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Due to its rapid economic growth and increasing demand for energy, China has engaged in numerous efforts to sustain its energy supplies and enhance its energy security. While existing literature argues that access to energy is oftentimes the driving force behind Beijing's foreign policy behavior, little work has been done to systemically examine the bilateral relationship between China and energy-producing countries. This paper explores how China's foreign policy making is influenced by its energy security concern, focusing on three foreign policy instruments—partnerships, foreign aid, and leadership visits. Using a large- N , quantitative approach, this paper analyzes the effect of oil production on these three foreign policy indicators. The results show that Beijing is more likely to form partnerships with oil-producing countries. Top Chinese leaders are also more likely to travel to countries that produce a higher level of oil. China's aid allocation to Africa is driven by oil abundance as well, although the findings on aid are only valid in the cross-national analysis. [ABSTRACT FROM AUTHOR]

Due to the gradual agglomeration of economic activities and the continuous reinforcement of spatial linkages in specific geographic locations, the geospatial factor should become an important starting point to understand the relationship between industrial restructuring and energy conservation and emission reduction. This paper first introduces a non-separable hybrid DEA model that considers undesirable output to measure the energy efficiencies of 285 prefecture or higher-level cities in China during 2003-2016; then, a dynamic spatial panel model is used to investigate the influence of different types of industrial agglomerations and agglomeration modes on energy efficiency. According to the obtained study results, for the investigation period, the overall energy efficiency of China with regard to pollutants remained at a low level and presented a "U-shaped" decreasing-increasing trend. To be specific, China's energy efficiency distribution presented a trend of "high in the east and low in the west." The energy efficiency of East China changed relatively gently, while the energy efficiencies of central China and western China changed dramatically. China's energy efficiency also presented a significant spatial agglomeration effect, i.e., cities with close energy efficiencies are usually adjacent to each other. At the national level, agglomeration of the manufacturing sector significantly inhibited the increase of energy efficiency; the agglomeration of the producer service sector and the co-agglomeration of the manufacturing sector and the producer service sector both facilitated an increase of energy efficiency. The influence of industrial agglomeration on energy efficiency differed across different city scale grades. Based on these conclusions, the paper proposes the following policy implications: 1) make full use of the energy savings and emission reduction effect of agglomeration; 2) accelerate the optimization of industrial layout; 3) develop high-end service industry and productive service industry; and 4) create an agglomeration environment that encourages benign industrial competition. [ABSTRACT FROM AUTHOR]

This paper selects China's renewable energy enterprises as a research sample and analyzes the impacts of equity balance and executive stock ownership on these companies' innovation efficiency from 2009 to 2018. The results show that equity balance has significant and positive impacts on innovation efficiency, while there is a significant nonlinear, inverted U-shaped relationship between the executive stock ownership and innovation efficiency. In addition, with changes in the shareholding ratio of the largest shareholder, equity balance and executive stock ownership are substitutive in terms of their impacts on innovation efficiency. Therefore, this paper proposes the following recommendations. The shareholding ratio of the largest shareholder should be controlled within a reasonable range to help force executives and outside blockholders to make decisions in the company's interests. When implementing an equity balance, companies should avoid shareholders' oversupervision of executives, which may restrict executives' enthusiasm for innovation investment. A moderate degree of freedom for management executives should be appropriate. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2006 to 2016, the Gaussian kernel density estimation was initially used to describe the characteristics of the inter-provincial differences in household energy consumption (HEC), a dynamic panel data model was established secondly to study the main factors affecting HEC, and finally the counterfactual decomposition method was used to calculate the contribution of each factor to the inter-provincial differences in HEC. The research results are shown as follows: First, the inter-provincial HEC in China shows a phenomenon of agglomeration and growth, and the HEC level of different regions presents difference and imbalance. Second, the logarithms of consumption habits, total population and residents' income have significant effects on the logarithm of HEC, the influence coefficients are 0.191, 0.073 and 0.745, respectively; HEC not only has significant inertia characteristics, but also has certain population size effect and wealth effect. Third, the logarithms of technological progress, urbanization and household energy price have significant effects on the logarithm of HEC, the influence coefficients are 0.864, 0.195 and −0.346, respectively; the HEC saved by technological transformation is not sufficient to offset the increase in HEC demand, urbanization can improve HEC significantly, but the household energy price significantly inhibits HEC. Finally, from the perspective of contribution, the total population, residents' income and urbanization contribute a lot to the inter-provincial differences, totaling 73.02%. The possible innovations of this paper are as follows: First, the contribution of the influencing factors to the difference of inter-provincial HEC is studied, which is rarely seen in the previous literature. Second, compared with traditional decomposition method, counterfactual decomposition method is more convenient for economic interpretation. Third, the divergent conclusions of scholars are pointed out in this paper, and the actual impact of influencing factors on HEC are clarified. Image 10086681 • The level of inter-provincial HEC shows difference and imbalance. • HEC has significant inertia characteristics, population size effect and wealth effect. • HEC saved by technology is not sufficient to offset the increase in HEC demand. • Total population, residents' income and urbanization contribute 73.02%. • The statistical analysis tool used in this paper is Stata15. [ABSTRACT FROM AUTHOR]

Based on 196 prefecture-level cities in China from 2006 to 2021, this paper constructs a weight matrix of urban economic geography and uses the spatial differential model to verify the impact of smart city policies on urban green energy efficiency. The results show that the efficiency value of green energy fluctuates in Chinese cities. Different test results show that smart city policies can effectively improve urban green energy efficiency, but mainly from the time effect rather than the individual effect. It means the improvement in urban green energy efficiency comes more from the fast-growing of the Chinese economy and urban construction in this period than from the country's smart city pilot policy. In addition, from the spatial spillover effect result, China needs to design a better urban spatial development plan to improve the capacity of smart city energy services and vigorously develop intelligent technology represented by information and communication science. [ABSTRACT FROM AUTHOR]

This paper constructs a two-stage undesirable and desirable congestion model, which distinguishes purely technical inefficiency from congestion, to study the energy congestion of 30 transportation sectors in China from 2011 to 2020. The Heckman model is used to analyze the influence mechanism of various factors on the undesirable congestion of energy, which avoids sample selection bias. The results show that: (1) The undesirable congestion of energy mainly exists in the transport sector of the western region, while the desirable congestion of energy only exists in the transport sectors of the eastern and central regions. (2) Purely technical inefficiency in the transportation sector does not usually occur in isolation. (3) Population density and the proportion of clean freight turnover have a negative impact on the undesirable congestion of energy. • A two-stage undesirable and desirable congestion model is designed innovatively. • Energy efficiency in transport sector is assessed from the perspective of congestion. • The factors affecting the undesirable congestion in transport sectors are analyzed. • Rational allocation of energy in transport sector is realized based on congestion. [ABSTRACT FROM AUTHOR]

[Display omitted] Particulate matter (PM) is an important air pollutant in subway systems. Exposure to high PM concentrations poses a threat to human health and raises concerns. Piston effect can provide the outdoor fresh air to subway stations through station exits, but it also brings PM from tunnels to platforms when the train enters the station. In this paper, a transient numerical model is developed according to an actual subway station and validated by field tests. The model is used to investigate PM 10 concentration at platform induced by train movement. The cumulative PM 10 concentration at platform in one day is calculated according to the train schedule. Platform screen door (PSD) with adjustable vents is studied to control the PM 10 level at platform and energy saving in 27 cities of five climatic zones in China are discussed. The results show that adjustable vent height should be less than 0.70 m to ensure that PM 10 concentrations at platform can be maintained at an acceptable level and the requirement of fresh air can be met. Moreover, energy consumption can be reduced by more than 70 % in different cities compared with the conventional mechanical ventilation system. The optimized adjustable vent can provide an important reference for improving indoor air quality (IAQ) and saving energy consumption of ventilation systems in underground facilities. [ABSTRACT FROM AUTHOR]

At present, the energy and environmental crisis is increasingly prominent, and how to solve the global energy and environmental problems is one of the challenges facing the world today. China is a major producer and consumer of organosilicon, so it is necessary to explore the stage of high energy consumption and high pollution in the organosilicon industrial chain. In 2022, the proportion of submerged arc furnaces of 25000 kVA and higher in China reached 40%. Further expansion of these furnaces in the future is inevitable. However, research on the life cycle assessment of organosilicon manufactured using large-capacity submerged arc furnaces is still blank.Therefore,in this paper, the life cycle assessment method is used to evaluate the synthesis process of chemical grade silicon-organosilicon monomer prepared by large capacity (33000 kVA) submerged arc furnace, and the dominant process in various environmental impacts is defined.At the same time, the measures to improve the production process of organosilicon monomer were put forward. In the production process of 1000 kg organosilicon monomer, global warming potential (GWP) contributed the most (73.43%) to the comprehensive environmental impact, followed by chronic public health impact (HTI, 10.55%). Energy consumption (EN) accounted for 8.50%, while resource consumption (RU) accounted for 7.43%. The contributions of other environmental factors were relatively small (0.09%).The energy consumption and environmental pollution in the production of organosilicon monomer can be reduced by strictly controlling the quality of raw materials into the furnace, using heat pump technology in the distillation unit, and comprehensively utilizing the heat of reaction by-products and steam condensate. [Display omitted] • This study is the first one in China to conduct LCA for the preparation of chemical grade silicon-organosilicon monomer synthesis process in 33000 kVA submerged arc furnace. It provides the best improvement suggestions for reducing the environmental load of the product life cycle process and achieving cleaner production. • In response to the national development policy of large-scale submerged arc furnace, the dominant process of preparing organosilicon monomer based on 33000 kva submerged arc furnace in various environmental impacts was clarified. • The main technical improvement directions are: Strictly control the quality of raw materials for submerged arc furnace; Strictly control the sulfur content and nitrogen content of carbonaceous reductant, and adopt the most suitable flue gas treatment technology route; Smelt with large submerged arc furnace; Use heat pump technology for distillation unit; Optimize the monomer synthesis device. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy use between urban and rural areas is very important in the context of the global energy transition and climate change. However, it is difficult to measure the differences and inequalities in energy consumption due to data limitations. In this paper, a dataset distinguishing urban-rural energy consumption has been generated. We construct an energy inequality index (EI) to assess the difference in per capita energy consumption (PEC) between urban and rural areas. We find that the EI has decreased significantly from 10.42 in 2000 to 1.43 in 2020. Western China has a higher EI than the developed coastal areas. We further define 7 urban-rural types and find that the urban center has the highest PEC, while the rural cluster has the lowest. Cluster analysis shows that prefectures have different equalization trends, namely volatile decline, rapid decline, increase before decline, incremental decline. The urban-rural structure plays an important role in the different trends, and 4 modes of urban-rural energy consumption are summarized, namely urban-centered, urban-suburban double-centered, multi-centered and rural-biased. These results are valuable for understanding the energy consumption between urban and rural China. • A dataset distinguishing urban-rural per capita energy consumption (PEC) has been generated. • China's urban-rural energy inequality has decreased from 10.42 in 2000 to 1.43 in 2020. • Western China are facing a more urban-rural energy inequality than the developed coastal areas. • Among the 7 defined types, urban center ranked highest PEC, while rural cluster ranked lowest. • 4 modes of urban-rural energy consumption are summarized. [ABSTRACT FROM AUTHOR]

With the comprehensive progression of China's electric power reform, the participation of hydropower in the spot market has become inevitable. For hydropower-dominated power grids, the tight hydraulic and electric coupling relationship between cascade hydropower plants and the policy requirement of clean energy consumption greatly increase the challenge of optimal scheduling. Based on the market characteristics and actual demand of the hydropower-dominated power grids, this paper discusses the day-ahead spot market trading mechanism to promote the guaranteed consumption of renewable energy. On this basis, a day-ahead optimal scheduling model is established which aims to minimize the comprehensive power purchase cost of the power system. The nonlinear factors in the scheduling model, such as the relationship between the water level and storage capacity of hydropower plants, the relationship between the water level and water consumption rate, and the constraints on the start-up and shutdown durations of thermal power units, are linearized through multiple linearization techniques. The original nonlinear model is transformed into a mixed integer linear programming (MILP) model and is then solved using a CPLEX solver. The developed model is verified by taking 10 thermal power plants and 22 hydropower plants in Yunnan Power Grid as a case study. The calculation time is 183.6s, the comprehensive power purchase cost of the system is 155.35·million CNY, and no abandoned water is generated in the three basins. The simulation results show that the proposed model has high solution accuracy and efficiency, and maximizes the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost. The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grids. [Display omitted] • A day-ahead spot market trading mechanism to promote consumption of renewable energy. • Day-ahead optimal scheduling of hydropower-dominated power grids under a spot market environment. • A novel MILP approach is employed to solve the model. • Proposed model has high solution accuracy and efficiency. [ABSTRACT FROM AUTHOR]

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening—energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process. • Green innovation resilience can promote energy efficiency. • Early digital economy development can lead to resource grabbing and technology constraints effects. • Pursuing the policy orientation of "digital greening—energy efficient". [ABSTRACT FROM AUTHOR]

Energy quota trading is critical to both energy conservation and the achievement of dual-carbon goals. However, little remains to be done on total factor productivity and economic potential for Chinese industry. The purpose of this paper is to counterfactually model and explore the effects of energy quota trading on total factor productivity and economic potential in industrial sector. We propose a command-controlled DEA model and an energy quota trading DEA model through non-parametric linear programming based on two policy strategies of energy consumption control. We then assess total factor productivity and its growth sources for 35 two-digit industrial sector in China, as well as examine economic potential and optimal path forecasts for carbon peaking. The results show that total factor productivity and economic potential for energy quota trading are higher than those for command-controlled energy policy. Energy-saving effect can be achieved for energy quota trading because the total energy input is lower. Additionally, the sources of productivity growth differ in timing. The average economic potential and total factor productivity of different industries differ due to the heterogeneity of the production conditions and scale of development of individual market players. Moreover, the catch-up emission reduction path with an increase of 8% in output and 4.76% in energy consumption is the optimal carbon peaking path under energy quota trading. Our findings shed valuable light on China's efforts to expand energy quota trading for high-quality development in the context of carbon peaking. • Propose a command-controlled DEA model and an energy quota trading DEA model. • Assess TFP and its growth sources for industrial sector in China. • Compare the impact of different energy policies on economic potential and TFP. • Estimate the energy saving and emission reduction potential of energy quota trading. • Examine the optimal energy-saving and emission-reduction path forecasts for carbon peaking.. [ABSTRACT FROM AUTHOR]

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies. • The internal mechanism of rebound effect is expounded from the view of producers and consumers. • The average energy efficiency of China's agricultural energy consumption was 68.9 % during 1999–2020. • The determinants of the agricultural energy rebound effect were further discussed by considering the spatial spillover effect. [ABSTRACT FROM AUTHOR]

With the completion of the poverty alleviation task in China, the Chinese economy has made great breakthroughs. Meanwhile, the implementation of Chinese "dual carbon" goal has entered an important window period of both strategic opportunities and difficulties. The emission of carbon dioxide (CO2) leads to the greenhouse effect, which affects the sustainable development of society. Therefore, this paper proposes an improved analytic hierarchy process (AHP) with Slacks-based measure integrating data envelopment analysis (SBMDEA) (AHP-SBMDEA) based efficiency evaluation model for different provincial-level administrative regions in China, which is used to analyze and optimize the Chinese energy structure of different provincial-level administrative regions. With coal, gasoline, petroleum, fuel oil, diesel, crude oil and natural gas as inputs, the per capita Gross Domestic Product (GDP) as the desired output and the CO2 as the undesired output, after linear weighted calculation of the results of the AHP-SP model and the SBMDEA model, the energy efficiency evaluation model of different provincial administrative regions in China is established. The results show that there is a large difference in efficiency between Chinese northern and southern regions, and the overall efficiency of southern regions is higher than that of northern regions. In addition, it is easier to find out the optimal energy efficiency benchmark, which can provide suggestions and help to guide the energy consumption input structure improvement of other inefficient provincial-level administrative regions. Furthermore, the energy structure can also be adjusted through the redundant variable calculated by the SBMDEA model. For example, Sichuan Province can reduce the consumption of the coal, the gasoline, the diesel, the fuel oil, the crude oil and the natural gas by 5269.95 × 10000 tons (WT), 513.01 WT, 59.05 WT, 34.37 WT, 4,73.33 WT and 130.37 billion cubic meters (BCM), respectively. Its CO2 emissions can be reduced by 1925.4 WT, and raise the efficiency of energy utilization in the province. [Display omitted] • Novel economy and CO 2 emissions evolution model based on a AHP-SBMDEA is proposed. • The proposed model can identify the optimal energy efficiency benchmark. • GDP per capita can be increased and CO 2 emissions can be decreased. [ABSTRACT FROM AUTHOR]

In this era of global warming the importance of climate risk cannot be understated, and finding ways to reduce climate risk is a topic worthy of study. In this paper, we innovatively examine the role of renewable energy technology innovation on climate risk in China. In addition to their linear relationship, we also investigate the asymmetric and heterogeneous impact, detect the impact channels, and find that (1) increased renewable energy technology innovation can effectively alleviate the climate risk situation. Accordingly, the development of renewable energy technology innovation can make a significant contribution to CR abatement. (2) Pronounced impacts of renewable energy technology innovation on climate risk can be observed in the higher quantiles (75th and 90th) of climate risk. (3) Renewable energy technology innovation is a powerful weapon for eradicating climate risk in provinces with a higher level of government fiscal expenditure. And (4) renewable energy technology innovation has an impact on climate risk by facilitating energy consumption efficiency, which is a necessary mediator. These conclusions inspire us to put forward several corresponding policy implications for better climate risk governance and renewable energy technology innovation development. [ABSTRACT FROM AUTHOR]

To achieve the goal of "carbon peaking and carbon neutrality", China is vigorously developing renewable energy. This paper aims to examine the major contributors to regional inequality in renewable energy consumption by analyzing the 30 provinces in China. We have analyzed the inequality of China's renewable energy consumption with Dagum Gini coefficient, and then use the Generalized Divisia Index Model (GDIM) to decompose the influencing factors contributing to the inequality of renewable energy consumption. The main conclusions are summarized as follows: First, renewable energy consumption was higher in the western region than in the central and eastern regions, and the regional inequality in renewable energy consumption have increased over time. Second, the study reveals that inter-group disparity is the primary source of regional inequality in renewable energy consumption in China. Third, at the national level, the results of the GDIM decomposition show that economic development continues to rely on fossil energy consumption, which negatively impacts the low-carbon transition of energy. Given China's complex geographical conditions, it is crucial for different provinces to develop their own strategies for renewable energy development, taking into account unique resources and challenges. [ABSTRACT FROM AUTHOR]

Battery electric industrial vehicles (BEIVs) offer significant environmental protection and decarbonization potential for rapidly growing logistics and transportation sectors in China. However, the limited driving range remains a major obstacle to the widespread adoption of BEIVs. Eco-driving is an effective solution that can improve energy efficiency and extend the driving range of vehicles by controlling driving behavior and speed. Therefore, this paper introduces an energy efficient speed planning method for BEIVs, in which data-driven models are developed to estimate energy consumption. Real-world driving data collected from a BEIV are used to model the energy consumption by curve fitting, random forest, and LSTM. The speed planning process is considered a Markov Decision Process, which is solved using Dynamic Programming and Q-learning, respectively. The case study of a battery electric forklift shows that speed planning can reduce energy consumption by 13%–27% compared to time-optimal speed, while only increasing the driving time by 10%–20%. • Energy efficient speed planning methods for electric industrial vehicles are proposed. • The speed planning method uses data-driven vehicle energy consumption models. • The energy consumption models are developed using random forest and LSTM. • The speed planning problem is formulated as a Markov decision process. • The speed planning problem is solved by Dynamic Programming and Q-learning. [ABSTRACT FROM AUTHOR]

• Fatigue effect of the PHF is dependent on the time scale of pulsating loading. • Coal porosity increases with the increased pulsating pressure based on the LF-NMR. • A larger pulsating pressure leads to a lower cracking pressure. • The PHF creates more cracks and higher porosity than the HF according to CT images. Coalbed methane recovery can largely ease the crisis of annually increasing energy consumption of China. Low permeability and porosity of deep coal reservoirs mainly cause the low gas production rate. Pulsating hydraulic fracturing (PHF) is an alternative tool to improve the reservoir permeability and stimulate the gas productivity. However, little has been done to directly observe the fatigue damage in coal created by the pulsating loading. Because the fatigue damage is primarily governed by the time-length of PHF period. Therefore, the effect of long period pulsating loading of PHF on coal damage has been investigated in this work. Results show that long-period pulsating loading of PHF can cause significant damage in coal. The low-field NMR data indicates coal porosity increases with the increase of maximum pulsating pressure. Pulsating pressure also plays an important role in the cracking pressure. A larger pulsating pressure leads to a lower cracking pressure. Comparison of PHF and HF damaged coal investigated by the X-ray CT indicates the PHF creates more fractures and higher porosity than conventional hydraulic fracturing. The increase ratios of the coal porosity by HF and PHF are 40 %–60 % and 80 %–100 %, respectively. This paper provides a better understanding the mechanism of the coal damage by the PHF under long-period pulsating loading which is of great importance for optimizing PHF technique and generating connected fracture networks. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) play a pivotal role in natural water recycling and safeguarding the water security of approximately 42% of the world's population, yet they confront challenges posed by escalating energy consumption and regional energy constraints. In this study, we developed an evaluation framework that integrated regional energy scarcity with the operation conditions of WWTPs to quantify their energy efficiencies by applying multiregional input–output (MRIO) analysis and data envelopment analysis (DEA). A case study using this framework was conducted on 3776 WWTPs in 30 provinces in China. The results showed that the average scarcity-based energy efficiency level of WWTPs in China was low, of which those in northern provinces were higher compared to southeastern provinces. Furthermore, only 24 WWTPs in China attained the highest efficiency levels, while the rest had different degrees of input redundancy, indicating an energy-saving potential of 9.05 × 109 kWh. This paper enables the development of optimal efficiency strategies for WWTPs in different provinces considering the potential energy scarcity risks caused by trading activities. • The DEA and MRIO analyses were combined for 3776 WWTPs in China. • Efficiency evaluation index was modified considering energy scarcity levels. • Scarcity-based energy efficiency assessment framework for WWTPs was developed. [ABSTRACT FROM AUTHOR]

Over the past decades, China's vast regional disparities in resource endowment, economic development, and industrial structure have driven large-scale relocations of high energy-consuming industries (RHEIs). Despite extensive research on broad-based industrial relocation and emission transfer, the trend, structure and environmental impact of China's RHEIs need further investigation. This paper employs the multi-regional input-output model (MRIO) to calculate the trend, scale, and structure of the RHEIs among China's 30 provinces. Additionally, we investigate the RHEIs' effect on green total factor energy efficiency (GEE) and its heterogeneity. Our results indicate that the net inflow of high energy-consuming industries decreases GEE, with a more noticeable effect observed in central provinces and after the execution of the Belt and Road Initiative (BRI). However, the positive effect of RHEIs on GEE in outflow areas is more substantial than their negative impact in inflow areas, suggesting that RHEIs can enhance overall efficiency. This study contributes to the understanding of China's industrial relocation by providing valuable insights into China's RHEIs. • China has a large-scale relocation of high energy-consuming industries. • The relocation of China's high energy-consuming industries is calculated. • The relocation's impact on green total factor energy efficiency is analyzed. • Regional heterogeneity is found among different provinces. [ABSTRACT FROM AUTHOR]

Based on the super-SBM model, this paper studies the agricultural energy efficiency of five provinces in China from 2004 to 2015. In addition, the Malmquist index is used for dynamic analysis of agricultural energy efficiency and to identify drivers of these changes. The results show that: (1) The inland provinces have lower agricultural energy efficiency than the wealthy eastern coastal provinces; (2) Technological progress is the most important factor affecting efficiency changes, and the provinces with lower efficiency are more likely to achieve greater improvements; (3) The energy efficiency of the provinces that are agricultural intensive areas is relatively low. Therefore, adjusting the agricultural production structure and emphasizing diversified agriculture will help improve the energy efficiency of agriculture. At the same time, it is necessary to strengthen agricultural cooperation among different provinces to jointly improve agricultural energy efficiency. [ABSTRACT FROM AUTHOR]

The equipment manufacturing industry is not only a high-carbon industry, but also an important export industry in China. There is a close relationship between the export growth of China's equipment manufacturing industry and its carbon emissions. Based on this, this paper focuses on the equipment manufacturing industry, and establishes a Tapio model to combine the decoupling theory with export carbon emissions. Meanwhile, the relative advantages and disadvantages of the eight decoupling modes are evaluated and determined. Then, the decoupling elasticity index and the decoupling grade index are used to analyze the carbon emissions of China's equipment manufacturing industry and its seven sub-sectors. The study implies that, from 2000 to 2018, the relationship between the overall carbon emissions of the equipment manufacturing industry and export growth was decoupling, and most of the sub-sectors were basically in the state of strong decoupling or weak decoupling. Therefore, the two decoupling optimization paths, which are increasing economic growth and decreasing energy consumption, are designed here to further improve the decoupling effect between the export growth of China's equipment manufacturing industry and its carbon emissions. [ABSTRACT FROM AUTHOR]

Windows are responsible for the largest amount of energy loss related to building envelope. Past studies on the energy consumption of windows have mainly focused on residential and commercial buildings, while few studies have explored the energy consumption of windows in educational buildings. The sizes and locations of classroom windows affect not only the building energy consumption but also the indoor environment quality, which is an issue that needs to be balanced. This paper takes a classroom in Guangzhou as the object. Under the premise of meeting the lighting standards of the classroom, two parameters—window height and sill height —were simulated in different corridors of north–south and east–west classrooms to analyse the impact of their changes on the indoor environment as well as energy consumption based on the parametric platform Grasshopper and its plug-ins Ladybug and Honeybee. The energy consumption of a number of fenestration combinations on both sides of the classroom was optimized automatically by genetic algorithm, and the sizes and positions of windows that benefitted energy savings were obtained. In the best case ~16.6% of energy consumed in a whole year can be saved compared with the worst case. This conclusion can provide a quick decision-making process for the design of window shapes for the purpose of energy savings in the early design stage of educational buildings in the Pearl River Delta such that energy savings can be quickly and clearly guaranteed in the subsequent window configuration. [ABSTRACT FROM AUTHOR]

Under the background of "carbon neutrality" and "carbon peak" concepts, China desires to develop a new power system based on renewable energy sources (RES), which will be the primary energy support in prospective China. Thus, it is imperative to improve the peak shaving capability of power system to address the problem of random fluctuation and intermittency of RES by developing various energy storage systems. An innovative approach to enhance the flexibility of the conventional thermal power unit (TPU) through the utilization of flywheel energy storage array (FESA) is presented, simulated, and evaluated in this paper. Using the relatively practical and specific model of TPU and FESA, modified frequency modulation and automatic generation control (AGC) instruction tracing operation scenario models are constructed. A comprehensive control strategy of FESA and a well-designed operation coordinated control method for TPU with FESA are proposed and applied. The simulation results are distinctively processed and evaluated by the methods in "two documents", aiming to assess the real-world operation performance of the model proposed in this paper. The comprehensive analysis of the indicators demonstrates that the FESA can improve the flexibility and economy of the units. This research may guide the usage of FESA to improve the operational flexibility of TPU. • Composition and Control Methods of the flywheel energy storage array are provided. • A coordinated control scheme for the thermal power unit with flywheel energy storage array is proposed. • Frequency modulation and AGC instruction tracking scenario models are constructed and simulated. • AGC regulation indicators are conducted and analyzed to evaluate the unit's performance. [ABSTRACT FROM AUTHOR]

The operation of tidal pumping station has an energetic impact on energy course of massive water pumping for a long time. Thus, a multi-objective optimal operation model was developed to optimize the operation scheme and reduce the energy consumption of the tidal pumping station. In the model, a day is divided into several sub-periods according to the regulation of water level in tidal reach. The partition of sub-periods, the number and blade angle of operating units in each sub-period are adjusted to minimize daily operation energy consumption. And the less switching times, the better the reliability and durability of the unit, the lower the failure rate. Therefore, the reduction of wearing parts' service life is quantified for each switching time in the form of cost. A case study is performed with the tidal pumping station of the South-to-North Water Transfer Project in China. In this paper, energy consumption and switching times are quantified as costs respectively, and the result shows that the daily energy consumption could be saved about 2.28%–6.56%, and the switching times reduced at least 60%. Therefore, this paper could provide an effective optimal operation scheme for the tidal pumping station whose operation is affected by tides. [ABSTRACT FROM AUTHOR]

Addressing energy poverty and promoting energy equity are crucial for China to eradicate poverty comprehensively and achieve shared prosperity. Through a combined dynamic evaluation approach to accurately measure the extent of energy poverty, this paper analyzes the staged time series, spatial distribution characteristics of energy poverty applies the Dagum Gini coefficient and variance decomposition to observe the imbalance characteristics of energy poverty and identify the sources of variation. The objective of this paper is to mitigate the influence of spatial disparities on coordinating efforts to eradicate energy poverty across different regions. Consequently, provides valuable insights for decision-making to effectively eradicate energy poverty and expedite the achievement of energy equity. The results indicate: The reduction process of energy poverty in China exhibit phased characteristics from 2000 to 2020, with significant variations in reduction levels among provinces. Different sources of energy poverty exhibits imbalanced spatial distribution and evolution. The overall disparity in energy poverty widens as the phases progress, with characteristic nodes experiencing a temporal delay of 2–3 years compared to the policy nodes. Inter-regional disparities are the primary spatial source of energy poverty differences, while energy use capacity is the main factor contributing to variation. [ABSTRACT FROM AUTHOR]

This paper studies the impact of the development of green finance on China's energy consumption structure. 17 basic indexes and the improved entropy weight method are used to construct the green finance index (GFI). Multiple regression, panel regression, and spatial regression are used to study the impact of green finance on China's traditional energy and renewable energy consumption. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. The green finance in each province not only helps the local development of green energy but also plays a good role in the production and utilization of clean energy consumption in surrounding provinces. Therefore, the government should support the green finance, reduce traditional energy consumption, and increase renewable energy consumption. [ABSTRACT FROM AUTHOR]

The development of the energy economy in Northeastern China is unbalanced. In this paper, some energy structures such as oil, coal, and electricity are chosen as input indexes, while per capita gross domestic product (GDP) and total retail sales of consumer goods are desirable output indexes. The main causes of haze are industrial waste gas emission, industrial wastewater discharge, and solid waste production, which are regarded as undesirable output indexes. Environmental variables include industrial structure, urbanization, per capita GDP, and government planning. The proportion of the tertiary industry's output value to its total output value is one of the important indexes to measure economic development in one area. Therefore, industrial structure plays a vital role in a region's economic development. The tertiary industry oriented by service sector is the main force to promote economic transformation. The development of the urban economy will change from high to low as the process of urbanization, which can be characterized by green coverage of the urban built-up area. The higher per capita GDP, the higher the economic development can be achieved. Government planning refers to the total number of construction projects and completed projects in the year the government takes measures to control pollution. It shows that the total factor productivity of energy green efficiency has been stable in the last decades but fluctuated wildly in special periods, in which technical progress has played a great role, as well as the increase of technical efficiency. [ABSTRACT FROM AUTHOR]

An efficient and equitable allocation scheme for renewable portfolio standard (RPS) quota is of great significance to renewable energy (RE) development and the improvement of the electricity trade market. This study establishes a quota allocation model based on the lowest cost of RE generation to determine the RPS targets (LC-RPS) of 30 Chinese provinces. Subsequently, an index system based on energy consumption, RE resource endowment, historical responsibility, and transmission facilities is constructed to determine the RPS targets (IN-RPS). Finally, the two scenarios mentioned above are compared with the RPS target allocation scenario published by the Chinese government (GM-RPS) and with the NO-RPS scenario. The results show that: Compared with those of GM-RPS and IN-RPS, the power generation cost associated with the LC-RPS is reduced by 8.5% and 49.4%, respectively, and the unit power generation cost is reduced by 9.4 and 39.7 RMB/MWh, respectively; the fairness of the LC-RPS is marginally worse than that of the other three scenarios, but the fairness of the power generation cost is still relative average, thereby demonstrating distribution fairness. This paper appeals to the Chinese government for the perfection of a national renewable energy certificates (REC) trade market and offering additional REC for solar generation. •Least-cost quota (LC-RPS) and index system allocation schemes are proposed. •The renewable energy (RE) generation capacity of 30 Chinese provinces is determined. •The power generation cost of the LC-RPS is reduced compared with other schemes. •The LC-RPS scheme is more efficient and meets national RPS targets. •The generation resources are diversified with the improvement of the national REC trade market. [ABSTRACT FROM AUTHOR]

During the construction of tunnels in the central and western regions of China, diorite is frequently affected by vibration, blasting and water which will lead to the questions of the quality and operational safety of project. However, there are few studies on the dynamic characteristics of diorite under the action of dry–wet cycles. Therefore, this paper selected the gray–green altered diorite from Ning shan County, Shaanxi Province, China, mainly composed of plagioclase, and used the Slit Hopkinson pressure bar (SHPB) to study the effect of dry–wet cycle on the dynamic characteristics of Diorite. The test results show that the strength decay rate of the peak strength of diorite is the maximum under 1–3 dry–wet cycles, then decreases gradually. The dynamic elastic modulus of diorite dropped by 35.02% after three dry–wet cycles, accounting for 98.45% of the total attenuation. Compared the test result of three dry–wet cycles, the decrease volumes of the stress growth rate of diorite are the largest after six dry–wet cycles. Because of the actions of the dry–wet cycles, the growth rate of the rapid growth stage of the reflected energy–time history curve reduces and the growth rate of the rapid growth stage of the transmitted energy–time history curve improves. Under the action of the dry–wet cycles, the dissipation energy ratio gradually decreases, and the decrease of energy consumption density follows a negative exponential function relationship. Under the action of multiple dry–wet cycles, the tension and compression stress frequently change between the particles of rock, resulting in a significant increase of micro-cracks and an obvious degradation effect on the dynamical properties of diorite. [ABSTRACT FROM AUTHOR]

Recently, the application of building information modeling (BIM) in building energy efficiency design programs has been emphasized in research. In China, faced with requirements in building energy efficiency design standards and specifications, researchers have been using BIM as a platform for breaking up bottlenecks in energy simulation and design software, and BIM is considered the key to improve the efficiency of building energy efficiency design. Firstly, based on the trade-off energy consumption judgment method proposed in the 'Public Building Energy Efficiency Design Standard (GB50189-2015)', this study combines the BIM platform with an orthogonal simulation design adopting an experimental building construction project in a cold region of China, to thereby study the influences of different envelope structural parameters on cooling and heating loads. Then, this study analyzes the continuity and consistency of data exchange between different BIM-related software, through the modeling software Revit and the sustainable analysis software Ecotect. Finally, through the experiment, the critical factors of the optimized design of the building envelope are investigated and applied for the optimized design of the building thermal system. In addition, this study uses BIM to complete an energy efficiency design for a laboratory heating, ventilation and air conditioning (HVAC) system. According to the experimental results, the following conclusions can be drawn: this study proposes a BIM-based optimized design method of building thermal system, which complies with various Chinese building energy efficiency standards and polices and can be used as a reference for Chinese designers. Also, the issues and challenges in building consumption simulation based on BIM technology and the application of BIM technology in the design of building thermal HVAC systems are discussed, and the development trends of BIM technology in China are analyzed. Building thermal system and HVAC system design are the key points of building efficiency design. The optimized design method proposed in this paper is of great significance to this system design. The optimized design method can improve the design efficiency of designers while complying with China's standards and policies. Therefore, it can save costs, improve the economic benefits of the projects and, at the same time, obtain an ideal building efficiency design. [ABSTRACT FROM AUTHOR]

China has set a goal to achieve peak CO2 emissions before 2030 and carbon neutrality by 2060. To achieve the goals of carbon peak and carbon neutrality, China needs to address the challenge of the large and still growing CO2 emission base. This paper investigated the energy consumption and CO2 emission in Beijing from 2020–2035 based on the energy elasticity coefficient and contribution value of the sub-energy increment (CVSI) method. Beijing is one of the first cities in China to propose the "carbon peak" target as of 2020. From 2020 Beijing will strive to achieve the goal of carbon neutrality. The results show that in 2035 the CO2 emission in Beijing may drop to 50% of 2020. This decline would be affected by economic growth, energy efficiency and the proportion of renewable energy use. Beijing's energy supply mainly comes from outside the region. Therefore, for Beijing, in addition to increasing the proportion of renewable energy sources outside the region, its own energy acceptance also needs to be strengthened, including strengthening energy storage construction, actively researching and promoting carbon capture and utilization of gas-fired units, which are effective ways to achieve carbon neutrality target. [ABSTRACT FROM AUTHOR]

Ecological deterioration, air pollution, and resource depletion have shrouded the vast regions of China, raising widespread concerns about the sustainable development of the domestic economy. Although financial agglomeration has become a pivotal approach for China to realize green transformation, there is a lack of evidence against the causal correlation between financial agglomeration and sustainable development of the regional economy. To fill this gap, using the data of 29 provincial capital cities in China spanning from 2009 to 2019 and adopting individual time bidirectional fixed effect model, IV-GMM approach, and alternative modeling techniques, this paper investigates the impact of financial agglomeration on sustainable development of the regional economy for the first time. The results indicate that there is a significant positive correlation between financial agglomeration and the sustainable development of the regional economy. Financial agglomeration facilitates the improvement of regional energy efficiency, and the latter further mediates the relationship between financial agglomeration and sustainable development of the regional economy. In addition, the empirical results also demonstrate that the higher the economic policy uncertainty, the weaker the positive relationship between financial agglomeration and energy efficiency. The present study is of great significance for China to implement energy-saving and emission-reduction tasks and achieve sustainable urban construction. [ABSTRACT FROM AUTHOR]

Coal-fired heating, mainly used in North China, has caused serious environmental problems. Schemes to replace coal have been established, but they are not suitable for all scenarios. This paper proposes a heating scheme that uses a methanol heating stove (MHS) to meet the demand for clean, low-cost rural heating. The economy, emissions, and energy consumption of the MHS were analyzed. The scheme was compared with five common rural heating methods. The effects of the methanol price, power grid transformation, and gas pipeline construction on the annual cost of each heating scheme were investigated using a theoretical model. The MHS emitted 66 % less CO 2 and 95 % less SO 2 and NO x and consumed 54 % less standard coal than bulk coal heating stoves. The low electricity supply required to vaporize methanol contributed to the cost and emission reduction. Methanol price fluctuations warrant government subsidies to incentivize the implementation of the scheme. For increased adoption, we recommend that the MHS be used in areas with low population densities and methanol prices. This approach can therefore be an ideal substitute for "coal-to-electricity" and "coal-to-gas" methods in areas that lack access to power or gas supplies and can replace air-source heat pumps in severe cold zones. [ABSTRACT FROM AUTHOR]

The article discusses an environmental research paper entitled "China's Growing CO2 Emissions--A Race between Increasing Consumption and Efficiency Gains." The paper examines the key drivers behind China's growing energy consumption using data compiled by the Chinese government, finding that CO2 emissions rose more than 50% between 1992 and 2002.

Water scarcity problem has become a major constraint in energy development. In this paper, we calculated virtual water flows and virtual water scarcity risk transfers driven by interprovincial energy consumption in China using multi-regional input–output analysis. The results of virtual water scarcity risk transfers show that major virtual water scarcity risk importers will be the "victims" suffering the consequences of increasing virtual water scarcity risks in the national energy system. For major virtual water scarcity risk exporters, they will transfer virtual water scarcity risks to downstream provinces along energy supply chains, threatening the stability of the national energy system. The promotion of energy policies and the energy consumption of developed regions make the water-deficient northwest regions export a large amount of water resources to the east and south regions. Therefore, it is necessary to fully consider local water scarcity and evaluate the impact on water environment before the construction of energy bases. Our findings can be used to provide a reference value for policymakers to develop new energy strategies and manage water resources sustainably. [ABSTRACT FROM AUTHOR]

Logistics is the booster of economic development, and it is imperative to further improve the logistics energy efficiency and adjust its development model. This paper is an attempt to investigate the logistics energy efficiency and main influencing factors of the Yangtze River Economic Belt, which is the most economically intensive region that spans East, Central, and West China. The input-oriented SBM-DEA model is employed to identify factors such as energy input, undesirable output, and service capacity output as well as the logistics energy efficiency of Yangtze River Economic Belt. Energy efficiency is then further decomposed into pure technical efficiency, scale efficiency, and technical efficiency, from the perspective of which provinces and cities are compared. The research results show that the logistics energy efficiency of Yangtze River Economic Belt needs to be further improved and that energy efficiency differs greatly among cities and provinces, indicating that the development is quite unbalanced in different areas. Therefore, the local government should develop development strategies according to the main influencing factors and constraints to the local logistics industry, so as to optimize and upgrade the energy structure of the logistics industry. [ABSTRACT FROM AUTHOR]

This paper aimed to optimize working quality and reduce energy consumption of the feeding and shearing device of the silage harvester by making a comprehensive analysis and experiment on the longitudinal compressing and shearing properties of the silage corn stalks. The main factors affecting the shearing energy consumption were obtained by compressing and shearing tests on internodes and nodes of silage corn stalk. The results of three-level and three-factor central combination experiments showed that the overall shearing energy consumption for nodes was much higher than that for internodes. Compressing the silage corn stalk to some extent before shearing at the loading direction of 0° and lower shearing speed was beneficial to saving energy. [ABSTRACT FROM AUTHOR]

This paper discusses the current development strategy, technology and industrialization of China's hydrogen energy industry in the transportation field, summarizes the characteristics and development experience, and makes a comparative study with the situation of some developed countries. The results show that the current development of hydrogen energy has formed a broad consensus in China and is becoming the overall development of China's national level consciousness. However, China's hydrogen energy industry is still facing problems such as high cost of comprehensive utilization, imperfect standards and regulations for hydrogen energy utilization, obvious tendency of industrial blind development and structural overcapacity risk. Therefore, some policy suggestions were proposed for the future development, such as strengthening top-level design, strengthening pilot demonstration, promoting the development of the whole hydrogen industry chain, and reducing the cost of hydrogen and fuel cell vehicles in the field of transportation. [Display omitted] • The development of hydrogen energy industry has become China's national consensus. • China has formed three major industrial clusters of hydrogen and fuel cells. • China's hydrogen industry is facing the risk of overcapacity. • China should strengthen the top-level design of hydrogen development strategy. [ABSTRACT FROM AUTHOR]

China accounts for more than 22% of the total energy consumption worldwide. Building energy consumption, among which consumption in public buildings was about 40% took the second place. With the problems of high energy waste, error rate and complexity of the control systems available, an indoor intelligent lighting system based on occupants' location is proposed in this paper to improve the energy efficiency of the current lighting systems indoors. The transmission model of electromagnetic wave in free space is optimized in both aspects of reference signal strength and attenuation coefficient radiation in complex environment dynamically based on which occupants' positions are obtained. The smart lighting system will turn on or off corresponding lights adaptively to provide a more energy efficient platform. Experimental results show that the proposed system is able to improve the energy efficiency of indoor lighting by at least 15%, with a lower error rate below 2% compared with the existing lighting systems based on voice control. [ABSTRACT FROM AUTHOR]

In recent years, the issues related to carbon emissions and environment have attracted extensive attentions. Considering four scenarios (the energy conversion, energy capital savings and loans, energy exports and cement production carbon emissions), this paper adopts the energy consumption method and input-output method to analyze China's carbon emissions structure on the supply-side and demand-side of energy, and finally provides policy recommendations for China's structural emission reduction. The results show that, if the four influencing factors were not considered, the measurement of carbon emissions from the final demand was 44.91% higher than the baseline scenario, 12.36% lower than the baseline scenario from intermediate demand, and 10.23% lower than the baseline scenario from the total. For China's carbon emissions structure on the supply-side of energy, the carbon emissions from high-carbon energy, represented by raw coal, accounted for 66.805% of the total energy-related carbon emissions, while the carbon emissions from low-carbon energy, represented by natural gas, only accounted for 2.485%. For China's carbon emissions structure on the demand-side of energy, the carbon emissions from intermediate demand (enterprise production) accounted for more than 95% of total energy-related carbon emissions, while the carbon emissions from final demand (residents and government use) accounted for less than 5%. For each specific industry in intermediate demand for energy, the heavy industry, electric power, fossil energy, and chemical industry have high carbon emissions and low carbon emissions efficiency. However, the agriculture, construction, light industry, and service are the opposite. Finally, we provide policy recommendations for improving the accuracy of carbon emissions measurement and carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

The development of regional industry in China has become one of the significant factors affecting energy efficiency. This paper combined the industry agglomeration theory and the improved Stochastic Impacts model to explore the impact mechanism of producer service industry agglomeration on energy efficiency. We applied spatial econometric model to estimate the spatial effects of the agglomeration on energy efficiency with panel data of 31 provinces from 2008 to 2017 in China. The results showed that China's inter-provincial energy efficiency has a significant spatial spillover effect. Simultaneously, the specialized agglomeration and diversified agglomeration of producer services have a "U"-shaped effect on energy efficiency. Finally, we need to pay attention to the coordination and synchronization of the specialized agglomeration and diversified agglomeration of the producer service industry. An increase in the relative gap between the two can inhibit energy efficiency, but its inhibitory effect gradually weakened. [ABSTRACT FROM AUTHOR]

Clean energy has become one of the more broadly acceptable options for the future transformation of existing energy systems. The energy transformation also requires comprehensive preparatory actions. Organizing a multi-chain clean energy value chain into a complex clean energy network system is likely to be critical to the successful utilization of clean energy in the future. This article proposes a novel concept for a clean energy value co-creation system covering the entire clean energy value chain with division on power generation, energy storage, and end utilization sections. This article mainly analyzes the self-organizing evolution mechanism and value co-creation of the clean energy value co-creation system (CEVCS), which is therefore critical to the further development of the renewable energy industry. First, this article analyzes the connotation and basic structure of CEVCS and introduces the self-organizing characteristics of CEVCS. Second, the self-organizing evolution mechanism of CEVCS is discussed, which is analyzed from four aspects: evolutionary power, evolutionary path, evolutionary form, and evolutionary process. Third, this paper analyzes the information cooperative evolution process of CEVCS, defines the value order parameter, and studies how the constituent elements of CEVCS realize value creation through a synergy mechanism based on the theory of synergy. Then the dissipative structure model and information resource collaborative model of CEVCS are presented. Finally, the conclusions are given in the end. The proposed CEVCS concept would support the effective operation of the clean energy value chain within municipalities by establishing virtual energy cooperatives aimed at meeting energy needs and supporting community development. [ABSTRACT FROM AUTHOR]

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China's urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 2001-2014, for the first time, we investigate the degrees and determinants of China's urban residential energy demand and energy rebound effect. The results show that residents' income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents' income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China. [ABSTRACT FROM AUTHOR]

The living energy consumption of residents has become an important technical index to promote the economic and social development strategy. The country's medium- and short-term living energy consumption is featured with both a certainty of annual increment and an uncertainty of random variation. Thus, it can be seen as a typical grey system and shall be suitable for the grey prediction model. In order to explore the future development trend of China's per capita living energy consumption, this paper establishes a novel grey model based on the discrete grey model with time power term and the fractional accumulation (FDGM (1, 1, tα) for short) for forecasting China's per capita living energy consumption, which makes the existing model to adapt to different time series by adjusting fractional order accumulation parameter and power term. In order to verify the feasibility and effectiveness of the novel model, the proposed and eight other existing grey prediction models are applied to the case of China's per capita living energy consumption. The results show that the proposed model is more suitable for predicting China's per capita energy consumption than the other eight grey prediction models. Finally, the proposed model based on metabolism mechanism is used to predict China's per capita living energy consumption from 2018 to 2029, which can provide a reference for energy companies or government decision makers. [ABSTRACT FROM AUTHOR]

Renewable energy has been considered as an effective way to solve environmental pollution and energy crisis in China. However, the development of renewable energy sector depends on economic growth and financial issues. Thus, it is significant to study the relationships of these three indicators in China. Using ARDL-PMG model, this paper explores the long-run and short-run impacts of economic growth and financial development on renewable energy consumption based on the panel data during period 1997–2017 at national and regional levels of China. The long-run relationships indicate that for China as a whole and western China, economic growth stimulates renewable energy consumption while financial development impacts it negatively. However, the short-run relationships show that economic growth and financial development influence renewable energy consumption negatively and positively, respectively. Moreover, we employ the Granger causality test to study the existence and direction of causality among variables. The causality test results display that the unidirectional causality relationships exist from financial development to renewable energy consumption for China as a whole and eastern China. Meanwhile, economic growth unidirectionally causes renewable energy consumption in China as a whole, eastern and western China. Our empirical results provide some policies to promote the development of renewable energy sector. • Dynamic impacts of financial development and economic growth on renewable energy use are studied. • The causalities among financial development and economic growth and renewable energy use are explored. • Our study was conducted at both national and regional levels using panel data models. • Financial development impacted renewable energy use negatively in the long run. • A unidirectional causality ran from renewable energy use to financial development. [ABSTRACT FROM AUTHOR]

This paper analyzes the time-varying impacts of Chinaʼs economic growth, energy efficiency, and industrial development on carbon dioxide (CO2) emissions from 1970 to 2019. First, we examined and found that there are two significant structural changes in the CO2 sequence over the years, and there was a significant nonlinear relationship among the four. The first nonlinear structural model constructed is the TVP regression model. According to the Bayesian model comparison criterion, TVP-SV-VAR was selected as the second constructed model from four types of VAR models containing nonlinear structures. The results show that the conduction intensity value of energy use efficiency to CO2 emissions has increased year by year, from 0.45 in 1971 to 0.97 in 2019. The short-term transmission mechanism of energy use efficiency to carbon emissions is the most significant. The conduction intensity of Chinaʼs economic growth on CO2 emissions increases year by year. Chinaʼs economic growth plays a major role in long-term CO2 emission reduction. The impact of industrial development on CO2 emissions reached a peak of 0.34 in 1977, and the intensity of the impact has basically stabilized at 0.26. [ABSTRACT FROM AUTHOR]

At this critical junction of industrialization, China is facing an increasingly prominent imbalance between energy supply and demand. It is of great social significance to study the energy-saving of buildings that consume a huge amount of energy. For most heating systems, energy waste mainly arises from inefficient operations of boilers, low efficiency of pipe transmission, and poor quality of heat supply. This paper researches and evaluates the energy-saving reconstruction of intelligent community heating (ICH) system based on the Internet of things (IoT). Firstly, the energy-saving reconstruction of the ICH system was analyzed, and a hydraulic regime model was derived from the simplified model of the water supply and return pipe networks. Then, the system pipe network was investigated in three aspects, namely, node flow balance, pipeline pressure drop balance, and loop pressure drop balance. On this basis, the authors presented the balance equation and finalized the hydraulic regime model of the system. After that, the energy consumption of the system was evaluated before and after the reconstruction, and the energy-saving benefit was predicted. The effectiveness of the proposed method was proved through experiments. [ABSTRACT FROM AUTHOR]