Author(s)

Yihui Zhang ¹, Jianxiang Li ¹, Jingping Che ¹

Affiliation(s)

¹ Shenyang Ligong University, Equipment Engineering College, Liaoning, Shenyang, 110159

Corresponding Author

Yihui Zhang

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.

KEYWORDS

carbon neutralization, Entropy weight method, Grey prediction model

CITE THIS PAPER

Yihui Zhang, Jianxiang Li, Jingping Che. Grey prediction model based on carbon emission optimization. Environment, Resource and Ecology Journal (2021) 5: 6-10. DOI: http://dx.doi.org/10.23977/erej.2021.050302

REFERENCES

[1] Li leiming, sun Liangping, Liu Bingquan. Evolution law and driving factors of carbon emission: a case study of Shandong Province [J]. Research on technology, economy and management, 2013 (06): 89-93
[2] Lu Sha. Digital transformation promotes high quality development of power energy enterprises [n]. China Information Weekly, December 23, 2019 (013)
[3] Fu Dongdong, Zhou Xinmiao. Analysis on Influencing Factors of China's carbon dioxide emissions from the perspective of regional differences [J]. Science and technology and management, 2016, 18 (02): 59-64 + 70

Sponsors, Associates, and Links

---

• International Journal of Geological Resources and Geological Engineering
  
  
• Big Geospatial Data and Data Science
  
  
• Solid Earth and Space Physics
  
  
• Environment and Climate Protection
  
  
• Journal of Cartography and Geographic Information Systems
  
  
• Offshore and Polar Engineering
  
  
• Physical and Human Geography
  
  
• Journal of Atmospheric Physics and Atmospheric Environment
  
  
• Trends in Meteorology
  
  
• Journal of Coastal Engineering Research
  
  
• Focus on Plant Protection
  
  
• Toxicology and Health of Environment
  
  
• Geoscience and Remote Sensing
  
  
• Advances in Physical Oceanography
  
  
• Biology, Chemistry, and Geology in Marine
  
  
• Water-Soil, Biological Environment and Energy
  
  
• Geodesy and Geophysics
  
  
• Journal of Structural and Quaternary Geology
  
  
• Journal of Sedimentary Geology
  
  
• International Journal of Polar Social Research and Review