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Jinying Li
Department of Economics and Management, North China Electric Power University, Baoding, Hebei, 071003, China

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Journal article
Published: 02 April 2020 in Renewable Energy
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With the global energy crisis and the increasing severity of environmental pollution, promoting the exploitation of clean energy, especially the renewable energy, has become an effective way to reduce the consumption of fossil fuels and the emissions of carbon dioxide. Based on the facts above, this paper carries out a comprehensive analysis of the carbon emissions during the whole life cycle of wind power project according to the life-cycle assessment theory, and both the construction of wind farm project and the corresponding networking project are taken into consideration. Then, the Life cycle inventory of wind power project is delivered to carry out the calculation of carbon emissions during the project’s whole life cycle. Finally, the 49.5 MW wind power project in Shi-san-jian-fang area of Xinjiang is employed for empirical analysis to discuss the project’s carbon intensity and the potential of emission reductions. The result shows that the carbon intensity of this wind power project is 4.429 g/kWh and the potential for emission reductions throughout its life cycle reaches 2.0416 million tons in theory, which means wind power project owes huge potential for emission reductions compared with general coal-fired stations.

ACS Style

Jinying Li; Sisi Li; Fan Wu. Research on carbon emission reduction benefit of wind power project based on life cycle assessment theory. Renewable Energy 2020, 155, 456 -468.

AMA Style

Jinying Li, Sisi Li, Fan Wu. Research on carbon emission reduction benefit of wind power project based on life cycle assessment theory. Renewable Energy. 2020; 155 ():456-468.

Chicago/Turabian Style

Jinying Li; Sisi Li; Fan Wu. 2020. "Research on carbon emission reduction benefit of wind power project based on life cycle assessment theory." Renewable Energy 155, no. : 456-468.

Journal article
Published: 14 March 2020 in Energy Policy
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The international community has reached a consensus on preventing the global climate from deterioration by stabilizing greenhouse gas concentrations in the atmosphere. Energy industry is a key field for greenhouse gas emission, and investment in the energy industry plays a crucial part in promoting the low-carbon development of China's energy industry. Energy investment can effectively break the high carbon ″lock-in effect″ of energy industry and achieve the low-carbon development of energy industry by guiding, regulating and gathering social funds into the field of cleaner production and the field of low-carbon technology. Based on the unified framework of energy, economy and environment, this article takes 30 provinces in China as the research object, and constructs a spatial econometric model to investigate the impact of energy investment and economic growth on carbon emission reduction. The results indicate that both energy investment and economic growth are responsible for the increase of China's provincial CO2 emissions, but their driving mechanisms are significantly different. Furthermore, the increase of carbon emissions in adjacent provinces will bring about the increase of local carbon emissions through spatial spillover effects. Based on these findings, the corresponding countermeasures and policy suggestions are put forward.

ACS Style

Jinying Li; Sisi Li. Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model. Energy Policy 2020, 140, 111425 .

AMA Style

Jinying Li, Sisi Li. Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model. Energy Policy. 2020; 140 ():111425.

Chicago/Turabian Style

Jinying Li; Sisi Li. 2020. "Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model." Energy Policy 140, no. : 111425.

Journal article
Published: 03 December 2019 in Journal of Cleaner Production
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In recent years, coal power has obvious advantages in terms of safety, economy and stability. As people gradually realize the importance of the environment, low carbon has become one of the core indicators of power system evaluation, so it is particularly important to guide the coal enterprises to achieve a win-win situation of economic and environmental benefits. Combined with the carbon emission policies, this paper takes the coal supply chain network as the research object and aims to develop a comprehensive decision model for sustainable design of coal supply chain. First, this paper extracts the influencing factors of low-carbonization in coal supply chain and constructs an interpretative structural model (ISM). The results show that low-carbon green technology, low-carbon production cost, utilization level of green energy and energy efficiency are the most basic manifestations of low-carbonization of coal supply chain and interact with each other, therefore this paper builds an optimization model with the objective of minimizing the low-carbon production costs in the coal supply chain. Concurrently, this paper introduces four policies (emission cap, carbon tax, carbon trade and carbon offset) as constraint condition. Then, in the aspect of model solving, this paper combines the differential evolution (DE) strategy to mutate, cross and select the leaders generated in each iteration of the salp swarm algorithm (SSA), further increases the diversity of the salp swarm, avoids the algorithm falling into a local optimum, and proposes the salp swarm algorithm based on differential evolution (DE-SSA). Finally, this paper compares the effects of four different carbon emission policies on the optimization of coal supply chain network through empirical analysis, and finds that coal enterprises have the best emission reduction effect under the carbon trade policy. The development and implementation of this paper not only enriches the related research of efficient supply chain, but also provides scientific and quantifiable decision-making technology for coal enterprises.

ACS Style

Jinying Li; Lin Wang; Xin Tan. Sustainable design and optimization of coal supply chain network under different carbon emission policies. Journal of Cleaner Production 2019, 250, 119548 .

AMA Style

Jinying Li, Lin Wang, Xin Tan. Sustainable design and optimization of coal supply chain network under different carbon emission policies. Journal of Cleaner Production. 2019; 250 ():119548.

Chicago/Turabian Style

Jinying Li; Lin Wang; Xin Tan. 2019. "Sustainable design and optimization of coal supply chain network under different carbon emission policies." Journal of Cleaner Production 250, no. : 119548.

Journal article
Published: 07 December 2016 in Sustainability
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Planning for electricity generation systems is a very important task and should take environmental and economic factors into account. This paper reviews the existing metrics and methods in evaluating energy sustainability, and we propose a sustainability assessment index system. The input indexes include generation capacity, generation cost, and land use. The output indexes include desirable and undesirable parts. The desirable outputs are total electricity generation and job creation. The undesirable outputs are external supply risk and external costs associated with the environment and health. The super-efficiency data envelopment analysis method is used to calculate the sustainability of electricity generation systems of 23 countries from 2005 to 2014. The three input indexes and three undesirable output indexes are used as the input variables. The two desirable outputs are used as the output variables. The results show that most countries’ electricity generation sustainability values have decreasing trends. In addition, nuclear and hydro generation have positive effects. Solar, wind, and fossil fuel generation have negative effects on sustainability.

ACS Style

Jinchao Li; Xian Geng; Jinying Li. A Comparison of Electricity Generation System Sustainability among G20 Countries. Sustainability 2016, 8, 1276 .

AMA Style

Jinchao Li, Xian Geng, Jinying Li. A Comparison of Electricity Generation System Sustainability among G20 Countries. Sustainability. 2016; 8 (12):1276.

Chicago/Turabian Style

Jinchao Li; Xian Geng; Jinying Li. 2016. "A Comparison of Electricity Generation System Sustainability among G20 Countries." Sustainability 8, no. 12: 1276.

Journal article
Published: 04 August 2016 in Energies
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Carbon emissions are the major cause of the global warming; therefore, the exploration of carbon emissions reduction potential is of great significance to reduce carbon emissions. This paper explores the potential of carbon intensity reduction in Beijing in 2020. Based on factors including economic growth, resident population growth, energy structure adjustment, industrial structure adjustment and technical progress, the paper sets 48 development scenarios during the years 2015–2020. Then, the back propagation (BP) neural network optimized by improved particle swarm optimization algorithm (IPSO) is used to calculate the carbon emissions and carbon intensity reduction potential under various scenarios for 2016 and 2020. Finally, the contribution of different factors to carbon intensity reduction is compared. The results indicate that Beijing could more than fulfill the 40%–45% reduction target for carbon intensity in 2020 in all of the scenarios. Furthermore, energy structure adjustment, industrial structure adjustment and technical progress can drive the decline in carbon intensity. However, the increase in the resident population hinders the decline in carbon intensity, and there is no clear relationship between economy and carbon intensity. On the basis of these findings, this paper puts forward relevant policy recommendations.

ACS Style

Jinying Li; Jianfeng Shi; Jinchao Li. Exploring Reduction Potential of Carbon Intensity Based on Back Propagation Neural Network and Scenario Analysis: A Case of Beijing, China. Energies 2016, 9, 615 .

AMA Style

Jinying Li, Jianfeng Shi, Jinchao Li. Exploring Reduction Potential of Carbon Intensity Based on Back Propagation Neural Network and Scenario Analysis: A Case of Beijing, China. Energies. 2016; 9 (8):615.

Chicago/Turabian Style

Jinying Li; Jianfeng Shi; Jinchao Li. 2016. "Exploring Reduction Potential of Carbon Intensity Based on Back Propagation Neural Network and Scenario Analysis: A Case of Beijing, China." Energies 9, no. 8: 615.

Journal article
Published: 10 February 2014 in Sustainability
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This paper measured the economic and unified efficiency of 24 electric power supply companies in China. With the development of a low carbon economy, further requirements for energy-saving and emission-reducing have been put forward for electric power supply companies. In this case, we considered the desirable (good) outputs (e.g., electricity sale amount) and undesirable (bad) outputs (e.g., line loss) in evaluating the performance of power supply companies. We combined the unified efficiency data envelopment analysis (DEA) model and the super-efficiency DEA model to create tge USDEA model, calculating companies’ unified efficiency. The unified efficiency DEA model can easily incorporate both desirable and undesirable outputs in a unified analytical structure. The super-efficiency data envelopment analysis model can make a comparison among various efficient decision making units (DMUs). Our results showed that the electric power supply companies of Hebei, Qinghai, Ningxia, Beijing and Shanghai achieved the highest levels of unified efficiency during the observed period (2003–2010), which differed from the economic efficiency results. The results meant that using unified efficiency to evaluate power supply companies will motivate them to care more about social and environmental benefit besides economic benefit.

ACS Style

Jinchao Li; Jinying Li; Fengting Zheng. Unified Efficiency Measurement of Electric Power Supply Companies in China. Sustainability 2014, 6, 779 -793.

AMA Style

Jinchao Li, Jinying Li, Fengting Zheng. Unified Efficiency Measurement of Electric Power Supply Companies in China. Sustainability. 2014; 6 (2):779-793.

Chicago/Turabian Style

Jinchao Li; Jinying Li; Fengting Zheng. 2014. "Unified Efficiency Measurement of Electric Power Supply Companies in China." Sustainability 6, no. 2: 779-793.