Effect of generation capacity factors on carbon emission intensity of electricity of Latin America &amp; the Caribbean, a temporal IDA-LMDI analysis

Jesús, P.M. De Oliveira-De

doi:10.1016/j.rser.2018.11.030

Cited by 113 publications

(46 citation statements)

References 22 publications

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“…For this reason, carbon emissions cannot be analyzed as a single magnitude but scaling by the unit of energy generated to take into account the relative size of each country. To do so, the Aggregate Carbon Intensity (ACI) is a performance indicator useful to characterize the behavior of the electricity sector from an environmental point of view [6,7]. The ACI indicator determines the relationship between the carbon dioxide emitted by fossil-fired power plants and the whole power generation system.…”

Section: Introductionmentioning

confidence: 99%

“…The carbon intensity of China's power sector has been analyzed in [17][18][19] in the period 1990-2015. Recently, [7] analyzed the effect of the generation system capacity factor LAC's power sector using a LMDI formulation considering a single period . The main drawback of the single-period approach is that the drivers behind ACI variability are difficult to capture.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…Since decomposition results are easy to be interpreted with the characteristics of uniqueness and consistency, the logarithmic mean divisia index (LMDI) method is widely used in the field of energy and environment [18,19,20], and gradually, its application to analyze the driving factors of water resources grew [21,22]. For instance, Li et al (2018) [23] and Chen et al (2017) [24] studied the changes of industrial water consumption and industrial wastewater discharge, respectively, and effectively identified the main influencing factors.…”

Section: Introductionmentioning

confidence: 99%

Decoupling Analysis of Water Footprint and Economic Growth: A Case Study of Beijing–Tianjin–Hebei Region from 2004 to 2017

Kong

Yuan

et al. 2019

IJERPH

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The Beijing–Tianji–Hebei region (BTHR) is economically developed and densely populated, but its water resources are extremely scarce. A clear understanding of the decoupling relationship between water footprint and economic growth is conducive to facilitating and realizing the coordinated development of water resources and economic growth in this region. This study calculated the water footprint and other related indicators of BTHR from 2004 to 2017, and objectively evaluated the utilization of water resources in the region. Then, logarithmic mean divisia index (LMDI) method was applied to study the driving factors that resulted in the change of water footprint and their respective effects. Finally, Tapio decoupling model was used to research the decoupling relationships between water footprint and economic growth, and between the driving factors of water footprint and economic growth. There are three main results in this research. (1) The water utilization efficiency in BTHR continues to improve, and the water footprint shows a gradually increasing trend during the research period, among which the agricultural water footprint accounts for a relatively high proportion. (2) The change of water footprint can be attributed to efficiency effect, economic effect, and population effect. Furthermore, efficiency effect is the decisive factor of water footprint reduction and economic effect is the main factor of water footprint increase, while population effect plays a weak role in promoting the increase in water footprint. (3) The decoupling status between water footprint and economic growth show a weak decoupling in most years, while the status between water footprint intensity and economic growth always remains strong decoupling. Moreover, population size and economic growth always show an expansive coupling state. In sum, it is advisable for policy makers to improve water utilization efficiency, especially agricultural irrigation efficiency, to raise residents’ awareness of water conservation, and increase the import of water-intensive products, so as to alleviate water shortage and realize the coordinated development of water resources and economic growth in BTHR.

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“…For example, Karmellos et al (2016) studied on the driving factors of CO 2 emissions from the power sector in the European Union countries. De Oliveira‐De Jesus (2019) analyzed the evolution of carbon accumulation intensity in Latin America and the Caribbean to identify the impact of generating capacity. Mousavi et al (2017) investigated the impacts of energy consumption and fossil fuels on generating carbon intensity.…”

Section: Literature Reviewmentioning

confidence: 99%

A LMDI decomposition analysis of carbon dioxide emissions from the electric power sector in Northwest China

Mai

Ran

2020

Natural Resource Modeling

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Taking advantage of the electrification strategy, Northwest China has made full use of its natural resources endowment, to develop renewable energy as the substitution of thermal power. To evaluate carbon dioxide (CO2) emissions from electric power sector, an extended Kaya identity equation and the Logarithmic mean Divisia index decomposition method are applied to Northwest China from 1998 to 2017. Six explaining factors are analyzed, including carbon intensity, energy mixes, generating efficiency, electrification, economy and population. The results show that driving forces of CO2 emissions from electricity system varied greatly among provinces. Generally, economic growth has mainly contributed to increase CO2 emission, while the improvement in the power‐generating efficiency has crucially decreased CO2 emission. In 2017, Promoting electrification directly increased CO2 emissions from electric system, but indirectly reduced CO2 emissions from the whole region by 5.10% through the estimation of a clean development mechanism method. Therefore, local governments are suggested continuing to promote electrification to guide future emission reduction, while enterprises and individuals need to make their own contributions to low‐carbon development. Recommendations for Resource Managers: Variations of carbon dioxide (CO2) emissions of all five provinces in Northwest China are analyzed. Logarithmic mean Divisia index analysis is used to study the main drivers of CO2 emission change. Improvements in the generating efficiency significantly reduced CO2 emissions. Due to electrification effects, CO2 emissions from electric power increased, but CO2 emissions from the region decreased. Economy effects were still the biggest drivers affecting CO2 emission.

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Effect of generation capacity factors on carbon emission intensity of electricity of Latin America & the Caribbean, a temporal IDA-LMDI analysis

Cited by 113 publications

References 22 publications

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

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

Decoupling Analysis of Water Footprint and Economic Growth: A Case Study of Beijing–Tianjin–Hebei Region from 2004 to 2017

A LMDI decomposition analysis of carbon dioxide emissions from the electric power sector in Northwest China

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