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

Article Preview

Abstract:

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.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 734-737)

Pages:

1910-1914

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Zhu Yuan-cheng, Zhang Shi-jie: The Driving Factor Analysis of Economy Carbon Emission in Beijing Based on STIRPAT. Special Zone Economy. 2012(1), pp.77-79.

Google Scholar

[2] Qu Shen-ning, Guo Chao-xian. Forecast of China􀀁s carbon emissions based on STIRPAT model. China Population, Resources and Environment. Vol. 20(2010.12). pp.10-15.

Google Scholar

[3] He Xiao-qun, Liu Wen-qing. An applied regression analysis (3rd Edition). China People University Press. Beijing (2011).

Google Scholar

[4] Jiang Lei, Ji Min-he. China's Energy Stress Based on the STIRPAT Model: A Spatial Econometric Perspective. Scientia Geographica Sinica. Vol.31 (2011.9). 1072-1077.

Google Scholar