Decomposition analysis of factors affecting carbon dioxide emissions across provinces in China. (10th January 2017)

• Record Type: Journal Article
• Authors: Li, Aijun; Zhang, Aizhen; Zhou, Yüxia; Yao, Xin
• Is Part Of: Journal of cleaner production. Volume 141(2017)
• Page Start: 1428
• Page End: 1444
• Publication Date: 2017-01-10
• Subjects: Production-theoretical decomposition analysis (PDA) -- Index decomposition analysis (IDA) -- Energy efficiency improvements -- Carbon emission performance -- Technology gaps -- Carbon dioxide emissions reductions; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2016.09.206
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Currently, China is the largest carbon emitter with large increased annual carbon dioxide emissions and thus faces growing pressure to control carbon dioxide (CO2 ) emissions. The Chinese government announced the targets of reducing carbon intensity by 2020 and peaking absolute carbon dioxide emissions around 2030. Against such background, this paper adopts an approach, which combines production-theoretical decomposition analysis (PDA) and index decomposition analysis (IDA). In the approach, this study adds two important pre-defined factors, i.e. GDP technical efficiency and GDP technology change. Furthermore, this study provides detailed information regarding the potential forces driving carbon dioxide emissions across provinces in China. The main findings are as follows. Firstly, economic activity is the dominant contributor to substantial increases in carbon dioxide emissions. GDP technology change and potential energy intensity change have considerable effects on carbon dioxide emissions in most provinces. Secondly, there are mixed results at provincial level, including several driving factors and the potential of carbon intensity improvements. In this regard, detailed information about provincial variations is quite important for policy makers in provincial governments. Finally, there are 9 provinces with large potential of carbon intensity improvements. Looking ahead, the local governments should adopt effective measures to promote "catching up". Highlights: This study provides detailed information regarding factors affecting carbon emissions. We find that economic activity effects are the dominant contributor. There are mixed results for several factors at provincial levels. There is large potential of carbon intensity improvements in 9 provinces by "catching up".