Assessing dynamic China’s energy security: Based on functional data analysis

Gong, Xu; You, Wang; Lin, Boqiang

doi:10.1016/j.energy.2020.119324

Cited by 63 publications

(19 citation statements)

References 71 publications

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“…Due to the difference of climate change influence and ability to adapt to climate change, different regions in China have different policy objectives and priorities to adapt to Figure 5. Human activities' optimization mechanism for climate environment climate change and energy conservation (Wen et al, 2020;Wang & Gong, 2020;Gong et al, 2021), which may be the reason why there are significant differences in the level of governance of regional climate in China (Sun et al, 2015). This conjecture has also been pointed out in studies in the fields of economics, politics and law.…”

Section: Can Human Beings Influence Climate Suitability In Other Ways?mentioning

confidence: 85%

The Impact Mechanism of Human Activities Over Climate Suitability Based on Social Network Data: Evidence From China

Ren

Tang

Guo

et al. 2022

Journal of Environmental Engineering and Landscape Management

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The impact mechanism of human activities on climate suitability is critical for understanding the human-environment nexus. In this study, social network data from Sina Weibo Platform was collected to quantitatively examined the relationship between the seven major types of human activities and climate suitability. The results indicated that the impacts of entertainment, tourism and daily life related human activities on climate suitability are significant (p-value < 0.05). With one-unit (one check-in record/km2) increase of entertainment and tourism related human activities, the coverage rate of climate suitable zone and the length of climate suitable period increase by 0.003% and 0.026 months, respectively. In contrast, one-unit of increase of daily life activities made the Theil entropy index of climate inequity and the length of climate suitable period increase 0.00035 units and shorten 0.014 months, respectively. Moreover, the impact mechanism of human activities on climate suitability showed a significant spatial heterogeneity within regions at different economic level or topographical conditions, which could be explained by the discrepancy of environmental policies, urban form and urban ventilation channel design strategies in China. This work exhibited a further step to new possibilities in clarifying the climate effect of human activities using open-sourced social network data.

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Section: Can Human Beings Influence Climate Suitability In Other Ways?mentioning

confidence: 85%

The Impact Mechanism of Human Activities Over Climate Suitability Based on Social Network Data: Evidence From China

Ren

Tang

Guo

et al. 2022

Journal of Environmental Engineering and Landscape Management

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“…Ramsay and Dalzell (1991) projected infinite dimensional functions into finite dimensional space and summarized the FDA methods, followed by an upsurge of research on FDA methods in the field of theory and application. At present, the FDA methods have been widely used in various fields, such as environmental science (Ignaccolo et al, 2013;Shaadan et al, 2015), finance (Cerovecki et al, 2019) and energy economics (Wang and Gong, 2020;Gong et al, 2021). Using this method, this study was able to describe the dynamic change of regional electrification level more accurately and then put forward targeted improvement suggestions according to the evaluation results, which can provide reference for the development of energy transformation, low-carbon development, and pollution prevention and control in different regions.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic assessment of China’s re-electrification level considering carbon peaking and carbon neutrality goals: A study based on functional data analysis

Guo¹,

Sun²,

Han³

et al. 2022

Front. Energy Res.

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Electrification is currently the most mature technological path to carbon neutrality. However, the traditional measurement methods of the electrification levels cannot meet the development requirements of China’s electrification under the dual-carbon strategy. Thus, this study incorporated carbon constraints into the re-electrification-level evaluation system and evaluated the re-electrification level of 30 provinces in China from 2007 to 2019 using the entropy weight method. Then, the functional data analysis method was employed to further explore the dynamic variation rule of the regional re-electrification level. The evaluation results show that the top three provinces in the mean value of the re-electrification index are Guangdong (0.628), Jiangsu (0.617), and Zhejiang (0.573). The clustering results show that there are great spatial differences in the development of electrification in China. According to the fitted function curve, China’s electrification development can be roughly divided into the following four stages: uptrend, brief decline, sharp uptrend, and slight and steady decline. At present, China’s electrification is entering a new stage. To implement re-electrification further, the government and the power grid enterprises need to find the priority and breakthroughs under carbon emissions and environmental constraints. Our research results provide reference for the improvement of regional re-electrification levels in China.

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“…This approach over time leads to a constant expansion of the set of "important" parameters. Thus, based on researchers' analyses [1,2,[4][5][6][7][8][9][10][11][12][13][14][15][16][17], energy security should be determined by the influence of factors that they grouped into four groups: the availability of energy, its affordability, efficiency of its use, and environmental stewardship. A. Azuni and C. Breyer [3], analyzing the research for the period of 1971-2016, distinguish between 15 groups of parameters (availability, diversification, price, technology and efficiency, localization, time interval, sustainability, environment, health, culture, access to information, employment, public policy, military dimension, and cybersecurity) [18], which are necessary to describe the object of energy security management.…”

Section: Introductionmentioning

confidence: 99%

“…1) GDP per person, thousand $/person. (at the current exchange rate) (S);(2) energy consumption per person, toe/year; (S);(3) electricity consumption per person, MWh/year, (S);(4) the cost of energy consumption for the country, % of GDP; (D);(5) energy intensity of GDP, toe/$ 1000; (D);(6) the level of CO 2 emissions per unit of GDP, kg per $ (D);(7) the cost of energy imports for the country, % of GDP; (D);(8) the level of involvement in EU markets (expert judgement), (S);The system's elements and linksManagement modelOrganization of the country's energy supply system: institutional; infrastructural. Provision: resource (energy resources, technologies); legislative.Resource sufficiency:(9) oil and oil products, % (D); (10) natural gas, % (D); (11) coal, % (D); (12) nuclear and thermonuclear energy, % (S); (13) hydropower, % (S); (14) solar and wind energy, % (S); (15) bioenergy, % (S); Institutional and organizational support:(16) production processes and infrastructure, % (expert judgement) (S); (17) (management processes and infrastructure, % (expert judgement) (S); (18) ancillary and service processes and infrastructure, % (expert judgement) (S); (19) processes and infrastructure to support facilities at all stages of the life cycle, % (expert judgement) (S); (20) information and communication processes and infrastructure, % (expert judgement) (S); Functions and roles Regulating requirements for the provision of target functions.…”

mentioning

confidence: 99%

The Systemic Approach for Estimating and Strategizing Energy Security: The Case of Ukraine

et al. 2021

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The current approaches to estimating the level of energy security are based on applying a comprehensive approach to selecting the factors that affect energy security and the dynamics of processes in this domain. This article reveals the application of the model of energy security estimation and strategizing based on the systemic description of energy security as an object of management: the integral system, elements and connections, functions, processes, and the system’s material. At the same time, this model is able to take into account the dynamics of technological, political, economic, and other factors operating in the country and on the global arena. The energy security estimation model developed uses a modern methodology of integrated estimation: a multiplicative form of the integrated index, a formalized definition of the safe existence limits in order to provide scientific substantiation of the threshold vector, a modified rationing method, the principal components method, and the sliding matrix method to substantiate dynamic weighting coefficients. The paper demonstrates the systemic approach application to shaping strategic goals in the energy security domain in the context of sustainable development; the trajectory of energy security development is calculated by the method of strategizing that applies the principle “future is determined by the trajectory to the future” instead of the classical forecasting “past determines the future”. In general, the article shows the possibility of unifying the process of formalizing energy security (according to the needs of the researcher: country, industry, energy network, supply chain) as an object of management, estimating energy security status, and strategizing the regulatory sphere transformation in accordance with the target values for monitoring the effectiveness of management.

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Assessing dynamic China’s energy security: Based on functional data analysis

Cited by 63 publications

References 71 publications

The Impact Mechanism of Human Activities Over Climate Suitability Based on Social Network Data: Evidence From China

The Impact Mechanism of Human Activities Over Climate Suitability Based on Social Network Data: Evidence From China

Dynamic assessment of China’s re-electrification level considering carbon peaking and carbon neutrality goals: A study based on functional data analysis

The Systemic Approach for Estimating and Strategizing Energy Security: The Case of Ukraine

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