scholarly journals Temporal Evolution and Influencing Factors of Energy Consumption and Related Carbon Emissions from the Perspective of Industrialization and Urbanization in Shanghai, China

2018 ◽  
Vol 10 (9) ◽  
pp. 3054 ◽  
Author(s):  
Pingxing Li ◽  
Wei Sun
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Temporal Evolution ◽  
Added Value ◽  
Living Standard ◽  
Total Energy Consumption ◽  
Consumption Level ◽  
Economic Output ◽  
Per Capita

Improvements of manufacturability and living standard driven by industrialization and urbanization typically cause a spike in total energy consumption (TEC) and related carbon emissions (TCEM). However, there have been few comparative studies to include industrial and residential energy consumption (IEC and REC, respectively) and related carbon emissions (ICEM and RCEM, respectively). Since China is a major emerging industrial country wherein urbanization is still ongoing, the present study was conducted in an attempt to analyze the temporal evolution of China’s continued energy consumption and related carbon emissions regarding both industrialization and urbanization. The influencing factors of TCEM, RCEM and ICEM are determined via the log-mean divisia index (LMDI) model. The results showed that both TEC and TCEM gradually increased (apart from a slight decrease in 2014); REC and RCEM increased steadily with no sharp peak; while IEC and ICEM declined sharply. TCEM was positively affected by economic output, consumption level, and population size; the influence of consumption level became more and more significant. Per capita GDP and per capita expenditure were the most significant driving factors for RCEM, while industrial added value (IAV) was the main driving factor for ICEM. The temporal evolution and influencing factors of energy consumption and carbon emissions had stage-related characteristics in accordance with Shanghai’s three stages of development. The Shanghai case study provided a comprehensive understanding of energy consumption and related carbon emissions from the dual perspective of industrialization and urbanization.

scholarly journals Analysis of Influencing Factors and Trend Forecast of Carbon Emission from Energy Consumption in China Based on Expanded STIRPAT Model

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3054 ◽  
Author(s):  
Zhen Li ◽  
Yanbin Li ◽  
Shuangshuang Shao
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Total Population ◽  
Industrial Structure ◽  
Global Climate ◽  
Primary Energy ◽  
Urbanization Level ◽  
Per Capita ◽  
Technology Level

With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020.

scholarly journals Analysis of Influencing Factors of Carbon Emissions in China’s Logistics Industry: A GDIM-Based Indicator Decomposition

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5742
Author(s):  
Changyou Zhang ◽  
Wenyu Zhang ◽  
Weina Luo ◽  
Xue Gao ◽  
Bingchen Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Added Value ◽  
Total Carbon ◽  
Carbon Intensity ◽  
Contribution Ratio ◽  
Logistics Industry ◽  
Per Capita ◽  
First Time

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China’s logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry.

Research on Influencing Mechanism of Industrial Carbon Emissions in Hebei Province

2012 ◽  
Vol 260-261 ◽  
pp. 1052-1056
Author(s):  
Wei Yang Yu ◽  
Hui Ning Zhao
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Value Added ◽  
Hebei Province ◽  
Added Value ◽  
Industrial Carbon ◽  
Decomposition Model ◽  
Influencing Mechanism ◽  
Index Decomposition ◽  
Main Factor

This paper calculates carbon emissions in Hebei Province based on energy consumption and carbon coefficients and adopts the index decomposition model to analyze the influence of value-added industries and carbon emissions per unit added value on carbon emissions.The results indicate that the increase of value-added industries in Hebei Province is the main factor affecting the growth of carbon emissions, but the decrease of carbon emissions per unit added value induces carbon emissions to a lesser reducing. The conclusions can offer the decision basis for reducing carbon emissions.

scholarly journals Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China

Land ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 158 ◽  
Author(s):  
Qianru Chen ◽  
Hualin Xie
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Spatial Differentiation ◽  
Utilization Efficiency ◽  
Added Value ◽  
Scale Model ◽  
Eastern Region ◽  
Cultivated Land ◽  
Land Utilization ◽  
Extension System

Cultivated land is closely related to national food security, rural economic development and social stability. The cultivated land pollution and carbon emissions caused by chemical fertilizers, pesticides, film residues, etc., in the process of cultivated land utilization pose a serious threat to the cultivated land ecosystem in China. The comprehensive analysis on the cultivated land green utilization efficiency (GUECL), its influencing factors, and optimization direction provides a valuable basis for the green utilization of cultivated land. Based on a panel data of 30 provinces (cities or districts) in China from 2001 to 2016, the GUECL in China under the constraints of pollution and carbon emissions was measured by using a super-efficient SBM-VRS (slack based model-variable return to scale) model. The influencing factors and optimization directions of the GUECL were analyzed through the Tobit model and slack values, respectively. The results show that the GUECL in China rose with fluctuations from 2001 to 2016. Since 2014, the eastern region has surpassed the western region and has become the region with the highest mean GUECL value. The room for resource conservation and pollution reduction varies in different regions of China. Farmers’ dependence on cultivated land and agricultural added value are positively related to the GUECL in China. Farmers’ occupational differentiation, agricultural machinery density, and agricultural disaster rate have had negative effects on the GUECL in China. The loss of the GUECL in China is mainly due to the redundancies of land input, pollution emission, and mechanical input. By analyzing these influencing factors and optimization directions, it is concluded that improving rural land transfer market and agricultural infrastructure construction, establishing a new agricultural technology extension system, and vigorously cultivating new professional farmers are the targeted measures to improve the GUECL.

scholarly journals The carbon emissions of Chinese cities

2012 ◽  
Vol 12 (14) ◽  
pp. 6197-6206 ◽  
Author(s):  
H. Wang ◽  
R. Zhang ◽  
M. Liu ◽  
J. Bi
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
National Policy ◽  
Emission Inventories ◽  
Chinese Cities ◽  
Industrial Energy ◽  
Per Capita ◽  
Policy Priority

Abstract. As increasing urbanization has become a national policy priority for economic growth in China, cities have become important players in efforts to reduce carbon emissions. However, their efforts have been hampered by the lack of specific and comparable carbon emission inventories. Comprehensive carbon emission inventories for twelve Chinese cities, which present both a relatively current snapshot and also show how emissions have changed over the past several years, were developed using a bottom-up approach. Carbon emissions in most Chinese cities rose along with economic growth from 2004 to 2008. Yet per capita carbon emissions varied between the highest and lowest emitting cities by a factor of nearly 7. Average contributions of sectors to per capita emissions for all Chinese cities were 65.1% for industrial energy consumption, 10.1% for industrial processes, 10.4% for transportation, 7.7% for household energy consumption, 4.2% for commercial energy consumption and 2.5% for waste processing. However, these shares are characterized by considerable variability due to city-specific factors. The levels of per capita carbon emissions in China's cities were higher than we anticipated before comparing them with the average of ten cities in other parts of the world. This is mainly due to the major contribution of the industry sector in Chinese cities.

scholarly journals Dynamic linkages between renewable energy, carbon emissions and economic growth through nonlinear ARDL approach: Evidence from Iran

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253464
Author(s):  
M. S. Karimi ◽  
S. Ahmad ◽  
H. Karamelikli ◽  
D. T. Dinç ◽  
Y. A. Khan ◽  
...  
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Gdp Per Capita ◽  
Bounds Testing ◽  
Renewable Energy Consumption ◽  
Economic Implications ◽  
Long Run ◽  
Per Capita

This study examines the relationship between economic growth, renewable energy consumption, and carbon emissions in Iran between 1975–2017, and the bounds testing approach to cointegration and the asymmetric method was used in this study. The results reveal that in the long run increase in renewable energy consumption and CO2 emissions causes an increase in real GDP per capita. Meanwhile, the decrease in renewable energy has the same effect, but GDP per capita reacts more strongly to the rise in renewable energy than the decline. Besides, in the long run, a reduction of CO2 emissions has an insignificant impact on GDP per capita. Furthermore, the results from asymmetric tests suggest that reducing CO2 emissions and renewable energy consumption do not have an essential role in decreasing growth in the short run. In contrast, an increase in renewable energy consumption and CO2 emissions do contribute to boosting the growth. These results may be attributable to the less renewable energy in the energy portfolio of Iran. Additionally, the coefficients on capital and labor are statistically significant, and we discuss the economic implications of the results and propose specific policy recommendations.

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