Uncovering CO₂ emission drivers under regional industrial transfer in China’s Yangtze River Economic Belt: a multi-layer LMDI decomposition analysis

Abstract

With the relocation of heavy industries moving from downstream region to upstream and midstream regions in the Yangtze River Economic Belt (YREB), it is critical to encourage coordinated low carbon development in different regions within the YREB. This paper uncovers the evolution of CO₂ emissions in different regions within the YREB for the period of 2000–2017. It decomposes regional CO₂ emission changes using the temporal and cross-regional three-layer logarithmic mean Divisia index (LMDI) method. Besides, it decomposes industrial CO₂ emission changes using the temporal two-layer LMDI method. The research results show that economic growth is the major driver for regional CO₂ emission disparities. The mitigation drivers, such as energy intensity and energy structure, lead to a more decreased CO₂ emission in the downstream region than in the upstream and midstream regions. In addition, it proposes several policy recommendations based upon the local realities, including improving energy efficiency, optimizing energy structure, promoting advanced technologies and equipment transfers, and coordinating the development in the upstream, midstream and downstream regions within the YREB.

Key words： CO₂ emission; multi-layer LMDI decomposition; industrial transfer; governance

Acknowledgment

This study was supported by the National Natural Science Foundation of China (Grant Nos. 71690241, 71810107001, 71704104, 71774100, and 71804071), the Fundamental Research Funds for the Central Universities through Shanghai Jiao Tong University (No. 16JCCS04), the Shanghai Municipal Government (No. 17XD1401800), and the Big Data Project funded by Shanghai Jiao Tong University (No. SJTU-2019UGBD-03).

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11708-020-0706-z and is accessible for authorized users.

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