Research on the Regional Low-Carbon Industrial Development: A Case of Tianjin Binhai New Area

2011 ◽  
Vol 219-220 ◽  
pp. 250-253 ◽  
Author(s):  
Xiao Ying Cui ◽  
Hui Ming Li ◽  
Lei Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Industrial Development ◽  
Carbon Emission ◽  
Large Scale ◽  
Industrial Structure ◽  
Industrial Sector ◽  
Energy Structure ◽  
Low Carbon ◽  
Tianjin Binhai New Area

Energy consumption induced by industry sector is the main source of carbon emission. So it is important to the policy making that research on the low-carbon industrial development, which is aiming to establish an industry system with low-carbon character. There are four restrictive factors on low-carbon industrial development in Tianjin Binhai New Area of China: the rather large scale of the secondary industry, the heavy industrial structure which strongly caused the increasing energy consumption, the high-carbon energy structure of industrial sector, and the lower industrial energy efficiency which has certain gap compared with other regions. Several countermeasures are proposed to reduce carbon emission induced by industrial sector, such as improving energy efficiency, optimizing energy structure, establishing multiple-access financing mechanism to encourage R&D on low-carbon technology, enhancing the development of low carbon industry, participating in the international cooperation actively, and making strategic plan of low-carbon industrial development.

Influencing Factors Decomposition of the Carbon Emission of Industrial Energy Consumption in Nanning Downtown Based on LMDI

2015 ◽  
Vol 737 ◽  
pp. 925-934 ◽  
Author(s):  
Jing Yang ◽  
Huan Mei Yao ◽  
Meng Lin Qin
Keyword(s):  
Energy Consumption ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Driving Factor ◽  
Low Carbon ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Industrial Energy Consumption

According to IPCC carbon emission calculation instruction, the amount of industrial carbon emission of downtown of Nanning from 2003-2012 is evaluated. With LMDI element decomposition method, the carbon emission of industrial energy consumption in Nanning downtown is decomposed into effect of five aspects such as energy structure, energy intensity, industrial structure, economic scale and population size. It turns out that: the energy structure change can promote the increase of carbon emission. The energy consumption structure should be optimized and the proportion of high-carbon energy consumption should be reduced; The energy intensity is the leading driving factor of carbon emission. The energy efficiency should be further improved to control the increase of carbon emission to some degree; The industrial structure restrains the increase of carbon emission in a great degree. Industrial restructuring should be strengthened and low-carbon industry should be developed; The scale of economy is the main driving factor of the increase of carbon emission. The extensive way of economic growth which depends on the large input of production factors should be changed; The population has a promoting function the increase of carbon emission, while the driving effect is weak, and the growth rate of the population should be strictly controlled.

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 Total Factor Energy Efficiency, Carbon Emission Efficiency, and Technology Gap: Evidence from Sub-Industries of Anhui Province in China

2020 ◽  
Vol 12 (4) ◽  
pp. 1402 ◽  
Author(s):  
Ya Chen ◽  
Wei Xu ◽  
Qian Zhou ◽  
Zhixiang Zhou
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Carbon Emission ◽  
Energy Use ◽  
Industrial Sector ◽  
Policy Implications ◽  
Light Industry ◽  
Heavy Industry ◽  
Technology Gap ◽  
Emission Efficiency

The phenomena of “large energy consumption, high carbon emission, and serious environmental pollution” are against the goals of “low energy consumption, low emissions” in China’s industrial sector. The key to solving the problem lies in improving total factor energy efficiency (TFEE) and carbon emission efficiency (TFCE). Considering the heterogeneity of different sub-industries, this paper proposes a three-stage global meta-frontier slacks-based measure (GMSBM) method for measuring TFEE and TFCE, as well as the technology gap by combining meta-frontier technology with slacks-based measure (SBM) using data envelopment analysis (DEA). DEA can effectively avoid the situation where the technology gap ratio (TGR) is larger than unity. This paper uses the three-stage method to empirically analyze TFEE and TFCE of Anhui’s 38 industrial sub-industries in China from 2012 to 2016. The main findings are as follows: (1) Anhui’s industrial sector has low TFEE and TFCE, which has great potential for improvement. (2) TFEE and TFCE of light industry are lower than those of heavy industry under group-frontier, while they are higher than those of heavy industry under meta-frontier. There is a big gap in TFEE and TFCE among sub-industries of light industry. Narrowing the gap among different sub-industries of light industry is conducive to the overall improvement in TFEE and TFCE. (3) The TGR of light industry is significantly higher than that of heavy industry, indicating that there are sub-industries with the most advanced energy use and carbon emission technologies in light industry. And there is a bigger carbon-emitting technology gap in heavy industry, so it needs to encourage technology spillover from light industry to heavy industry. (4) The total performance loss of industrial sub-industries in Anhui mainly comes from management inefficiency, so it is necessary to improve management and operational ability. Based on the findings, some policy implications are proposed.

Energy Consumption and Structural Reformation in Chinese Northeast Old Industrial Base

2013 ◽  
Vol 448-453 ◽  
pp. 4281-4284 ◽  
Author(s):  
Shao Bo Liu
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Energy Utilization ◽  
Energy Structure ◽  
Energy Technology ◽  
Industrial Base ◽  
Old Industrial Base ◽  
Emissions Intensity

Using IPCC methodology, the carbon emissions of Chinese Northeast Old Industrial Base is calculated, and the energy's synthesized impact on carbon emissions intensity is presented. The resulting shows that the carbon emissions in the three northeast provinces decreased 52.87% from 2000 to 2010, of which, Liaoning, Jilin and Heilongjiang are individually 60.09%, 45.47% and 54.14% lower. The implications are that the energy structure is one of the main factors in carbon emission in the Old Industrial Base of Northeast China, and its industrial structure is changing greatly due to energy consumption carbon emission. To adjust optimally the energy and industrial structure, and to develop the energy technology to promote energy utilization are recommended.

scholarly journals Appraisal of CO2 Emission in Tunisia's Industrial Sector: A Dynamic Vector Autoregression Method

2021 ◽  
Author(s):  
Besma Talbi ◽  
Muhammad Ramzan ◽  
Hafiz Arslan Iqbal ◽  
Buhari Doğan
Keyword(s):  
Economic Growth ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Natural Gas ◽  
Environmental Degradation ◽  
Large Scale ◽  
Dominant Role ◽  
Industrial Sector ◽  
Kuznets Curve ◽  
Additional Energy

Abstract The World is confronted with a slew of environmental issues, one of which is how to attenuate the detrimental impacts of CO2 emissions-induced climate change. The ever-increasing use of energy is eroding natural resources to the point that our economic future may be jeopardized. The Tunisian economic growth indicates the excellent performance in the industrial sector as the minimum required input for these developments necessitates additional energy consumption, resulting in increased CO2 emissions and environmental degradation. This study explores the role of energy efficiency, urbanization, economic growth, and natural gas energy usage in the industrial sector on carbon dioxide (CO2) emissions of Tunisia. The research mainly employs the Vector Autoregressive Model (VAR) to examine the factors driving the evolution of CO2 emissions through the industrial sector from 2000 to 2018. The findings assess that natural gas as an energy source and efficiency are crucial for reducing CO2 emissions. The study has shown the existence of the Environmental Kuznets Curve (EKC), which demonstrates that economic development in Tunisia has an inverted U-shape connection with CO2 emissions. The results indicate that energy consumption and GDP significantly affect CO2 emissions due to large-scale population movements and industrial structure transformation. In contrast, energy efficiency plays a dominant role in decreasing CO2 emissions. The article will assist economic decision-makers and related authorities in formulating an appropriate energy policy for the industrial sector based on the study's outcomes to protect environmental degradation in the long run by reducing carbon emissions.

Shanghai's CO2 Emissions and Policy Implication for Low Carbon Construction

2013 ◽  
Vol 869-870 ◽  
pp. 893-897
Author(s):  
Lin Hui Zeng ◽  
Guang Ming Li ◽  
Ju Wen Huang ◽  
Hao Chen Zhu ◽  
Jing Cheng Xu
Keyword(s):  
Industrial Structure ◽  
Industrial Sector ◽  
Energy Structure ◽  
Low Carbon ◽  
Carbon Mitigation ◽  
The Past ◽  
Energy Efficiency Improvement ◽  
Structure Adjustment ◽  
Industrial Structure Adjustment ◽  
The City

Cities are the main contributors of anthropogenic greenhouse gases (GHGs) emissions. Comprehensive countermeasures are needed in cities to mitigate GHGs emissions. The aim of this paper is to study the results that Shanghai achieved in carbon mitigation by comprehensive green measures. It demonstrated that Shanghai has made significant progress in carbon emission reduction through technological innovation, industrial structure adjustment, and energy efficiency improvement in recent years. The results showed that Shanghais energy related CO2 intensity reduced to 1.14 t/104 yuan in 2010, owing to adjustments in energy structure and industry structure. It also showed that Shanghai had made abundant reduction in carbon emissions in the past few years. 9.2 million tons of CO2 reductions were obtained in industry, transportation, and building in the city level. Among them, reductions in industrial sector and transportation were the major contributors. Further efforts should be taken to realize a low carbon future.

The Study on Carbon Emission Influencing Factors of Industrial Energy Consumption of Changchun City

2012 ◽  
Vol 164 ◽  
pp. 302-305
Author(s):  
Zhuo Ma ◽  
Xiao Gang He ◽  
Xun Zhou Tong ◽  
Hai Yan Duan ◽  
Xian En Wang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Industrial Development ◽  
Carbon Emission ◽  
Low Carbon ◽  
Industrial Energy ◽  
Emission Changes ◽  
Major Factors ◽  
Industrial Energy Consumption

To make great efforts for energy saving and promote low-carbon transition of industrial development pattern have been the most crucial tasks for Changchun industrial developmen. Using Logarithmic Mean Divisia Index (LMDI) mode decomposes the carbon emission influencing factors of the industrial department in Changchun, and study on the effects of factors on the carbon emissions of industrial energy consumption. The result shows that the major factors for carbon emissions of industrial energy consumption in Changchun are economic development, the population size and the industrialization rate, and the key factors for the carbon emission changes in industrial department of Changchun are the energy consumption structure and the energy intensity.

scholarly journals Evolution of Renewable Energy in BRI Countries: A Combined Econometric and Decomposition Approach

2020 ◽  
Vol 17 (22) ◽  
pp. 8668 ◽  
Author(s):  
Feng Dong ◽  
Yuling Pan
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Economic Effect ◽  
Energy Structure ◽  
Low Carbon ◽  
Renewable Energy Consumption ◽  
Intensity Effect ◽  
Emission Effect

The development of renewable energy is an important cooperation theme among countries along the Belt and Road Initiative (BRI countries). Through map description, we first explore the changes in renewable energy consumption in BRI countries. Then, β-convergence is employed to examine the development direction of renewable energy consumption in BRI countries. Finally, based on the expanded Kaya equation, we decompose the factors effecting renewable energy consumption into energy structure effect, energy intensity effect, low-carbon economic effect, carbon emission effect, population distribution effect and population effect. The Logarithmic Mean Divisia Index (LMDI) is utilized to calculate the contribution of each factor to renewable energy consumption in the expanded Kaya equation. Our research reaches the following conclusions: (1) β-convergence exists in renewable energy consumption among BRI countries, indicating that it will converge to a relatively stable level, and countries with low renewable energy consumption will increase their renewable energy consumption with a higher convergence rate to chase the countries with high renewable energy consumption. (2) Energy structure effect makes a positive impact on renewable energy consumption, and is the main contributor to renewable energy consumption. (3) The energy intensity effect makes a negative contribution to renewable energy consumption, and the negative impact has deepened in recent years. (4) Both the low-carbon economic effect and the carbon emission effect have positive impacts on renewable energy consumption. Our research not only provides a description of the experience of developing renewable energy for BRI countries, but also makes reference to other organizations.

Research on the Driving Force Factors of Development of Low Carbon of Urban Transportation: Taking Tianjin as an Example

2013 ◽  
Vol 798-799 ◽  
pp. 1115-1118
Author(s):  
Jian Li ◽  
Hong Yuan Liu ◽  
Xin Teng
Keyword(s):  
Energy Consumption ◽  
Urban Space ◽  
Public Transportation ◽  
Carbon Emission ◽  
Urban Transportation ◽  
Correlation Method ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Energy Structure ◽  
Low Carbon

Urban transportation is the main way of carbon emission, development of low-carbon transportation has become the focus of attention of the countries all over the world. This paper analyses the influencing factors of carbon emission of Tianjin transportation based on grey correlation method, putting forward that the cost of urban resident transportation, traffic volume of urban passenger, number of private car and energy consumption of urban transportation are the most important key factors. Therefore, in order to construct low-carbon transportation system, Tianjin should design the layoff of urban space reasonably to control the demand of transportation effectively to reduce the urban transportation cost first, develop urban public transportation to optimize the urban traffic structure in response to the growing urban traffic volume of passenger second , establish a series of laws and regulations to improve the urban traffic management level to strengthen the supervision of private cars third, develop and apply new technology and new energy to adjust the energy structure of urban transportation to reduce urban transportation energy consumption at last.

scholarly journals Construction and Application Analysis of Carbon Emission Influence Factor Model of Energy Consumption in Mining Industry

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lili Wei ◽  
Xiwen Feng ◽  
Guangyu Jia
Keyword(s):  
Energy Consumption ◽  
Emission Intensity ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Mining Industry ◽  
Energy Structure ◽  
Low Carbon ◽  
Greenhouse Gas Inventory ◽  
Carbon Emission Intensity ◽  
Low Carbon Development

With the proposal of China’s “double carbon goal,” as a high energy-consuming industry, it is urgent for the mining industry to adopt a low-carbon development strategy. Therefore, in order to better provide reasonable suggestions and references for the low-carbon development of mining industry, referring to the methods and parameters of the 2006 IPCC National Greenhouse Gas Inventory Guidelines and China’s Provincial Greenhouse Gas Inventory Preparation Guidelines (Trial), a carbon emission estimation model is established to estimate the carbon emission of energy consumption of China's mining industry from 2000 to 2020. Then, using the extended Kaya identity, the influencing factors of carbon emission in mining industry are decomposed into energy carbon emission intensity, energy structure, energy intensity, industrial structure, and output value. On this basis, an LMDI model is constructed to analyze the impact of five factors on carbon emission from mining industry. The research shows that the carbon emission and carbon emission intensity of energy consumption in China’s mining industry first rise and then fall and then rise slightly. The carbon emission intensity in recent three years is about 2 tons/10000 yuan. The increase in output value is the main factor to increase carbon emission. The reduction in energy intensity is the initiative of carbon emission reduction. The current energy structure of mining industry is not conducive to carbon emission reduction.

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