Next Article in Journal
Sustainability and EMAS: Impact of Motivations and Barriers on the Perceived Benefits from the Adoption of Standards
Previous Article in Journal
Sustainability Investigation of Resource-Based Cities in Northeastern China
Open AccessArticle

Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China

School of Economic & Management, China University of Petroleum (Huadong), No. 66 West Changjiang Road, Qingdao 266580, China
*
Author to whom correspondence should be addressed.
Academic Editor: John Barrett
Sustainability 2016, 8(10), 1059; https://doi.org/10.3390/su8101059
Received: 13 August 2016 / Revised: 26 September 2016 / Accepted: 11 October 2016 / Published: 20 October 2016
(This article belongs to the Section Energy Sustainability)
China has overtaken the United States as the world’s largest producer of carbon dioxide, with industrial carbon emissions (ICE) accounting for approximately 65% of the country’s total emissions. Understanding the ICE decoupling patterns and factors influencing the decoupling status is a prerequisite for balancing economic growth and carbon emissions. This paper provides an overview of ICE based on decoupling elasticity and the Tapio decoupling model. Furthermore, the study identifies the factors contributing to ICE changes in China, using the Kaya identity and Log Mean Divisia Index (LMDI) techniques. Based on the effects and contributions of ICE, we close with a number of recommendations. The results revealed a significant upward trend of ICE during the study period 1994 to 2013, with a total amount of 11,147 million tons. Analyzing the decoupling relationship indicates that “weak decoupling” and “expansive decoupling” were the main states during the study period. The decomposition analysis showed that per capita wealth associated with industrial outputs and energy intensity are the main driving force of ICE, while energy intensity of industrial output and energy structure are major determinants for ICE reduction. The largest contributing cumulative effect to ICE is per capita wealth, at 1.23 in 2013. This factor is followed by energy intensity, with a contributing cumulative effect of −0.32. The cumulative effects of energy structure and population are relatively small, at 0.01 and 0.08, respectively. View Full-Text
Keywords: industrial carbon emissions (ICE); decomposition analysis; decoupling analysis; LMDI (Log Mean Divisia Index) industrial carbon emissions (ICE); decomposition analysis; decoupling analysis; LMDI (Log Mean Divisia Index)
Show Figures

Figure 1

MDPI and ACS Style

Wang, Q.; Li, R.; Jiang, R. Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China. Sustainability 2016, 8, 1059. https://doi.org/10.3390/su8101059

AMA Style

Wang Q, Li R, Jiang R. Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China. Sustainability. 2016; 8(10):1059. https://doi.org/10.3390/su8101059

Chicago/Turabian Style

Wang, Qiang; Li, Rongrong; Jiang, Rui. 2016. "Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China" Sustainability 8, no. 10: 1059. https://doi.org/10.3390/su8101059

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop