The effects of industrial energy consumption on energy‐related carbon emissions at national and provincial levels in China

Lu, Lanlan; Zhou, Li; Zhang, Hongyu; Weng, Yuyan

doi:10.1002/ese3.206

Cited by 12 publications

(7 citation statements)

References 26 publications

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“…A large and growing body of literature has investigated the concept (Teng et al, 2019;Zhang et al, 2020;Wang and Wei, 2014;Zhang et al, 2021), measurement (Yao et al, 2015;Liu et al, 2016a;Wang et al, 2017;Cai et al, 2019), impact factors (Zhou et al, 2016;Zhang et al, 2017;Yu and Zhang, 2021;Zhang et al, 2018;, and effects (Zhang and Cheng, 2009;Zhang, 2011;Long et al, 2015;Lu et al, 2018;Zhu et al, 2019;Wu and Gu, 2021) of carbon emission efficiency (CEE). The indicators for measuring CEE have shifted from a single factor measurement method (Ang, 1999;Mielnik and Goldemberg, 1999;Pretis and Roser, 2017;Ferreira et al, 2018) to a total factor measurement method (Kortelainen, 2008;Marklund and Samakovlis, 2007).…”

Section: The Measurement Of Carbon Emission Effeciencymentioning

confidence: 99%

Regional differential decomposition and the formation mechanism of the dynamic carbon emissions efficiency of industrial energy in China

Tang

Liu³

et al. 2022

Front. Environ. Sci.

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Industrial carbon emissions efficiency requires a balance between economic development and carbon reduction to be achieved through structural adjustment and technological change, which is the key to low-carbon economic development and the essence of China’s carbon reduction commitment. Existing research has focused more on static carbon emission efficiency and provides insufficient analysis of the internal causes of inter-regional differences in carbon emission efficiency. This paper aims to fill this gap in the existing research. The data of 30 provinces in China, obtained from the Chinese Official Statistical Yearbook, were taken as the sample. We accurately measured the dynamic carbon emission efficiency of industrial energy (DCEEIE) in China by combining the three-stage slacks-based measure data envelopment analysis (SBM-DEA) model and the Malmquist-Luenberger model. This study further uses Dagum’s Gini coefficient decomposition and the panel vector auto regression (PVAR) model to empirically estimate regional differences in DCEEIE and the effects of its internal structure. The results show, first, that DCEEIE in China is increasing, and that overall energy efficiency is at a high level. Although both efficiency change and technological change are fundamental to efficiency, an attenuation of efficiency and a diffusion of technology are evident. Second, the total Gini coefficients of dynamic efficiency, efficiency change (EC), and technological change (TC) are all decreasing; regional differences and transvariation intensity are the main reasons for long-term gaps. Third, TC improves dynamic efficiency in the initial stages, but the main driving force in the long run is EC. The limitation of this paper is that we do not fully discuss the external factors which might impact TC and EC, nor do we continue the discussion on how to transform the energy mix by improving carbon efficiency, which is the future direction for green development. These issues represent avenues for future research.

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Section: The Measurement Of Carbon Emission Effeciencymentioning

confidence: 99%

Regional differential decomposition and the formation mechanism of the dynamic carbon emissions efficiency of industrial energy in China

Tang

Liu³

et al. 2022

Front. Environ. Sci.

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“…Based on principle of mass conservation and the mean residence time method, the general system dynamics model for each subsystem in fusion fuel cycle is shown in formula (1).…”

Section: Mixed Fuel Burning and Cycle Modelmentioning

confidence: 99%

Insights into fuel start‐up and self‐sufficiency for fusion energy: The case of CFETR

Nie¹,

Ran

Zeng

et al. 2019

Energy Science & Engineering

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Commercial tritium resources available are too scarce to fully supply the future fusion reactors after International Thermonuclear Experimental Reactor (ITER). Tritium self‐sufficiency, ITER fails to fully validate, was regarded as one of the most important issues needed to be solved in the pathway of achieving fusion energy. After ITER, several concepts of fusion engineering test reactors and fusion demonstration reactors have been proposed worldwide, for example, Chinese Fusion Engineering Test Reactor (CFETR), Fusion Nuclear Science Facility (FNSF), DEMOnstration fusion reactor (DEMO) in European Union and Korea. CFETR is in the engineering design phase and would be hopefully completed around 2020. Tritium resources for the reactor start‐up and tritium self‐sufficiency are two primary issues besides the steady‐state operation for CFETR. The objectives of this work are as follows: (a) to introduce the preliminary fuel cycle concept and available tritium resources for CFETR, (b) to evaluate and discuss the tritium demand for CFETR start‐up (phase I: 200 MW) and the feasibility of DD start‐up, (c) to identify the possible pathways to tritium self‐sufficiency through sensitivity analysis based on the design baseline of CFETR, (d) to evaluate the consequences in case of failing tritium self‐sufficiency, and (e) to identify future R&D needed for tritium self‐sufficiency. It is expected to give insights into the question on how to start the reactor in a more economical way, into the feasibility of tritium self‐sufficiency, and into the question on what will happen in case of failing tritium self‐sufficiency.

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“…The promotive and inhibitive drivers of emissions were explored at the national [ 11 , 12 ], provincial [ 13 , 14 ], regional [ 15 , 16 ], and sectoral levels [ 17 , 18 ]. The main factors identified included: economic growth, industrial structure, energy structure, energy intensity, population, urbanization, and so on [ 19 , 20 , 21 , 22 ]. Economic growth is considered as a primary contributor to increasing emissions, while energy intensity significantly inhibits emissions [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Tracking Key Industrial Sectors for CO2 Mitigation through the Driving Effects: An Attribution Analysis

Wang

Song

et al. 2022

IJERPH

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The heavy pressure to improve CO2 emission control in industry requires the identification of key sub-sectors and the clarification of how they mitigate CO2 emissions through various actions. Focusing on 30 Chinese provincial regions, this study quantifies the contribution of each industrial sector to regional CO2 mitigation by combining the logarithmic mean Divisia index with attribution analysis and extract the key sectors of CO2 mitigation for each region. Results indicate that during 2010–2019, significant emission reduction was achieved through energy intensity (74%) in Beijing, while emission reductions were attained through industrial structure changes for Anhui (50%), Henan (45%), and Chongqing (45%). The contribution to emission reduction through energy structures is not significant. The production and supply of power and heat (PSPH) is a central factor in CO2 mitigation through all three inhibitive factors. Petroleum processing and coking (PPC) generally contributes to emission reduction through energy structures, while the smelting and pressing of ferrous metals (SPMF) through changes in industrial structures and energy intensity. PSPH and SPMF, in most regions, have not achieved the emission peak. Except in the case of coal mining and dressing (CMD), CO2 emissions in other key sectors have almost been decoupled from industrial development. CMD effectively promotes CO2 mitigation in Anhui, Henan, and Hunan, with larger contribution of PPC in Tianjin, Xinjiang, Heilongjiang, and that of smelting and pressing of nonferrous metals in Yunnan and Guangxi. The findings help to better identify key sectors across regions that can mitigate CO2 emissions, while analyzing the critical emission characteristics of these sectors, which can provide references to formulating region- and sector-specific CO2 mitigation measures for regions at different levels of development.

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The effects of industrial energy consumption on energy‐related carbon emissions at national and provincial levels in China

Cited by 12 publications

References 26 publications

Regional differential decomposition and the formation mechanism of the dynamic carbon emissions efficiency of industrial energy in China

Regional differential decomposition and the formation mechanism of the dynamic carbon emissions efficiency of industrial energy in China

Insights into fuel start‐up and self‐sufficiency for fusion energy: The case of CFETR

Tracking Key Industrial Sectors for CO2 Mitigation through the Driving Effects: An Attribution Analysis

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