Unveiling the driving factors of carbon emissions from industrial resource allocation in China: A spatial econometric perspective

Energy Policy ◽  
2021 ◽  
Vol 158 ◽  
pp. 112557
Author(s):  
Bin Wang ◽  
Minxiu Yu ◽  
Yucheng Zhu ◽  
Pinjuan Bao
2021 ◽  
Vol 13 (3) ◽  
pp. 1339
Author(s):  
Ziyuan Chai ◽  
Zibibula Simayi ◽  
Zhihan Yang ◽  
Shengtian Yang

In order to achieve the carbon emission reduction targets in Xinjiang, it has become a necessary condition to study the carbon emission of households in small and medium-sized cities in Xinjiang. This paper studies the direct carbon emissions of households (DCEH) in the Ebinur Lake Basin, and based on the extended STIRPAT model, using the 1987–2017 annual time series data of the Ebinur Lake Basin in Xinjiang to analyze the driving factors. The results indicate that DCEH in the Ebinur Lake Basin during the 31 years from 1987 to 2017 has generally increased and the energy structure of DCEH has undergone tremendous changes. The proportion of coal continues to decline, while the proportion of natural gas, gasoline and diesel is growing rapidly. The main positive driving factors affecting its carbon emissions are urbanization, vehicle ownership and GDP per capita, while the secondary driving factor is residents’ year-end savings. Population, carbon intensity and energy consumption structure have negative effects on carbon emissions, of which energy consumption structure is the main factor. In addition, there is an environmental Kuznets curve between DCEH and economic development, but it has not yet reached the inflection point.


2021 ◽  
Vol 248 ◽  
pp. 02026
Author(s):  
Hua Gao ◽  
Zhoujie Huang

After further processing the input-output tables of 2007, 2012 and 2017, the carbon emissions are decomposed into four driving factors: energy intensity effect, Leontief technology effect, final demand structure effect and final total demand effect through IO-SDA model. The results show that the energy intensity effect has a significant negative effect, which is the main factor to promote the reduction of carbon emissions. The Leontief technical effect and the final total demand effect are positive effects, and the total final demand effect is the main factor leading to the increase in carbon emissions, and the effect of the final demand structure effect is not significant. In addition, the results of the influence coefficient and the inductance coefficient show that: metal smelting and rolling manufacturing, petroleum processing and coking and nuclear fuel processing, coal mining and processing, and oil and gas mining and processing industries are high-energy-consuming industries, but the status of the basic industry makes it possible to formulate energy-saving policies only in terms of technological progress.


2021 ◽  
Author(s):  
Xianzhao Liu ◽  
Xu Yang

Abstract Facing the growing problem of carbon emission pollution, the scientific and reasonable division of environmental management power between governments is the premise and institutional foundation for realizing China's carbon emission reduction target in 2030. Although existing studies have focused on the relationship between Chinese decentralization and carbon emissions, most of them are based on fiscal decentralization indicators to depict China's environmental decentralization, lacking of systematic analysis and empirical test of institutional factors affecting carbon emissions from the perspective of environmental management. In this paper, we directly assess the environmental decentralization degree according to the allocation of environmental management personnel among different levels of government. By incorporating fiscal decentralization indicators, the provincial panel data and dynamic spatial econometric model are used to empirically test the impact of environmental decentralization on carbon emissions from spatial perspective. The study found that: (1) China's provincial carbon emissions have a significant positive spatial autocorrelation, showing a clear trend of high-high, low-low aggregation, and the carbon emissions of the previous period and the current have an obvious positive relationship. (2) At the national level, environmental decentralization, environmental administrative decentralization and environmental monitoring decentralization significantly reduce China's carbon emissions, while environmental supervision decentralization and fiscal decentralization significantly aggravate carbon emissions, which means that China's current environmental decentralization systems are generally conducive to carbon emission governance. The interaction between fiscal decentralization and environmental decentralization with its decomposition indicators significantly promotes carbon emissions, and its impact is related to the category of environmental decentralization, indicating that when local governments have greater environmental management power and fiscal autonomy, the combination of the two will push up carbon emissions. (3) The carbon emission effects of environmental decentralization in different regions are spatially heterogeneous. In the central region, environmental decentralization, environmental administrative decentralization and environmental supervision decentralization can promote carbon emissions apart from environmental monitoring decentralization. In the western region, the carbon emission suppression effect of environmental decentralization, environmental administrative decentralization and environmental monitoring decentralization is stronger than the eastern region, but the inhibitory effect of fiscal decentralization and environmental decentralization with its decomposition index interaction on carbon emissions in the eastern region is significantly better than the central and western regions. The above results provide policy ideas and theoretical support for the construction of the environmental management system with long-term carbon emission control in China in terms of regional differences and categories of environmental management power.


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