Assessing Multiple Pathways for Achieving China’s National Emissions Reduction Target

Abstract

In order to achieve China's target of carbon intensity emissions reduction in 2030, there is a need to identify a scientific pathway and feasible strategies. In this study, we used stochastic frontier analysis method of energy efficiency, incorporating energy structure, economic structure, human capital, capital stock and potential energy efficiency to identify an efficient pathway for achieving emissions reduction target. We set up 96 scenarios including single factor scenarios and multi-factors combination scenarios for the simulation. The effects of each scenario on achieving the carbon intensity reduction target are then evaluated. It is found that: (1) Potential energy efficiency has the greatest contribution to the carbon intensity emissions reduction target; (2) they are unlikely to reach the 2030 carbon intensity reduction target of 60% by only optimizing a single factor; (3) in order to achieve the 2030 target, several aspects have to be adjusted: the fossil fuel ratio must be lower than 80%, and its average growth rate must be decreased by 2.2%; the service sector ratio in GDP must be higher than 58.3%, while the growth rate of non-service sectors must be lowered by 2.4%; and both human capital and capital stock must achieve and maintain a stable growth rate and a 1% increase annually in energy efficiency. Finally, the specific recommendations of this research were discussed, including constantly improved energy efficiency; the upgrading of China's industrial structure must be accelerated; emissions reduction must be done at the root of energy sources; multi-level input mechanisms in overall levels of education and training to cultivate the human capital stock must be established; investment in emerging equipment and accelerate the closure of backward production capacity to accumulate capital stock.Nations Climate Change Conference in 2015, China submitted its Intended Nationally Determined Contribution (INDC) report, in which it states that it will reduce its carbon intensity (CO 2 emissions per unit GDP) by 60-65% in 2030 compared to the level in 2005 [7]. The realization of this target can accelerate China's transformation to a green, low-carbon economy and serve as an important foundation and model in achieving the global target of 2 • C temperature increase [8]. Although some progress has been achieved (i.e., the energy intensity decreased 33.8% from 2005 to 2014), China's carbon intensity is still at a high level. The energy consumption structure still needs to be optimized [9]. In order to achieve its target on emissions reduction in 2030, there is a need for identifying a scientific pathway and feasible strategies, especially before China achieves the early peaking of its carbon emissions [10][11][12].The imbalance in economy development between regions appears in all economies, as differentiated growth always results in early-developing and late-developing regions [13]. The imbalances are visible not only in economic growth, but also in other facets like sectorial structures and models of energ...

Provincial Carbon Emissions Efficiency and Its Influencing Factors in China

“…Based on the framework of total-factor productivity, Hu and Wang [18] firstly put forward the concept of total-factor energy efficiency using the DEA method, Forsund and Kittelsen [19] defined the concept of total-factor energy efficiency based on the Malmquist index, and many academics have developed this method. Wang et al [20] used the stochastic frontier analysis (SFA) method of energy efficiency, incorporating energy structure, economic structure, human capital, capital stock, and potential energy efficiency to identify an efficient pathway for achieving emissions reduction targets.…”