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Currently, emerging as well as industrialized countries are transitioning toward adopting clean energy sources because of increased environmental calamities. Additionally, the rapid increase in population has improved global food production and demand. Nevertheless, the environmental consequences of food production and water investments have received limited attention from scholars. The present research investigates China's environmental determinants between 1988 and 2022. This study uses three parametric approaches (fully modified ordinary least squares [FMOLS], dynamic ordinary least squares [DOLS], and canonical cointegrating regression [CCR]) for the primary model assessment. However, this research also employed the least squares method with breaks and quantile regression to account for structural breaks and nonnormality issues. The predicted outcomes asserted that economic expansion and investment in water significantly improve the carbon emissions level in the country. However, enhanced food production and clean energy adoption improve environmental sustainability and the probability of achieving COP27 targets by reducing emissions. The outcomes are robust and reliable based on the given literature. Based on the outcomes, this research recommends improved investment in research and development, increased renewable energy production, and strong policies for decoupling economic growth from emissions via clean energy. [ABSTRACT FROM AUTHOR]

To gain a deeper understanding of the intrinsic dynamic relationship between energy consumption and economic growth in China. This study employs panel cointegration and causality models, utilizing the SYS-GMM technique to assess the factors influencing economic growth in China's green finance sector from 2002 to 2022. The research explores the interactions among multiple variables related to the Chinese economic context, including economic growth, carbon dioxide emissions, total natural resource rents, energy consumption, and environmental impact. While considering key factors that may cause structural disturbances in the time series analysis. The findings indicate the existence of long-term cointegration relationships among these variables, with positive correlations between economic growth and total natural resource rents, energy consumption, energy quantity, and ecological footprint. Results also show a bidirectional causal relationship between carbon dioxide emissions and energy consumption and a unidirectional correlation between energy consumption and GDP growth. Additionally, energy intensity (EI) improvements supported by green finance are linked to a significant reduction in CO2 emissions, with a coefficient of -1.933 (p < 0.05), underscoring the role of technological innovation. Further evaluations suggest that investments in renewable energy can promote economic growth, create job opportunities, and reduce greenhouse gas emissions. Energy-saving measures and green finance-supported technological innovations play crucial roles in improving energy intensity and reducing CO2 emissions. The study also underscores the importance of economic diversification to reduce dependence on natural resources and enhance economic stability. Future research should further explore the economic feasibility and environmental benefits of emerging technologies such as Carbon Capture and Storage (CCS), providing deeper insights into sustainable energy practices. [ABSTRACT FROM AUTHOR]

Net radiation (Rn), a critical component in land surface energy cycling, is calculated as the difference between net shortwave radiation and longwave radiation at the Earth's surface and holds significant importance in crop models for precision agriculture management. In this study, we examined the performance of four machine learning models, including extreme learning machine (ELM), hybrid artificial neural networks with genetic algorithm models (GANN), generalized regression neural networks (GRNN), and random forests (RF), in estimating daily Rn at four representative sites across different climatic zones of China. The input variables included common meteorological factors such as minimum and maximum temperature, relative humidity, sunshine duration, and shortwave solar radiation. Model performance was assessed and compared using statistical parameters such as the correlation coefficient (R2), root mean square errors (RMSE), mean absolute errors (MAE), and Nash–Sutcliffe coefficient (NS). The results indicated that all models slightly underestimated actual Rn, with linear regression slopes ranging from 0.810 to 0.870 across different zones. The estimated Rn was found to be comparable to observed values in terms of data distribution characteristics. Among the models, the ELM and GANN demonstrated higher consistency with observed values, exhibiting R2 values ranging from 0.838 to 0.963 and 0.836 to 0.963, respectively, across varying climatic zones. These values surpassed those of the RF (0.809–0.959) and GRNN (0.812–0.949) models. Additionally, the ELM and GANN models showed smaller simulation errors in terms of RMSE, MAE, and NS across the four climatic zones compared to the RF and GRNN models. Overall, the ELM and GANN models outperformed the RF and GRNN models. Notably, the ELM model's faster computational speed makes it a strong recommendation for Rn estimates across different climatic zones of China. [ABSTRACT FROM AUTHOR]

High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method's accuracy showed significant improvements, with determination coefficients (R2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies. [ABSTRACT FROM AUTHOR]

The targets of energy conservation, decarbonization, and industry reinvigoration have significantly influenced the design of China's new energy vehicle (NEV) industrial policies and nationwide electrification. As a monumental policy framework for energy transition in transportation sector, the NEV industry development plan plays an influential role in promoting cleantech diffusion and enhancing NEV competitiveness. This study employs an event study method to investigate the stock market reaction to the NEV plan shocks. The NEV plan announced in 2020 receives a markedly positive stock price effect of 3.72% in the 6-day event window. Heterogeneity tests on subsamples indicate that state-backed entities exhibit a similar effect to the total sample, while the automotive manufacturing class and original equipment manufacturers see a significantly higher market value gain of 6.56% and 13.34%, respectively. However, battery manufacturers, as one of the key participants in the NEV value chain, experience an insignificant stock price effect. This study documents the financial consequences of clean energy policies specific to the emission-intensive automotive manufacturing sector, highlights the effectiveness of government-to-investor signalling in a cleantech diffusion context, and reveals the implications to other economies seeking to deploy clean transport and enhance environmental sustainability. The national NEV industry development plan aiming at the energy transition of the transportation sector can incur outperformance of NEV stocks in the financial market. Different stock market performances between NEV plans manifest investor preference for market-oriented industry policies. The long-term policy framework for green industry transition can send positive signals to investors, guide capital reallocation, and direct investment flows into key financial assets. The implications from the Chinese market offer valuable insights for other countries in formulating concrete industry planning, transition agendas, and binding targets for climate change mitigation. [ABSTRACT FROM AUTHOR]

This paper constructs a unique dataset of clean energy and collects firm-level green innovation data that matches it with provinces and cities. Then, this paper executes quasi-natural experiments on green innovation to examine the effects of China's emission trading policy on green innovation. Further, this paper introduces the interactive terms of the pilot time and pilot area dummy variables into the spatial Durbin model (SDM) and spatial dynamic panel model (SDPM) to construct quasi-natural experiments to examine the spatial effect. The findings confirm a negative association between the 'policy treatment effect' and green innovation. The results also indicate a significant negative association between the emissions trading policy and clean energy. Besides, the empirical results reveal a positive correlation between clean energy and green innovation; clean energy promotes green innovation in the region and the surrounding areas. This paper complements existing research and provides empirical evidence and policy implications for developing clean energy, promoting green innovation, and improving the emission trading policy. [ABSTRACT FROM AUTHOR]

The potential of clean energy is constrained by various social, environmental, and technological challenges. The current work is likely the first to observe the influence of economic complexity on production-based carbon emissions to develop clean and sustainable energy solutions that address climate change apprehensions. The study examines the impacts of clean energy, economic complexity, public service transportation, and improving technology on production-based carbon emissions. This study employ the novel dynamic autoregressive distributive lag simulation method and a novel machine learning technique, Kernel-based regularized least squares, to ascertain the causal effect among variables. The results reveal that economic complexity is escalating environmental contamination. Similarly, public service transportation increases environmental costs, but clean energy and improving technology decrease the production-based emissions in China. These findings offer valuable guidance for China's public transportation system to integrate and consolidate the road, railway, airline transportation, and aviation sectors. [ABSTRACT FROM AUTHOR]

China introduced the Intermodal Transport Demonstration Project Policy in 2015, spurring the rapid expansion of sea-rail intermodal transport (SRT) at coastal ports. This policy is of crucial importance as SRT is pivotal in supporting the transport sector's achievement of the "double carbon target". Despite strong policy backing and notable growth of SRT, the impact of these SRT demonstration projects on curbing transport carbon emissions has not been comprehensively evaluated. This study addresses this gap by using panel data from hub seaports across nine provinces and applying a multi-period-continuous difference-in-differences model. The research quantifies SRT's contribution to reducing transport carbon emission reductions as a result of the policy. Key findings indicate: (1) Each 10,000 TEU increase in containerized SRT volume results in a 0.162% reduction in transport carbon emissions, with projected growth by 2025 leading to a 9.02% decrease in emissions. (2) SRT lowers transport energy consumption and carbon emission intensity, fostering a green transformation in energy use. (3) Geographical analysis indicates that policy implementation in the southern region requires further strengthening. This study enhances empirical understanding of low-carbon SRT development in hub ports, emphasizing its critical role in China's transition to decarbonized transport. It also highlights the importance of regional policy effectiveness, offering valuable insights for policymakers striving to promote sustainable transport modes. • Evaluates the impact of China's sea-rail intermodal transport policy on reducing transport carbon emissions. • Uses a multi-period continuous difference-in-differences model with panel data from major ports. • The policy significantly reduces emissions, but regional disparities in effectiveness exist. [ABSTRACT FROM AUTHOR]

The role of China is increasingly pivotal in climate change mitigation, and the formulation of energy conservation and emission reduction policies requires city-level information. The effectiveness of national policy implementation is contingent upon the support and involvement of local governments. Accurate data on final energy consumption is vital to formulate and implement city-level energy transitions and energy conservation and emission reduction policies. However, there is a dearth of data sources pertaining to China's city-level final energy consumption. To address these gaps, we developed computational modeling techniques along with top-down and downscaling methods to estimate China's city-level final energy consumption. In this way, we compiled a final energy consumption inventory for 331 Chinese cities from 2005 to 2021, covering seven economic sectors, 30 fossil fuels, and four clean power sources. Moreover, we discussed the validity of the estimation results from multiple perspectives to enhance estimation accuracy. This dataset can be utilized for analysis in various cutting-edge research fields such as energy transition dynamics, transition risk management strategies, and policy formulation processes. [ABSTRACT FROM AUTHOR]

China is now the world leader with green capital actually creating renewable energy technologies. We address the possibility of whether China can emerge a new ecological civilization, as well as become the global leader to reach climate security. In particular, China has the potential to implement a solar energy infrastructure in the deserts of the Middle East as part of the Belt and Road Initiative, mainly in the form of concentrated solar power. The creation of this renewable energy capacity could supply electricity to much of the world, as well as power the direct air capture (DAC) of carbon dioxide with a permanent burial in the crust, in particular, using the ultramafic deposits in Oman. This realization would increase the chances of not breaching the International Panel on Climate Change (IPCC) warming target of 1.5 ℃, of course only if coupled with the termination of utilizing fossil fuels as early as possible and their replacement with renewable energy supplies globally. In this context, our pioneering model establishes that coupling a DAC-driven drawdown of atmospheric carbon dioxide with a rapid increase in the renewable energy capacity is more than capable of producing enough clean energy to eliminate energy insecurity globally (to all 8–10 billion humans) and to provide energy for the drawdown for the rest of the 21st century, thereby reducing atmospheric carbon dioxide to safe levels. This contingency will likely only be realized with a shift to demilitarization of the global economy. Likewise, this potential emergence of China as the global leader for climate security would likely inspire the push for a global Green New Deal to make this goal possible. [ABSTRACT FROM AUTHOR]

This study investigates the application of advanced simulation and modeling technologies to optimize the performance and reliability of renewable energy systems. Given the urgent need to combat climate change and reduce greenhouse gas emissions, integrating renewable energy sources into existing infrastructure is essential. Using bibliometric methods, our research spans from 1979 to 2023, identifying key publications, institutions, and trends. The analysis revealed a significant annual growth rate of 16.78% in interest in simulation and modeling, with a notable surge in published articles, reaching 921 in 2023. This indicates heightened research activity and interest. Our findings highlight that optimization, policy frameworks, and energy management are central themes. Leading journals like Energies, Energy, and Applied Energy play significant roles in disseminating research. Key findings also emphasize the importance of international collaboration, with countries like China, the USA, and European nations playing significant roles. The three-field plot analysis demonstrated interconnections between keywords, revealing that terms like "renewable energy sources", "optimization", and "simulation" are central to the research discourse. Core funding agencies, such as the National Natural Science Foundation of China (NSFC) and the European Union, heavily support this research. This study underscores the importance of policies and sustainability indicators in promoting renewable energy technologies. These insights emphasize the need for ongoing innovation and interdisciplinary collaboration to achieve a sustainable energy future. [ABSTRACT FROM AUTHOR]

Constructing solar-powered cities with photovoltaic panels installed on building façades saves energy and reduces carbon emissions. Since photovoltaic integrated shading devices (PVSDs) differ from rooftop photovoltaics, their design must consider power generation capacity, indoor thermal environment, and lighting control to maximise the energy-saving potential. This study simulates and evaluates the performance of PVSDs combined lighting control in energy-efficient buildings based on EnergyPlus and addresses the conflict between the indoor environment and photovoltaic power generation by optimising the geometric parameters of photovoltaic systems in China's hot summer and cold winter (HSCW) zones. The findings indicate that the combined lighting control mitigates the detrimental effects of PVSDs on lighting, and the design optimisation makes it possible to acquire positive shading benefits and significantly boost the performance of PVSDs, thus saving more energy than rooftop photovoltaics. The maximum energy-saving rate of a room with 12.5% of its façade wall utilised reached 49.295%. This study provides an example of the practical application and evaluation of PVSDs in HSCW zones. [ABSTRACT FROM AUTHOR]

Using a panel data set from 2007 to 2019, we empirically evaluate the impact of carbon capture, utilization, and storage (CCUS) technology innovation on green total factor productivity (GTFP). The findings show that (1) CCUS technology innovation significantly improves GTFP. (2) CCUS technology innovation significantly contributes to GTFP by promoting industrial structure upgrading and carbon emissions efficiency. (3) Environmental regulation plays a positive moderating role in the nexus between CCUS technology innovation and GTFP. The findings of this paper provide guidance for China to achieve green energy transition and build a green energy system. [ABSTRACT FROM AUTHOR]

China's green financial pilot policies (GFPPs) are an important start to build a green financial system in China. It is also an important part of achieving the "dual-carbon" goal. This paper calculates China's total factor energy efficiency (TFEE), analyzes the impact of GFPPs on TFEE, and explores the conduction mechanism. The results show that the relationship between GFPPs and TFEE in the pilot areas is statistically significant. The GFPP mainly improves the TFEE through the green innovation effect and the optimization of the energy structure. The GFPP has a significant effect on TFEE enhancement in eastern coastal cities, non-old traditional industrial cities, and non-resource-based cities with high initial energy. China should continue to deepen the pilot work of green finance, formulate differentiated green finance policies, and ensure green technology innovation. This study provides empirical evidence for further optimization of green finance and energy efficiency. [ABSTRACT FROM AUTHOR]

With the energy structure transition and the development of the green power market, the role of electricity retailers in multi-market green power trading has become more and more important. Particularly in China, where aggressive green energy policies and rapid market transformations provide a distinct context for such studies, the challenges are pronounced. Under demand-side response, electricity retailers face the uncertainty of users' electricity consumption and incentives, which complicates decision-making processes. The purpose of this paper is to explore the optimization decision-making problem of multi-market green power trading for electricity retailers under demand-side response, with a special focus on the Chinese market due to its leadership in implementing substantial green energy initiatives and its potential to set precedents for global practices. We first construct a two-party benefit optimization model, which comprehensively considers the profit objectives for electricity retailers and utility maximization for users. Then, the model is solved by the Lagrange multiplier method and distributed subgradient algorithm to obtain the optimal solution. Finally, the effectiveness of the incentive optimization strategy under the multi-market to promote green power consumption and improve the profit of electricity retailers is verified by arithmetic simulation. The results of this study show that the incentive optimization strategy under multi-market, particularly within the Chinese context, is expected to provide a reference for electricity retailers to develop more flexible and effective trading strategies in the green power market and to contribute to the process of promoting green power consumption globally. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality, the Chinese government needs to gain a comprehensive understanding of the sources and drivers of greenhouse gas (GHG) emissions, particularly at the county level. Anji County in eastern China is a typical example of an industrial transformation from quarrying to a low-carbon economy. This study analyzed the decoupling types and structural characteristics of GHG emissions and the driving factors of carbon dioxide (CO 2) emissions in the Anji from 2006 to 2019, and explored the differences between county-level and provincial-level or city-level results. It was observed that energy-related activities are the main source of GHG emissions in Anji and that economic development is the driving factor behind the increasing CO 2 emissions. However, industrial transformation and upgradation coupled with the alternative use of clean energy limit the growth of GHG emissions. This study details the GHG emissions of county during the industrial transformation stage and provides corresponding policy recommendations for county governments. [ABSTRACT FROM AUTHOR]

Ensuring access to modern energy for all is a fundamental aim of Sustainable Development Goal 7 (SDG7). Whereas education is often considered important in supporting the energy transition, there is limited empirical evidence to confirm this causal relationship. Using microdata from the 2010 census, this study investigates the causal impact of education on the adoption of clean cooking fuels in rural China. To address the challenge of endogeneity, an instrumental variable (IV) approach was adopted, based on the enactment of compulsory schooling laws (CSLs) in China. Individuals' educational choices are driven by their exposure to these CSLs, which vary across cohorts and provincial regions. The results show that an additional year of schooling significantly reduces biomass use by 6.1% and increases the adoption of clean fuels by 5.9%. The positive impact of education is more pronounced in less developed regions. These findings suggest that strengthening education can be a crucial policy tool for mitigating air pollution, particularly in developing countries. [ABSTRACT FROM AUTHOR]

Water and energy are mutually reinforcing elements in production and consumption activities, forming an inseparable relationship. This study, conducted at the provincial level, investigates the intricate connections between energy water footprint flow, water shortage, and water pollution. It aims to elucidate the vulnerability of provincial energy sectors to water use, fostering regional coordinated management for sustainable energy and water development. Utilizing a multi-regional input–output model, the research analyzes both the quantity and quality of water resources. The water footprint of China's provincial energy sector is quantified and scrutinized. Furthermore, an evaluation index system is constructed based on the water footprint concept. The entropy weight TOPSIS method is then applied to assess the vulnerability of inter-provincial energy sector water footprints. The key findings are as follows: (1) The energy water footprint has shifted from water resource-deficient areas, such as the northwest, North China, and northeast, to economically developed regions with relatively abundant water resources, such as East China and South China. This reveals that the transfer of water footprints in economic activities does not entirely alleviate water shortages in China and may even exacerbate shortages in certain water-deficient areas. (2) The graywater footprint of the energy sector is significantly larger than the blue water footprint and water shortage footprint. (3) The production and supply departments of power and heat emerge as the largest contributors to the transfer of energy and water footprints from water shortage areas to water-rich areas, followed by coal mining and dressing departments. (4) Top 10 Vulnerable Provinces: Tibet, Zhejiang, Ningxia, Tianjin, Jiangsu, Henan, Hunan, Beijing, Chongqing, and Hebei are identified as the top 10 provinces vulnerable to water footprints in the energy sector. This vulnerability closely correlates with the energy sector's dependence on water footprints and production leverage. Recommendations include optimizing the energy mix and establishing stable external water footprint supply channels for provinces with high water footprint dependence. Provinces with high production leverage are advised to accelerate innovation and application of water-saving technologies in key energy sectors, increase the utilization of clean energy, and enhance resource recycling. National government departments should focus on controlling and reducing water pollutants in the energy sector across regions, addressing water shortages by purifying water bodies and improving water quality. [ABSTRACT FROM AUTHOR]

Energy poverty, especially in rural areas, has become a central focus of scholarly and policy discussions. However, there is a significant gap in understanding the impact of religious beliefs on this phenomenon. This paper aims to fill this gap by utilizing household survey data from the China Labor-force Dynamics Survey (CLDS) spanning three waves (2012, 2014, and 2016) to examine the causal link between religious beliefs and energy poverty, covering clean energy accessibility and affordability among rural residents. Our analysis unveils a substantial positive influence of religious beliefs on the likelihood of experiencing energy poverty, especially concerning accessibility and affordability. This effect is notably pronounced among males, ethnic minorities, and low-income groups. Low income and education are recognized as pivotal mediating factors through which religious beliefs contribute to energy poverty. The findings of this study offer valuable insights for formulating strategies to mitigate energy poverty in rural China, with a particular emphasis on the role of religious beliefs. [ABSTRACT FROM AUTHOR]

The purpose of this article is to investigate the new driving forces behind China's green energy and further assess the impact of green energy on climate change. The existing literature has used linear methods to investigate green energy, ignoring the non-linear relationships between economic variables. The nonparametric models can accurately simulate nonlinear relationships between economic variables. This paper constructs a nonparametric additive model and uses it to explore green energy. The empirical results show that the impact of green finance on green energy is more prominent in the later stage (a U-shaped impact). Fiscal decentralization also exerts a positive U-shaped impact, meaning that expanding local fiscal autonomy has contributed to green energy growth in the later stage. Similarly, the impact of oil prices and foreign direct investment demonstrates a positive U-shaped pattern. However, the nonlinear impact of environmental pressure displays an inverted U-shaped pattern. Furthermore, this article explores the impact of green energy on climate change and its impact mechanisms. The results exhibit green energy generates a positive U-shaped impact on climate change, meaning that the role of green energy in mitigating climate change gradually becomes prominent over time. Mechanism analysis exhibits that industrial structure and energy structure both produce a nonlinear influence on climate change. [ABSTRACT FROM AUTHOR]

This paper combines the Generalized Autoregressive Conditional Heteroskedasticity-Extreme Value Theory-Value at Risk (GARCH-EVT-VaR) method in conjunction with the Time-Varying Parameter Diebold-Yilmaz (TVP-VAR-DY) model to investigate the contagion of extreme risks between fossil and green energy markets in China. Specifically, the study concentrates on coal, crude oil, and natural gas markets as representative sectors for fossil energy, while green bonds, investments, green power, and associated new energy markets are chosen as representatives for the green energy sector. Our analysis reveals that extreme events can rapidly propagate risks between fossil and green energy markets, particularly during significant shifts in the external environment. Notably, green energy markets exhibit greater susceptibility to severe risks compared to their fossil energy counterparts, indicative of their instability and immaturity. Moreover, the analysis highlights the green bond market's heightened sensitivity to extreme risks, with green investments playing a pivotal role in propagating such risks throughout the system. These insights underscore the intricate dynamics of risk contagion between fossil and green energy markets, emphasizing the need for comprehensive risk management strategies in both sectors. [ABSTRACT FROM AUTHOR]

With the increasingly prominent issues of climate change and energy shortages, large-scale development of renewable and clean energy has become a common choice for countries around the world. Among them, onshore wind power plays an important role in the global energy transformation process due to its mature technology, safety, and efficiency advantages. However, because wind energy resources have the characteristics of low energy density, instability, and spatial dispersion, large-scale development of onshore wind power requires a large amount of land resources to support. To ensure the land resource demand for wind power development under the goal of 'carbon neutrality,' this paper conducted a quantitative study on the land occupation of onshore wind power in China. Firstly, based on the criterion of exclusivity, this paper reclassified the types of land occupation for wind farms from a spatio-temporal perspective. Secondly, based on the sample parameter method and the alpha shape algorithm, this paper calculated the land area of existing onshore wind farms in China categorically. Finally, considering the development trend of wind power technology, this paper systematically simulated and predicted the wind power land demand in different development scenarios under the 'carbon neutrality' goal. The results indicated that: (1) Based on the principle of exclusivity, the total land use area of wind farms could be divided into two parts in the spatial dimension: the direct impact area and the indirect impact area. The direct impact area could be divided into two parts in the temporal dimension: permanent land use and temporary land use. (2) In 2022, the land occupied by the wind turbine foundation, permanent land use, temporary land use, and direct impact area of China's onshore wind farms reached 48.28 km², 352.08 km², 1 234.86 km², and 1 638.81 km², respectively. (3) In 2022, the indirect impact area and total land use area of China's onshore wind farms reached 9.81x104 km ² and 9.99x104 km², respectively. The total land use area was almost equivalent to the total urban land use area of China. (4) Compared with the scenario of current technical level, under the scenario of technological progress and wind turbine upgradation, the various types of land use demand for wind power in China will have significantly decreased by 2060, and land use demand will have reached its peak by around 2050. The large-scale upgradation of wind turbines has great potential for saving land resources. Therefore, perfecting the land use standards of wind power construction, improving the land use efficiency of wind power development, and promoting the construction of offshore wind power are important paths for coordinating the sustainable use of wind energy resources and land resources. [ABSTRACT FROM AUTHOR]

Clean energy transformation in major powers, especially the rapidly expanding electric vehicle and wind power industries, has sparked an increasing demand for strategic resources such as rare earths (RE). The RE industrial chain has become a focal area of geopolitical competition between China and the United States. This paper utilizes theories and methods from law and political economics, employing the classic paradigm of global governance, to examine the underlying motivations and geopolitical impacts of the United States in promoting the restructuring of the global rare earth industrial chain. Taking into account the two major characteristics of the U.S.' geopolitical strategy, namely 'controlling key industrial chains' and 'containing China with allies,' this paper reveals the underlying logic and strategic responses of significant political and economic relationships in the ongoing geopolitical competition. These relationships include the connection between the decoupling of the RE industrial chain and reconstruction of the global 'dual chain' pattern, the enactment of the 'three major acts' by the U.S., and the dominance of the global clean energy industry system, as well as the game between China and the United States as major powers and Japan's industrial security. The results show that: (1) In terms of controlling key industrial chains, the technological 'de-rare earth' initiatives of downstream enterprises are reinforcing the 'de-sinicization' strategic orientation of western governments, and vice versa. This joint effort is promoting the formation of a global strategic resource 'dual chain' pattern. (2) In terms of containing China with allies, the United States requires that Japan and other allied countries share the responsibility in geopolitical competition with China. Japan, driven by its own interests, has been deeply involved in the restructuring of the global RE industrial chain, shifting from a high dependence on Chinese RE imports to a deep participation in a new global RE industrial chain led by the U.S. (3) The promulgation of the 'three major acts' by the U S. is a strong proof of its consistent use of domestic laws to shape geopolitical relations. The underlying motivation behind this is to reshape the strategic resource industrial chain and gain control of the global clean energy transformation. In the face of escalating strategic resource competition and based upon the 'dual circulation' new development pattern, China should, on the one hand, leverage its resources and production capacity advantages in the front and middle streams of the industrial chains, leading the independent extension of the strategic resource industry chain through innovation. On the other hand, China should engage strategically and integrate global key mineral resources, develop effective countermeasures, and continuously enhance the resilience of key industrial chains such as rare earths, so as to improve the level of national strategic resource security. [ABSTRACT FROM AUTHOR]

With the gradual attention of global climate change, a series of carbon emission plans have been formally implemented in the field of energy. There is a consistent relationship between the carbon market and the electricity market in promoting clean energy development and improving carbon dioxide emission reduction targets. The market design of a low‐carbon power system should be considered as a whole to promote the coordinated development of carbon and power markets. Taking an industrial park in China as the research object, an internal market trading model of an industrial park considering carbon dioxide emission reduction targets is proposed. The proposed trading mechanism considers both carbon dioxide emission reduction targets and social welfare maximization. The proposed market trading model connects day‐ahead and intraday electricity markets, which deal with uncertainty about renewable energy sources. [ABSTRACT FROM AUTHOR]

The development of renewable energy has become an important measure for countries worldwide to improve air quality, reduce greenhouse gas emissions, and achieve sustainable development. This trend may have implications for green total factor productivity (GTFP), which represents the economic growth efficiency in terms of resource and energy use. However, the current research on the impact of renewable energy development (RED) on GTFP based on China's provincial data is still insufficient, and it has not yet integrated multiple factors such as economic, social, environmental, and technological aspects to jointly analyze potential nonlinear effects. This paper first calculates the GTFP of 30 provinces in China using a global super-efficiency slack-based measure model. Then, a two-way fixed effects model and a panel threshold regression (PTR) model were used to explore the linear and nonlinear effects of RED on GTFP. The results show that: First, RED has a significant positive effect on GTFP, which remains in effect after a sequence of robustness tests including endogenous treatment. For every 1% increase in RED, GTFP increases by 0.025%–0.039%. Second, the contribution of RED to GTFP shows a clear characteristic of diminishing marginal benefits, with the impact coefficient decreasing from 0.058% to 0.022%. Third, the higher the level of economic activity, social conditions, environmental protection, and technological advancement, the greater the favorable impact of RED on GTFP. The range of coefficient changes under the influence of economic- and social-level factors reaches 0.012%–0.143%, while the range of coefficient changes at the technological and environmental levels is only 0.026%–0.057%. Based on the above conclusions, some policy implications related to the development of renewable energy are proposed. [ABSTRACT FROM AUTHOR]

This editorial discusses the dynamics and prospects of the energy market and energy transition. It emphasizes the global shift towards renewable energy due to government initiatives and technological advancements. However, challenges to the transition process exist, such as the impact of the COVID-19 pandemic on global energy demand and fossil fuel prices. The editorial highlights the varying dynamics of the energy market and transition process at the national and firm levels. The collection of research papers covers topics such as renewable energy subsidies in China, efficiency of hydropower electricity generation, and the impact of oil prices on consumer and producer prices. It also explores behavioral economics and the role of natural gas in achieving urban ecological civilization. The editorial acknowledges the contributions of the authors, reviewers, and journal editors in making this collection possible. [Extracted from the article]

The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS's robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS's robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power. [ABSTRACT FROM AUTHOR]

Adoption of clean electric energy depends not only on administrative regulations, but also on public support, in particular, the public is willing to pay for environmental improvements. However, the increase of solar photovoltaic power generation willingness to pay (WTP) associated with higher education attainment and the identification of their causality has been missing. Present paper used the enactment of the Compulsory Schooling Law as an instrumental variable to solve the causal relationship between education and willingness to pay for photovoltaic power generation. The results are as follows:Heckman two-stage model and instrumental variable both confirmed that higher education has a positive impact on WTP for solar photovoltaic power generation. For each level of public education in the east, the WTP of photovoltaic power generation will increase by 7.540 CNY, 8.343 CNY and 8.343 CNY respectively, the central public will increase by 9.637 CNY, 10.775 CNY and 11.758 CNY, and the western public will increase by 12.723 CNY, 15.740 CNY and 17.993 CNY respectively. The positive influence of education level is smaller among the people who know the ladder price better, but it is bigger among the people who are male, older than 45 years old, healthier, higher income and stronger awareness of safe electricity use. The total socio-economic value of photovoltaic power generation is significantly different in eastern, central and western region China. [ABSTRACT FROM AUTHOR]

Understanding of how rural livelihood systems embedded in different social‐ecological contexts affect household energy consumption behaviour is critical for facilitating rural energy transition. This study assesses the energy consumption level and structure for three different livelihood systems, including mobile livelihood (ML), semi‐settled livelihood (SSL) and settled livelihood (SL), from the pastoral regions of the Tibetan Plateau. Results show that the average household energy consumption in ML, SSL and SL systems is 9250.1, 14 714.3 and 7004.5 kgce, respectively. Although yak dung is the dominant energy source in the ML and SSL systems, commercial energy sources are extensively used. When rural herders are resettled into peri‐urban areas, commercial energy sources become dominant though the percentage of yak dung consumption remains high. Mobile livestock production strategies and the associated rangeland tenure regimes and cultural practices are key determinant household energy choice factors of the ML and SSL systems. Comparatively, the role of income is more impactful on fuel consumption patterns in the SL system. Accordingly, this study argues that utilising a livelihood system approach in understanding household energy consumption behaviour allows us to design energy policies and innovative and customised clean energy sources that better fit rural livelihood systems. [ABSTRACT FROM AUTHOR]

The anaerobic digestion (AD) disposal of stover and cattle manure is of great significance to the development of lowcarbon economy and green energy in China, but it will also have an impact on the environment, and the degree of influence is different for various raw materials. In this study, life cycle assessment (LCA) methods were applied to analyze and compare the impact of corn stovers biogas projects (CSBP) and dairy manure biogas projects (DMBP) on the environment during the whole operation stage. The results of inventory analysis were evaluated by ReCiPe2016 Hierarchy(H) mid-point (problem-oriented) and end-point (destruction-oriented) method, respectively. The results showed that the net energy efficiency of CSBP was higher (763.903 kW·h/FU) and the greenhouse gas (GHG) emission reduction of DMBP was more (5541.418 kg CO2-eq/FU). The anaerobic digestion (AD) units have the greatest environmental impacts, and human carcinogenic toxicity is the largest environmental impact category (1.16-1.43 PE). The key to reducing environmental impact is reducing the input of chemical substances and the waste of electric energy. Both CSBP and DMBP have a favorable impact on ecosystem quality and resources, and CSBP is more beneficial to the environment (-10.297 Pt). Co-digestion is an important measure to reduce the environmental damage from biogas projects. These research results provide theoretical support for the selection of raw materials for large-scale biogas projects in China, provide technical basis for reducing the impact of actual operation on the environment, and promote the resource utilization of agricultural waste and carbon dioxide emission reduction and sequestration. [ABSTRACT FROM AUTHOR]

China Pakistan Economic Corridor (CPEC) is very significant project owing to its development in Pakistan and China. It is evident that this project is promoting sustainable development in both countries in many ways. The objective of this research paper is to study about the sustainability of CPEC in adopting the environment related initiatives. It has been argued that CPEC is a difference maker in terms of improving infrastructure, protecting environment and boosting of the trade between Beijing and Islamabad. That is why, both nations have adopted multi-dimensional initiatives to save the environment. However, there is need to improve this process. Still there are many environmental challenges to this significant project. Considering the development under this project both Pakistan and China aspire to engage in clean energy cooperation to ensure sustainable environment. Both countries need to formulate guidelines and protocols for a green investment project roadmap to address the challenges of sustainable environment which are still missing at the policy level. By employing qualitative methods based on research material from secondary sources, this research aims to study the initiatives taken by Pakistan to make CPEC an ecofriendly and environmentally sustainable project. This is evident that CPEC project experience moderate but short term environment challenges due major infrastructure reforms. Furthermore, these environmental challenges are stern and can create hindrance in economic development for Pakistan and China if certain environmental regulations could not be adopted. This paper recommends that both states needs to adopt concrete, composite, bilateral environmental cooperation for the sustainability of CPEC project for durable time frame. [ABSTRACT FROM AUTHOR]

Combining various sources to create a complementary system plays a key role in utilizing clean energy sources economically and mitigating air pollution during the heating season in Northern China. However, there is a lack of unified and reasonable design methods for such systems, resulting in the excessive capacity of equipment and the waste of energy. In this work, a unified design method is proposed to solve this problem. A generalized structure and its mathematical model are firstly established, enabling transient simulations on the TRNSYS platform. Then, a preliminary screening criterion for the system composition a general operation strategy is proposed. Finally, the system configuration is optimized by using the genetic algorithm. The method is successfully applied in a demonstration project in China. The results show that the coupling system consisting of a biomass boiler (384 kW), an air-source heat pump (430 kW) and a ground-source heat pump (369 kW) is the most economical, and the annual cost is 26.7% lower than that of a single-equipment system. Additionally, the sensitive factors that strongly affect the optimization results are explored. The establishment of the generalized structure and its mathematical model enables the quick calculation and convenient comparison of various schemes, and simplifies the complicated optimization problem of the capacity optimization of each piece of equipment. The proposed design method can reduce the annual cost to a minimum value, and thus it provides a theoretical basis for the large-scale application of clean energy sources for heating. [ABSTRACT FROM AUTHOR]

Hydropower and photovoltaic power are widely used as clean energy sources around the world. Hydro-Photovoltaic complementary is precisely the use of the regulation performance of hydropower stations and the peak regulation performance of PV electric fields to improve the system's power generation efficiency. The Yalong River basin as one of China's clean energy bases, is rich in water and light resources. And now its midstream Yangfanggou hydropower station has just been completed, and the relevant PV electric field is in the construction planning stage. It is worth studying how to effectively utilize its hydropower and PV output resources. Therefore, Yangfanggou hydropower station and its PV electric field are taken as the research objects in this paper. The possibility of hydro-photovoltaic complementarity is analyzed within the year and day respectively. Then, a short-term scheduling model of hydrophotovoltaic complementarity is constructed according to the principle, and its operation mode and effect are optimized using the genetic algorithm NSGA-II. The results indicate that the annual power generation of the system is increased by about 1.4 billion kWh from the original hydropower through the hydrophotovoltaic complementary, and the annual guaranteed output is also increased with a large increase degree at the same time. [ABSTRACT FROM AUTHOR]

Nowadays, the development of green and smart ships has become a trend in the global shipping industry. Some countries such as Japan and Korea, as well as several European countries, have already made some progress and advantages. In recent years, China has issued a series of policies to encourage and support the development of green and smart ships. Beyond that, the demonstration of green and smart ships has been promoted along with the trend of larger-sized and standardized inland vessels. The Chinese status and plans of green technologies are summarized including air layer drag reduction, efficient propulsion, DC networking, and clean energy. Some smart technologies have also been illustrated, for instance, intelligent driving, intelligent engine rooms, energy efficiency, hulls, cargo control, and information integration. Smart ship technologies need to be fully validated in order to improve industrialization applications. In the shipping industry, the development and application of smart ship technology need international and inter-regional cooperation, so as to achieve much higher energy savings, ensure environmental protection, achieve collaborative intelligence, and ensure safety and reliability. In turn, this will aid economic advances worldwide. [ABSTRACT FROM AUTHOR]

This study examines the impact of urban management on the efficiency of regional innovation in China's manufacturing industry, with a specific focus on modern sustainable energy. The research takes into consideration the regional diversity in innovation development across China's three major regions and integrates common Frontier theory with the MSBM model. By employing a non-radial distance function approach, this study develops the MMSBMP model, incorporating various improved methods proposed by researchers. The Luenberger index methodology is utilized to assess the innovation efficiency of the national manufacturing industry from 2017 to 2021, enabling the identification of efficiency losses. The findings highlight significant disparities and opportunities for enhancing innovation efficiency across the three major regions, both at the common Frontier and the group Frontier. However, caution is advised due to the potential overestimation of regional Frontier efficiency values resulting from variations in technical reference datasets. Analysis of the Total Growth Rate (TGR) values reveals distinct development characteristics among the regions, with the eastern region exhibiting smaller extremes and the central and western regions displaying larger extremes. This comprehensive examination of China's manufacturing industry emphasizes the influence of urban management. By investigating the consequences of urban management practices, this research provides insights into the relationship between urban development strategies and the performance, efficiency, and sustainable growth of the manufacturing industry. The study highlights the significance of urban management in shaping regional innovation efficiency and emphasizes the continual improvement of the industry's innovation performance in the context of modern sustainable energy. [ABSTRACT FROM AUTHOR]

Over the past few decades, China has undergone an unprecedented structural transformation, stupendously transforming its energy and environmental systems and decarbonizing pathways. Nevertheless, around the share of clean and renewable energy generation with the goal of low‐carbon, it is still ambiguous how the dynamic relationship between the upgrading of grid infrastructure, interregional power trading and the investment and economic foundation that support their collaborative promotion forms. Thus, under the framework of panel vector autoregressive models, we study the bridge that links the key dominant factors in the pattern of electricity supply and demand such as grid infrastructure, power generation share of clean and renewable energy, net power input and carbon emissions. The results show that the governance framework dominated by power grid infrastructure upgrading, interregional power input dependence and carbon constraint mechanism to promote clean‐oriented energy mix is still flawed. In addition to improve the utilization rate of power grid infrastructure, relevant policy makers should devote more efforts to software conditions including interregional and interprovincial power trading and grid‐connecting mechanisms of clean and renewable energy. [ABSTRACT FROM AUTHOR]

Regarding the impact of digitization on the environment, a definitive consensus remains elusive in the scholarly discourse. This article evaluates the carbon emissions impact of China's National Supercomputing Centers (NSCs) in terms of computational power, aiming to determine whether NSCs exhibit significant carbon emissions effects and to identify the underlying factors driving them. Theoretically, we integrate both direct and indirect effect into a comprehensive research framework, comprising the dimensions of energy consumption and energy structure. Empirically, the synthetic control method (SCM) is employed, constructing a group of synthetic control cities that closely resemble the NSC cities. The research findings show that NSC cities exhibit statistically significant differences in carbon emissions compared to synthetically non-NSC cities, yet this phenomenon manifests with intercity heterogeneity. Upon scrutinizing the driving factors, it becomes apparent that NSCs primarily elevate urban energy consumption scale through increased industrial electricity usage, thus fostering the escalation of local carbon emissions. Interestingly, in certain cities, despite witnessing a surge in energy consumption scale attributable to NSC, carbon emissions effects were not observed, which could be predominantly ascribed to a higher proportion of clean energy within the energy structure. The above results unveil the existence of NSC carbon emissions effect as well as its driving factors (high energy consumption and dirty energy using), providing policy guidance for public sectors aiming to enhance NSC operational efficiency, optimize energy structure, and broaden the spillover effect. [ABSTRACT FROM AUTHOR]

Green hydrogen produced from renewable sources such as wind and photovoltaic (PV) power is expected to be pivotal in China's carbon neutrality target by 2060. This study assessed the potential production, levelized costs of hydrogen (LCOH), and the cost structure in diverse mainland Chinese provinces from 2020 to 2060. It considered various combinations of electrolysis technologies, specifically alkaline electrolysis (AE) and proton exchange membrane (PEM), in conjunction with green electricity sources. The analysis considers the technological learning effects of wind power, PV power, AE, and PEM. This study's primary conclusions and policy recommendations are as follows: (1) PV power would be the predominant energy for green hydrogen production in nearly all of mainland China, providing a potential 2.25–28 642.19 kt/yr hydrogen production in different provinces. (2) AE exhibits cost (with LCOH around 3.18–8.74 USD/kg) competitiveness than PEM (with LCOH around 3.33–10.24 USD/kg) for hydrogen production. Thus, policymakers are advised to focus on the PV power combined with the AE pathway for large-scale hydrogen production. PEM is suggested to be mainly used in cases with high power fluctuations and end devices. (3) The provinces (especially Inner Mongolia, Xinjiang, and Gansu Province) in the Northwest of China show the greatest potential (about 74.35%) and have the lowest LCOH (with around 3.18–4.78 USD/kg). However, these provinces are quite distant from existing energy demand hubs. Thus, decision-makers are advised to focus on developing long-distance transmission/transportation infrastructure for either green electricity or green hydrogen. [ABSTRACT FROM AUTHOR]

Energy supply policy quality is an important factor that would impact national energy security. While existing research conducted policy evaluation from the lens of performance assessment, less study has been devoted to evaluating energy supply policy from the perspective of policy making. This study takes the energy supply policy documents issued by China's central government during the '13th Five‐Year Plan' period (2016–2020) as the research sample, and pioneers the use of the extended policy modelling consistency (PMC) index model combined with the text mining methodology to construct a policy evaluation index system with the characteristics of the energy supply policy which conducts a more in‐depth quantitative evaluation of the energy supply policy documents. The results show that the average PMC index value of China's energy supply policies is 7.26, and the overall quality is high. The concerns of existing policies are mainly focused on reform and development planning, safety production management and project engineering construction, but there is still room for improvement in policy predictability, coordination of policy areas, clarity of policy basis and goals and comprehensiveness of policy tool combinations. Based on this, China should improve the comprehensiveness of its energy supply policy tool combinations in terms of policy design norm; strengthen policy predictability and coordination of policy areas in terms of policy implementation guarantee; and clarify the basis and goals of policies in terms of policy orientation enhancement, to provide a reference basis for the formulation and improvement of future energy supply policies and to realise the sustainable development of energy supply. [ABSTRACT FROM AUTHOR]

The energy rebound effect, characterized by increasing energy use despite enhanced efficiency, has emerged as a complex interdisciplinary topic in the literature, reflecting its significance in both production and consumption sustainability. Recognizing the pivotal role of academic research in shaping energy management strategies and policies, this study conducted a comprehensive bibliometric review, accessing 530 articles from major citation indexes. This analysis provides insights into the evolution of the energy rebound field and potential future directions. Understanding the existing literature on the rebound effect serves as a valuable foundation for forthcoming research endeavors, addressing the intricate challenge of reconciling energy efficiency with sustainable energy consumption and production. The review explores the extensive literature on the energy rebound effect, highlighting a predominant focus on residential (e.g., cooling, heating, lighting, transportation) and industrial energy consumption in the majority of studies. Empirical applications primarily emphasize the measurement of the energy rebound effect, with a notable trend of increasing research concentration in China in recent years. Additionally, there is a growing body of economy‐wide analyses in this field. However, the literature exhibits complexity in both the analyses conducted and the methods employed for measuring the rebound effect. Research gaps are apparent, numerous studies tend to concentrate solely on the rebound effect at the overall energy consumption level, neglecting variations in energy types and the behavioral patterns of economic actors. Furthermore, despite consistent findings of a higher rebound effect in developing nations, there is a noticeable lack of scholarly literature addressing this issue about these countries. This article is categorized under:Sustainable Energy > Energy EfficiencyHuman and Social Dimensions > Behavioral SciencePolicy and Economics > Governance and Regulation [ABSTRACT FROM AUTHOR]

To achieve high-quality economic development in the process of promoting the development of China's environment quality, and green economy, green total factor productivity is an important indicator to measure high-quality economic development. Therefore, it is of great significance to study the impact of changes in energy and industrial structure on green total factors. Each specific province in China is taken as the research object, and the green total factor productivity index into green technology efficiency and green technology progress are decomposed in this paper. On the basis of constructing the industrial structure upgrading index and energy structure upgrading index, a fixed-effect model and threshold regression model are used to analyze the influence of industrial structure and energy structure on green total factor productivity and its internal mechanism. Results shows that green total factor productivity, industrial structure and energy structure all show a trend of "continuous rise in small fluctuations," but there is a spatial disequilibrium; the upgrading and optimization of industrial structure and energy structure can effectively promote the improvement of green total factor productivity, and the growth mainly comes from the improvement of green technology progress, not the improvement of green technology efficiency; the impact of the improvement of industrial structure and energy structure on green technology efficiency has a significant nonlinear trend of increasing marginal effect; the upgrading of the industrial structure has a stronger role in promoting green total factor productivity in the central and western regions than in the eastern region; while the optimization of the energy structure has a significant promoting effect on green total factor productivity in the eastern region, but has a certain inhibitory effect on the central and western regions. [ABSTRACT FROM AUTHOR]

Photovoltaics, a clean energy source, have received widespread attention worldwide recently. Many countries are carrying out photovoltaic construction, while also compiling and analyzing their photovoltaic development status. The same goes for China. In northwestern China, a considerable number of cities lack electricity. Meanwhile, its vast plains and abundant sunlight are conducive to the construction of photovoltaics. Therefore, the northwestern China has vigorously carried out photovoltaic construction nowadays. With the support of high-resolution and multi-temporal remote sensing images, we are able to analyze the development status of photovoltaics in these regions. We chose six provinces in northwestern China as our research areas and took three steps to complete our studies. Firstly, we extracted patterns of photovoltaics using deep learning methods. Secondly, based on the patterns and national land use survey data, we calculated the distribution and development status of photovoltaics in each province. Thirdly, we present the statistical results in figures and charts, showing the photovoltaic construction status and its development trend. We finally made conclusions and discussions about our insufficiency in work and future plans for further study. [ABSTRACT FROM AUTHOR]

As important green energy, wind power and photovoltaic power have great development prospects. The suitability evaluation of wind and solar power plants is a popular research field, which is related to the sustainable and healthy development of wind and solar power generation. In this paper, based on multiple dimensions such as land types, climatic conditions, topographic features and policy environment, we selected 10 indicators and combined (analytical hierarchy process) AHP method to build a suitability assessment model for evaluating the suitability of solar and wind power in Inner Mongolia, China. The findings revealed that, Inner Mongolia has a great potential to generate wind and solar electricity, for wind power, the category of 'excellent' regions covers 83855 km2 and represents 7.10% of the total surface area; for solar power, 7.66% (nearly 90420 km2) are classified as 'excellent'. The suitability of both solar and wind energy in the western region is considered to have the most suitable development region, parts of Alxa League and Bayannur City have great potential for combined wind and solar power generation. The research results could provide important technical and data support for capacity evaluation and power station location decision. [ABSTRACT FROM AUTHOR]

The ongoing transition from fossil fuel-based electricity generation toward green energy relying on the intermittent renewable energy sources indispensably requires development of novel energy conversion and storage methods. Depending on a particular location and local resources, pumped storage, lithium- or sodium-ion batteries, compressed air energy storage, as well as the so called power-to-gas (P2G) technologies may be applied. Taking into account the abundant solar energy resources available in the northwestern China, such as Ningxia hui autonomous region, and local water resources coming from the Yellow River, a power-to-hydrogen (P2H2) distributed energy conversion system is proposed in this paper, which is based on a high-efficiency reversible Solid Oxide Cell (rSOC). The conducted studies comprise tests with simulated current based on the actual photovoltaic power station data, and with usage of the as-obtained Yellow River water for the electrolysis mode without any pretreatment. It is documented that the reversible operation is beneficial, and the tested cell can operate for a prolonged time. Of importance, Na, Ca, Mg, and Si elements remain in an evaporator, and do not contaminate the cell, while higher than the initial boron concentration can be found in the condensed exhaust gases. The respective operational parameters of the system correspond to an electrolysis current density loading up 433.3 mA cm−2 for 4 h, as well as fuel cell operation mode with a current density of 8.3 mA cm−2 for 12 h. It is found that the average voltage losses in the electrolysis cell and fuel cell mode are 0.27 %/cycle and 0.886 %/cycle, respectively, indicating that the lifetime of the cells can be more than 800 h. The reported studies demonstrate validity of applying rSOC-based P2H2 system, especially if abundant photovoltaic power and water resources are available. [Display omitted] • The Yellow River water was utilized by rSOC for the first time. • The designed test current was modeled with local photovoltaics. • The P2H2 nearby consumption system can reversibly operate for over 800 h. • The degradation rates in SOFC mode are lower than those in SOEC mode. • The Yellow River water has no significant effect on the degradation rate. [ABSTRACT FROM AUTHOR]

In order to achieve the ambitious goal of "carbon neutrality", countries around the world are striving to develop clean energy. Against this background, this paper takes China and Italy as representatives of developing and developed countries to summarize the energy structure composition and development overview of the two countries. The paper analyzes the serious challenges facing the future energy development of both countries and investigates the possibilities of energy cooperation between the two countries, taking into account their respective advantages in energy development. By comparing the policies issued by the two governments to encourage clean energy development, this paper analyzes the severe challenges faced by the two countries' energy development in the future and combines their respective energy development advantages to look forward to the possibility of energy cooperation between the two countries in the future. This lays the foundation for China and Italy to build an "Energy Road" after the "Silk Road". [ABSTRACT FROM AUTHOR]

Based on China's empirical data from 2000 to 2020 of 1875 county-level administrative units, combined with the multi-phase by the propensity score matching and difference-in-difference (PSM-DID) model, this paper studies the impact of clean energy demonstration province policies on the carbon intensity of pilot counties, and its further impact on carbon emissions and economic development level. The results showed that 1. from a county-level perspective, although the economic development level of the pilot areas of clean energy demonstration provinces has improved as the carbon emissions have also increased, what is more, the carbon intensity has also significantly improved in this process; 2. there is no time lag in the impact of policies on the carbon intensity of counties, and the impact effects gradually increase over time along with strong regional heterogeneity; 3. the clean energy demonstration policy has weakened the technological level of the county and reduced the proportion of industrial-added value to GDP, thereby increasing the carbon intensity of the county through these intermediaries. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy poses intractable uncertainties in cascade hydropower systems, such that excessively conservative operations and unnecessary curtailment of clean energies can be incurred. To address these challenges, a quantum neural network (QNN)-based coordinated predictive control approach is proposed. It manipulates coordinated dispatch of multiple clean energy sources, including hydro, wind, and solar power, leverages QNN to conquer intricate multi-uncertainty and learn intraday predictive control patterns, by taking renewable power, load, demand response (DR), and optimal unit commitment as observations. This enables us to exploit the stability and exponential memory capacity of QNN to extrapolate diversified dispatch policies in a reliable manner, which can be hard to reach for traditional learning algorithms. A closed-loop warm start framework is finally presented to enhance the dispatch quality, where the decisions by QNN are fed to initialize the optimizer, and the optimizer returns optimal solutions to quickly evolve the QNN. A real-world case in the ZD sub-grid of the Sichuan power grid in China demonstrates that the proposed method hits a favorable balance between operational cost, accuracy, and efficiency. It realizes second-level elapsed time for intraday predictive control. [ABSTRACT FROM AUTHOR]