2018
DOI: 10.3390/su10093251
|View full text |Cite
|
Sign up to set email alerts
|

Decomposition Analysis in Electricity Sector Output from Carbon Emissions in China

Abstract: Carbon emissions from China’s electricity sector account for about one-seventh of the global carbon dioxide emissions, or half of China’s carbon dioxide emissions. A better understanding of the relationship between CO2 emissions and electric output would help develop and adjust carbon emission mitigation strategies for China’s electricity sector. Thus, we applied the electricity elasticity of carbon emissions to a decoupling index that we combined with advanced multilevel Logarithmic Mean Divisia Index tools i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
5
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 14 publications
(8 citation statements)
references
References 50 publications
0
5
0
Order By: Relevance
“…The outcomes of their study indicated that, overall, China’s transportation industry is moving away from decoupling, with negative decoupling or non-decoupling observed during the study. Following Jiang, Su and Li 100 applied LMDI and decomposition stability index to investigate the decomposition mechanism of carbon emissions from China’s electric sector. Their results suggested that the electric output effect is vital in rising CO 2 emissions.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The outcomes of their study indicated that, overall, China’s transportation industry is moving away from decoupling, with negative decoupling or non-decoupling observed during the study. Following Jiang, Su and Li 100 applied LMDI and decomposition stability index to investigate the decomposition mechanism of carbon emissions from China’s electric sector. Their results suggested that the electric output effect is vital in rising CO 2 emissions.…”
Section: Literature Reviewmentioning
confidence: 99%
“…where, E indirect is indirect carbon emission; S i represents energy consumption converted into standard coal in domestic, industrial and transportation sectors; Y i represents the carbon emission coefficient corresponding to each energy source. Referring to the relevant literature, the coefficient is 0.67 in this study [25]. After the carbon emissions of construction land in Zhuhai are calculated, the total carbon emissions will be allocated to each cluster according to the proportion of living, industrial and road land area in the whole city.…”
Section: Measurement Of Carbon Emission Indexmentioning
confidence: 99%
“…In terms of models, most scholars take economy or income, population, energy consumption intensity, fuel structure, carbon emission intensity, energy structure and industrial structure as factors influencing the change of carbon emissions in the power industry [14], [15], [16], [17], [18]. Most scholars have generally proved that socioeconomic factors such as economic development and population growth are the main driving factors of carbon emissions in the power industry, while energy factors such as energy structure can inhibit carbon emissions [19,20]. For example, Li et al [19] show that the main factors affecting carbon emissions in public buildings in Henan Province were identified as the urbanization rate, public floor area per capita, and energy intensity per unit of public floor area.…”
Section: Introductionmentioning
confidence: 99%
“…For example, Li et al [19] show that the main factors affecting carbon emissions in public buildings in Henan Province were identified as the urbanization rate, public floor area per capita, and energy intensity per unit of public floor area. Jiang et al [20] applied the electricity elasticity of carbon emissions to a decoupling index. The findings indicate that the electric output effect exerted the most substantial influence on the rise of CO2 emissions within China's electric sector.…”
Section: Introductionmentioning
confidence: 99%