Socioeconomic driving forces and scenario simulation of CO 2 emissions for a fast-developing region in China

Abstract

Guangdong is one of China's fastest developing provinces, and thus faces the challenge of reducing CO <inf>2</inf> emissions whilst fostering economic growth. In order to advance the goal of developing a low-carbon economy in China, this study explored influencing factors, change trends, and reduction potential in relation to CO <inf>2</inf> emissions in Guangdong Province using a provincial dataset covering the period 1995 to 2014. We used extended STIRPAT (stochastic impacts by regression on population, affluence, and technology) model and the technique of ridge regression in order to identify key influencing factors behind Guangdong's CO <inf>2</inf> emissions. We also forecasted emission trends and estimated reduction potential in the period 2015–2030. Our empirical results indicate that economic development, population growth, urbanization, fixed asset investment, and industrialization level all positively affected CO <inf>2</inf> emissions during the period studied, while the impacts of energy consumption structure and technology progress were found to be negative. Scenario simulations reveal that the aggregate CO <inf>2</inf> emissions of Guangdong Province will increase continuously up to 2030 under all of the twenty scenarios developed and tested in this study; despite this, we argue that the potential for emission reduction remains large. An optimal scenario was identified after cross-sectional comparison. Our analysis casts new light on the importance of exploring socioeconomic determinants and reduction potential in relation to emissions, in order to plan for rapidly developing regions like Guangdong. The empirical findings have significant implications for the Chinese government in implementing policy measures in order to promote low-carbon development.