The pilot trading of carbon emission rights and upgrading of industrial structure

2020 ◽  
Vol 68 (1/2) ◽  
pp. 82
Author(s):  
Dongsheng Zhao ◽  
Yu Ma ◽  
Huaiwen Zhang ◽  
Xinyu Wang
Keyword(s):  
Carbon Emission ◽  
Industrial Structure ◽  
Emission Rights

scholarly journals Research on Carbon Emission Reduction Effect of China's Carbon Trading Pilot

2020 ◽  
Vol 7 (5) ◽  
pp. 240-250
Author(s):  
Linshan Wang ◽  
Chuanming Liu ◽  
Xi Yang
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Government Support ◽  
Carbon Trading ◽  
Carbon Emission Reduction ◽  
Carbon Emissions Trading ◽  
Emission Rights ◽  
Development Levels

Carbon emissions trading is one of the important ways to reduce carbon emissions by giving CO2 emission rights a commodity attribute that allows them to trade on the market and to reduce greenhouse gas emissions through the market mechanisms. Based on the inter-provincial panel data from 1997 to 2016, this paper constructs a basic theoretical analysis framework to analyze the carbon emission reduction effects of carbon trading policies, adopts PSM-DID to study the carbon emission reduction effects of carbon trading pilots. This study finds that: (1) The implementation of the carbon trading pilot can promote carbon emission reduction, but the pilot provinces and municipalities have different economic development levels, industrial structure and supporting measures adopted after the implementation of the carbon trading pilot policy, resulting in differences in carbon emission reduction effects between pilot provinces. (2) For the seller of carbon emission rights, carbon emission reduction is achieved through three effects of "market return-inducing", "technical innovation incentive" and "government support"; for the buyer, carbon emission reduction is achieved through three effects of "enterprise cost pressure", "process innovation motivation" and "market guiding". (4) The results of traditional PSM-DID further prove that the carbon trading pilot can significantly reduce CO2 emissions.

The pilot trading of carbon emission rights and upgrading of industrial structure

2020 ◽  
Vol 68 (1/2) ◽  
pp. 82
Author(s):  
Huaiwen Zhang ◽  
Xinyu Wang ◽  
Yu Ma ◽  
Dongsheng Zhao
Keyword(s):  
Carbon Emission ◽  
Industrial Structure ◽  
Emission Rights

Carbon Emission of Mining Industry’s Energy Consumption in Heilongjiang Province

2015 ◽  
Vol 1092-1093 ◽  
pp. 1597-1600
Author(s):  
Zhong Hua Wang ◽  
Xin Ye Chen
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Mining Industry ◽  
Calculation Model ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Heilongjiang Province ◽  
Low Carbon

The need to reduce carbon emission in Heilongjiang Province of China is urgent challenge facing sustainable development. This paper aims to make explicit the problem-solving of carbon emission to find low carbon emission ways. According to domestic and foreign literatures on estimating and calculating carbon emissions and by integrating calculation methods of carbon emissions, it was not possible to consider all of the many contributions to carbon emissions. Calculation model of carbon emissions suitable to this paper is selected. The carbon emissions of energy consumption in mining industry are estimated and calculated from 2005 to 2012, and the characteristics of carbon emission are analyzed at the provincial level. It makes the point that carbon emissions of energy consumption in mining industry can be reduced when we attempt to alter energy consumption structure, adjust industrial structure and improve energy utilization efficiency.

scholarly journals Strategies for Capital Constrained Timber and Carbon Sink Supply Chain under the Cap-and-Trade Scheme

2020 ◽  
Vol 12 (11) ◽  
pp. 4380
Author(s):  
Xinyue Yang ◽  
Ye Song ◽  
Mingjun Sun ◽  
Hongjun Peng
Keyword(s):  
Supply Chain ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Carbon Sink ◽  
Cap And Trade ◽  
Stackelberg Model ◽  
Emission Rights ◽  
The Government ◽  
The Impact ◽  
Reduction Costs

We consider a capital constrained timber and carbon sink supply chain under the cap-and-trade scheme, where the forest company produces timber and carbon sink. We consider two subsidy modes: financing subsidy to the carbon sink forests and financing subsidy to the manufacturer’s emission reductions. We apply a Stackelberg model and mainly consider the impact of subsidies on the profits and the strategies of the supply chain members. The results show that when the government gives a financing subsidy to the carbon sink forests, it is conducive to promoting the expansion of carbon sink forests, as well as the enhancement of the forest company’s profit. However, a larger supply of carbon sinks generates a lower price, which leads to the manufacturer reducing the technical emission reduction level and purchasing more carbon emission rights instead. On the other hand, when the manufacturer receives a financing subsidy for the technical emission reduction costs, its production becomes cleaner than before, and the profits of the forest company and the manufacturer increase.

scholarly journals Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3081 ◽  
Author(s):  
Zeng ◽  
Lu ◽  
Liu ◽  
Zhou ◽  
Hu
Keyword(s):  
Influencing Factors ◽  
Regional Differences ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Tobit Model ◽  
Policy Implications ◽  
Dea Model ◽  
Emission Efficiency ◽  
Unit Root Testing ◽  
Technology Level

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.

scholarly journals Factors Affecting Energy-Related Carbon Emissions in Beijing-Tianjin-Hebei Region

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Jing-min Wang ◽  
Yu-fang Shi ◽  
Xue Zhao ◽  
Xue-ting Zhang
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Factors Affecting ◽  
Economic Output ◽  
Level Model ◽  
The Impact ◽  
The Relationship

Beijing-Tianjin-Hebei is a typical developed region in China. The development of economy has brought lots of carbon emissions. To explore an effective way to reduce carbon emissions, we applied the Logarithmic Mean Divisia Index (LMDI) model to find drivers behind carbon emission from 2003 to 2013. Results showed that, in Beijing, Tianjin, and Hebei, economic output was main contributor to carbon emissions. Then we utilized the decoupling model to comprehensively analyze the relationship between economic output and carbon emission. Based on the two-level model, results indicated the following: (1) Industry sector accounted for almost 80% of energy consumption in whole region. The reduced proportion of industrial GDP will directly reduce the carbon emissions. (2) The carbon factor for CO2/energy in whole region was higher than that of Beijing and Tianjin but lower than that of Hebei. The impact of energy structure on carbon emission depends largely on the proportion of coal in industry. (3) The energy intensity in whole region decreased from 0.79 in 2003 to 0.40 in 2013 (unit: tons of standard coal/ten thousand yuan), which was lower than national average. (4) The cumulative effects of industrial structure, energy structure, and energy intensity were negative, positive, and negative, respectively.

Carbon Emission and Urban Construction Land Expansion in China: Evidence from Co-Integration Tests and Impulse Response Model

2014 ◽  
Vol 1010-1012 ◽  
pp. 1883-1888
Author(s):  
Wen Wen Qiu
Keyword(s):  
Urban Development ◽  
Impulse Response ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Urban Expansion ◽  
Response Analysis ◽  
Causality Test ◽  
Construction Land ◽  
Urban Construction ◽  
The Impact

Using co-integration analysis, Granger causality test, and impulse response analysis in an integrated way, this paper makes empirical study of the impact on China’s carbon emission by its urban construction land expansion. The result shows that there is a long-run equilibrium relationship between carbon emission and urban construction land expansion in China, with the latter being the Granger cause of the increase in carbon emission. However, the impact process shows a lagging nature. The impact effect is not so evident in a short term, but is rather significant in a long term (five to ten years). To reduce its carbon emission, China should optimize its urban development mode and control the scale of urban development reasonably, especially focusing on the economical and intensive use of land and upgrading of industrial structure, so as to reduce energy consumption by its urban expansion, check excessive increase in carbon emission, and promote the sustainable urbanization.

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