Examining the impact factors of energy-related CO₂ emissions using the STIRPAT model in Guangdong Province, China

To find the key impact factors of CO₂ emissions to realize the carbon intensity target, this paper examined the impact factors of population, economic level, technology level, urbanization level, industrialization level, service level, energy consumption structure and foreign trade degree on the energy-related CO₂ emissions in Guangdong Province, China from 1980 to 2010 using an extended STIRPAT model. We employed ridge regression to fit the extended STIRPAT model. Empirical results indicate that factors such as population, urbanization level, GDP per capita, industrialization level and service level, can cause an increase in CO₂ emissions. However, technology level, energy consumption structure and foreign trade degree can lead to a decrease in CO₂ emissions. The estimated elastic coefficients suggest that population is the most important impact factor of CO₂ emissions. Industrialization level, urbanization level, energy consumption structure, service level and GDP per capita are also significant impact factors, but the other factors such as technology level and foreign trade degree are less important impact factors. Some policy recommendations are also given on how to mitigate the growth of CO₂ emissions.