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中国长江三角洲城市群工业碳排放的时空异质性与脱钩分解。

Spatiotemporal heterogeneity and decoupling decomposition of industrial carbon emissions in the Yangtze River Delta urban agglomeration of China.

机构信息

School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang, 330013, China.

Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang, 330013, China.

出版信息

Environ Sci Pollut Res Int. 2023 Apr;30(17):50412-50430. doi: 10.1007/s11356-023-25794-z. Epub 2023 Feb 16.

Abstract

The objective of this study is to identify the spatiotemporal change law and the leading factors of industrial carbon emission decoupling. Based on the industrial carbon emission level of the Yangtze River Delta urban agglomeration (YRDUA) from 2006 to 2020, the spatiotemporal heterogeneity was explored with the help of the spatial Markov chain, the Tapio decoupling model was used to analyze its decoupling state from the industrial economy, and its driving factors were decomposed using the Kaya identity and logarithmic mean Divisia index (LMDI) model. The results show that (1) in 51.9% of the YRDUA's cities, the industrial carbon emission situation was stable, the emission reduction observation area (medium carbon) occupied a dominant position, and the emission reduction key area (relatively high carbon) gradually decreased. (2) Industrial carbon emissions had spatial overflow and path dependency characteristics, and the probability of carbon emission type transfer maintaining the original state reached 80.0%. From 2006 to 2011, the average probability of the downward migration of high-carbon cities was 5.0%. From 2011 to 2020, the average probability of the upward transfer of low-carbon cities was 9.4%. (3) The negative decoupling rate of carbon emissions in the YRDUA experienced a transition from 3.7% to 44.4% and then back to 7.4%, showing spatial imbalance. Unsatisfactory decoupling cities were concentrated along the Yangtze River and in coastal areas. (4) The promoting efficiency of energy intensity, carbon emission coefficient, and employment structure was gradually strengthened, and the carbon-increasing effect of labor input was gradually weakened. (5) The decoupling mode of heavy difficult cities is dominated by the three-factor balanced type, which is jointly affected by industrial production, labor input, and carbon emission coefficient. The findings in this study can provide inspiration for industrial carbon emission reduction in megalopolises.

摘要

本研究旨在识别工业碳排放脱钩的时空变化规律及其主导因素。基于 2006 年至 2020 年长三角城市群(YRDUA)的工业碳排放水平,借助空间马尔可夫链探讨其时空异质性,采用 Tapio 脱钩模型分析其工业经济脱钩状态,并利用 Kaya 恒等式和对数平均迪氏分解(LMDI)模型对其驱动因素进行分解。结果表明:(1)在 YRDUA 的 51.9%的城市中,工业碳排放形势稳定,减排观测区(中碳)占据主导地位,减排关键区(相对高碳)逐渐减少。(2)工业碳排放具有空间溢出和路径依赖特征,保持原碳排类型的转移概率达到 80.0%。2006 年至 2011 年,高碳城市向下迁移的平均概率为 5.0%。2011 年至 2020 年,低碳城市向上转移的平均概率为 9.4%。(3)YRDUA 的碳排放负脱钩率经历了从 3.7%到 44.4%再到 7.4%的转变,呈现出空间不平衡的特征。不理想的脱钩城市集中在长江沿线和沿海地区。(4)能源强度、碳排放系数和就业结构的促进效率逐渐增强,劳动力投入的碳增效应逐渐减弱。(5)重难城市的脱钩模式以三因子平衡型为主,受工业生产、劳动力投入和碳排放系数的共同影响。本研究结果可为特大城市的工业碳排放减排提供启示。

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