Author(s)

Yaping Han, Jintao Hu, Lei Zhao, Yuan Luo, Yangke Ying, Keke Han

Corresponding Author

Jintao Hu

Abstract

In the context of "double carbon", this article establishes a PMC indicator model and quantitatively analyzes the content correlation relationships in policy texts. This model can clearly display the hierarchy of policy implementation effects and help decision-makers quickly judge the quality and impact of policies. The use of multi-input-output tables and text mining methods can effectively obtain important content in policy texts, reflect the correlation between variables, and provide strong support for green and low-carbon development paths. Research results show that it is expected that the energy structure adjustment will increase by 4% in 2025, and carbon emissions will be reduced by 3.51 million tons. The research results of this article have important practical significance and practical value in promoting high-quality economic development and building a strong country.

Keywords

dual carbon goals; PMC indicators; green and low carbon; text mining; carbon emissions