An extended method for key factors in reducing CO2 emissions

Understanding the key factors in regard to CO2 emissions is beneficial in providing a basis for reducing CO2 emissions in the future. Generally speaking, from related studies in the literature on the key factors influencing CO2 emissions, three types of effect can be inferred, namely, the output effect, structural effect and the intensity effect. If we are able to engage in analysis using an objective, quantitative analytical approach, namely, the factor decomposition analysis approach, this will serve as valuable reference to policy-makers who are seeking to implement reductions in CO2 emissions.In this paper, we use the Divisia logarithmic average analytical method referred to by Ang and Choi [B.W. Ang, K.H. Choi, Decomposition of aggregate energy and gas emission intensities for industry: a refined Divisia index method, The Energy Journal 18 (3) (1997) 59–73] as the basic analytical framework. While most studies only focused on between three and five variables when performing the decomposition, in this study we first of all decompose the CO2 emission factors into five factors, namely, population, economic growth, the contamination coefficient, energy intensity and the industrial structure effect. Moreover, in this study we examine in detail the most important factor to influence CO2 emissions (i.e., the output effect), which we partially decompose (using an expanded model), so that our decomposition of the CO2 emission factors can be more comprehensive. In this way, we can provide policy-makers with more effective and in-depth evidence that can serve as valuable reference for them.