Total-factor energy efficiency of coal consumption: An empirical analysis of China's energy intensive industries

Guo, Pibin; Qi, Xiaoyan; Zhou, Xijun; Li, Wei

doi:10.1016/j.jclepro.2017.11.149

Cited by 105 publications

(33 citation statements)

References 20 publications

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“…This study is also a pioneering study regarding the exploration of the impact of technically derived energy efficiency on the ecological footprint. Most of the previous studies were carried out to examine the impact of energy consumption/efficiency in the industrial sector on carbon dioxide emissions [33,34]. In addition, this study also explores the impact of urbanization and investment in the agricultural sector on the ecological footprint, which were ignored by previous studies.…”

Section: Introductionmentioning

confidence: 99%

Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region

et al. 2021

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The sustainable environment has been a desired situation around the world for the last few decades. Environmental contaminations can be a consequence of various economic activities. Different socio-economic factors influence the environment positively or negatively. Many previous studies have resulted in the efficient allocation of inputs as an environment-friendly component. This paper investigates the effects of energy efficiency on ecological footprint in the ASEAN region using balanced panel data from 2001 to 2019. First, this paper technically derives the energy efficiency, using the stochastic frontier analysis (SFA) of the translog production type of single output and multiple inputs. Findings of the SFA show that the Philippines and Singapore have the highest energy efficiency (94%) and Laos has the lowest energy efficiency (85%) in the ASEAN region. The estimated average efficiency score of the ASEAN region was around 90%, ranging from 85% to 96%, indicating that there is still 10% room for improvement in energy efficiency. Second, this study employed the panel autoregressive distributed lag (ARDL) model to explore the short run and long run impact of technically derived energy efficiency on ecological footprint in the ASEAN region. Results of the panel ARDL model show that energy efficiency is a reducing factor of ecological footprint in the long run. Moreover, energy efficiency plays a significant role to control the environmental contaminations. In addition, results of this study also explored that urbanization is an increasing factor of ecological footprint, and investment in agriculture is also beneficial for the environment. Moreover, to obtain the directional nature of the associations between the ecological footprint and its independent variables, this paper has employed the paired-panel Granger causality test. The results of the paired wise panel Granger causality test also confirm that the energy efficiency, urbanization, and investment in agriculture cause ecological footprint. Finally, this study recommends that efficient utilization of energy resources as well as investment in agriculture are necessary for sustainable environment.

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Section: Introductionmentioning

confidence: 99%

Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region

et al. 2021

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“…Secondly, given the strong relationship between electricity production and carbon emission, a great deal of researches on carbon reduction is carried out from the perspective of electricity generation. On the one hand, to identify critical industries and sectors for reduction efforts, many researchers carried out inventory analysis on carbon emission, verifying that the energy industry and energy-intensive industries, such as electric power industry and the iron and steel industry, are the main contributors to carbon emission (Munksgaard and Pedersen, 2001;Satterthwaite, 2008;Xi et al, 2011;Guo et al, 2012Guo et al, , 2018Wang et al, 2013;Liu et al, 2015;Wu et al, 2016Wu et al, , 2020. On the other hand, to formulate effective carbon mitigation policy, a number of carbon reduction studies related to electricity generation have been conducted at multiple levels.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Interprovincial Cooperative Carbon Reduction in China: An Electricity Generation Perspective

Zeng

Zhao

et al. 2021

Front. Energy Res.

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As the world faces great challenges from climate change, carbon reduction has become China’s basic national policy. However, as the main model for carbon reduction in China, the non-cooperative carbon reduction model (NCCRM) is a simple regulation mode, which is not beneficial for optimization of electricity generation capacity structure and cannot effectively motivate carbon reduction at the provincial level. Therefore, we propose an interprovincial cooperative carbon reduction model (CCRM) from the perspective of electricity generation, which provides a mechanism integrating two fundamental principles of efficiency and fairness. The CCRM consists of two parts: (1) an optimal model of carbon reduction with the object of minimizing the carbon emission of the cooperation union to determine the optimal annual electricity generation for each participating province and (2) a model that distributes the economic benefits of the cooperation among the provinces in the cooperation based on the Shapley value method. We applied the CCRM to the case of an interprovincial union of Shanghai, Sichuan, Shanxi, and Gansu in China. The results, based on the data from 2014 to 2017, show that cooperation can significantly reduce the carbon emission of the union by 425.78 × 108 kg, 11.06%; meanwhile, Shanghai, Sichuan, Shanxi, and Gansu can, respectively, get 2.79 × 108, 11.11 × 108, 4.07 × 108, and 3.19 × 108 CNY of extra benefits from carbon reduction. To test the impact of different parameter values on the results of the CCRM, a sensitivity analysis was conducted. Some policy recommendations are proposed to promote the implementation of the CCRM.

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“…Liu et al (2019) found that the energy-intensive industries of China had a significant downward trend in their carbon emission intensity, showing spatially differentiated patterns of "West High East Low" and "North High South Low" and significant spatial correlation; and Sueyoshi et al (2020) took power industry as an example to verify the regional heterogeneity of energy efficiency in China. Guo et al (2018) found that the economic efficiency of coal in energy-intensive industries was greater than the environmental efficiency of coal, and the empirical results showed the potential for energy savings and emission reduction in the industries. In addition, Qi et al (2020) found that the coal efficiency of the major coal-intensive industries of China was mainly derived from technological progress, and there were differences in the driving factors of coal efficiency in different industries.…”

Section: Literature Reviewmentioning

confidence: 99%

What Is the Regional Differences in Carbon Emission Performance: Evidences From Energy-intensive Industries in China?

Chen

2021

Preprint

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As the major energy consumers, energy-intensive industries are the key players in achieving carbon emission reduction targets. Grasping the carbon emission reduction potential has a direct impact on the implementation of the carbon emission reduction policies of China. The paper builds a super-Slack Based Model(SBM) considering this undesirable output, and calculates the carbon emission efficiency. Then, the Meta-Frontier Malmquist-Luenberger productivity index (MF-MLPI) is constructed to dynamically analyse the growth rate changes of the carbon emission efficiency and the regional differences in energy-intensive industries. Furthermore, the carbon emission reduction potential of the energy-intensive industries in various economic regions of China is discussed and the conclusions are as follows: there is a big difference in the carbon emission Technology Gap Ratios (TGRs) of the energy-intensive industries in different economic regions; the growth rate of the carbon emission efficiency of energy-intensive industries shows a trend of first declining and then slowly recovering while the carbon reduction potential generally shows a trend of decreasing and then rising; and the carbon emission reduction potential in the eastern region keeps decreasing. The following is recommended: the government should rationally distribute energy-intensive industries, promote industrial structure adjustment, optimize the energy structure according to the regional industrial advantages; increase investment in R&D, promote energy technology innovation in energy-intensive industries; prioritize the promotion of carbon peaks on key emission industries and regional, formulate differentiated plans for the regions and industries with different carbon emission reduction potentials.

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Total-factor energy efficiency of coal consumption: An empirical analysis of China's energy intensive industries

Cited by 105 publications

References 20 publications

Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region

Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region

Modeling Interprovincial Cooperative Carbon Reduction in China: An Electricity Generation Perspective

What Is the Regional Differences in Carbon Emission Performance: Evidences From Energy-intensive Industries in China?

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