Analysis of influencing factors of the carbon dioxide emissions in China’s commercial department based on the STIRPAT model and ridge regression

2019 ◽  
Vol 26 (26) ◽  
pp. 27138-27147 ◽  
Author(s):  
Lei Wen ◽  
Hengyang Shao
Keyword(s):  
Carbon Dioxide ◽  
Influencing Factors ◽  
Ridge Regression ◽  
Carbon Dioxide Emissions ◽  
Stirpat Model

Driving Factors Analysis of Carbon Dioxide Emissions in China Based on STIRPAT Model

2013 ◽  
Vol 734-737 ◽  
pp. 1910-1914 ◽  
Author(s):  
Qiao Zhi Zhao ◽  
Qing You Yan
Keyword(s):  
Economic Growth ◽  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
High Speed ◽  
Carbon Dioxide Emission ◽  
Urbanization Process ◽  
Stirpat Model ◽  
Factors Analysis ◽  
Secondary Industry

China is developing at relatively high speed, not only the regional development speed should be focused upon, but also the environmental impact of economic growth should be paid attention to, especially the level change of carbon dioxide emission. To some degree, quantity of carbon dioxide emission has become one of the most important indexes for measuring quality of a nations economic growth. Thus, this thesis is trying to analyze the driving relations between economic growth and carbon dioxide. Upon STIRPAT model, ridge regression method and elasticity theory are applied to analyze the influencing factors of carbon dioxide quantity such as the population quantity, Chinas urbanization process, per capita GDP, energy density and the percentage of the secondary industry. Correspondingly, based on the different influencing variables to carbon dioxide emission quantity, needy measures are brought out to control and decrease emissions. Feasible suggestions are trying to improve Chinas economic development quality.

Calculation of Carbon Dioxide Emission in Nanjing City and its Influencing Factors

2014 ◽  
Vol 665 ◽  
pp. 517-520
Author(s):  
Qiang Zhao ◽  
Xiu Mei Li ◽  
Xiang Yu Cui
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Dioxide Emissions ◽  
Carbon Dioxide Emission ◽  
Clean Energy ◽  
Energy Structure ◽  
Low Carbon ◽  
Index Decomposition ◽  
Laspeyres Index

The research estimates the carbon dioxide emissions of energy consumption from 2003 to 2011 using the method in IPCC national greenhouse gases listing guidance, by adopting the method of Kaya identities and Laspeyres index decomposition technique to analyze the influencing factors and the influencing degree. The result shows that the main factors influencing carbon dioxide emissions are energy structure and per capita GDP, and to develop clean energy, to improve energy structure are important choice to reduce the carbon dioxide emissions of energy consumption, realize low carbon in the future. This research provides an important reference to protect the environment and to promote the sustainable development of economy.

Influencing Factors Analysis of Carbon Dioxide Emissions of Liaoning Power Consumption Based on Kaya Model

2013 ◽  
Vol 779-780 ◽  
pp. 1476-1481 ◽  
Author(s):  
Chang He Jiang ◽  
Wen Ru Zang ◽  
Lei Lei Hu
Keyword(s):  
Carbon Dioxide ◽  
Power Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Liaoning Province ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Carbon Reduction ◽  
Industry Investment

In order to achieve the carbon reduction targets committed by China, Liaoning Province must take the way of low-carbon economy. Based on the related Statistical Yearbook data, applying the IPCC carbon emissions equation and Kaya model, this paper analyses the influencing factors of the carbon dioxide emissions produced from the power consumption of Liaoning Province. and then put forward some suggestion on reducing carbon emissions. The results show that Liaoning Province can achieve the goal, but unit GDP CO2 emissions reduction is mainly due tothe investment expansion of the second industry and construction industry investment expansion. As a result, it puts forward some suggestions.

Spatial pattern and influencing factors of carbon dioxide emissions efficiency of tourism in China

2015 ◽  
Vol 35 (21) ◽  
Author(s):  
王坤 WANG Kun ◽  
黄震方 HUANG Zhenfang ◽  
曹芳东 CAO Fangdong
Keyword(s):  
Carbon Dioxide ◽  
Spatial Pattern ◽  
Influencing Factors ◽  
Carbon Dioxide Emissions
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