| 长江经济带工业减污降碳协同增效水平测度、时空跃迁及驱动因素 |
| 摘要点击 526 全文点击 11 投稿时间：2025-10-29 修订日期：2026-02-27 |
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| 中文关键词 长江经济带 工业减污降碳协同增效 水平测度 时空跃迁 驱动因素 |
| 英文关键词 Yangtze River Economic Belt synergistic effect of industrial pollution and carbon reduction horizontal measurement spatiotemporal transition driving factors |
| DOI 10.13227/j.hjkx.202510342 |
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| 中文摘要 |
| 实现工业减污降碳协同增效是推动长江经济带全面绿色低碳转型的必由之路. 探析长江经济带工业减污降碳协同增效的时空跃迁及驱动因素，对统筹生态文明建设与经济高质量发展具有重要的决策参考意义. 在测度2003~2023年长江经济带110个地级市工业减污降碳协同增效水平基础上，结合空间相关性分析、Dagum基尼系数及分解、核密度估计与地理探测器等方法探究其时空跃迁及驱动因素. 结果表明：①长江经济带工业减污降碳协同增效水平呈现先下降后上升的“U”型趋势，且中游和上游地区工业减污降碳协同增效水平明显低于下游地区. ②长江经济带工业减污降碳协同增效水平具有较强的空间正相关性，工业减污降碳协同增效高值区域与低值区域在空间分布上呈现明显的集聚特征. ③区域间净差异是长江经济带工业减污降碳协同增效水平区域差异的主要来源，其次是区域内分异，超变密度对区域差异的贡献率最小. ④绿色技术创新、金融发展、政府干预、降水量和能源消费强度是长江经济带工业减污降碳协同增效水平空间格局分异的主要驱动因素，绿色技术创新和能源消费强度的交互作用显著. |
| 英文摘要 |
| Achieving the synergistic effect of industrial pollution and carbon reduction is essential for promoting the comprehensive green and low-carbon transformation of the Yangtze River Economic Belt. Exploring the spatio-temporal transition and driving factors of such synergy holds important decision-making reference significance for coordinating ecological civilization construction and high-quality economic development. Based on measuring the industrial pollution and carbon reduction synergistic effect level of 110 cities at the prefecture level in the Yangtze River Economic Belt from 2003 to 2023 using the entropy weight method， the spatial and temporal jumps and driving factors are explored by employing the spatial correlation analysis， Dagum's Gini coefficient and decomposition， kernel density estimation， and geographical detector method. The results show that： ① The overall synergistic effect level of industrial pollution and carbon reduction in the Yangtze River Economic Belt presented a U-shaped evolutionary characteristic of “first decreasing and then rising”. During the study period， the industrial pollution and carbon reduction synergistic effect level experienced a process of first decreasing and then rebounding， but the regional gap remained significant. ② The spatio-temporal differentiation characteristics of the industrial pollution and carbon reduction synergistic effect were significant. From the time series perspective， 2008 was the key node for the change of the industrial pollution and carbon reduction synergistic effect level， which showed a continuous downward trend from 2003 to 2008 and then gradually increased. From the spatial dimension， the overall Moran's I from 2003 to 2023 was significantly positive， indicating a strong spatial positive correlation in the industrial pollution and carbon reduction synergistic effect level among various cities. From the perspective of spatial correlation pattern， the industrial pollution and carbon reduction synergistic effect level showed obvious spatial agglomeration characteristics， with a more prominent regional polarization trend. ③ The inter-regional net difference was the main source of regional differences in the industrial pollution and carbon reduction synergistic effect level. Dagum Gini coefficient decomposition results indicated that inter-regional differences contributed the most to the overall differences， followed by intra-regional differences. The overlap degree among different regions contributed the least， indicating that the difference in regional development level was the dominant force causing spatial differentiation. ④ Green technology innovation， financial development， and energy consumption intensity were the key driving factors for forming the spatial pattern of the industrial pollution and carbon reduction synergistic effect. Single-factor detection results showed that green technology innovation and financial development were important factors affecting the spatial differentiation of the industrial pollution and carbon reduction synergistic effect. In 2023， the explanatory power of energy consumption intensity exceeded that of green technology innovation and financial development， indicating that the focus of the Yangtze River Economic Belt on promoting the industrial pollution and carbon reduction synergistic effect was shifting from “end-of-pipe governance” to “combination of source control and end-of-pipe governance”. Interaction detection results showed that the interaction type among driving factors was mainly “two-factor enhancement”， indicating that the synergistic effect of industrial pollution and carbon reduction in the Yangtze River Economic Belt had obvious multi-factor coupling characteristics. Among them， the interaction among green technology innovation， energy consumption intensity， and financial development was the most significant， indicating that green technology innovation and multi-factor synergy have become important power sources for improving the synergy level. |
