• Energy Research

Abstract Ecological balance and carbon sink economies have gained increased attention for tackling global warming. Based on an improved Carnegie–Ames–Stanford Approach model, this study demonstrated regional Net Primary Productivity (NPP) and analyzed regional carbon overdraft situations in China during 2005–2015. Regional carbon allowances were allocated according to carrying capacity of carbon sequestration and China's carbon intensity reduction goals in “13th Five-year plan”. Data Envelopment Analysis (DEA) technology with panel data was further employed to estimate potential benefits resulting from carbon trading and a carbon sink economy. Regional NPP decreased from south to north and from coast to inland, while regions with severe carbon overdrafts were gathered in North and East China. In order to maintain a regional carbon balance with lower abatement costs, regional cooperation of emission reduction within either North or East China is proposed in this study. It is concluded that the majority of provinces and cities in Eastern China and some provinces in the west would be the major purchasers of carbon credits under a national carbon emissions trading (CET) market. Following the introduction of emissions offset mechanisms, Yunnan, Sichuan, and Heilongjiang would be the major providers of carbon sinks in China.

Abstract Net primary productivity, which reflects vegetation's carbon sequestration capacity, should not be ignored in the process of low-carbon development. To explore the paths of achieving low-carbon development goals from the perspective of carbon sequestration, this study takes net primary productivity as the study object and uses the logarithmic mean Divisia index decomposition model to analyze the influences of urbanization and land utilization change on net primary productivity in China. The results show that urbanization is the driving factor of the net primary productivity increase, and land utilization change is the main determinant of its decrease. This study argues that making reasonable land utilization planning is essential to reduce the net primary productivity loss caused by land utilization changes in the process of urbanization.

Abstract Under the framework of the Kaya identity, this paper uses the Logarithmic Mean Divisia Index (LMDI 1 ) decomposition method to explore the impacts of CO2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita Gross Domestic Product (GDP 2 ), population distribution, and population size on CO2 emissions in the Organisation for Economic Co-operation and Development (OECD 3 ) from 2001 to 2015. Additionally, the Tapio decoupling analysis is used to explore the decoupling relationships between the above influencing factors and CO2 emissions. Moreover, the LMDI decomposition formula is embedded into the decoupling analysis to analyze the influences of technical and non-technical factors on above decoupling elasticity. The results indicate that energy intensity and per capita GDP are the main factors affecting CO2 emissions. The former is the main reason for the decrease in CO2 emissions, and the latter is the main reason for the increase in CO2 emissions. The impact of population distribution on CO2 emissions is negligible. The decoupling states between the overall CO2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita GDP, and population size and CO2 emissions during 2001–2015 are recessive decoupling, recessive decoupling, weak negative decoupling, strong decoupling, and strong decoupling, respectively. Moreover, the influence of technical factors is greater than that of non-technical factors, and their influence directions are always opposite. In addition to our primary contributions, there are three marginal contributions in this paper. First, the population distribution is included in LMDI factorization. Second, LMDI decomposition is combined with Tapio decoupling analysis to explore the decoupling relationships between CO2 emissions and the above factors. Finally, the findings related to the impacts of technical and non-technical factors are novel.