Measuring multiple impacts of low-carbon energy options in a green economy context

Ürge-Vorsatz, Diana; Kelemen, Ágnes; Herrero, Sergio Tirado; Thomas, Stefan; Thema, Johannes; Mzavanadze, Nora; Hauptstock, Dorothea; Suerkemper, Felix; Teubler, Jens; Gupta, Mukesh Kumar; Chatterjee, Souran

doi:10.1016/j.apenergy.2016.07.027

Cited by 63 publications

(44 citation statements)

References 82 publications

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“…The second group is about assessment of energy‐economy‐environmental performance, including index assessment and efficiency evaluation. The data envelopment analysis (DEA) which is based on mathematical programming is usually used to evaluate the efficiency performance.…”

Section: Literaturementioning

confidence: 99%

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Pan

Liu

Tsai

et al. 2019

Energy Science & Engineering

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China is transforming the growth model and speeding up industrial structural improvement and upgrading now and in the coming years, which means the slowdown of economic growth and more serious environmental costs in economic and social development would be the “New Normal.” As the world's largest energy consumer and carbon‐emitting country, China's emissions reduction commitments are crucial to global greenhouse gas emissions mitigation, so there is a profusion of research focused on China's economy‐environment nexus. Among which, the dynamic relationship of carbon emission and economic growth and its evolution combined the national, regional, provincial data have not been discussed thoroughly. This paper analyses the elasticity of economic performance of carbon emissions based on 30 Chinese provincial data from 2000 to 2016; furthermore, a panel vector autoregressive model is constructed to discuss the interactions of variables within environmental economic system. It is concluded that China is experiencing a turning point from weak decoupling to strong decoupling in recent years, and its economic performance of carbon emissions has been gradually improved with larger disparities among provinces though. Regression result confirms the role of the energy mix on carbon emissions, and it also indicates that the impact of most factors influencing that have been discussed in previous studies may not be direct, prominent, and for long term.

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Section: Literaturementioning

confidence: 99%

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Pan

Liu

Tsai

et al. 2019

Energy Science & Engineering

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“…COMBI aims at calculating the energy and non-energy impacts 21 energy efficiency improvement (EEIs) in the 28 European Union members (EU-28) in 2030. The analyzed impacts cover the areas of air pollution, social welfare, macro economy, energy systems/security and resources (further information such as reports and a tool to visualize the effects, can be found at https://combi-project.eu or [14][15][16]). They are calculated from a snapshot view.…”

Section: Scopementioning

confidence: 99%

Metals for Fuels? The Raw Material Shift by Energy-Efficient Transport Systems in Europe

2018

Self Cite

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Abstract:The long-term transition towards a low-carbon transport sector is a key strategy in Europe. This includes the replacement of fossil fuels, modal shifts towards public transport as well as higher energy efficiency in the transport sector overall. While these energy savings are likely to reduce the direct greenhouse gas emissions of transport, they also require the production of new and different vehicles. This study analyses in detail whether final energy savings in the transport sector also induce savings for material resources from nature if the production of future vehicles is considered. The results for 28 member states in 2030 indicate that energy efficiency in the transport sector leads to lower carbon emissions as well as resource use savings. However, energy-efficient transport sectors can have a significant impact on the demand for metals in Europe. An additional annual demand for 28.4 Mt of metal ores was calculated from the personal transport sector in 2030 alone. The additional metal ores from semiprecious metals (e.g., copper) amount to 12.0 Mt, from precious metals (e.g., gold) to 9.1 Mt and from other metals (e.g., lithium) to 11.7 Mt, with small savings for ferrous metal ores (−4.6 Mt).

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“…Macro control behavior is gradually effective for economic growth, albeit with a lag, which cannot be ignored in the research of low-carbon economy growth [35]. However, most studies of low-carbon economy growth test influential factors, such as the correlation among energy consumption, carbon emissions, and Gross Domestic Product (GDP) [36,37]; the relationship between energy efficiency and carbon emission [4,38]; and the factors that influence carbon emission efficiency [26,39]. These studies only focus on the single period effect of resources, which defines the single period product feasible set as a reference.…”

Section: Literature Reviewmentioning

confidence: 99%

Low Carbon Economy Performance Analysis with the Intertemporal Effect of Capital in China

Zhao

Zhong

2017

Sustainability

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Abstract:The "New Normal" of Chinese economy represents the importance of economic performance. To analyze the provincial performance of the low-carbon economy in China, this paper constructed a three-stage dynamic Malmquist model considering the evolutionary promotion of productivity and technical progress. This paper incorporates the lag effect of capital accumulation into the performance evaluation to ensure transitivity and continuity. Furthermore, the inefficiency of the low-carbon economy arises from the disadvantages of resources endowments; therefore, it is necessary to eliminate these to evaluate managerial performance. This paper not only evaluates the provincial performance of the low-carbon economy but also suggests the sources and impetus of regional low-carbon economy development to find feasible transition paths. The empirical results reveal that the performance of the low-carbon economy presents a gradient distribution with obvious distinctions among the eastern, central, and western regions. Tianjin and Hebei should emphasize the optimal allocation of their own resources. Jiangxi and Hunan, by contrast, should focus on the perfection of the resources endowments.

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Measuring multiple impacts of low-carbon energy options in a green economy context

Cited by 63 publications

References 82 publications

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Metals for Fuels? The Raw Material Shift by Energy-Efficient Transport Systems in Europe

Low Carbon Economy Performance Analysis with the Intertemporal Effect of Capital in China

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