Regional industrial development trend under the carbon goals in China

ABSTRACT

The arrival of the dual-carbon era indicates that it is imperative to reduce industrial carbon emissions with high carbon emissions. The implementation of carbon emission reduction will inevitably have an impact on industrial development. Three different carbon emission scenarios were established. Based on the average annual carbon emission growth rate of the past decade, it is set as a medium carbon scenario. According to the economic development stage and actual social development situation of each region, the corresponding annual average carbon emission growth rate is increased and decreased to set up high carbon and low carbon scenarios. The adjacent accumulation gray multivariate model for industries is established based on different scenarios. The results indicate that the carbon emission scenarios most suitable for industrial development in various regions are different. Heavy industrial provinces and cities such as Beijing, Tianjin and Hebei have the highest industrial output value under high carbon scenarios; Provinces and cities with high levels of industrialization, such as Jiangsu, Shanghai, Guangdong and Chongqing have the highest industrial output value under low-carbon scenarios. The industrial output value of Hebei is expected to grow the fastest under the high carbon scenario, reaching 2.15 trillion yuan by 2030. The industrial output value of Guangdong achieves the greatest improvement under low-carbon scenario. It is expected that the industrial output value of which will reach 6.86 trillion yuan by 2030, ranking first in the country. Therefore, the setting of carbon emission scenarios needs to be tailored to local conditions, increase technological innovation efforts, and further promote industrial development.

KEYWORDS:

• Double carbon target
• industrial output value
• carbon emission scenarios
• gray multivariate model
• AGMC model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contribution

All authors contributed to the study conception and design. data collection, and analysis were performed by Yuhan Xie, Yan Chen and Lifeng Wu. All authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript

Data availability statement

All data sets used for this paper are available at the China Statistical Yearbook and Panel data of Carbon Emissions Database.

Additional information

Funding

The relevant research is supported by the National Natural Science Foundation of China (71871084, U20A20316), Graduate Demonstration Course in Hebei Province (KCJSX2022095), the key research project in humanity and social science of Hebei Education Department (ZD202211), the Natural Science Foundation of Hebei Province (E2020402074) and the Social Science Federation Project of Handan (2023031).

Notes on contributors

Yuhan Xie

Yuhan Xie is a master's degree in management science and engineering from Hebei University of Engineering, China. Her research direction is uncertain forecasting and decision-making.

Yan Chen

Yan Chen is a lecture of the College of Management Engineering and Business, Hebei University of Engineering. His main research direction is grey system modeling.

Lifeng Wu

Lifeng Wu is a professor of the College of Management Engineering and Business, Hebei University of Engineering. His main research direction is grey system modeling.