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China's economy has transtioned into the “new normal”, which demands higher standards for energy utilization efficiency. Meanwhile, the spatial distribution of China's energy consumption and economic development exhibits a significant imbalance, complicating efforts to achieve Pareto optimization of regional energy allocation efficiency. Addressing this issue, this study explores the heterogeneity of the factors influencing energy consumption in China from the dual perspectives of economic “new normal” and geographic space, using an exponential decomposition model. The results of the study show that: (1) the inhibitory effect of the energy intensity effect on the growth of regional energy consumption is differentiated, with stronger inhibitory effects in Guangdong, Jiangsu and other provinces, and weaker inhibitory effects in Hainan, Qinghai, and other provinces. Living standard effect on the regional energy consumption growth of the promotion of the effect also has differences, Jiangsu, Shandong and other provinces of the promotion of the effect is stronger, while Hainan, Qinghai, and other provinces of the promotion of the effect is weaker. (2) Population size effect on regional energy consumption growth is not consistent in the direction of the role of Guangdong, Zhejiang, and other provinces have a promotional effect and the role of the effect of the stronger, on the contrary, the provinces of Heilongjiang, Jilin, and Gansu has an inhibitory effect. (3) In the late stage of the economic “new normal”, the effects of energy intensity effect, living standard effect and population size effect on the growth of energy consumption in the four regions show a weakening trend, and this weakening trend is more obvious in the northeast region. This study expands theoretical research on factors affecting energy consumption and offers practical guidance for China's government to coordinate regional energy allocation under the economic “new normal” and geographical considerations. [ABSTRACT FROM AUTHOR]

In recent years, the issues related to carbon emissions and environment have attracted extensive attentions. Considering four scenarios (the energy conversion, energy capital savings and loans, energy exports and cement production carbon emissions), this paper adopts the energy consumption method and input-output method to analyze China's carbon emissions structure on the supply-side and demand-side of energy, and finally provides policy recommendations for China's structural emission reduction. The results show that, if the four influencing factors were not considered, the measurement of carbon emissions from the final demand was 44.91% higher than the baseline scenario, 12.36% lower than the baseline scenario from intermediate demand, and 10.23% lower than the baseline scenario from the total. For China's carbon emissions structure on the supply-side of energy, the carbon emissions from high-carbon energy, represented by raw coal, accounted for 66.805% of the total energy-related carbon emissions, while the carbon emissions from low-carbon energy, represented by natural gas, only accounted for 2.485%. For China's carbon emissions structure on the demand-side of energy, the carbon emissions from intermediate demand (enterprise production) accounted for more than 95% of total energy-related carbon emissions, while the carbon emissions from final demand (residents and government use) accounted for less than 5%. For each specific industry in intermediate demand for energy, the heavy industry, electric power, fossil energy, and chemical industry have high carbon emissions and low carbon emissions efficiency. However, the agriculture, construction, light industry, and service are the opposite. Finally, we provide policy recommendations for improving the accuracy of carbon emissions measurement and carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Given the evident spatial disparity in China's energy consumption and economic development, achieving Pareto optimization of regional energy allocation efficiency proves to be a formidable challenge. Based on this, this paper ingeniously proposed an extended "labor-capital-energy-environment" resource mismatch mode, using 2004–2018 provincial panel data to measure and analyze the spatiotemporal pattern of China's energy mismatch and efficiency loss, while further investigating influencing factor. The results show that: (1) Although the degree of resource misallocation has decreased, the reduction of the number of provinces with excessive energy allocation and the serious shortage of energy allocation are the only effects of the optimization of energy resource misallocation, which has not significantly improved the situation overall. (2) Energy resource misallocation has grown to be a significant factor in China's losses in green total factor productivity (GTFP) brought on by resource misallocation. In addition, the extent of energy mismatch's loss in GTFP demonstrates the spatial heterogeneity of the "eastern > central > northeast > west" region. (3) Environmental regulation can significantly reduce energy mismatch and it is more successful at addressing the issue of excess energy than inadequate energy allocation. Also, the "rebound effect" of technological progress is the main factor aggravating the shortage of energy allocation. • We innovatively proposed an expanded "labor-capital-energy-environment" HK model to construct a theoretical framework for the impact of factor price distortions on GTFP. • The optimization of energy resource misallocation is only reflected in the serious shortage of energy allocation and the reduction of the number of provinces with excessive energy allocation. • The degree of GTFP loss of energy mismatch shows the regional heterogeneity of "eastern > central > northeast > west" spatially. • Environmental regulation can significantly improve the problems of energy mismatch and surplus. [ABSTRACT FROM AUTHOR]

The greenhouse effect caused by excessive carbon emissions seriously threatens the sustainability of the global economy. Although the secondary and tertiary industries are the principal contributors to CO 2 emissions' growth, the continuous and stable development of agriculture also intensifies carbon emissions to a certain extent. Based on this, this paper uses the input–output method, an energy consumption model, and structural decomposition analysis to study energy-related CO 2 emissions and structural emissions' reduction in China's agriculture from 2007 to 2017. The research results show that (1) In 2007–2017, the input structure effect and the energy intensity effect inhibited the growth of energy-related CO 2 emissions in China's agriculture, with the reduction effect of energy intensity effect being the more prominent, whereas the final demand effect and the energy structure effect contributed to promoting China's agricultural energy-related CO 2 emissions' growth, with the final demand effect being the greater promoting factor. (2) The energy structure effect failed to reduce energy-related CO 2 emissions in China's agriculture because the optimization of consumption structure is still not obvious on China's agricultural supply-side. The share of energy consumption from high-carbon fuels such as raw coal, coke, and other washed coal has increased, rather than decreased, and the optimization of low-carbon energy sources such as natural gas is still slow, thus limiting the emissions' reduction effect in the energy structure. (3) The reason why the final demand effect has promoted the growth of energy-related CO 2 emissions in China's agriculture is the expanding demand for agriculture in the entire industrial system. Specific to each industry, the secondary industry has played a major role in the final demand effect, accounting for more than 50% of the final demand effect, followed by the primary and the tertiary industries. Finally, this paper provides a theoretical and practical basis for accurately and efficiently implementing emissions' reduction from the perspectives of the industrial system on the demand-side and the energy system on the supply-side and also in China's agriculture. [ABSTRACT FROM AUTHOR]

Excessive CO 2 emissions from energy combustion are the main cause of the global greenhouse effect, while the energy consumption in China's heating and power industries account for more than a half of national energy consumption. Based on this, to more accurately implement carbon emission reduction in heating and power industries, we studied the evolution and driving factors of the carbon emission structure in these industries between 2007 and 2015 from supply-side and demand-side dual perspectives. The results indicated that: (1) From the view of supply-side, the change of energy consumption structure led to the decline driving force of high-carbon energy (washed coal, crude oil, diesel oil and raw coal) and the rising driving role of low-carbon energy (coke oven gas, other gas and natural gas) for CO 2 emissions growth. Moreover, seen from the entire sample interval, 2007–2010 and 2010–2012 were the best period and the worst period for energy consumption optimization in China's heating and power industries, respectively. (2) From the view of demand-side, the expansion of industrial scale was the responsibility of the carbon emissions growth in China's heating and power industries, and the driving force of the second industry on carbon emissions growth was stronger than that of tertiary industry and primary industry. (3) However, since the direct consumption coefficient of heating and power energies in the tertiary industry and primary industry was lower than that of the secondary industry, the optimization of industrial structure was conducive to slowing the growth of CO 2 emissions in the China's heating and power industries on the demand-side. At last, this paper provides a theoretical analysis for the carbon emission structure of the heating and power industries, and a practical guidance for the industries to carry out more accurate and efficient emission reduction from both sides of supply and demand subsequently. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China's energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future. [ABSTRACT FROM AUTHOR]