Measurement on carbon lock-in of China based on RAGA-PP model

Abstract

The measurement indicator system of carbon lock-in was constructed from four dimensions: fixed investment, technique, institution and social behavior; and the projection pursuit evaluation model based on the Real-coded Accelerating Genetic Algorithm, (RAGA-PP model) was established. In this study, China’s carbon lock-in level was measured and analyzed based on relevant data from 2003 to 2016. The model application contributes to solving problems such as the subjectivity of weight estimation and premature convergence. The results indicate that, in addition to the increasing degree of social behavior lock-in, for China, the overall carbon lock-in and lock-in levels of fixed input, technique, and institution have decreased dramatically. The overall carbon lock-in level of the eastern provinces is the weakest, followed by the central and northeastern regions, with the western regions being the strongest, and the polarization of provincial carbon lock-in levels being the most significant in the central and western areas. The government should make prudent decisions on the main investment and construction of social infrastructure from a long-term perspective. It is essential to make breakthroughs in the core technologies of complementary and coupled energy utilization to accelerate the formation of new power systems.