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

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.

2020 ◽  
Vol 12 (8) ◽  
pp. 3185 ◽  
Author(s):  
Enkhjargal Enkhbat ◽  
Yong Geng ◽  
Xi Zhang ◽  
Huijuan Jiang ◽  
Jingyu Liu ◽  
...  

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.


Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2328 ◽  
Author(s):  
Paulo M. De Oliveira-De Jesus ◽  
John J. Galvis ◽  
Daniela Rojas-Lozano ◽  
Jose M. Yusta

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.


Author(s):  
Tomas Baležentis ◽  
Irena Kriščiukaitienė

The paper aims to analyse the main driving forces behind the changes in milk revenue in Lithuania during 1993–2013 by the virtue of the index decomposition analysis. Specifically, an index decomposition model based upon Shapley value is introduced to account for dynamics in endogenous and exogenous factors underlying dynamics of the revenue. Particularly, the number of cows, average milk yield, market integration, milk composition, and milk price are considered as the main factors causing variation in milk revenue. The country level data are used for the analysis. Results show that such practices as animal recording and application of improved fodder have increased milk revenue by 67 million EUR and 75 million EUR during 1993–2004 and 2004–2013, respectively, due to increase in milk yield and fat.


2017 ◽  
Vol 52 ◽  
pp. 336-348 ◽  
Author(s):  
Zhiping Wang ◽  
Chao Feng ◽  
Jinyu Chen ◽  
Jianbai Huang

Sign in / Sign up

Export Citation Format

Share Document