What Is the Regional Differences in Carbon Emission Performance: Evidences From Energy-intensive Industries in China?

Abstract

As the major energy consumers, energy-intensive industries are the key players in achieving carbon emission reduction targets. Grasping the carbon emission reduction potential has a direct impact on the implementation of the carbon emission reduction policies of China. The paper builds a super-Slack Based Model(SBM) considering this undesirable output, and calculates the carbon emission efficiency. Then, the Meta-Frontier Malmquist-Luenberger productivity index (MF-MLPI) is constructed to dynamically analyse the growth rate changes of the carbon emission efficiency and the regional differences in energy-intensive industries. Furthermore, the carbon emission reduction potential of the energy-intensive industries in various economic regions of China is discussed and the conclusions are as follows: there is a big difference in the carbon emission Technology Gap Ratios (TGRs) of the energy-intensive industries in different economic regions; the growth rate of the carbon emission efficiency of energy-intensive industries shows a trend of first declining and then slowly recovering while the carbon reduction potential generally shows a trend of decreasing and then rising; and the carbon emission reduction potential in the eastern region keeps decreasing. The following is recommended: the government should rationally distribute energy-intensive industries, promote industrial structure adjustment, optimize the energy structure according to the regional industrial advantages; increase investment in R&D, promote energy technology innovation in energy-intensive industries; prioritize the promotion of carbon peaks on key emission industries and regional, formulate differentiated plans for the regions and industries with different carbon emission reduction potentials.

Study on the Environmental Impact and Benefits of Incorporating Humus Composites in Anaerobic Co-Digestion Treatment

“…These methods are presented in the following formula. Additionally, the correlation coefficient used in these calculations was derived from the research conducted by Ren et al [16].…”