ISSN:2325-6192 (print)
ISSN:2325-6206 (online)
Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn

Study on the Driving Factors of CO2 Emissions in China’s Coal Consumption Using the STIRPAT Model

Journal of Environmental Accounting and Management 2(4) (2014) 325--334 | DOI:10.5890/JEAM.2014.12.004

Li Li$^{1}$,$^{2}$, Yalin Lei$^{1}$,$^{2}$, Dongyang Pan$^{3}$

$^{1}$ School of Humanities and Economic Management, China University of Geosciences, Beijing, 100083, China

$^{2}$ Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resource, Beijing, 100083, China

$^{3}$ Central University of Finance and Economics, Beijing, 100081, China

Abstract

The Pampas region contributes 80% of the total national production of Coal resource is an important material basis for China’s economic and social development. Coal consumption in China has been increasing rapidly especially in recent years. According to the data of IEA, China is the top country in coal production and consumption. Thereupon, CO2 emissions from coal consumption have also been increasing. China is facing more and more pressure from CO2 emissions. Under the background of economic globalization and the pressure of ecological environment deterioration, China's CO2 emissions have become a hot issue in the world. Previous studies mainly focus on the main driving factors of CO2 emissions in economic development or in total energy consumption. Only several studies focus on the driving factors of CO2 emissions from single kind of energy that is coal consumption, which provides much space for this study. This paper aims to inspect the main factors driving CO2 emissions from coal consumption and their driving degree using the STIRPAT model. The ridge regression is borrowed to test the multicollinearity among population, GDP per capita, technology level and urbanization level. The results show that the sequence of the driving factors in CO2 emissions from coal consumption is GDP per capita (A)>urbanization level (UL)>the total population (P)> economic structure (ES) >Technology level (T). The research results provide a scientific basis for Chinese government and relevant departments in making policy decisions to limit CO2 emissions.

Acknowledgments

The authors express sincerely thanks for the support from the National Natural Science Foundation of China under Grant No.71173200 and the support from the Development and Research Center of China Geological Survey under Grant No.1212011220302.

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