Abstract
With the implementation of Chinese carbon neutrality policy, the Yangtze River Delta calls for great concern. As a benchmark for the development of Chinese logistics industry, it accompanies energy consumption and environmental problems. This study explores how Chinese logistics industry can achieve energy conservation and emission reduction and high-quality development in the context of carbon neutrality. It analyzes the relationship between the logistics industry and economy, energy, as well as environment in Yangtze River Delta. The data is based on China Statistical Yearbook from 2001 to 2019, by means of the entropy method and panel vector autoregressive (PVAR) model. The main findings are summarized as follows: firstly, the economy, industrial structure, energy, and environment have significant impact on the development of logistics industry in Yangtze River Delta. Secondly, the development of logistics industry in Yangtze River Delta is not balanced. The provinces including Jiangsu, Shanghai, Zhejiang, and Anhui have great differences in economy, industrial structure, demographic dividend, energy consumption, and environmental protection, but they show the possibility of complementary advantages. Thirdly, the economic development and energy consumption have bidirectional effects. Environmental protection is relevant to economic development, industrial structure, energy consumption and logistics supply. Finally, some suggestions are provided on how to realize the high-quality development of logistics industry in Yangtze River Delta. In the context of carbon neutrality, it is necessary to consider energy conservation and emission reduction.
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This work was supported by the National Social Science Foundation of China (17BJY141) for the research on logistics resource allocation and logistics cost reduction in the context of sharing economy.
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Fan, L., Liu, H., Shao, Z. et al. Panel data analysis of energy conservation and emission reduction on high-quality development of logistics industry in Yangtze River Delta of China. Environ Sci Pollut Res 29, 78361–78380 (2022). https://doi.org/10.1007/s11356-022-21237-3
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DOI: https://doi.org/10.1007/s11356-022-21237-3