The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimations

2019 ◽  
Vol 133 ◽  
pp. 685-691 ◽  
Author(s):  
Arshian Sharif ◽  
Syed Ali Raza ◽  
Ilhan Ozturk ◽  
Sahar Afshan
Keyword(s):  
Energy Consumption ◽  
Carbon Emission ◽  
Dynamic Relationship ◽  
Global Study ◽  
Relationship Of ◽  
Heterogeneous Panel ◽  
Nonrenewable Energy

Study on the Relationship between Energy Consumption, Carbon Emission and Economic Growth in China

2013 ◽  
Vol 869-870 ◽  
pp. 746-749
Author(s):  
Tian Tian Jin ◽  
Jin Suo Zhang
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Structure ◽  
Ardl Model ◽  
Relationship Of ◽  
The Relationship ◽  
Reducing Energy

Abstract. Based on ARDL model, this paper discussed the relationship of energy consumption, carbon emission and economic growth.The results indicated that the key to reduce carbon emissions lies in reducing energy consumption, optimizing energy structure.

scholarly journals Dynamic relationship between urban carbon dioxide emissions and economic growth

2020 ◽  
Keyword(s):  
Economic Growth ◽  
Carbon Dioxide ◽  
Energy Consumption ◽  
Granger Causality ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Carbon Dioxide Emission ◽  
Dynamic Relationship

<p>Urban economic development cannot be separated from energy consumption, and energy consumption directly leads to a large number of carbon emissions. It is of great significance to study the relationship between carbon dioxide emissions and economic growth for the implementation of energy conservation, emission reduction and the development of low-carbon economy in cities. A new method of dynamic relationship between urban carbon dioxide emission and economic growth is put forward. The carbon dioxide emission data in cities are calculated by using urban carbon dioxide emission measurement method. The data of economic attributes are obtained by using classification algorithm under uncertain data flow environment. Based on this data, a decoupling model of carbon emission and economic growth is constructed to measure economic growth elasticity of urban carbon emissions; Granger causality test model is established to analyze the Granger causality between urban carbon dioxide emissions and economic growth. The experimental results show that the growth rate of urban economy is obviously faster than that of carbon emissions. Economic growth is the Granger causality of carbon dioxide emissions. On the contrary, the implementation of carbon emission reduction measures will not hinder economic growth.</p>

scholarly journals Nexus Among Energy Consumption Structure, Energy Intensity, Population Density, Urbanization And Carbon Intensity: A Heterogeneous Panel Evidence Considering Differences In Electrification Rates

2021 ◽  
Author(s):  
Jingqi Sun ◽  
Xiaohui Guo ◽  
Yuan Wang ◽  
Jing Shi ◽  
Yiquan Zhou ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Population Density ◽  
Energy Intensity ◽  
Absolute Convergence ◽  
Carbon Intensity ◽  
Conditional Convergence ◽  
Consumption Structure ◽  
Urbanization Rate ◽  
Relationship Of ◽  
Heterogeneous Panel

Abstract In this paper, the clustering method is used to divide the 30 provinces of the country into high, medium and low electrification rates according to the electrification rate from 2000 to 2017. The heterogeneous panel technology is used to analyze the relationship of energy consumption structure, energy intensity, population density, urbanization rate and carbon intensity. According to Cross-sectional dependence(CD) test and cross-section Im-Pesaran-Shin (CIPS) test results, the data of each panel are not in the form of same order single integer, so α convergence analysis, β absolute convergence, and β conditional convergence analysis are required. The results show that the carbon intensity of the four panels shows an α convergence; the β absolute convergence shows there is a “catch-up effect”; β conditional convergence indicates that the carbon intensity approaches their respective steady state levels; there is a long-term equilibrium relationship of energy consumption structure, energy intensity, population density and carbon intensity in all panels, but the urbanization rate has a significant impact on carbon intensity only in areas with high electrification rates. Finally, based on the results of empirical research, policy recommendations for reducing the carbon intensity in different regions are proposed.

The Short-Term Dynamic Relationship of China's Energy-Economy-Environment System

2013 ◽  
Vol 448-453 ◽  
pp. 4325-4328
Author(s):  
Lei Zhang ◽  
Sen Guo ◽  
Kun Yang ◽  
Si Qi He ◽  
Hui Ru Zhao
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Impulse Response Function ◽  
Annual Data ◽  
Short Term ◽  
Dynamic Relationship ◽  
Vec Model ◽  
Energy Economy ◽  
Consumption Energy ◽  
Relationship Of

Energy is the foundation of economy for China. The economic growth depends on energy, but recent years, the carbon dioxide from energy consumption hinders the GDP to grow. Environment starts to affect economic growth and it becomes a restriction to energy consumption. Energy, economy and environment have formed a new system which is called 3E system, so its practical to study the dynamical relationships among the 3E system. This paper selects annual data from 1970 to 2009 to establish a VEC model and takes the impulse response function and variance analysis to analyze the short-term dynamical relationship of Chinas 3E system, finding that there is at least one co-integration relationship among 3E system in China. Finally, this paper discusses how the energy, economy, and environment affect each other in short term from a quantitative perspective and intends to provide some advices to draft applicable energy policy for China.

scholarly journals Examining the Driving Factors of the Direct Carbon Emissions of Households in the Ebinur Lake Basin Using the Extended STIRPAT Model

2021 ◽  
Vol 13 (3) ◽  
pp. 1339
Author(s):  
Ziyuan Chai ◽  
Zibibula Simayi ◽  
Zhihan Yang ◽  
Shengtian Yang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Driving Factors ◽  
Series Data ◽  
Lake Basin ◽  
Stirpat Model ◽  
Consumption Structure ◽  
Ebinur Lake ◽  
Ebinur Lake Basin

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.

scholarly journals Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3287
Author(s):  
Alireza Tabrizikahou ◽  
Piotr Nowotarski
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Structural Optimization ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Construction Materials ◽  
High Energy ◽  
Building Structures ◽  
Life Cycle Stages ◽  
Reduction Of Energy Consumption

For decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the embodied stage occurs in a time-intensive manner. In this paper, an attempt has been made to review the existing methods, aiming to lower the consumption of energy and carbon emission in the construction buildings through optimizing the construction processes, especially with the lean construction approach. First, the energy consumption and emissions for primary construction materials and processes are introduced. It is followed by a review of the structural optimization and lean techniques that seek to improve the construction processes. Then, the influence of these methods on the reduction of energy consumption is discussed. Based on these methods, a general algorithm is proposed with the purpose of improving the construction processes’ performance. It includes structural optimization and lean and life cycle assessments, which are expected to influence the possible reduction of energy consumption and carbon emissions during the execution of construction works.

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