An overview of the inequality in China’s carbon intensity 1997–2016: a Theil index decomposition analysis

2021 ◽  
Author(s):  
Qi Tian ◽  
Tao Zhao ◽  
Rong Yuan
Keyword(s):  
Decomposition Analysis ◽  
Theil Index ◽  
Carbon Intensity ◽  
Index Decomposition Analysis ◽  
Index Decomposition

scholarly journals Multitemporal LMDI Index Decomposition Analysis to Explain the Changes of ACI by the Power Sector in Latin America and the Caribbean between 1990–2017

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2328 ◽  
Author(s):  
Paulo M. De Oliveira-De Jesus ◽  
John J. Galvis ◽  
Daniela Rojas-Lozano ◽  
Jose M. Yusta
Keyword(s):  
Latin America ◽  
Power Plants ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Power Sector ◽  
Index Decomposition Analysis ◽  
Energy Flows ◽  
Index Decomposition ◽  
The Caribbean ◽  
The One

This paper analyzes the drivers behind the changes of the Aggregate Carbon Intensity (ACI) of Latin America and the Caribbean (LAC) power sector in five periods between 1990 and 2017. Since 1990 the carbon intensity of the world has been reduced almost 8.8% whereas the carbon intensity of LAC countries only decreased 0.8%. Even though by 2017 the regional carbon intensity is very similar to the one observed by 1990, this index has showed high variability, mainly in the last three years when the ACI of LAC fell from 285 gCO2/kWh in 2015 to 257.7 gCO2/kWh. To understand what happened with the evolution of the carbon intensity in the region, in this paper a Logarithmic Mean Divisia for Index Decomposition Analysis (IDA-LMDI) is carried out to identify the accelerating and attenuating drivers of the ACI behavior along five periods. The proposal outperforms existing studies previously applied to LAC based upon a single period of analysis. Key contributions are introduced by considering the type of fuel used in power plants as well as specific time-series of energy flows and CO2 emissions by country. Results reveal structural reasons for the increase of the ACI in 1995–2003 and 2008–2015, and intensity reasons for the decrease of the ACI in 1990–1995, 2003–2008 and 2015–2017.

Driving factors of energy-relevant CO2 emissions in China’s fixed asset investment

2018 ◽  
Vol 12 (4) ◽  
pp. 601-616
Author(s):  
Hongtao Liu ◽  
Jin Shang
Keyword(s):  
Intensity Factor ◽  
Carbon Emissions ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Policy Recommendations ◽  
Fixed Asset ◽  
Content Type ◽  
Index Decomposition Analysis ◽  
Index Decomposition

Purpose The purpose of this paper is to use an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. Design/methodology/approach This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented. Findings The results suggest that the amount of CO2 emissions related to fixed asset investments increased during the entire period. The social and economic effect played a major role in promoting carbon emissions, followed by the fixed asset effect. Therefore, the activity factor was the dominant positive factor, followed by the construction factor. The negative element was the energy effect, in which the energy intensity factor played an important role in reducing emissions, followed by the structural factor. Moreover, the carbon intensity factor might be a potential inhibitory force in reducing carbon emissions. Research/limitations/implications A steady financial policy, relaxed family planning, sustainable urbanization, strategy of innovation-driven development, reform of scientific and technological structures, development of science and technology and exploration of new energy sources are proposed to mitigate carbon emissions from fixed asset investments. The conclusion also provides a reference for developing countries in similar situations. Originality/value This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented.

Decomposição do consumo de energia na indústria brasileira: efeitos do aumento da atividade entre 1970 - 2019

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Marlon Salazar
Keyword(s):  
Decomposition Analysis ◽  
Index Decomposition Analysis ◽  
Index Decomposition

A indústria é um dos setores da economia que mais consomem energia, sendo responsável por 32% do consumo final em 2019. Compreender como se comporta o consumo da indústria ao longo das décadas, decompondo a variação do consumo entre os efeitos atividade, estrutura e intensidade, através da decomposição de números índices, é de grande importância e é o objetivo principal deste trabalho. Este trabalho inova ao utilizar o método “Index Decomposition Analysis (IDA)” para os dados de consumo de energia industrial. Conclui-se que o efeito atividade é o principal responsável pelo aumento no consumo de energia, já que captura a participação do aumento da produção industrial sobre o consumo de energia. Por outro lado, o efeito intensidade cresce no período, o que indica que a indústria brasileira está se tornando menos eficiente no consumo de energia. Já o efeito estrutura contribui reduzindo o consumo no período estudado, o que indica que os setores energo intensivos perderam participação na produção industrial. Além disso, a partir da estimação da equação de demanda de energia utilizando como proxy do consumo o efeito atividade, constata-se que a elasticidade renda da demanda de energia foi de 1,57% no período, já que a elasticidade preço da demanda não é significante.

scholarly journals Driving Forces of Air Pollution in Ulaanbaatar City Between 2005 and 2015: An Index Decomposition Analysis

2020 ◽  
Vol 12 (8) ◽  
pp. 3185 ◽  
Author(s):  
Enkhjargal Enkhbat ◽  
Yong Geng ◽  
Xi Zhang ◽  
Huijuan Jiang ◽  
Jingyu Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Air Pollutant ◽  
Capital City ◽  
Energy Structure ◽  
Index Decomposition Analysis ◽  
Socioeconomic Drivers ◽  
Index Decomposition ◽  
Concentration Changes

Ulaanbaatar, the capital city of Mongolia, is facing serious air pollution challenges—especially during the cold and long winter months—mainly due to fossil fuel combustion. This study investigates the socioeconomic drivers of the sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter (PM2.5) concentration changes in Ulaanbaatar between 2005 and 2015 by applying the index decomposition analysis (IDA) method. Five socio-economic driving forces are considered in the decomposition analysis. All the driving forces contributed to more air pollution concentration changes in 2015 than in 2005, despite the decreasing trends of decomposition results for the period of 2010–2015. In general, economic growth, pollution intensity, and energy intensity significantly contributed to the changes of air pollutant concentrations, while energy structure and population growth had marginal effects. Finally, appropriate policy recommendations are proposed to the local government so that they can initiate feasible policies to effectively reduce air pollution, protect human health, and respond to climate change in Ulaanbaatar.

Sign in / Sign up

Export Citation Format

Share Document