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A reduction in the CO2 emission intensity (ton per gross domestic product) from a base year to a target year with different rates of reduction in each individual year can yield different cumulative CO2 emissions over time, which could have different effects on the climate. In this paper, an indicator is proposed to measure the extent to which the cumulative CO2 emissions are generated by a specific reduction trajectory of CO2 emission intensity, especially for emerging economies with a relatively higher economic growth rate. The proposed indicator is important for less-developed countries and regions in which economic growth is heavily reliant on energy and in which significant potential exists for improvement of energy efficiency. The indicator is applied to evaluate the CO2 emission reduction performance in China's 12th Five-Year Plan period, and the result is not encouraging, especially when the likely gap between the energy conservation goals and temperature goals is further examined. Mitigation goals should be set by considering not only the performance in the final year, but also the reduction in cumulative emissions over the evaluation period. [ABSTRACT FROM AUTHOR]

Recently the expansion of urban-rural income inequality and the rapid growth of fossil-energy consumption have become two significant challenges China should address to achieve its ambitious goals. For the first time, this study uses the Chinese provincial panel data during the period of 1996–2013 to perform a quantitative analysis on the relationship between the urban-rural income gap and the per capita electricity consumption. Fully considering the potential endogeneity problem, this paper uses the orthogonal-difference Generalized Method of Moments (GMM) as the benchmark estimation method. To ensure the robustness of the estimations, the Theil index and per capita urban-rural income are utilized to measure the urban-rural income gap. The estimation results indicate that the influences of urban-rural income inequality on electricity depend on the income level. At the current stage of economic development, the income disparity has significantly negative impacts on provincial per capita electricity consumption. Moreover, there is also strong evidence for the existence of the inverted U-shaped relationship between per capita electricity consumption and GDP per capita. Furthermore, other economic and social factors, including the enhancement of urbanization and industrialization levels, the adjustment of the population structure, and the development of import-export trade may also promote electricity consumption. [ABSTRACT FROM AUTHOR]

With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020. [ABSTRACT FROM AUTHOR]

To tackle climate change, Chinese government has applied an array of mitigating measures to reduce CO2 emissions. During the 11th Five-year Plan, Chinese government set the emission reduction target policy to reduce energy consumption per unit of gross domestic product (GDP) by 20%. This paper attempts to estimate the effect of this emission reduction target policy on industrial performance from complexity perspective. The result shows more complex industrial structure is related to less coal consumption. In general, emission reduction target policy has a negative effect on the probability of branching into new industries and lower the productivity and profitability of a given industry. However, this negative effect is weaker for more complex industries. Only for industries with very high complexity, emission reduction target policy can improve the performance of an industry rather than exerting a negative effect. Our finding not only helps to design a more effective policy to achieve industrial development strategy, but also provides a potential way to achieve economic growth while reduce the emission of greenhouse gases at the same time. • We investigate the impact of Emission reduction target policy(ERT) on industrial performance from complexity perspective. • We apply the method of reflection to calculate the Economic Complexity of provinces and Industry Complexity of industries. • More complex industrial structure contributes to the coal consumption reduction. • ERT has negative effects on the probability of branching into new industries, lowers the productivity and profitability of a given industry. • ERT has weaker negative effects for more complex industries. [ABSTRACT FROM AUTHOR]