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As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment. [ABSTRACT FROM AUTHOR]

After the carbon peaking and carbon neutrality goals were proposed, different institutions and scholars carried out research on China's medium- and long-term mitigation pathways. Through the literature review of China's research on carbon neutrality, this paper finds that the zero-carbon energy transition is the key to achieving carbon neutrality. The main driving factors of reducing energy-related carbon emissions include the cleanliness of primary and secondary energy supply systems, the electrification of energy consumption and the development of hydrogen energy, energy efficiency improvement, carbon capture and storage (CCS), and negative emissions. Furthermore, based on the literature, this paper conducts a quantitative comparative analysis, and selects key indicators for comparative analysis and summary from seven dimensions, including economic and social development, carbon emission pathways, primary energy consumption, final energy consumption, final hydrogen energy consumption, electricity demand and supply, and installed capacity and structure of power generation. Main conclusions are as follows: (i) In terms of carbon emission pathways, the institutions generally believed that China will peak carbon emissions around 2028 and achieve carbon neutrality between 2050 and 2060. Achieving net-zero or near-zero emissions first in the power sector is the key to carbon neutrality across the society; (ii) In terms of energy supply, it is a consensus to increase the proportion of clean energy and reduce carbon emissions from the source. The proportion of clean energy in primary energy will increase to more than 85%, and the proportion of clean energy power generation and installed capacity will reach more than 90%; (iii) In terms of energy use, electricity will become the core of final energy consumption in the future. The predicted electricity consumption across the society will range 14.3–18.4 PWh, and the predicted electrification rate will exceed 65%. [ABSTRACT FROM AUTHOR]

China's economic growth miracle of the past decades has been accompanied by a massive increase in fossil fuel consumption and severe environmental pollution. To control air pollution, China is implementing some green finance policies. Although they have improved the air quality, it is little known whether and how green finance affects the firm labor demand. Taking the 2012 Chinese green credit policy (GCP) as an exogenous setting, this paper adopts the difference-in-difference (DID) method to investigate the effect of green finance on firm labor demand based on A-share listed firms covering 2007–2017. We find that green finance had a significant negative impact on firm labor demand. Specifically, the high-polluting firms with stricter green finance constraints would reduce firm employment by 4.8%. This effect is especially prominent when firms are state-owned enterprises (SOEs) or workers are low-skilled employees. Further evidence indicates that there are the Compliance Cost Hypothesis and Porter Hypothesis in China. In these two effects, the effect of CCH dominates, so the overall effect of green finance is detrimental to corporate performance, which in turn leads to lower corporate employment. Our paper provides the real effect of green finance from the firm labor market. And this paper has strong policy recommendations that the government should reconcile the relationship between air pollution control and employment. [ABSTRACT FROM AUTHOR]

Whether the technological finance cooperation pilot (TFCP) policy in China can promote energy efficiency remains under investigated. Using the dataset covering 284 cities in China from 2003 to 2019, this paper adopts the Super-SBM model with undesirable outputs to measure energy efficiency. Based on this efficiency, the Difference-in-Differences model (DID) and Spatial Durbin model (SDM) are employed to discuss the impact of TFCP policy on energy efficiency. Results demonstrate that TFCP policy has significantly promoted energy efficiency. And the conclusion is still valid after the robustness checks and endogenous treatment has been carried out. The impact of the TFCP policy on energy efficiency is heterogeneous, depending on the geographical, administrative, and resource characteristics of cities. To be specific, the promotion effect tends to be pronounced in east-central cities, high-ranking cities, and high-tech cities. Moreover, TFCP policy could significantly improve energy efficiency through the effects of technological innovation, industrial upgrading, and financial development. A further policy spillover analysis shows that TFCP policy has exerted a remarkable incentive influence on energy efficiency locally, while the neighboring cities are inhibitive. To sum up, this research is of important theoretical value and policy-making reference on green economy transformation for cities with differential features and energy utilization capacity, by shedding light on the impacts of such a technological finance cooperation system on energy efficiency. [ABSTRACT FROM AUTHOR]

The current approaches to study the coupling mechanism between economy and environment seem to fall into self-circulation, failed to reveal "economy–environment interdependence". In this context, an exogenous variable is introduced into these models for better understanding the relationship. Benzo[a]pyrene (Bap) environment inventories in different cities in China were estimated by fugacity model based on Bap concentration data collected from previous studies. An extended model, stochastic impacts by regression on population, affluence and technology (STIRPAT), generated from original IPAT (a model that expresses the idea that environmental impact (I) is the product of three factors: population (P), affluence (A) and technology (T)) was used to study the relationship between Bap environment inventory and anthropogenic factors including population, vehicle amount, affluence and energy consumption. A ridge regression has been applied to optimize the model parameters. Overall, there exist good relationships between Bap inventories and economic factors. Specifically, population and affluence are the most significant factors that influence Bap inventory. Rise of the scale of population and vehicle amount increases the Bap inventory, as growth of GDP per capita and the efficiency of energy utilization have inhibitory effect on Bap inventory. Apparently, the influences of anthropogenic factors on Bap inventory are different between north and south China. Bap inventory in north China is more sensitive to the change of population and energy consumption, while is highly correlated to GDP per capita in south China. Further, according to social-economic development prediction, with assist of the result from STIRPAT model, we find out that Bap inventory drop 31% from 2001 to 2020 in China. Our estimates are comparable with the published data and confirmed that Bap can be regarded as a chemical indicator of social-economic development in China. Image 1 • An extended STIRPAT model derived from original IPAT was developed. • Population and affluence are the key factors that influence Bap inventory. • Advance of affluence and technology level curbs Bap environmental exposure. • We predict Bap environmental inventory drop 31% from 2001 to 2020 in China. • Bap can be used as an indicator of social-economic development in China. [ABSTRACT FROM AUTHOR]

This paper investigates whether and how tax and fee support policies at the firm level in China influence the total factor energy productivity of enterprises. Using panel data from Chinese public trading companies for the period 2004–2020, this study employs a panel model for estimation. The findings suggest that tax rebates contribute to the improvement of the total factor energy productivity of enterprises. Specifically, a 1% increase in tax refunds leads to a growth of approximately 0.008% in total factor energy productivity. Robustness tests and endogeneity checks confirm the validity of the results. Heterogeneity analysis reveals that tax rebates have a significant impact on state-owned enterprises, small- and medium-sized enterprises, and non-technology firms in terms of enhancing their total factor energy productivity. Mechanism analysis indicates that tax rebates facilitate firms in alleviating financing constraints and enhancing their innovation capabilities, thereby improving energy efficiency. The research findings of this paper provide empirical support for optimizing policy supply, improving energy usage efficiency, and promoting the development of a globally sustainable economy. [ABSTRACT FROM AUTHOR]

Air pollution is an important part of ecological environment problems. Gaseous energy combustion pollution is a key part of air pollution. Analysis of its spatial distribution and drivers is important to effectively manage air quality and promote regional green development. This paper uses panel data of 30 provinces in China from 2006 to 2019 to analyze the spatial distribution and drivers of gaseous energy combustion pollution in each province of China through a combination of quantitative and qualitative analysis based on the spatial Durbin model, and further decompose the spatial effects of each influencing factor. The empirical results show, firstly, that inter-provincial gaseous energy combustion pollution in China shows significant spatial differences and cluster characteristics. Secondly, most areas are located in high–high aggregation area and low–low aggregation area. Finally, population, energy consumption and other independent variables have different impacts on gaseous energy combustion pollution in different regions. The changes of these variables will affect the adjacent areas through spatial transmission while affecting a region. According to the empirical results, this study proposes policy recommendations to balance the pollution degree of gaseous energy combustion in various regions and effectively reduce the emissions of various pollution sources. The research results are helpful to understand the spatial distribution of gaseous energy combustion pollution in various regions of China, provide reference for the future development of various regions, and have important practical significance for the reduction and balance of pollution levels. [ABSTRACT FROM AUTHOR]

The highlighted energy consumption of Internet data center (IDC) in China has become a pressing issue with the implementation of the Chinese dual carbon strategic goal. This paper provides a comprehensive review of cooling technologies for IDC, including air cooling, free cooling, liquid cooling, thermal energy storage cooling and building envelope. Firstly, the environmental requirements for the computer room and the main energy consumption items for IDC are analyzed. The evaluation indicators and government policies for promoting green IDC are also summarized. Next, the traditional cooling technology is compared to four new cooling technologies to find effective methods to maximize energy efficiency in IDC. The results show that traditional cooling consumes a significant amount of energy and has low energy efficiency. The application of free cooling can greatly improve the energy efficiency of IDC, but its actual implementation is highly dependent on geographical and climatic conditions. Liquid cooling, on the other hand, has higher energy efficiency and lower PUE compared to other cooling technologies, especially for high heat density servers. However, it is not yet mature and its engineering application is not widespread. In addition, thermal energy storage (TES) based cooling offers higher energy efficiency but must be coupled with other cooling technologies. Energy savings can also be achieved through building envelope improvements. Considering the investment and recovery period for IDC, it is essential to seek efficient cooling solutions that are suitable for IDC and take into account factors such as IDC scale, climate conditions, maintenance requirements, etc. This paper serves as a reference for the construction and development of green IDC in China. [ABSTRACT FROM AUTHOR]

The role of the transparent envelope in energy savings is crucial as it accounts for a significant proportion of the total energy loss (between 30 and 40%). This paper focuses on the identification of reasonable parameters for the transparent envelope in different climatic regions. To achieve this goal, typical urban office buildings from four different climatic regions are used as research objects. A total of 1600 scenarios were simulated to investigate the variation of energy use intensity, including transparent envelope parameters, meteorological parameters and different types of glazing. The results show that for south-facing transparent envelope facades, type D glazing is the most energy efficient in severe cold regions, type C in colder regions and type B in the other two climatic regions. No solar shading is required in the very cold region. Horizontal shading can be an effective method for saving energy in colder climates, while comprehensive shading can be beneficial in other regions. Deep shading is particularly energy efficient if it meets lighting requirements. For example, in Guangzhou, energy savings of 13.46%, 15.47%, 7.01% and 7.02% can be achieved in the east, west, south and north directions, respectively, using B-type glazing and a comprehensive shading depth of 900 mm. [ABSTRACT FROM AUTHOR]

China will strive to achieve a 'dual carbon' target: 'carbon peak' by 2030 and 'carbon-neutral' by 2060. In this context, improving the efficiency of renewable energy and reducing the use of thermal power are important ways to achieve the target. Clean, efficient and large-capacity energy-storage technology is the key to improving the utilization rate of renewable energy. First, this paper proposes to use compressed-air energy-storage technology instead of the old energy-storage technology to build an economical and environmentally friendly comprehensive energy park capacity optimization configuration model. Second, this paper uses the newly proposed improved chicken swarm optimization algorithm to solve the model, which is more accurate and faster. Finally, this paper analyzes a comprehensive energy park in north-west China. Through case analysis, it can be seen that the average utilization rate of renewable energy can reach 73.87% through the model proposed in this paper, while the average power-abandonment rate is only 9.32%. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is an important measure of environmental governance. At present, studies on the impact of high-speed rail on energy efficiency need to be further studied. This paper constructs panel data of 285 cities at prefecture-level and above in China from 2003 to 2017, and uses the difference-in-difference (DID) to study the impact of high-speed railway on urban energy efficiency. Based on the theories of "factor flow," "knowledge spillover," and "center-periphery," this paper discusses the influence mechanism and heterogeneity of high-speed railway on energy efficiency. The empirical results show that high-speed railway can significantly improve energy efficiency, and the conclusion is still valid after parallel trend test, propensity score matching and difference-in-difference (PSM-DID) test, and instrumental variable method. The results remained true after a series of robustness tests. Mechanism analysis shows that high-speed railway can improve energy efficiency by promoting industrial structure upgrading, technological innovation, and market integration. Analysis of heterogeneity shows that the promotion effect of high-speed railway on energy efficiency is greater in central and western cities and core cities. This study provides useful enlightenment for optimizing China's high-speed rail construction planning and seizing the opportunity of high-speed rail development to improve energy efficiency. [ABSTRACT FROM AUTHOR]

With the rapid growth rate of China's economy, the extensive pattern of economic growth of "high energy consumption and low output" has magnified the constraints of energy issues on China's economic development and environmental protection, which highlights the importance of improving energy efficiency. As one of the three major economic zones in China, the Pearl River Delta region also faces high energy consumption and pollution emissions while developing at a high speed. Hence, improving the energy efficiency of the Pearl River Delta region is needed, as it not only is conducive to driving its development of the surrounding green economy, but also promotes the subsequent sustainable economic development. However, there are few literatures on the calculation and analysis of energy efficiency in the Pearl River Delta, and lacking a systematic analysis of input–output index system of energy efficiency measurement. Therefore, this paper calculates the energy efficiencies and the Malmquist indexes based on the panel data of the nine cities in the Pearl River Delta from 2005 to 2019 through super-efficiency SBM model and Malmquist index method by using MAXDEA and MATLAB software. The result illustrates that all regions in the Pearl River Delta except Guangzhou and Shenzhen show obvious energy inefficiency, which is mainly caused by the imbalance between technical efficiency and scale efficiency. Based on the calculation results, this paper gives some relevant suggestions for the further approach of energy reform in the Pearl River Delta according to the calculation results. [ABSTRACT FROM AUTHOR]

To cope with climate change, China commits that it will strive to achieve carbon peaking by 2030. Using the Cointegration model and the Markov Chain model, this paper forecasts China's carbon emissions during 2019–2030 in six scenarios, and assesses the contribution of optimizing the energy mix to China's carbon peaking. The research obtains three main conclusions. Firstly, optimizing the energy mix will contribute to achieving China's carbon peaking. In the economic slow-growth scenario, taking China's planned target of energy mix (PTEM) into account, the carbon peaking year will be brought forward from 2028 to 2023. In the economic medium-speed-growth scenario, optimizing the energy mix will make China achieve carbon peaking in 2028. Without considering the PTEM, however, the carbon emissions will not peak before 2030. In the economic fast-growth scenario, the peaking year will not occur whether considering the PTEM or not, but the growth rate of carbon emissions with the PTEM will be far lower than that without considering the PTEM. Secondly, in all three economic growth scenarios, optimizing the energy mix will largely reduce the growth rate of carbon emissions, and thus significantly reduce the peak value of carbon emissions. Thirdly, optimizing the energy mix has a negative adjusting effect on the impact of economic growth on the growth rate of carbon emissions, and the negative effect rise as the economic growth rate increases. [ABSTRACT FROM AUTHOR]

With the development of energy technology, hydrogen is gradually becoming widely used. China is also rapidly developing its own hydrogen energy industry in an effort to accomplish the "dual carbon target'. Hydrogen from methane is one of the mainstream sources, of which hydrogen from methane cracking is the decomposition of methane into hydrogen and solid carbon, with the solid carbon also having a high economic value. In particular, this technology does not emit carbon dioxide, which is very friendly to the environment, but it cannot avoid larger energy consumption. In contrast, hydrogen production from methane cracking driven by solar energy not only combines the characteristics of no CO 2 emission, but also greatly reduces the consumption of primary energy, which is the future development trend of hydrogen production from methane. This paper provides a brief overview of the various technological pathways for methane to hydrogen production in the context of China's actual development, focusing on the current status of the development and application of solar methane cracking to hydrogen production technologies at home and abroad. Among them, this paper mainly discusses the characteristics of solar reactors of different sizes and structures, and summarizes the results of related optimization studies. Meanwhile, the application of catalysts in solar reactors and the problem of carbon deposition are analyzed, and the practical application of solar methane cracking hydrogen production system is outlined. Finally, the future development of solar methane cracking hydrogen production technology is prospected from the national situation of China. [Display omitted] • Solar methane cracking for hydrogen can reduce emissions and energy consumption. • The current state of research on solar reactors is summarized. • Solar methane cracking requires higher performing catalysts. • Providing insights into the future development of solar methane cracking in China. [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]

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

In the context of increasing global resource and environmental problems, it is of great practical significance to accurately test the impact of various factors on energy use efficiency for maintaining national energy security and formulating relevant policies. This paper measures firms' total factor energy efficiency (TFEE) using the two-stage stochastic frontier method within the data envelopment analysis (DEA) framework, leveraging data from listed firms in China spanning 2010 to 2022. Employing the establishment of free trade zones (FTZs) as a quasi-natural experiment, we apply the staggered differences-in-differences (DID) and stacked DID methods and analyze the impact of FTZs on firms' TFEE. The results show that the establishment of FTZs significantly promotes the improvement of firms' TFEE, and it has a greater promotion effect on heavily polluting, non-manufacturing, state-owned, private, and small-scale firms. The results of the mechanistic analysis showed that the promotion effect of FTZs on firms' TFEE is mainly realized through three channels: increasing government subsidies, reducing the financing constraint effect, and encouraging the technology innovation effect. Furthermore, industry-level decomposition results indicate that the surge in industry energy efficiency primarily results from improvements within firms rather than inter-industry variations. This paper's results propose that countries can enhance energy efficiency by progressively endorsing the implementation of FTZs. [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]

Promoting high-quality economic development, boosting high-level ecological environment protection, and integrating deeply digital economy and energy efficiency has become a general trend. This paper, based on 284 prefecture-level Chinese cities from 2008 to 2018, uses the entropy weight method and super-efficient SBM-DEA model to measure the digital economy and energy efficiency (decompose into energy pure technical efficiency and energy scale efficiency), respectively. After the spatial and temporal evolution characteristics, a fixed-effect model is constructed to study the impact of the digital economy on energy efficiency. The research results show that: (1) the development of the digital economy effectively promotes energy efficiency, mainly reflected in the improvement of pure technical efficiency of energy; (2) the development of both the digital economy and the energy efficiency in China has complex spatial and temporal evolutionary characteristics, and there is heterogeneity in the impact of the digital economy on energy efficiency at the temporal and spatial levels; and (3) digital economy effectively improves energy efficiency by reducing unnecessary energy consumption through the R&D innovation effect. The development of the digital economy has far-reaching significance on the optimization and upgrading of the economic system, accelerating the improvement of energy efficiency and achieving green transformation. [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]

The behaviors of local governments can affect the enforcement of environmental regulations. Environmental regulation can influence the behaviour of energy-intensive enterprises. This paper examines the relationship between local government competition, environmental regulation and the investment efficiency of high energy consuming firms using a basic panel regression and moderating effects model based on data from 2011-2020 for high energy consuming firms in China. The paper found that local government competition and environmental regulation can promote increased investment efficiency in energy-intensive firms in the short term. However, environmental regulation is not beneficial to investment efficiency in the long run. Local government competition plays a positive moderating role in the impact of environmental regulation on the investment efficiency of high energy consuming firms. There is a threshold effect on the role of local government competition. When the level of government competition exceeds 2.097, it has a negative impact on the investment efficiency. We further test for heterogeneity and we find that this promotion effect is also more obvious in areas with high environmental taxes and low marketability. Finally, we provide constructive suggestions for the development of government and the improvement of the investment efficiency of high energyconsuming firms. [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]

Recycling carbon tax revenue is a significant part of the design of a nation's carbon tax system. The impact of different recycling principles on the socio-economy and carbon emission reduction varies greatly. Under the background of China's goal of reaching peak carbon emissions, this paper designed three carbon tax recycling principles based on the goal of Nationally Determined Contributions (NDCs), including recycling principles based on output ratio, export ratio, and carbon intensity. A recursively dynamic CGE model was developed in this study to evaluate the economic effects of these three carbon tax recycling principles based on tax neutrality under China's goal of reaching peak carbon emissions. Carbon tax recycling measures could mitigate the economic losses caused by carbon tax, and the results could be greatly affected according to different recycling principles. The results showed that: 1 The recycling principle based on output ratio could reduce economic losses and improve households' social welfare. 2 China's carbon intensity in 2030 could be reduced by more than 65% compared with that in 2005, and the proportion of non-fossil energy in primary energy consumption could reach 25% using the recycling principle based on carbon intensity, but the economic loss mitigation effect of the recycling measures based on this principle was small. 3 Adopting the recycling principle based on export ratio would narrow the competitive gap between China and foreign countries, and the exports of high-carbon-intensity goods would not increase under this principle. 4 According to principles based on output ratio and export ratio, the NDC goal of non-fossil energy accounting for about 25% of primary energy consumption by 2030 could not be achieved, and only the NDC goal of reducing carbon emissions per unit of GDP by more than 65% compared with that of 2005 could be achieved. In brief, as an essential policy tool to achieve China's goal of reaching peak carbon emissions, the carbon tax should be implemented as soon as possible. At the same time, according to China's national conditions, a targeted choice of carbon tax recycling principle is needed. The role of the carbon tax in the process of achieving the goal of Nationally Determined Contributions should be fully utilized. [ABSTRACT FROM AUTHOR]

With the implementation of China's carbon-peaking and carbon-neutrality strategy, new energy will achieve leapfrog growth. Due to the good economics of distributed new-energy generation, it can not only save users' own investment, but also help to achieve local consumption of new energy. However, it will also bring about a series of incremental costs to the power grid. This paper first enumerates the concept, development status and scheduling mode of a distributed new-energy storage system. Based on the above, it establishes a new-energy power generation model and an energy storage system charging and discharging model, and proposes a global optimization scheduling model for a distributed new-energy storage system, considering the time-of-use electricity price and taking the lowest total operating cost of the distributed new-energy power generation system as the objective function. Finally, it proposes a distribution network incremental cost analysis model based on the penetration of distributed new energy. The calculation results show that the incremental cost of grid-connected distributed new energy is 1.0849, 1.2585 and 1.3473 yuan/kWh, respectively, which indicates that the global dispatching model can optimize the power consumption structure of a distributed power generation system, and has the function of peak shaving and valley filling, but the incremental cost of the distribution network will also increase. [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]

The development of renewable energy in China has made remarkable achievements, but the problem of renewable energy consumption has become increasingly prominent. This paper establishes a power market trading system for renewable energy, with the aim of promoting large-scale renewable energy consumption and increasing the enthusiasm of renewable energy producers and users to participate in market transactions. First, according to the power generation cost, the backup cost of renewable energy power plants and the possible quotation strategies of other renewable energy producers, a quotation model of renewable energy producers is established. In the clearing of the spot market by renewable energy producers, the independent market operator conducts the first-stage clearing of the electricity market with the goal of maximizing social welfare. After the announcement of the clearing results, the renewable energy producers that did not win the bid will revise their quotations and carry out the second stage clearing to realize the consumption of renewable energy. In this paper, the particle swarm algorithm combined with the CPLEX solver is used to solve the problem, and finally, different scenarios are analyzed through example analysis. The results show that, compared with the conventional power market trading mechanism, the energy abandonment rate of the power market trading mechanism for renewable energy proposed in this paper drops from 8.2% to 2.1%, and the profit margin of renewable energy producers increase by 6.6%. It is demonstrated that the proposed electricity market mechanism can effectively promote the consumption of renewable energy and increase the income of renewable energy producers. [ABSTRACT FROM AUTHOR]

Energy efficiency is the key to green development, and the government plays a vital role in energy efficiency. This paper clarifies the mechanism by which the Yangtze River Delta Economic Coordination Committee affects the energy efficiency of urban agglomeration by promoting market integration. Based on panel data of China's prefecture-level cities from 2004 to 2017, we take the Yangtze River Delta Economic Coordination Committee as a quasi-natural experiment of government cooperation and use the difference-in-difference method to test whether this organization has enhanced the energy efficiency of urban agglomeration. The results show that the Yangtze River Delta Economic Coordination Committee can significantly improve energy efficiency in urban agglomerations. The mechanism analysis shows that it reduces the energy consumption per unit of gross domestic product by enhancing the marketization level, perfecting the relationship between the government and the market, and improving the factor market development. The heterogeneity analysis shows that cities with lower city size, lower level of innovation, and cleaner industrial structures gain more benefits in energy efficiency from government cooperation in urban agglomeration. This paper provides empirical evidence for cities to realize integrated energy conservation through government cooperation and market integration. [ABSTRACT FROM AUTHOR]

Saving energy is an important strategy to address the current energy crisis and environmental degradation. Regarding the pilot policy of the energy quota trading as a quasi-natural experiment by employing a difference-in-differences method, the purpose of this paper is to investigate the effect of this pilot policy on energy saving and its mechanisms based on city-level data in China from 2006 to 2020. We find that the energy quota trading policy can reduce the total energy consumption and energy consumption intensity of pilot cities, and the effect of the policy can gradually strengthen over time. The market-oriented reform of energy factor allocation can effectively promote energy saving and economic growth. These results are convincing through a series of robustness checks. The heterogeneity test shows that the energy quota trading has a significant energy saving effect on economically developed cities, densely populated cities and southern cities, but not in economically underdeveloped cities, sparsely populated cities and northern cities. Further mechanism inspection suggests that the pilot policy of energy quota trading mainly achieves energy conservation through industrial structure upgrading and green technology innovation. Our findings provide a valuable insight for China to control energy consumption and promote the high-quality development of the energy economy. [ABSTRACT FROM AUTHOR]

(1) Background: The decoupling of energy consumption from economic growth in the construction industry is crucial to the sustainable development of the global construction industry. The existing studies focus on the advancements in energy efficiency by designers for building monoliths or construction techniques, involving no exploration of energy efficiency management from a regional perspective, which is unfavorable for the formulation of energy efficiency policies and systematic control of the construction industry by local governments. (2) Methods: From the perspective of regional management, this paper constructs an integrated analysis and application framework of "spatio-temporal characteristics + matching evaluation + policy design" based on the decoupling model and GIS tools. It studies the spatio-temporal characteristics of energy consumption in the construction industry in 30 provinces of China from 2010 to 2019, and its decoupling relationship with the economic development of the construction industry, and proposes an optimal zoning and recommendations for energy consumption in the construction industry, providing a reference for energy conservation management in the construction industry in China. (3) Results: First, the change of energy consumption amount (ECA) in the construction industry in the provinces was dominated by ascent, while the energy consumption intensity (ECI) predominantly decreased, and most provinces are still in a period of growth or plateau in energy consumption. Second, ECA and ECI had prominent spatial heterogeneity and aggregation. High-energy-consuming regions are concentrated along the coast and along the Yangtze River, while low-energy-consuming regions are mainly clustered in remote areas, such as the northeast, northwest, and southwest of China. Energy consumption shows a clear north-south difference in intensity, with high-intensity regions clustered in the north compared to low-intensity regions in the south. Third, most of the provinces were in strong negative decoupling, expansive coupling, and weak decoupling, and better decoupling regions were mainly gathered in south and central China. Nearly one half of these provinces showed decoupling degradation and only a few achieved evolution, with evolutionary regions clustered mainly in central and southern China. The northeast and northwest were the key problem areas of energy-saving transformation in China's construction industry. (4) Conclusion: The 30 provinces were divided into three types: leader, intermediate, and laggard, and the development goals and suggestions on low energy consumption in the construction industry for three zones were put forward, significantly improving the precision of policy design and implementation. The study in this paper expands the research perspective on energy saving management in the construction industry and provides a methodology and basis for developing energy efficiency policies and plans for the construction industry in China and similar developing countries. [ABSTRACT FROM AUTHOR]

Since their inception with Bitcoin in the late 2000s, cryptocurrencies have grown exponentially, reshaping traditional financial paradigms. This transformative journey, while innovative, brings forth pressing concerns about their energy consumption and carbon footprint. While many studies tend to zoom in on Bitcoin, this paper broadens the perspective by evaluating energy consumption across various cryptocurrencies. We analyze nine cryptocurrency projects, chosen for their market value, technology, and data availability. These span a spectrum from pioneering to emerging digital coins, offering a holistic view of the crypto realm. To contextualize, we juxtapose the energy usage of these digital currencies with traditional payment means like Visa and Mastercard. Our analysis shows vast differences in energy use among cryptocurrencies, largely tied to their consensus algorithms. Notably, while Bitcoin stands out as highly energy-intensive, several newer digital currencies have energy footprints mirroring those of conventional payment methods. Additionally, CO2 emissions estimation presents challenges due to variances in miner locations and regional energy sources, with potential higher emissions if concentrated in carbon-intensive regions like China. Nonetheless, the silver lining emerges as many cryptocurrencies, especially those beyond Bitcoin, register considerably lower CO2 emissions. By moving the lens beyond Bitcoin, this paper paints a more nuanced picture of the environmental ramifications of the crypto world. [ABSTRACT FROM AUTHOR]

China has abundant agricultural and forestry waste resources that are crucial sources of energy for substituting fossil fuels and achieving the carbon peaking and carbon neutrality goals. These resources play an essential role in reducing carbon dioxide emissions and promoting sustainable development. This paper presents an estimation of the number of biomass resources that can be used for energy in 2020 by using parameters such as the grass-to-grain ratio coefficient and excretion coefficient. Moreover, the potential for conversion of biomass resources into biomass energy is evaluated by using parameters such as lower heating value and gas production coefficient. Finally, based on the whole life cycle theory, the potential of biomass energy utilization to reduce carbon dioxide emissions and its impact on carbon peaking is calculated. It was found that the total amount of fossil fuels that can be replaced by biomass energy is 256 million tons of standard coal. Utilizing biomass energy can reduce carbon dioxide emissions by approximately 520 million tons, with a peak impact of 4–6% on carbon peaking. The research results presented in this article can provide valuable data to support the promotion of green transformation in various regions. The findings can serve as a useful reference for formulating localized biomass utilization plans and designing effective emission reduction policies. [ABSTRACT FROM AUTHOR]

Urban carbon emissions are one of the most important areas contributing to the growth of carbon emissions, and resource-dependent cities with natural resource extraction and processing as their leading industries tend to have higher carbon emissions. Ordos is the city with the highest coal production in China, and its economic development is dominated by coal, oil and gas, and other resource extraction and processing industries, with industrial activities making a large contribution to carbon emissions. At the same time, Ordos has undergone rapid industrialization in recent years, but still faces the problem of environmental pollution, epitomizing a typical resource-dependent city in China. Therefore, this paper takes Ordos as an example and uses the Generalized Divisa Index Method (GDIM) to study the drivers of industrial carbon emissions in Ordos from 2005–2020, a typical resource-dependent city in China, and further analyzes are conducted in relation to the three phases of development. Based on the key drivers, the Monte Carlo method is used to forecast industrial carbon emissions from 2021 to 2030. The results show that the most important factors driving the growth of industrial carbon emissions are the scale of industrial output and industrial energy consumption, while the intensity of industrial energy investment is the most important factor mitigating industrial carbon emissions, and that energy efficiency and carbon intensity of energy consumption can also mitigate carbon emissions after economic transformation. At the same time, investment is the factor with the greatest potential for optimization on the path to emissions reduction. [ABSTRACT FROM AUTHOR]

With the construction of a new-type power system under the China "double carbon" target and the increasing diversification of the energy demand on the user side, the short-term load forecasting of the power system is facing new challenges. To fully exploit the massive information contained in data, based on the graph convolutional network (GCN) and long short-term memory network (LSTM), this paper presents a new short-term load forecasting method for power systems considering multiple factors. The Spearman rank correlation coefficient was used to analyse the correlation between load and meteorological factors, and a model including meteorology, dates, and regions was established. Secondly, GCN and LSTM are jointly used to extract the spatial and temporal characteristics of massive data, respectively, and finally achieve short-term power load prediction. Historical electrical load data from 2020 to 2022 public data of a real industrial park in southern China were selected to verify the validity of the proposed method from the aspects of forecasting accuracy, feature dimension, and training time. [ABSTRACT FROM AUTHOR]

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

Improving green energy efficiency is crucial to promoting China's high-quality economic development and reducing the environmental pollution. In this paper, the Malmquist-Luenberger index measures the green energy efficiency of 30 provinces in China from 2004 to 2019. Based on the measurement results, the spatial Durbin model is used to empirically study the impact of environmental regulation on green energy efficiency and its spatial spillover effects. The results show that China's green energy efficiency is low, and its growth mainly comes from technological progress (TECH) rather than technological efficiency (EFFCH). The eastern region has the highest efficiency of green energy, followed by the West and the lowest in the Central region. The estimation results of the spatial Durbin model show that both environmental regulation and green energy efficiency have a significant spatial correlation. Environmental regulation can improve the green energy efficiency in the local province but inhibit green energy efficiency in the adjacent provinces. Finally, this paper puts forward relevant policy suggestions according to the research results. [ABSTRACT FROM AUTHOR]

Traditional historical buildings carry the culture and spirit of China for thousands of years and have a unique charm that modern buildings do not have. However, traditional historical buildings have gradually declined over time, and their restoration not only takes time and materials but also causes certain harm to the environment. Therefore, this paper has aimed to explore how traditional historical buildings can develop in a sustainable and ecologically adaptive image in modern times. For traditional historical buildings, this paper has taken traditional cave dwellings in northern Shaanxi as an example to analyze their ecological adaptability, and based on the analysis results, traditional cave dwellings have been transformed. Specifically, this paper has taken the comfort of residential houses as the evaluation standard and has selected the thermal stability of the building and the energy consumption of heat supply as indicators to compare and analyze the traditional cave dwellings and the renovated cave dwellings. The experimental results of this paper have found that the traditional historical buildings are the crystallization of the wisdom of the ancients for thousands of years. However, due to the limitation of technology, the lighting and thermal stability of traditional cave dwellings are not high. After scientific design, the lighting and thermal stability of the transformed cave are 100% and 30% higher than those of the traditional cave, respectively, and the heating energy consumption is reduced by 50%. [ABSTRACT FROM AUTHOR]

In order to accurately predict China's future total energy consumption, this article constructs a random forest (RF)–sparrow search algorithm (SSA)–support vector regression machine (SVR)–kernel density estimation (KDE) model to forecast China's future energy consumption in 2022–2030. It is explored whether China can reach the relevant target in 2030. This article begins by using a random forest model to screen for influences to be used as the input set for the model. Then, the sparrow search algorithm is applied to optimize the SVR to overcome the drawback of difficult parameter setting of SVR. Finally, the model SSA-SVR is applied to forecast the future total energy consumption in China. Then, interval forecasting was performed using kernel density estimation, which enhanced the predictive significance of the model. By comparing the prediction results and error values with those of RF-PSO-SVR, RF-SVR and RF-BP, it is demonstrated that the combined model proposed in the paper is more accurate. This will have even better accuracy for future predictions. [ABSTRACT FROM AUTHOR]

In several rural areas of China, ecological public welfare work is an effective way to improve farmers' social participation. This job does not only increase farmers' income but also greatly improves their enthusiasm for ecological environment protection. Under the goal of carbon neutrality in peak carbon dioxide (CO2) emissions, it is necessary to explore the impact of ecological public welfare jobs on the usage of Clean Energy (CE) in rural areas. Based on the data of 1100 farmers from Tibet areas in China, this paper applied the Ordered Probit model to explore the impact of ecological public welfare jobs on farmers' use of CE. The results are as follows: (1) Holding ecological public welfare jobs can raise farmers' willingness to use CE; (2) Holding ecological public welfare jobs can also promote farmers' use of CE by enhancing their ecological environment cognition and influencing their social behavior; (3) The impact of ecological public welfare work on CE use has regional and income heterogeneities. Firstly, this effect is smaller in mixed pastoral-farming areas than in agricultural and pastoral areas. Secondly, this effect is more obvious in low-income groups. Our study provided several policies aimed at improving rural and environmental development. [ABSTRACT FROM AUTHOR]

The significant acceleration of China's urbanization process has greatly promoted economic development. At the same time, the massive construction of urban buildings has also caused many problems such as environmental pollution and increased energy consumption. Therefore, in architectural design, it is particularly important to pay attention to the sustainable development of the environment, handle the relationship between good people and nature under the guidance of the concept of green development, and focus on the recycling of resources. Focusing on resource utilization in architectural design and based on certain planning can better control the construction process of urban buildings, save energy consumption, reduce construction costs, and contribute to the green development of cities. The comprehensive evaluation of energy conservation and emission reduction of construction projects is a classical MAGDM problems. Recently, the Logarithmic TODIM (LogTODIM) method has been employed to cope with MAGDM issues. The single-valued neutrosophic sets (SVNSs) are used as a tool for characterizing uncertain information during the comprehensive evaluation of energy conservation and emission reduction of construction projects. In this paper, the single-valued neutrosophic number Logarithmic TODIM (SVNN-LogTODIM) method is built to solve the MAGDM under SVNSs. In the end, a numerical case study for comprehensive evaluation of energy conservation and emission reduction of construction projects is given to validate the proposed method. [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]