Driving forces of national and regional CO₂ emissions in China combined IPAT-E and PLS-SEM model

In China, carbon dioxide (CO₂) emissions have been in a state of constant growth, and CO₂ emission reduction is a considerable challenge for China. The paper uses the IPAT-E (I = Human Impact, P = Population, A = Affluence, T = Technology, E = Energy) model to determine and classify the influencing factors of CO₂ emissions. Based on the provincial panel data, the paper used the partial least squares (PLS) method to establish a structural equation model (SEM), and analyzes the path coefficient between CO₂ emissions and its influencing factors. The paper contains 16 indicators from 2001 to 2016. Empirical results show that affluence, technology and energy have a significant positive impact on CO₂ emissions at the national level. And the affluence factor under the influence of population factor has the greatest impact. From a regional perspective, affluence factor has a significant positive impact on CO₂ emissions in the Northeast, East, Northwest, Southwest, and Central South China, with the largest impact on the Southwest. Technology factor has a small positive impact on East, Northwest and Southwest China. Energy factor has a significant positive impact on the Northeast, North, East China, Northwest and Central South China, with the greatest impact on North China. Affluence and technology factors have a negative impact on CO₂ emissions in North China. In addition, the population has a greater impact on affluence, with minimal impact on the Southwest. This study provides a comprehensive and accurate indicator estimation framework for CO₂ emissions. And the paper provides theoretical support for the government to formulate policies.