Search

This paper studies the impact of digital economy development on carbon emissions, which is a hot topic in the field of environmental economics. This topic is within the scope of the Frontiers in Environmental Science and is particularly in line with the theme of Environmental Economics and Management section in the journal. Firstly, this paper constructs the Digital Economy Development Index and its variable indicators to measure the development of the digital economy. Secondly, this paper uses urban panel data to reveal the impact of digital economy development on carbon emissions, and further adopts IV method to deal with endogeneity issues. Thirdly, this paper performs the heterogeneity analyses depending on the characteristics of the city. The results can provide a basis for formulating differentiated policies. Fourthly, this paper further explores the mechanism by which the digital economy affects carbon peaking. The results show that the digital economy may influence carbon peaking through upgrading of the industrial structure, technical innovation, and energy consumption. [ABSTRACT FROM AUTHOR]

Based on panel data for 30 provinces in China from 2000 to 2020, this paper uses entropy method to construct the integrated development indicators of energy Internet, and explores the impact of the development of the energy Internet on reducing carbon emissions in China and its internal transmission mechanism. The research results show that the development of energy Internet can significantly reduce regional carbon dioxide emissions, and increasing the use of renewable energy is an important mechanism for the comprehensive development of energy Internet to curb carbon emissions. Heterogeneity analysis shows that the emission reduction effect brought by the development of energy Internet is more remarkable in the regions with lower carbon emissions and western China. Furthermore, this paper finds that in the setting of the development of energy Internet, the development of renewable energy can promote natural gas consumption and advance energy conversion efficiency. The government's emphasis on regional technology development has an external strengthening effect on carbon emission reduction. The research in this paper expands and diversifies carbon reduction pathways and provides reference for more developing countries to utilize the development of energy internet to achieve carbon reduction. [ABSTRACT FROM AUTHOR]

This paper uses the exogenous shock of China's formal implementation of the environmental information disclosure system in 2008 to construct a quasi-natural experiment. Based on the panel data of prefecture-level cities from 2003 to 2019, the propensity score matching and difference in difference (PSM-DID) approach was used to systematically evaluate the impact of environmental information disclosure on energy efficiency. Overcoming the difficulties in measuring environmental information disclosure and the endogenous problem, this paper investigates the energy-saving effect of environmental information disclosure and illustrates its mechanism for the first time. The results show that environmental information disclosure significantly improved energy efficiency, and public participation played an important role in energy conservation, a conclusion that remained true after a series of robustness tests. The test of the impact mechanism shows that environmental information disclosure can achieve the goal of improving energy efficiency by promoting industrial structure upgrading and technological innovation. This paper enriches the discussion on the relationship between environmental information disclosure and energy efficiency, and provides useful policy inspiration for improving the level of energy efficiency and achieving sustainable economic development. [ABSTRACT FROM AUTHOR]

The government's environmental protection policy can significantly contribute to alleviating resource shortages and curbing environmental pollution, but the impact of various policy instruments implemented by the government on energy efficiency is unclear. Based on the panel data of 30 provinces in China from 2005 to 2021, this paper analyses the impact of environmental regulation and the industrial structure on energy efficiency from the perspective of resource taxes. The U-shaped relationship between environmental regulation and energy efficiency and between the optimization of industrial structure can significantly improve energy efficiency, and the optimization of industrial structure is conducive to weakening the initial inhibitory effect of environmental regulation. In addition, the analysis of regional heterogeneity showed that the impact of environmental regulation was stronger in the central and western regions, while the impact of industrial structure was stronger in the eastern and western regions. The conclusions of this study can help to expand the understanding of the relationship between environmental regulation and industrial structure on energy efficiency, provide policy enlightenment for the realization of green development and high-quality development, and provide Chinese examples and experiences for developing countries to improve energy efficiency. [ABSTRACT FROM AUTHOR]

Effective forecasting of energy consumption structure is vital for China to reach its "dual carbon" objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023–2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is crucial for China's power industry to meet global energy conservation and emission reduction goals. The rapid development of photovoltaic (PV) and hydropower has greatly assisted in the construction of China's novel power system. The stochastic characteristics of PV power generation pose significant challenges to the reliable and economical scheduling of power systems. In fact, the cascade hydropower station can effectively address the issue. To fully utilize the advantages of hydropower, this paper proposes a bi-layer scheduling optimization model for the cascade hydro-PV complementary system considering power market. The upper-layer model simultaneously maximizes the benefit and minimizes the output volatility of the complementary system. The lower-layer model carries out market clearing with the objective of social cost. Besides, PV uncertainty and market price volatility are considered in the decision-making process for power market transactions. To solve the bi-layer model, a novel meta-heuristic algorithm (geometric mean optimizer) is applied, demonstrating excellent performance compared to similar methods. For the complementary system, the results show that its total power output can be improved, and its output volatility can be effectively alleviated. [ABSTRACT FROM AUTHOR]

In this paper, 22 indexes are selected at three levels, including the informatization development level, the Internet development level, and the digital transaction development level, based on China's provincial panel data from 2011 to 2020, so as to build a digital economy development index system. Moreover, 28 basic indexes are selected from three aspects, including energy construction, energy production and energy consumption, so as to develop an energy economy development evaluation index system. The development index of China's digital economy and energy economy are measured by using the entropy weight method. The effect of the digital economy on the energy economy and its mechanism are tested by the static panel, the dynamic panel, and the mediating effect and regulating effect models. The results indicate that the digital economy has pronouncedly promoted the development of China's energy economy, and the development of the digital economy can have an effect on the rationalization of the industrial structure and then affect the development of the energy economy, and there is an intermediary effect. Moreover, the upgrading of the industrial structure is conducive to regulating the digital economy and facilitates the development of the energy economy. The development of the energy economy can be better promoted by focusing on the coordinated regional layout of the digital economy development, building a reliable energy commodity trading platform, and expediting the optimization and upgrading of the industrial structure. [ABSTRACT FROM AUTHOR]

Tourism has become a major driver of China's economic growth and consumes much energy causing environmental pollution problems. This paper combines the LMDI (logarithmic mean Divisia index) method and K-means clustering to analyze the factors influencing tourism energy consumption in seven Chinese provinces and discusses strategies for energy consumption in tourism. Specifically, firstly, this paper decomposes the tourism energy consumption factors in each province into six factors and identifies the driving forces of different factors on energy consumption. Secondly, K-means clustering method is used to classify different provinces into three categories using the latest dynamic influencing factors as clustering factors and provincial targeted suggestions are made according to the characteristics of different categories. This paper combines the LMDI model with cluster analysis to find targeted energy optimization strategies for the energy consumption of the Chinese tourism industry. [ABSTRACT FROM AUTHOR]

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry. [ABSTRACT FROM AUTHOR]

Typical public institutions such as government offices, hospitals, and schools play important leading and exemplary roles in the green and low-carbon development of the whole society. This paper analyzes the business and energy consumption characteristics of public institutions, as well as the characteristics of personnel travel, and constructs a carbon accounting model for public institutions. It innovatively proposes a methodology for carbon accounting of personnel travel related to public institutions and validates and analyzes it using a comprehensive hospital as an example. The paper analyzes the carbon emission characteristics of various energy types, systems, and types of travelers in hospitals, provides schemes for the transformation of main energy systems, and corresponding emission reduction effects, thereby providing technical support for the full-chain carbon accounting of public institutions. Additionally, this paper explores the carbon reduction pathways for hospitals to support the peak carbon and carbon neutrality goals of public institutions, and promote the high-quality development of public institutions in China. [ABSTRACT FROM AUTHOR]

Under the new development model, the digital economy has become a new engine to promote the green development of the economy and realize the goal of "double carbon". Based on the panel data of 30 provinces in China from 2010 to 2020, this paper empirically investigates the impact of the development of the digital economy on energy and carbon emissions using a series of econometric models such as baseline regression, a mechanism test, and the spatial Durbin model, etc. Common prosperity plays an intermediary role between digital economy development and carbon emissions; digital economic development optimizes resource allocation, effectively solves the problem of uneven resource distribution, and reduces energy and carbon emissions while achieving common prosperity. In addition, green innovation, industrial structure, urbanization level, R&D intensity, and the degree of marketization also have different degrees of influence on energy and carbon emissions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the digital economy development strategy according to local conditions, so as to promote the digital economy to produce a more significant carbon emission reduction effect. [ABSTRACT FROM AUTHOR]

Energy is known as the lifeline of national development, and from the last decade or so, the security of human energy supply has been frequently disturbed by natural disasters due to global warming and frequent geological activities. In this paper, by combing the literature, we found that the past literature on the relationship between energy and natural disasters mainly focused on measuring energy consumption under natural disasters, but less on the integrated evaluation of human economic activities, energy security and natural disasters, and less on the evaluation of the energy governance efficiency of each provincial, municipal, and autonomous region government in preventing and managing exposure to natural disasters from the perspective of Chinese provinces. Therefore, in order to fill the gap in the literature in this field, this paper collects panel data of energy consumption efficiency stages and natural disaster treatment stages from 2013 to 2017 for 30 provinces in China (excluding Hong Kong, Macao and Taiwan as well as Tibet Autonomous Region) and uses the two-stage undesirable dynamic DDF model as a framework to study the relationship between economic, environmental pollution and natural disasters for the sample data and to analyze the phase-by-phase evaluation of energy and natural disaster efficiency and make corresponding policy recommendations. The following conclusions are drawn: (1) The overall efficiency of China's eastern coastal provinces is higher than that of the central and western provinces. (2) The first-stage efficiency of Chinese provinces is better than the second stage, and the difference in efficiency of the first stage of each province is smaller than that of the second stage. (3) In terms of the efficiency of disaster prevention and relief inputs, the efficiency values are generally lower in most regions of China. (4) Finally, the annual efficiency of natural disaster losses is not high in all regions, and the efficiency values are higher in the eastern coastal regions than in the central and western regions. Accordingly, this paper proposes that each province should formulate relevant disaster prevention and economic development strategies according to regional characteristics, while the central government should also propose locally appropriate coordinated governance policies to effectively control carbon dioxide emissions and air pollution, as well as increase disaster prevention publicity and incorporate disaster prevention education-related work into the performance assessment mechanism of local governments to promote the interactive development of the two. [ABSTRACT FROM AUTHOR]

This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration. [ABSTRACT FROM AUTHOR]

Green consumption has become an important part of an environmentally friendly society. Policy guidance can effectively promote green consumption. Green consumption policies are extensive because of the diversity of green consumption objects. However, the various objects are not completely isolated, and policy must have a certain level of consistency. Therefore, from the perspective of green consumption objects, this paper first uses the text mining method to mine 308 green consumption policies in China, analyzing the objects covered in China's green consumption policies. Then, the evaluation system of green consumption policy consistency was built, seven key policies were selected, and the PMC-index method was used to measure policy consistency. The results show that (i) the main objectives of China's green consumption policy are the promotion of green products and the efficient use of energy. Green services and green recycling have been subject to fewer policy efforts. (ii) In terms of the links involved in green consumption, China pays more attention to the supply and the consumption chain and less attention to the recycling chain. (iii) The quantitative evaluation results of the seven typical policies show that the policy consistency is good but not perfect. The policy shortcomings are mainly reflected in the incentive methods. Therefore, it is recommended to further improve the green consumption objectives and enrich the means and methods of green consumption guidance. [ABSTRACT FROM AUTHOR]

Since the power generation structures and load characteristics in each province in China are quite different, the distribution of peak regulating resources and demands are extremely imbalance. Restricted by a low power marketization degree, peak regulating resource shortages, and transmission channel blocks, the efficient utilization of new energy is facing greater pressures. In order to improve the mutual aid in regional power grids and to obtain more precise simulation results, this paper proposes a two-layer optimization dispatching model, considering the mutual aid of peak regulation resources between each province. It determines the optimal startup mode and the units' power output in each province and obtains the power output arrangements for all the units and the technical and economic indicators. The model and the solution method are original and innovative. And it effectively solved the unequal distribution problem between the peak regulating demands and resources of each provincial power grid. Finally, taking an actual regional power grid in China as an example, the simulation results show that the proposed model can significantly improve the utilization rate of new energy, which verifies the effectiveness and feasibility of the proposed model and methods presented in this paper. [ABSTRACT FROM AUTHOR]

CO2 capture from coal power plants is an important and necessary solution to realizing carbon neutrality in China, but CCS demonstration deployment in power sector is far behind expectations. Hence, the reduction potential of energy consumption and cost for CCS and its competitiveness to renewable powers are very important to make roadmaps and policies toward carbon neutrality. Unlike the popular recognition that capturing CO2 from flue gases is technically and commercially mature, this paper notes that it has been proved to be technically feasible but far beyond technology maturity and high energy penalty leads to its immaturity and therefore causes high cost. Additionally, the potential energy penalty reduction of capture is investigated thermodynamically, and future CO2 avoidance cost is predicted and compared to renewable power (solar PV and onshore wind power). Results show that energy penalty for CO2 capture can be reduced by 48%-57%. When installation capacity reaches a similar scale to that of solar PV in China (250 GW), CO2 capture cost in coal power plants can be reduced from the current 28-40 US$/ton to 10-20 US$/ton, and efficiency upgrade contributes to 67%-75% in cost reduction for high coal price conditions. In China, CO2 capture in coal power plants can be cost competitive with solar PV and onshore wind power. But it is worth noting that the importance and share of CCS role in CO2 emission reduction is decreasing since renewable power is already well deployed and there is still a lack of large-scale CO2 capture demonstrations in China. Innovative capture technologies with low energy penalties need to be developed to promote CCS. Results in this work can provide informative references for making roadmaps and policies regarding CO2 emission reductions that contribute towards carbon neutrality. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative cooperative model for energy efficiency retrofitting that incorporates carbon emission rights, addressing critical financial constraints in Energy Performance Contracting (EPC). By employing the fuzzy analytic hierarchy process (F-AHP) to evaluate risk assessment indicators and stakeholder contributions and utilizing the enhanced Shapley method for equitable benefit distribution, the model demonstrates significant improvements in financing and efficiency for energy conservation projects. The findings are as follows: (1) the energy efficiency retrofit model, which integrates carbon emission rights, effectively alleviates the financial constraints and fosters energy conservation and emission reduction in guaranteed-savings EPC projects; (2) the enhanced Shapley method is deemed appropriate for the equitable distribution of energy-saving benefits among stakeholders; (3) when compared with the traditional model and the benefit allocation-absent carbon rights, the energy-saving benefits of the energy efficiency retrofit model incorporating carbon emission rights are higher in individual and overall terms. The findings of this study offer a viable solution to financing challenges faced by stakeholders in such projects and delineate a pragmatic approach for enterprises to enhance energy efficiency and reduce emissions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has posed a severe challenge to the global economic recovery and China's economic growth. Although China has achieved stage victory against the epidemic, the impact and influence of the epidemic on China's economy will linger. On the positive side, the epidemic has led to a dramatic reduction in air pollution levels and a sharp slowdown in greenhouse gas emissions such as CO2. Forecasting China's CO2 emissions under the impact of the COVID-19 epidemic is crucial for formulating policies that contribute to smooth economic development and rational energy consumption. To this end, this paper improves on the traditional grey model, GM(1, N), by developing a novel fractional multivariate nonlinear grey model, FMNGM(q, N). These improvements include two key points. First, different power exponents are assigned to each relevant factor variable to explain their nonlinear, uncertain, and complicated relationships with the system characteristic variables. Second, the integer accumulation is changed to fractional accumulation to preprocess the data, and the Caputo-type fractional derivative is used to characterize the endogenous relationships among the system characteristic data. In addition, the quantum particle swarm optimization (QPSO) algorithm is used to optimize the above parameters with the goal of minimizing MAPE. The collected data on China's CO2 emission from 2001 to 2018 were divided into two parts according to different stages of economic development: 2001–2009 and 2010–2018. Both sets of data were modelled and analysed separately and compared with other models. Results showed that the proposed model had better prediction accuracy than other models. Finally, the model built using the 2010–2018 data was used to forecast China's CO2 emissions. Results show that China's CO2 emissions in 2020 under the impact of COVID-19 will decrease by approximately 3.15% from 2019 to 9893 million tons. The results bear important policy implications for planners in investment in clean energy and infrastructure to achieving the goal of a low-carbon transition. [ABSTRACT FROM AUTHOR]

The issues of scaling, pipeline corrosion, and the growth of sludge, bacteria, and algae within circulating cooling water systems have been consistently limiting the enhancement of production efficiency in enterprises. The trending new electrochemical water softening technology, with its environmentally friendly, high efficiency, and low energy consumption characteristics, offers a fresh approach to addressing the stable operation of industrial circulating water systems. This paper begins by detailing the mechanisms of active scale removal, sterilization, and algae control facilitated by electrochemical water softening technology. Subsequently, it compares and analyzes the crucial core components of electrochemical devices (including the selection and preparation of anode and cathode materials, as well as the power system). Furthermore, it introduces the main types and installation modes of electrochemical equipment available in the market. Additionally, it uncovers the key factors influencing the efficiency of electrochemical descaling and validates the impact of electrochemical water softening technology on industrial circulating water systems through illustrative examples. Lastly, the paper concludes by summarizing and forecasting the future development direction of this technology. [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]

Knowledge of wind field characteristics and variation principles in complex topographical regions is of great importance for the development of numerical prediction models, aviation safety support, and wind energy utilization. However, there has been limited research focused on the lower-tropospheric wind fields in the Qinghai-Tibet Plateau. This paper aims to study the wind characteristics, vertical distributions, and temporal variations in the northeast of the plateau by analyzing a four-year continuous dataset collected from a Doppler wind LiDAR deployed in Xining, Qinghai Province of China. The results indicate that the prevailing horizontal wind direction in the low levels is primarily influenced by the mountain-valley wind circulation. However, as the altitude increases, the prevailing winds are predominantly affected by the westerlies. From a diurnal perspective, noticeable transition processes between up-valley and down-valley winds can be observed. The west-northwest wind (down-valley wind) dominates from late night to morning, while the east-southeast wind (up-valley wind) prevails from afternoon to early evening. The vertical winds in the low levels exhibit a downward motion during the daytime and an upward motion during the nighttime. In this plateau valley, the wind shear exponent is found to be highest in spring and lowest in winter, and it is generally lower during the daytime compared to the nighttime. [ABSTRACT FROM AUTHOR]

This paper proposes a temperature-adaptive radiative cooling (TARC) coating with simple preparation, cost effectiveness, and large-scale application based on a thermochromic powder. To determine the energy efficiency of the proposed TARC coating, the heat transfer on the surface of the TARC coating was analyzed. Then, a typical two-story residential building with a roof area of 258.43 m2 was modeled using EnergyPlus. Finally, the energy-saving potential and carbon emission reduction resulting from the application of the proposed TARC roof in buildings under different climates in China were discussed. The results showed that the average solar reflectivity under visible light wavelengths (0.38–0.78 μm) decreases from 0.71 to 0.37 when the TARC coating changes from cooling mode to heating mode. Furthermore, energy consumption can be reduced by approximately 17.8–43.0 MJ/m2 and 2.0–32.6 MJ/m2 for buildings with TARC roofs compared to those with asphalt shingle roofs and passive daytime radiative cooling (PDRC) roofs, respectively. This also leads to reductions in carbon emissions of 9.4–38.0 kgCO2/m2 and 1.0–28.9 kgCO2/m2 for the buildings located in the selected cities. To enhance building energy efficiency, TARC roofs and PDRC roofs are more suitable for use on buildings located in zones with high heating demands and high cooling demands, respectively. [ABSTRACT FROM AUTHOR]

In recent years, companies have employed numerous methods to lower expenses and enhance system efficiency in the oilfield. Energy consumption has constituted a significant portion of these expenses. This paper introduces a normalized consumption factor to effectively evaluate energy consumption in the oilfield. Statistical analysis has been conducted on nearly 45,000 wells from six fields in China. Critical factors such as lifting method, daily production, pump depth, gas–oil ratio (GOR), and well deviation angle were evaluated individually. Results revealed that higher production could lead to lower normalized consumption for beam pumps, progressive cavity pumps, and electric submersible pump systems, thus enhancing system efficiency. Additionally, a higher GOR might result in lower normalized consumption for the beam pump system, while the deviation angle of the well showed negligible impact on the normalized consumption factor. This manuscript offers a method to assess the impacts of artificial lift methods on production and discusses suggestions for reducing consumption associated with each lifting method in the oilfield. [ABSTRACT FROM AUTHOR]

South Africa possesses extremely rich renewable energy resources, including solar energy and wind energy, in spite of this, South Africa traditionally relies on coal as its primary energy source. Recently, South Africa confronted with severe electricity shortage. With pressure of power shortage and the transition to low- carbon energy, South Africa has been actively promoting the development of renewable energy, aiming to diversify its energy structure. China, as the world's leading country in the development and utilization of renewable energy, has long been committed to helping South Africa achieve renewable energy development. This article reviews the cooperation progress between China and South Africa in renewable energy, and provides an in-depth analysis of the challenges currently faced by both sides. To address such challenges, it is suggested to strengthen the design of top-level cooperation mechanisms, create diverse collaboration platforms, prioritize the exchange and collaboration of scientific talents. This paper aims to provide a typical reference for deepening renewable energy cooperation between China and South Africa. [ABSTRACT FROM AUTHOR]

Public institutions, emblematic of public infrastructure, exhibit extensive reach and operational scope, positioning them as vanguards in China's dual carbon initiatives and serving as exemplars. Electricity and natural gas predominantly fuel the operations of public institutions. Notably, the fixed commute routes and consistent procurement patterns of office personnel yield a standardized energy consumption profile within these entities. Researching carbon emissions related to commuting and evaluating procurement strategies for reducing carbon footprints in public institutions demonstrate a precision-tailored approach. This paper, through an analysis of the energy consumption characteristics, utilization structure of public institutions, and the commuting behaviors and procurement practices of office personnel, establishes a bespoke carbon accounting model specifically designed for public institutions, seamlessly embedded within a comprehensive platform. By providing fundamental methodological frameworks and advanced technological foundations for carbon accounting in public institutions across China, this work propels the nation's efforts towards carbon peak and ultimately carbon neutrality. [ABSTRACT FROM AUTHOR]

With the development of Non-Intrusive Load Monitoring (NILM), it has become feasible to perform device identification, energy consumption decomposition, and load switching detection using Deep Learning (DL) methods. Similar to other machine learning problems, the research and validation of NILM necessitate substantial data support. Moreover, different regions exhibit distinct characteristics in their electricity environments. Therefore, there is a need to provide open datasets tailored to different regions. In this paper, we introduce the Transient Dataset of Household Appliances with Intensive Switching Events (TDHA25). This dataset comprises switch instantaneous data from 10 typical household appliances in China. The TDHA dataset features a high sampling rate, accurate labelling, and realistic representation of actual appliance start-up waveforms. Additionally, appliance switching is achieved through precise control of relay switches, thus mitigating interference caused by mechanical switches. By furnishing such a dataset, we aim not only to enhance the recognition accuracy of existing NILM algorithms but also to facilitate the application of NILM algorithms in regions sharing similar electricity consumption characteristics to those of China. [ABSTRACT FROM AUTHOR]

All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently. [ABSTRACT FROM AUTHOR]

Ensuring optimal building performance is vital for enhancing student activity comfort and fostering energy-saving initiatives toward low-carbon objectives. This paper focuses on university student centers in China, aiming to diminish building energy consumption while enhancing indoor thermal comfort. Parametric modeling of typical cases is executed using the Grasshopper 1.0.0007 software package, and the simulation of building energy consumption and indoor thermal comfort relies on the Ladybug and Honeybee plug-in. Employing a multi-objective optimization design method and the Octopus multi-objective optimization algorithm, this study integrates numerical simulations and on-site surveys to analyze how factors like building form, orientation, envelope structure, and others impact the indoor and outdoor environment. A comprehensive optimization design approach is implemented for the building's exterior components, including the walls, windows, roof, and shading system. After conducting a comparative analysis of the annual comprehensive energy consumption and indoor thermal comfort before and after the optimization plan, it is determined that implementing these measures reduces the annual comprehensive energy consumption of the building under study by 58.8% and extends the duration of indoor thermal comfort by 53.0%. This study presents a practical optimization design methodology for university student center architecture in China, aiding architects in decision making and advocating for energy-efficient building designs. [ABSTRACT FROM AUTHOR]

Sorting out the requirements for intelligent functions is the prerequisite and foundation of the top-level design for the development of intelligent ships. In light of the development of inland intelligent ships for 2030, 2035, and 2050, based on the analysis of the division of intelligent ship functional modules by international representative classification societies and relevant research institutions, eight necessary functional modules have been proposed: intelligent navigation, intelligent hull, intelligent engine room, intelligent energy efficiency management, intelligent cargo management, intelligent integration platform, remote control, and autonomous operation. Taking the technical realization of each functional module as the goal, this paper analyzes the status quo and development trend of related intelligent technologies and their feasibility and applicability when applied to each functional module. At the same time, it clarifies the composition of specific functional elements of each functional module, puts forward the stage goals of China's inland intelligent ship development and the specific functional requirements of different modules under each stage, and provides reference for the Chinese government to subsequently formulate the top-level design development planning and implementation path of inland waterway intelligent ships. [ABSTRACT FROM AUTHOR]

As an essential material basis and power source for economic and social development, Western China's low energy use efficiency has hindered its sustainable economic development. This study aims to evaluate the total factor energy efficiency of the region and identify its influencing factors. A three-stage DEA model was used to measure the efficiency of 11 provinces from 2006 to 2021, and the Tobit model was employed to investigate internal factors. The findings show that (i) external environmental factors and stochastic perturbations have a significant impact on TFEE in the western region, overestimating integrated efficiency and scale efficiency and underestimating pure technical efficiency. (ii) the study of external influencing factors finds that the level of economic development increases input redundancy; the industrial structure increases capital input and labor input redundancy while decreasing energy input redundancy; and the energy consumption structure increases capital input and energy input redundancy while decreasing labor input redundancy. (iii) the study of internal influencing factors finds that the level of scientific and technological innovation, the level of openness to the outside world, and the TFEE have a positive correlation. In contrast, the intensity of environmental regulation has a negative correlation. [ABSTRACT FROM AUTHOR]

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

China's rapid economic development has consumed a large amount of energy, causing serious environmental pollution problems and contributing to global warming. This paper calculates the carbon emissions of the fishery sector and uses Random Forest (RF) for the first time to analyze the influencing factors of future carbon emissions. The results of the study show that increasing carbon sinks dominate the reduction of carbon emissions in the fisheries sector. Carbon sinks will continue to dominate emission reductions in the fisheries sector if positive mitigation measures are taken. Continuing the current pattern of fisheries development, the fishery population has a significant impact on future carbon emissions. Per capita incomes under a crude economic model will inhibit carbon emission reductions. The research results can provide guidance for the development of fishery low carbon economy and the formulation of emission reduction policies. [ABSTRACT FROM AUTHOR]

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development. [ABSTRACT FROM AUTHOR]

Rice production is the agricultural activity with the highest energy consumption and carbon emission intensity. Water and fertilizer management constitutes an important part of energy input for rice production and a key factor affecting greenhouse gas emissions from paddy fields. Water–fertilizer integration management (AIM) is an automated water and fertilizer management system for large-scale rice production, which can effectively save water and fertilizer resources. At present, the energy utilization and environmental impact of AIM in rice production are not clear. To clarify whether AIM is a water and fertilizer management measure that combines energy conservation and carbon emission reduction, a comparative study between the widely used farmers' enhanced water and fertilizer management (FEM) in China and AIM was conducted in this paper. Field experiments were conducted to evaluate the rice yield, carbon emission, energy utilization, and economic benefits of the two management methods. The results showed that AIM reduced water and fertilizer inputs, energy inputs, and economic costs by 12.18–28.57%, compared to FEM. The energy utilization efficiency, energy profitability, and energy productivity under AIM were improved by 11.30–12.61%. CH4 and N2O emissions and carbon footprint were reduced by 20.79%, 6.51%, and 16.39%, respectively. Compared with FEM, AIM can effectively improve the utilization efficiency of water and fertilizer resources and reduce carbon emissions. This study presents a mechanized water and fertilizer management approach suitable for large-scale rice production systems in China. By analyzing rice yield, resource utilization efficiency, and environmental benefits, AIM can serve as a crucial management strategy for enhancing productivity, economic returns, and environmental conservation within profitable rice production systems. In the future, further investigation into the impact of AIM on the microbial mechanisms underlying rice yield formation and greenhouse gas emissions is warranted. [ABSTRACT FROM AUTHOR]

Due to their higher energy efficiency and better economic performance, distributed energy resource (DER) systems are expected to be one of the main energy supply forms in the future and have gained increasing attention in recent years. Thus, there is a need to boost our understanding of how to apply DER systems in different types of actual cases. This paper investigates a techno-economic analysis of a DER system applied in a real case in a hot-summer and cold-winter zone in China, where the climate is considered to be Cfa according to the Köppen–Geiger climate classification system. An urban underground transportation infrastructure system located in Changsha (China) was chosen to analyze the techno-economic performance of a natural-gas-fired DER system in comparison with a centralized energy system (CES). First, a scientific and reasonable application program of the natural-gas-fired DER system was developed by an overall load analysis (electric load, air-conditioner load, and domestic hot water load during the operating period). Based on this load analysis, this research combined the energy consumption and the actual operating situation and then compared and analyzed different types and capacities of equipment in this case. Moreover, a comprehensive analysis of the economic benefits was estimated by comparing the natural-gas-fired DER system with conventional CESs. Overall, the total annual cost of the DER system was reduced by 18.73%, and its additional investment can be paid back within about 2.2 years. A better economic benefit was achieved by applying the natural-gas-fired DER system in an actual case, which will help encourage the widespread application of DER systems. [ABSTRACT FROM AUTHOR]

The platform economy is growing fast in the world. Its expansion, exemplified by industry giants like Amazon, Airbnb, and Uber, is reshaping societal lifestyles and commercial businesses. However, its environmental impacts are uncertain. Currently, the relationship between electronic commerce (e‐commerce) activities and environmental pollution has attracted a lot of attention. This paper attempts to construct a comprehensive theoretical model to investigate the nexus between e‐commerce and regional environmental pollution, with a particular focus on the effects of air pollution and waste pollution. Fixed effect models and China's provincial data during the period from 2008 to 2018 are employed to examine the roles of energy efficiency and resource consumption in such a nexus. The findings suggest that the development of e‐commerce is linked to a reduction in regional air pollution through the channel of improving transportation energy efficiency. The results also show that e‐commerce is associated with an increase in regional waste pollution due to the mechanism of resource consumption in the express packaging industry. As a result, the relationship between e‐commerce and environmental pollution is quite complex at the regional level, transcending a binary distinction of solely positive or negative impacts. This paper contributes to a better understanding of the complex environmental impacts of e‐commerce and helps governments design more efficient and targeted policies to reduce regional pollution. [ABSTRACT FROM AUTHOR]

In order to evaluate the effect of market-oriented environmental management measures on regional carbon emission intensity in the pilot areas better, this paper adopts a quasinatural experiment of energy-use rights trading (EURT) policy by using the difference-in-difference method from the perspective of cities in China from 2006 to 2019. The results show that the policy of EURT can significantly reduce regional carbon emission intensity, which varies in different regions and different scales of cities. The main goal of implementing the policy is to reduce regional carbon emission intensity by improving the energy consumption structure and promoting the improvement of industrial structure and green innovation. In addition, the spatial impact of the EURT pilot project is demonstrated by its ability to not only reduce local carbon emission intensity but also decrease carbon intensity in and around the designated areas. [ABSTRACT FROM AUTHOR]

An analytical hierarchy model of the impact of solar reflectance, thermal emittance, heat transfer coefficient, and heat storage coefficient on building energy consumption was established through the implementation of orthogonal design experiments. The EnergyPlus software (v9.0.1) was utilized to simulate building energy consumption across diverse climatic regions in China, providing essential benchmarks for the orthogonal design. The results of the range analysis consistently indicate that, barring regions characterized by extremely cold climates, solar reflectance emerges as the predominant factor exerting an influence on building energy consumption. As geographical latitude increases, the impact of the heat transfer coefficient becomes progressively larger, while the weight of thermal reflectance concurrently diminishes. Drawing upon the principles rooted in the gradient refractive rate theory and the concept of atmospheric window radiation, a range of high-reflectance and high-emittance cool roof coatings in various colors were meticulously developed. A spectrophotometer was employed to precisely quantify their reflectance properties, and simulations were subsequently conducted to scrutinize their energy-saving characteristics. The results demonstrate that the cool roof coatings that were developed using the methodology described in this paper exhibit substantial enhancements in reflectance, with increases of 0.24, 0.25, 0.37, and 0.35 for the yellow, red, blue, and green cool roofing materials, respectively, in comparison to conventional colored coatings. Under typical summer conditions, these enhancements translate to significant reductions in roof temperatures, ranging from 9.4 °C to 14.0 °C. Moreover, the simulations exploring the cooling loads for the roofs of differing colors consistently revealed remarkable energy savings. These savings were quantified to be 4.1%, 3.9%, 5.5%, and 5.4%, respectively, when compared to conventional coatings of the corresponding colors. These findings offer valuable insights into strategies for optimizing the energy efficiency of buildings through the application of high-reflectance cool roofing materials. [ABSTRACT FROM AUTHOR]

The energy consumption of office buildings has increased sharply since the 21st century with the increasing urbanization coverage. At this stage, the energy consumption of office buildings in China mainly comes from air conditioning and lighting. This paper obtains the regression equation of natural lighting illumination and radiant heat gain under different curtain conditions through experiments and simulations, and gives the theoretical calculation process of curtain regulation of office thermal and light environment and energy consumption. DeST and Ecotect software were used to analyze the thermal and light environment and energy consumption of the office. The results show that setting curtains in the room can effectively improve the indoor thermal light environment, the higher the transmittance of curtains the lower the lighting energy consumption, the higher the number of high temperature hours of natural room temperature and the greater the radiant heat gain. The room with thick curtains has the lowest energy consumption for air conditioning in summer, followed by the room with thin curtains, and the room without curtains has the highest energy consumption for air conditioning. The room without curtains has the lowest energy consumption for artificial lighting, the room with thin curtains has the second lowest, and the room with thick curtains has the highest electricity consumption for artificial lighting. The air conditioning energy consumption accounts for the main building energy consumption, followed by the lighting energy consumption. After setting curtains in the office, the air conditioning energy consumption caused by the solar radiation heat entering the room through the exterior windows is smaller than the lighting energy consumption caused by artificial lighting. Therefore, the installation of internal shading with moderate transmittance and good thermal insulation performance can make the energy saving of lighting and air conditioning energy consumption reach the optimal value. [ABSTRACT FROM AUTHOR]

The unavoidable option for socially sustainable development is a low-carbon economy. One of the essential steps for China to attain high-quality development is reducing carbon emissions. It is necessary to realize low-carbon development in Sichuan, as it is not only an important economic zone but also an ecological protected area. The concurrent relationship among energy consumption, carbon emissions, and economic growth was examined in this study using the Tapio decoupling indicator, and the factors affecting energy consumption and carbon emissions in Sichuan were broken down using the logarithmic mean Divisia indicator (LMDI). The findings demonstrate a fundamental relative decoupling relationship between Sichuan's energy use and carbon emissions. Analysis of energy consumption and carbon emissions in Sichuan Province from 2005 to 2020 shows distinct patterns. From 2005 to 2012, in 2014, and from 2016 to 2020, the relationship between energy use and carbon emissions was relatively decoupled, with decoupling values ranging between 0 and 1. Absolute decoupling occurred in specific years: 2010, from 2013 to 2018, and in 2020. These periods are characterized by economic growth alongside reductions in carbon emissions. Factors affecting energy consumption and carbon emissions were consistently analyzed, showing similar impacts throughout the study periods. We find that population and economic growth are the main driving forces of these effects. The effects of energy intensity and industrial structure mainly play restraining roles, and the latter has a slightly weaker effect than the former. [ABSTRACT FROM AUTHOR]

Green innovation possesses dual externalities of "innovation" and "environmental protection", and enhancing energy efficiency serves as a crucial means to promote high-quality economic development. Building upon the energy rebound effect, we use the balanced panel data of cities at prefecture level and above in China from 2008 to 2018 to explore the impact of urban green innovation on total factor energy efficiency (TFEE). The findings of this study indicate that, firstly, the impact of green innovation on TFEE exhibits a positive U-shaped pattern, characterized by initial suppression followed by subsequent promotion. This conclusion remains robust after undergoing a series of rigorous robustness tests. Second, high-quality green innovation is found to reach the turning point more quickly, implying that substantial green innovation can cross the turning point in smaller quantities. Thirdly, on the whole, in comparison to non-resource-based cities, resource-based cities are capable of reaching the turning point at an earlier stage. Finally, the new energy demonstration cities have not yet reached the turning point, while the non-new energy demonstration cities have crossed the turning point. This study contributes novel insights into the relationship between green innovation and TFEE, which holds significant implications for the formulation and implementation of sustainable development policies. [ABSTRACT FROM AUTHOR]

This study used a double machine learning model (based on the random forest algorithm) and spatial Durbin DIDs model to conduct quasi-natural experiments. The results are as follows: (1) innovation and reform policy regarding regional industrial chains as well as their resilience can significantly and positively address the development of China's impossible triangle coupling of energy; (2) implementing the innovation and reform policy for regional industrial chains in other regions can have a significant positive spatial transmission effect on the impossible triangle coupling coordinated development of energy in the region; (3) regional industrial chain resilience can produce a significant positive mediating effect between the innovation and reform policy of regional industrial chains and the safety, reliability, and economic feasibility of green and clean energy systems; (4) under the counterfactual framework, the mechanism path "innovation and reform policy of the regional industry chain→regional industry chain resilience→coordination degree of impossible triangle coupling of energy" has significantly positive direct and indirect effects in both the treatment group and the control group. However, "innovation and reform policy of the regional industrial chain→regional industrial chain resilience→the energy sector's impossible triangle coupling coordination degree" and "innovation and reform policy of the regional industrial chain→leading power of the regional industrial chain→the energy sector's impossible triangle coupling coordination degree" have significantly positive direct and indirect effects in the treatment group, but only the direct effect is significant in the control group. [ABSTRACT FROM AUTHOR]

Environmental protection tax is of great significance to the realization of an environment-friendly society. Using data from 280 Chinese cities from 2010 to 2020, this paper measures total factor energy efficiency in China by the super slack-based measure model. The impact of China's environmental protection tax reform on total factor energy efficiency is tested through differences-in-differences method, and its transmission mechanism is explored. Environmental protection tax reform policies have a significant positive impact on total factor energy efficiency. Environmental protection tax reform policies have greater impact on resource-intensive cities in central region and cities with lower initial energy efficiency. Cities with increased tax have positive spillover effects on the neighboring cities. This study provides empirical evidence for further optimization of environmental protection taxes and energy efficiency. The structure of the environmental tax system should be optimized, and the environmental tax policy should be implemented according to local conditions. [ABSTRACT FROM AUTHOR]

The building sector is one of the largest energy user and carbon emitters globally. To increase the utilization rate of renewable energy and reduce carbon dioxide emissions, the optimal technical scheme of active public institutions and coupled utilization of renewable energy is studied. In this study, the energy consumption of three types of public institutions in various regions of China was simulated by using DeST building energy consumption software, combined with energy conversion efficiency and data released by the National Bureau of Statistics, and the total energy demand and total energy supply of public institutions were predicted using the load density method. Based on the coupling mechanism of the MARKAL model, the optimal proportion of renewable energy in the energy supply of public buildings in different regions is determined. Through the study of the number of public institutions in various regions of China, energy consumption characteristics, construction area, and other related data, the reverse energy flow method is creatively proposed, and the active and renewable energy coupling algorithm from the energy demand side of public institutions to the energy supply side is established. The results show that the central region has the highest utilization rate of renewable energy in the public sector, reaching 36.18%. The use of renewable energy in public buildings in hot summer and warm winter zones decreased to 35.08%, and it was 12.82% in cold zones. By 2025, the proportion of renewable energy resources in China is expected to reach 29.2%. The energy coupling model and algorithm constructed in this paper can provide a basis for the coupling macro configuration of renewable energy in public institutions in China. [ABSTRACT FROM AUTHOR]

The green fiscal policy stands as a potent catalyst for fostering the green and low-carbon transition, with aims to garner multifaceted social, economic, and ecological gains. However, empirical evidence elucidating the impacts of green fiscal policies on firm energy performance remains scarce. Based on a unique firm-level dataset from 2008 to 2016, this paper utilizes the staggered difference-in-differences strategy to examine the energy-saving benefits of China's energy saving and emission reduction (ESER) fiscal policy. The results indicate that the ESER fiscal policy effectively enhances firm energy performance, supported by various robustness checks. Mechanism analysis reveals that technology innovation and energy consumption restructuring are significant channels through which the ESER fiscal policy improves firm energy performance. Moreover, the ESER fiscal policy contributes more remarkably to the energy performance of large-scale firms and non-resource-based urban firms. This study highlights the essential policy insights for further optimizing green fiscal policies to facilitate the upgrading of firm energy consumption. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable sources, the cogeneration integrated energy system (CIES) is much more efficient and flexible to achieve various types of energy supply for remote loads. Due to uncertainties in both sources and loads, the CIES should be carefully planned and optimised to keep it working at the suitable operation condition. Therefore, this paper proposes a multi-objective capacity allocation optimisation method for the islanded CIES, which is composed of renewable energy generation unit, electric-thermal conversion unit, electric storage, thermal storage and various loads. Firstly, three optimisation objectives are selected as typical indexes, including economic cost, solar energy utilisation, and life cycle carbon emission. An improved radar chart evaluation (RCE) solution is subsequently utilised for calculating a fitness function and building the multi-objective optimisation model. Besides, several compulsory constraints are supplemented to ensure the overall CIES performance satisfy energy supply requirement. As a mature and widely accepted algorithm, a genetic algorithm is chosen as an example to obtain the optimal capacity allocation scheme. Case study of an islanded CIES is provided on the basis of real data from the remote region of northwestern China, which successfully verifies the effectiveness of the proposed optimal capacity allocation method. [ABSTRACT FROM AUTHOR]

Based on the panel data of 227 prefecture-level and above cities in China from 2002 to 2018, a panel linkage equation model is constructed to explore the bidirectional influence relationship between haze pollution and urban sprawl, and the results of the study find that, firstly, there is a bidirectional promotion of causality between haze pollution and urban sprawl. That is, PM2.5 not only has a significant positive effect on urban sprawl, but also urban sprawl has a significant positive correlation with haze pollution, which is further strengthened by adding the air flow coefficient instrumental variable. Second, the heterogeneity analysis yields that haze pollution has different effects on urban sprawl in different regions. Under the sub-regional samples, haze pollution and urban sprawl have a bi-directional significant negative impact relationship in the eastern region, none of the haze pollution and urban sprawl have a bi-directional significant impact relationship in the western region, but both the central region and the northeastern region have a significant positive impact relationship. Under different city sizes, haze pollution and urban sprawl in large, medium and small cities have a bi-directional significant positive impact relationship, and from the numerical size, the degree of influence of haze pollution on urban sprawl in large cities is greater than that in small and medium cities; while the degree of influence of urban sprawl on haze pollution in medium cities is greater than that in large and small cities. Accordingly, it is proposed that urban governance should be adapted to local conditions, focus on innovative technologies to reduce energy consumption, and utilize big data to manage cities. [ABSTRACT FROM AUTHOR]

Introduction: The creation of infrastructure in rural areas is an essential guarantee for the economic development and in improving farmers' living standards. As a critical link between urban and rural production and consumption, rural logistics is essential to maximize the efficiency of rural infrastructure investment. Methods: Based on the panel data of 31 provinces in China from 2011-2020, the study analyzes the impact of high-quality development of rural logistics on the enhancement of residents' consumption in terms of scale and quality, using a fixed-effects model. Results: It suggest that this development promotes the growth of rural residents' consumption and quality, with a noticeable regional heterogeneity. The most significant effect is observed in the eastern region. Further analysis shows that inland and less developed provinces of rural e-commerce stimulate residents' consumption upgrade with the help of high-quality development of rural logistics at a level weaker than coastal provinces and developed provinces of rural e-commerce. Discussion: Consequently, it is recommended to boost the building of logistics infrastructure in rural areas and actively cultivate diversified rural logistics operators in the western and northeastern regions. The contribution of this study is to examine the impact of rural logistics on rural residents' consumption from the perspective of infrastructure, further validating the role of infrastructure development in promoting economic growth. [ABSTRACT FROM AUTHOR]

In rural areas with higher agricultural energy consumption, ensuring low-carbon transformation and rapid penetration is crucial; therefore, the importance of rural energy system in energy transformation is even more prominent. In order to better understand the research progress of rural integrated energy system, the existing structure of rural energy system and design method are briefly introduced, and the bibliometric method is applied to analyze publications from 2013 to 2023. Based on the Scopus database, 915 publications have been retrieved. These publications are analyzed from the perspective of citation, author, address, and published journal. It is concluded that existing researches mostly use conventional energy technologies to achieve power supply in rural areas, lacking analysis of the potential application of emerging energy technologies and research on multi-energy demand. Furthermore, the review reveals the economy of grid-connected rural energy system is mainly related to geographical location, system configuration, and resource endowment. The bibliometric analysis indicated that these publications are mainly from India and China; the average citation is 24.98, and each article is co-published by 3.66 authors, 2.26 institutes, and 1.46 countries. This work is helpful for scholars to understand the research status on the rural integrated energy system. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]