『Abstract
　With the intensification of global warming and continued growth in energy consumption, China is facing increasing pressure to cut its CO2 (carbon dioxide) emissions down. This paper discusses the driving forces influencing China's CO2 emission based on Path-STIRPAT model - a method combining Path analysis with STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The analysis shows that GDP per capita (A), industrial structure (IS), population (P), urbanization level (R) and technology level (T) are the main factors influencing China's CO2 emissions, which exert an influence interactively and collaboratively. The sequence of the size of factors' direct influence on China's CO2 emission is A＞T＞P＞R＞IS, while that of factors' total influence is A＞R＞P＞T＞IS. One percent increase in A, IS, P, R and T leads to 0.44, 1.58, 1.31, 1.12 and -1.09 percentage change in CO2 emission totally, where their direct contribution is 0.45, 0.07, 0.63, 0.08, 0.92, respectively. Improving T is the most important way for CO2 reduction in China.

Keywords: Influence factor; CO2 emission; China』

1. Introduction
2. Methodology
　2.1. Estimation of CO2 emissions
　2.2. Path-STIRPAT model
　　2.2.1. STIRPAT model
　　2.2.2. Path analysis
　　2.2.3. Path-STIRPAT model
3. Data resource
4. Main results
　4.1. CO2 emission analysis
　4.2. Correlation analysis
　4.3. Path-STIRPAT analysis
5. Conclusions and policy implications
Acknowledgments
References