Factor Decomposition Analysis of China's Energy-Related CO2 Emissions Using Extended STIRPAT Model
Polish Journal of Environmental Studies
Excessive growth of energy use has made the greatest impact on the environment of any human living environment, especially the greenhouse effect. Global warming has come to the forefront of policy debates on international and national levels, thus seriously affecting people's living environment and energy sustainability. Global warming is being driven by greenhouse gases (GHG) growth, most notably CO 2 emissions that account for 56% of the greenhouse effect among six kinds of GHG. Anthropogenic
... GHG. Anthropogenic activities -more specifically fossil fuels combustion and consequent carbon emissions -are responsible for significant warming of the global climate. The 2009 Copenhagen Agreement has urged the Chinese government to commit to a significant cut in carbon intensity of at least 40% by 2020 from 2005 levels. Since the Copenhagen Agreement, the persistent combustion of fossil fuels responsible for greenhouse gas growth has made China a focal point of international attention. During the past 20 years, China's economic development has shown an overreliance on energy consumption with annual growth rate of energy consumption approaching 6.3% since 1991. Accordingly, CO 2 emissions have increased sharply and pose a significant problem as far as energy conservation and emission reduction are restrictive in China. Abstract For the purpose of diminishing the growing impact of energy use on the environment and providing policy focus in China, this study decomposes impact factors of energy-related CO 2 emissions into nine parts using various economic methods, typically using the extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to incorporate necessary factors and ridge regression to eliminate multicollinearity. Results indicate the positive and conversely inhibitory impact factors, which we sort by influencing degrees as: total population, industrialization level, service level, energy consumption structure, urbanization level, GDP per capita, capital asserts investment, foreign trade degree, and technology level. Factors excluding technology level and energy consumption structure are main positive determinants of accelerated CO 2 emissions. Above all, total population has the greatest interpretative ability. Given these regression results, policy proposals concerning key impact factor regulations are provided to maintain carbon emission abatement and sustainability.