2016
DOI: 10.3390/en9040295
|View full text |Cite
|
Sign up to set email alerts
|

Decomposition Analysis in Decoupling Transport Output from Carbon Emissions in Guangdong Province, China

Abstract: Abstract:With a continuously growing share of the world's overall energy consumption, the transport sector has been acknowledged as one of the most important contributors to global carbon emissions. This paper applies a complete decomposition and decoupling analysis to investigate and quantitatively analyze the main factors influencing the energy-related carbon emissions of the transport (TCE) sector during 1995-2012 in Guangdong, the richest and most populated province in China. Results showed that decoupling… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

2
14
0

Year Published

2017
2017
2021
2021

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 30 publications
(16 citation statements)
references
References 39 publications
2
14
0
Order By: Relevance
“…The previous research results mentioned in our literature review indicated that the optimization of tertiary industry structure played an inhibiting role with regard to transportation-related carbon emissions [60,63]. Given the actual situation, it is hard to adjust the industrial structure, so the industrial structure trend is not pronounced.…”
Section: Influencing Factors Of Carbon Emissions From the Transportatmentioning
confidence: 99%
See 1 more Smart Citation
“…The previous research results mentioned in our literature review indicated that the optimization of tertiary industry structure played an inhibiting role with regard to transportation-related carbon emissions [60,63]. Given the actual situation, it is hard to adjust the industrial structure, so the industrial structure trend is not pronounced.…”
Section: Influencing Factors Of Carbon Emissions From the Transportatmentioning
confidence: 99%
“…Some studies have also measured environmental and energy performance in China [11,13,[58][59][60] and have also conducted a comparative analysis of China's regional energy and emissions performance [60][61][62] using a DEA model. Zhao et al [63] performed a complete decomposition and decoupling analysis, in order to quantitatively analyze the main factors influencing the carbon emissions of the transportation (TCE) sector in Guangdong Province over the period from 1995 to 2012. Zhao's results indicated that the decoupling degree between transportation output and TCE was relatively low.…”
Section: Literature Reviewmentioning
confidence: 99%
“…With increasing emissions from the transport sector and rising environmental awareness, CO 2 emissions mitigation has attracted more attention in China [15,17,21,[29][30][31][32][33]. Researchers have analyzed the carbon emissions of the transport sector from various perspectives.…”
Section: Introductionmentioning
confidence: 99%
“…However, in the "Industrial classification for national economic activities of 2017", production of transportation goods belongs to the manufacturing industry, and the use of vehicles belongs to the transportation industry. This article uses the official classification, and the definition of the transportation industry in this paper is also widely used in other studies, such as Zhao et al [51], Wang et al [59], and Hao et al [12].…”
Section: Estimation Of Carbon Emissions In China's Transportation Indmentioning
confidence: 99%
“…Loo et al [50] explored the potential and the reality of decoupling transportation from economic growth in 15 major countries such as China, Russia and Canada. Zhao et al [51] analyzed the relationship between transportation growth and carbon emissions associating the decomposition technique with the decoupling elasticity in Guangdong province, China. Using the Tapio elasticity analysis method, Liu et al [52] explored the decoupling between transportation development and economic growth.…”
Section: Literature Review Of Carbon Emissions Decouplingmentioning
confidence: 99%