scholarly journals The Decoupling of China's Economy-Carbon Emission and Its Driving Factors

2021 ◽  
Author(s):  
Peng Kuai ◽  
Yao Cheng ◽  
Shu'an Zhang
Keyword(s):  
Carbon Emission ◽  
Energy Intensity ◽  
Driving Factors ◽  
Gdp Per Capita ◽  
Energy Structure ◽  
Heterogeneity Effects ◽  
Per Capita ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics ◽  
China’S Economy

Abstract Decoupling between economic growth and carbon emission is a global hot topic. This paper studies China’s economic-carbon decoupling and its driving factors. By using the panel data of 30 Chinese provinces from 2000 to 2016, the decoupling index of each province is calculated with the Tapio model. It is found that many provinces have progressed from no decoupling to weak decoupling and then strong decoupling. Then, the econometric models are used to explore the driving factors. Results show that energy structure is the most important factor, followed by GDP per capita and energy intensity, which all increase CO2 emission significantly. The results are robust when tested with GMM, PCSE and FGLS estimation and LMDI decomposition. Further, we conduct a comparative analysis regarding the temporal and spatial characteristics of the above three driving factors to identify their relationship with decoupling, four groups of regions that represent different economic features are selected for the analysis. Heterogeneity effects of the factors among the regions has been observed, based on this we provide targeted strategies for different regions.

scholarly journals Scenario Analysis of Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China

2019 ◽  
Vol 11 (15) ◽  
pp. 4220 ◽  
Author(s):  
Jiancheng Qin ◽  
Hui Tao ◽  
Minjin Zhan ◽  
Qamar Munir ◽  
Karthikeyan Brindha ◽  
...  
Keyword(s):  
Scenario Analysis ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Gdp Per Capita ◽  
Energy Structure ◽  
Urbanization Level ◽  
Autonomous Region ◽  
Per Capita ◽  
Xinjiang Autonomous Region

The realization of carbon emissions peak is important in the energy base area of China for the sustainable development of the socio-economic sector. The STIRPAT model was employed to analyze the elasticity of influencing factors of carbon emissions during 1990–2010 in the Xinjiang autonomous region, China. The results display that population growth is the key driving factor for carbon emissions, while energy intensity is the key restraining factor. With 1% change in population, gross domestic product (GDP) per capita, energy intensity, energy structure, urbanization level, and industrial structure, the change in carbon emissions was 0.80%, 0.48%, 0.20%, 0.07%, 0.58%, and 0.47%, respectively. Based on the results from regression analysis, scenario analysis was employed in this study, and it was found that Xinjiang would be difficult to realize carbon emissions peak early around 2030. Under the condition of the medium-high change rates in energy intensity, energy structure, industrial structure, and with the low-medium change rates in population, GDP per capita, and urbanization level, Xinjiang will achieve carbon emissions peak at of 626.21, 636.24, 459.53, and 662.25 million tons in the year of 2030, 2030, 2040, and 2040, respectively. At last, under the background of Chinese carbon emissions peak around 2030, this paper puts forward relevant policies and suggestions to the sustainable socio-economic development for the energy base area, Xinjiang autonomous region.

scholarly journals The Regional Inequity of CO2 Emissions per Capita in China

2017 ◽  
Vol 9 (7) ◽  
pp. 228 ◽  
Author(s):  
Ting Liu ◽  
Wenqing Pan
Keyword(s):  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Theil Index ◽  
Energy Structure ◽  
Co2 Emission Reduction ◽  
Index Method ◽  
Per Capita

This paper combines Theil index method with factor decomposition technique to analyze China eight regions’ inequality of CO2 emissions per capita, and discuss energy structure, energy intensity, industrial structure, and per capita output’s impacts on inequality. This research shows that: (1) The trend of China regional carbon inequality is in the opposite direction to the per capita CO2 emission level. Namely, as the per capita CO2 emission levels rise, regional carbon inequality decreases, and vice versa. (2) Per capita output factor reduces regional carbon inequality, whereas energy structure factor and energy intensity factor increase the inequality. (3) More developed areas can reduce the carbon inequality by improving the energy structure, whereas the divergence of energy intensity in less developed areas has increased to expand the carbon inequity. Thus, when designing CO2 emission reduction targets, policy makers should consider regional differences in economic development level and energy efficiency, and refer to the main influencing factors. At the same time, upgrading industrial structure and upgrading energy technologies should be combined to meet the targets of economic growth and CO2 emission reduction.

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.

scholarly journals Symmetric and Asymmetric Impact of Poverty, Income Inequality, and Population on Carbon Emission in Pakistan: New Evidence From ARDL and NARDL Co-Integration

2021 ◽  
Vol 9 ◽  
Author(s):  
Salim Khan ◽  
Wang Yahong
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Environmental Degradation ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Policy Implications ◽  
Gdp Per Capita ◽  
Long Run ◽  
Asymmetric Impact ◽  
Per Capita

Several researchers have studied the relationship between poverty and environmental degradation, as these concerns are remained at top priority in achieving Sustainable Development Goals (SDGs). However, the symmetric and asymmetric impact of poverty and income inequality along with population and economic growth on carbon emissions (CO2e) has not been studied in the case of Pakistan. For this purpose, the short and long-run impact of poverty, income inequality, population, and GDP per capita on CO2e investigated by applying the Autoregressive Distributive Lag (ARDL) along with Non-linear Autoregressive Distributive Lag (NARDL) co-integration approach in the context of Pakistan for period 1971–2015. The symmetric results of the current study show poverty and population density along with GDP per capita increase carbon emissions in both the short and long-run, while income inequality has no impact on carbon emissions in the short-run. While in the long-run the symmetric results show that income inequality weakens environmental degradation in terms of carbon emissions. The analysis of NARDL also supports the results obtained from ARDL and suggests a positive effect of poverty, population, and economic growth on carbon emission in Pakistan. The empirical findings of the current study provide policy implications in light of the United Nation's SDGs for the development of Pakistan.

scholarly journals Emisi Karbon dan Produk Domestik Bruto: Investigasi Hipotesis Environmental Kuznets Curve (EKC) pada Negara Berpendapatan Menengah di Kawasan ASEAN

2020 ◽  
Vol 8 (3) ◽  
pp. 230-246
Author(s):  
Muhamad Ameer Noor ◽  
Putu Mahardika Adi Saputra
Keyword(s):  
Environmental Kuznets Curve ◽  
Carbon Emission ◽  
Time Series Data ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Series Data ◽  
Kuznets Curve ◽  
Middle Income ◽  
Trade Offs ◽  
Per Capita

Policymakers in the world are concerned with carbon emission due to the risk of global warming. Many studies on Environmental Kuznets Curve (EKC) consider carbon emission as a proxy of environmental degradation. This study aimed to investigate the existence of EKC and identify variations of relationships between carbon emissions and GDP per capita in ASEAN middle-income countries. The study was conducted on Indonesia, Thailand, Philippines, and Malaysia based on 1971-2014 time series data using a simultaneous model (2SLS) for each country. The main variables studied were GDP per capita, square of GDP per capita, and carbon emission supported by other variables as the controlling variables. Validation on EKC existence was determined by GDP and GDP squared influence on carbon emission, while variations of relationship between GDP and carbon emission were based on the result of simultaneous regressions. The results showed that the existence of the EKC could not be validated in all countries because energy and transportation policies in each country failed to reduce the emission. On the other hand, carbon emission had a positive unidirectional influence on GDP in all countries. The effect of carbon emission coefficient to GDP showed that Thailand ranked the highest in CO2 efficiency, followed by Indonesia, Philippines, and Malaysia. This study recommended that carbon emission reduction policies in the four countries should focus more to easier access to environmentally friendly technology from developed countries for ensuring trade-offs between the economy and environment.

Energy consumption and economic development in Guangdong, China: Distribution, relationship and causes

2021 ◽  
Author(s):  
Mengmeng Hu ◽  
Yafei Wang ◽  
Beicheng Xia ◽  
Guohe Huang
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Energy Consumption ◽  
Energy Intensity ◽  
Hot Spot ◽  
Generalized Method Of Moments ◽  
Gdp Per Capita ◽  
Per Capita ◽  
The Pearl River ◽  
Panel Vector Autoregression

Abstract Analysing the relationship between energy consumption and economic growth is essential to achieve the goal of sustainable development. We employ hot spot analysis to discover the spatial agglomeration of GDP per capita and energy intensity in Guangdong, China, from 2005–2018. Furthermore, panel vector autoregression coupled with a system generalized method of moments is performed to examine the dynamic causal relationship between energy consumption and economic growth under the framework of the Cobb-Douglas production function. Using a multivariate model and grouped studies based on the differences in regional economic development, we show that the GDP per capita of the Pearl River Delta (PRD) is significantly higher than that of the peripheral municipalities. However, energy intensity shows an entirely different spatial distribution. The development of the regional economy depends on its own “assembling effect”. GDP explains approximately 68.3% of the total variation in energy consumption in the PRD and only approximately 34.5% of that in the peripheral municipalities. We do not confirm Granger causality between energy consumption and economic development. Guangdong can decrease its energy consumption growth without substantially sacrificing its economic growth. The analysis framework of this paper has significant implications for regions in balancing economic development and energy consumption.

System Model of Long-Term Technical and Economic Development

2016 ◽  
Vol 4 (5) ◽  
pp. 18-35 ◽  
Author(s):  
Басовский ◽  
Leonid Basovskiy ◽  
Басовская ◽  
Elena Basovskaya
Keyword(s):  
Energy Intensity ◽  
Capital Intensity ◽  
Econometric Models ◽  
System Model ◽  
Gdp Per Capita ◽  
Real Gdp ◽  
Economic Paradigm ◽  
Real Gdp Per Capita ◽  
Per Capita

The results of the research of dissemination of technical and economic paradigms in developed economies are given. A system model of long-term technical and economic development is developed. The model assumes the simultaneous existence in the economy of several subsystems of different technical and economic paradigms. Each techno-economic paradigm is a new stage of development and different from the previous paradigm of higher productivity. Each subsequent industrial techno-economic paradigm provides higher productivity due to higher capital intensity and energy intensity of production. In the post-industrial techno-economic paradigms the higher performance is provided at a lower capital intensity and energy intensity of production due to a higher volume of information used. Beginning, transition to domination, the beginning of the withering away of each paradigm is accompanied by the formation of an upward half-wave of Kondratieff cycle. Econometric models of Kondratieff cycles and econometric models of real GDP per capita is obtained, provided technical and economic paradigms in developed countries. The fourth techno-economic paradigm provides the real per capita GDP value from 1929 to 3258 dollars Gehry-Hemis 1990. The fifth techno-economic paradigm provides a real GDP per capita value of 11,606 to 12,883 dollars Gehry-Hemis 1990. The sixth techno-economic paradigm provides a real GDP per capita value of 22 360 to 28 385 dollars Gehry-Hemis 1990.

Dynamic Change and Analysis of Driving Factors of Carbon Emissions from Traffic and Transportation Energy Consumption in Jilin Province

2014 ◽  
Vol 472 ◽  
pp. 851-855 ◽  
Author(s):  
Biao Gao ◽  
Qing Tao Xu ◽  
Yu Bo Li
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Growth Stage ◽  
Dynamic Change ◽  
Driving Factors ◽  
Jilin Province ◽  
Energy Structure ◽  
Estimation Model ◽  
Transportation Energy

Based on the traffic and transportation energy consumption, the carbon emissions of traffic and transportation energy consumption are obtained by using the estimation model of carbon emissions from 1999 to 2011 in Jilin Province, and the dynamic changes and the Environmental Kuznets Curve (EKC) of carbon emissions are analyzed. The result indicates that the carbon emission of traffic and transportation energy consumption increased continuously from 99.3750×104 t to 331.8255×104 t between 1999 and 2011 in Jilin Province, the change process is divided into three stages which include the stage of the stationary growth phase, accelerated growth stage and slow growth stage, the large consumption of diesel energy is the main reason of the rapid growth in carbon emissions. The EKC of carbon emission shows the inverted U shape roughly and the turning point appeared in 2011, after 2011, carbon emissions will decrease along with the economic growth. Based on the STIRPAT model, the study reveals that elasticity coefficients of driving factors such as population, per capita GDP, the unit GDP energy consumption, the investment of traffic and transportation, city rate, the number of private cars are 0.23440.2202-0.22470.16570.2864 and 0.2163, respectively. Jilin Province must implement effective measures to change the existing development mode of traffic and transportation, change the energy structure, and increase the innovation of scientific and technological, to strive for the realization of negative growth in carbon emissions of traffic and transportation energy consumption.

scholarly journals Evaluating the EKC Hypothesis for the BCIM-EC Member Countries under the Belt and Road Initiative

2020 ◽  
Vol 12 (4) ◽  
pp. 1478 ◽  
Author(s):  
Arifur Rahman ◽  
S. M. Woahid Murad ◽  
Fayyaz Ahmad ◽  
Xiaowen Wang
Keyword(s):  
Panel Data ◽  
Carbon Emission ◽  
Structural Breaks ◽  
Energy Use ◽  
Trade Openness ◽  
Gdp Per Capita ◽  
Ekc Hypothesis ◽  
Long Run ◽  
Short Run ◽  
Per Capita

This paper attempts to examine the environmental Kuznets curve (EKC) hypothesis for the BCIM-EC (Bangladesh–China–India–Myanmar economic corridor) member countries under the Belt and Road Initiative (BRI) of China. Both time series and panel data are covered, with respect to carbon dioxide (CO2) emissions, GDP per capita, energy use, and trade openness. For panel data analysis, GDP per capita and energy consumption have positive effects on CO2, while the effect of the quadratic term of GDP per capita is negative in the short-run. However, the short-run effects do not remain valid in the long-run, except for energy use. Therefore, the EKC hypothesis is only a short-run phenomenon in the case of the panel data framework. However, based on the Autoregressive Distributed Lag (ARDL) approach with and without structural breaks, the EKC hypothesis exists in India and China, while the EKC hypothesis holds in Bangladesh and Myanmar with regard to disregarding breaks within the short-run. The long-run estimates support the EKC hypothesis of considering and disregarding structural breaks for Bangladesh, China, and India. The findings of the Dumitrescu and Hurlin panel noncausality tests show that there is a unidirectional causality that runs from GDP per capita to carbon emission, squared GDP to carbon emission, and carbon emission to trade openness. Therefore, the BCIM-EC under the BRI should not only focus on connectivity and massive infrastructural development for securing consecutive economic growth among themselves, but also undertake a long-range policy to cope with environmental degradation and to ensure sustainable green infrastructure.

scholarly journals Driving Factors and Future Prediction of Carbon Emissions in the ‘Belt and Road Initiative’ Countries

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5455
Author(s):  
Lili Sun ◽  
Huijuan Cui ◽  
Quansheng Ge
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Driving Factors ◽  
Peak Time ◽  
Belt And Road Initiative ◽  
Belt And Road ◽  
Future Prediction ◽  
Global Carbon ◽  
The Belt And Road

‘Belt and Road Initiative’ (B&R) countries play critical roles in mitigating global carbon emission under the Paris agreement, but their driving factors and feasibility to reduce carbon emissions remain unclear. This paper aims to identify the main driving factors (MDFs) behind carbon emissions and predict the future emissions trajectories of the B&R countries under different social-economic pathways based on the extended STIRPAT (stochastic impacts by regression on population, affluence, and technology) model. The empirical results indicate that GDP per capita and energy consumption structure are the MDFs that promote carbon emission, while energy intensity improvement is the MDF that inhibits carbon emission. Population, as another MDF, has a dual impact across countries. The carbon emissions in all B&R countries are predicted to increase from SSP1 to SSP3, but emissions trajectories vary across countries. Under the SSP1 scenario, carbon emissions in over 60% of B&R countries can peak or decline, and the aggregated peak emissions will amount to 21.97 Gt in 2030. Under the SSP2 scenario, about half of the countries can peak or decline, while their peak emissions and peak time are both higher and later than SSP1, the highest emission of 25.35 Gt is observed in 2050. Conversely, over 65% of B&R countries are incapable of either peaking or declining under the SSP3 scenario, with the highest aggregated emission of 33.10 Gt in 2050. It is further suggested that decline of carbon emission occurs when the inhibiting effects of energy intensity exceed the positive impacts of other MDFs in most B&R countries.

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