The influence and forecast of three industries and energy structure on regional carbon emission

ABSTRACT

Carbon emission reduction is an important part of regional low-carbon economic development. In this paper, gray correlation analysis, neural network model, Gaussian multi-mode fitting and other methods were used to analyze the relationship between total carbon emissions and regional economic development, industrial structure, and energy consumption in Henan Province. On this basis, the future development of carbon emissions is predicted. The calculation results showed that the correlation between the three industries and carbon emissions in Henan Province is more than .7, among which the secondary industry has the highest correlation (.77). In the secondary industry, the correlation coefficient between coal and carbon emissions is the highest .87, while the correlation coefficient between other energy sources is about .5. In the neural network prediction model, the correlation coefficient between the prediction curve and the actual total carbon emission curve is .989, and the prediction results have a good degree of fit. The carbon emission prediction curve was divided into two parts: a linear decline stage from 2018 to 2024, and a rapid decline stage after 2024.The results showed that more efforts should be made in industrial structure, energy consumption structure and environmental protection to achieve low-carbon development in Henan province.

KEYWORDS:

• Neural network
• energy structure
• carbon emission prediction
• grey correlation analysis
• Gaussian multimodal fitting

Disclosure statement

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

Author contributions

Chongyang Wang supervised the research and proposed the research direction. Yisha Pan was responsible for report analysis and paper writing. Zhanwu Wang and Yuyang Zhang was responsible for data processing.

Data availability statement

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Notes on contributors

Yisha Pan

Yisha Pan (1996-), master student,College of Surveying, Mapping and Land Information Engineering, Henan Polytechnic University, major in land resource management.

Zhanwu Wang

Zhanwu Wang (1973-), deputy section level cadre of Ruzhou Statistics Bureau.

Chongyang Wang

Chongyang Wang (1996-),PhD student, College of Resources and Security, Chongqing. University, major in security science and Engineering.

Yuyang Zhang

Yuyang Zhang is an undergraduate, College of economics, Henan University, major in International Economics and Trade.