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.