Grey prediction model based on carbon emission optimization

Abstract

In the context of developing low-carbon economy to cope with climate change, China, as an economic power and energy consuming country, undertakes an important task of emission reduction. However, many factors, such as unreasonable industrial structure and energy consumption structure, have brought great challenges to the successful completion of China's carbon emission reduction task. In this paper, the entropy weight method is used to quantitatively analyze the relationship between the driving factors of carbon emission of energy structure and industrial structure and the result factors of carbon emission of energy consumption, and then the grey prediction model based on carbon emission optimization is established. According to the relationship between the driving factors and the result factors, the evolution law is summarized. At last, the advantages and disadvantages of the model are evaluated and summarized objectively. At the same time, the model can also provide reliable conclusions for the pollution of other polluting gases.