Delta； Yangtze River Delta； and Guangdong, Fujian, and Zhejiang regions. With the rapid economic development and urbanization in Jiangxi, Fujian, and Guangdong, transportation-related high carbon emissions have become increasingly prominent. The 14th Five-Year Plan proposes to deepen the implementation of the regional coordinated development strategy and improve the mechanism for regional coordination. Academic research and policy attention have long focused on economically developed regions, such as the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei Region. The economic development models and mechanisms in these regions have been extensively studied and validated. However, the Jiangxi, Fujian, and Guangdong regions exhibit characteristics of uneven economic development, with both economically developed areas, such as Guangdong Province and relatively underdeveloped inland regions like Jiangxi Province. Research on the Jiangxi, Fujian, and Guangdong regions could contribute to a comprehensive understanding of the diversity and imbalance in regional economic development, providing references for other underdeveloped areas. Therefore, facing challenges of spatial-temporal differences in transportation carbon emissions in Jiangxi, Fujian, and Guangdong regions with unclear driving forces, this study introduces standard deviation ellipse analysis to explore the spatial distribution characteristics of transportation carbon emissions （2009-2021）. Additionally, logarithmic mean divisia index （LMDI） and multi-regional spatial decomposition （M-R） models are constructed to explore temporal-spatial drivers contributing towards spatial differentiation of carbon emissions. The findings are revealed below： ① The total traffic-related carbon emissions within the Jiangxi, Fujian, and Guangdong regions have been increasing annually and continue to shift toward the “northeast-southwest” direction, with the epicenter of carbon emission lying at the border between the Guangdong and Fujian provinces. ② The level of economic development and population size were the main driving factors for transportation carbon emissions, whereas energy intensity was a key restraining factor. ③ Notable spatial disparities existed between carbon emissions and average levels across the three provinces. The research findings can offer crucial insights for formulating tailored emission reduction policies and collaborative governance measures in the regions of Jiangxi, Fujian, and Guangdong. |
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