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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]

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 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]

Currently, coal is still the main energy source for China's economic development, and the environmental issues caused by coal consumption have aroused widespread concern. Predicting and analyzing coal consumption will help to formulate a higher level of energy consumption planning and economic development strategy. The main purpose of this study is to develop a new fractal time-series prediction (FTSP) model to predict coal consumption, providing reference for formulating effective energy consumption planning and economic development strategies. Hurst index is an important indicator of whether time-series data have long memory and fractal characteristics. This paper uses the rescaled range (R/S) method to calculate Hurst index of the coal consumption per-10000-Yuan-GDP (CC/GDP). The Hurst index is 0.8025, exceeding 0.5, indicating that the time-series data CC/GDP has a long memory and fractal characteristic. Based on this, this paper uses the FTSP model to predict China's coal consumption (CC/GDP). The prediction results show that the FTSP model accurately predicted China's coal consumption with a relative error rate (RER) of less than 5% and a mean absolute percentage error (MAPE) of 6.62%. The model predicts a decrease in China's coal consumption from 0.25 tons of standard coal in 2021 to 0.11 tons of standard coal in 2030, a decrease of 44%. To sum up, the FTSP model provides a new and accurate way to predict coal consumption, and the results suggest that China's coal consumption is sustainable and will decrease significantly in the coming years. This study has important implications for energy consumption planning and economic development strategies. [ABSTRACT FROM AUTHOR]

To protect energy resources and alleviate environmental pollution, many countries attach great importance to the transformation of traditional industries into clean energy industries. In this paper, fuel vehicles (FVs), hybrid vehicles (HVs), and electric vehicles (EVs) are included in the research. Then, based on the aging chain and coflow theory of SDs, we construct a dynamic matching model of the auto industry upgrade process and its energy consumption attributes. The simulation results of China's auto industry show that (1) the upgrading of the auto industry is an evolutionary process from high energy consumption and high pollution to low energy consumption and no pollution and the transition from FVs and HVs to EVs will undergo two adjustments; (2) simply reducing energy supply does not have the expected impact on vehicle size and vehicle energy consumption intensity and only by adjusting the energy supply and upgrade ratios together, energy utilization efficiency can be improved; (3) market screening time has an impact on auto industry upgrade speed by affecting vehicle market share and dwell time; (4) China's auto industry upgrade process should adhere to "problem-oriented" and strengthen consumer guidance, technology innovation, and infrastructure construction. The conclusions can provide references for industrial policy adjustment and industrial structure optimization. [ABSTRACT FROM AUTHOR]

A significant corridor under the "Belt and Road Initiative" is announced by the government of China for numerous transport and energy projects. China focuses greatly on the sustainability of these projects, in accordance with Green Investment Principles. For this, environmental, social, governance, and technological considerations are taken into account. This paper offers a novel assessment of the impact of green sustainability under BRI and the current emission scenario in Pakistan. The question that needs to be addressed here is whether the projects under Belt and Road Initiative are as environment friendly as they claim. In the first phase of this study, we review theories establishing evidence based on existing literature to determine the influence of Belt and Road on economic development. In the next phase, we use Environment Kuznets Curve and apply estimates from Johansson's Cointegration Test to quantify the present environmental scenario of Pakistan and probable environmental risk portrayed by the China-Pakistan Economic Corridor (CPEC). This paper helps in determining the relationship between carbon emission and three major variables including energy consumption, economic growth, and foreign direct investment (FDI). Cointegration analysis is applied on time series data comprising of a 40 years' period from 1979 to 2019. The paper finds that (i) the belt and road corridors could substantially improve trade, foreign investment, and living conditions for citizens in participating countries; (ii) moreover, this study confirms the presence of one cointegrated equation suggesting the presence of a long term relationship between the CO2 and independent variables and a short run association running from EnC to CO2. The study also proposes a Green BRI Model which formulates a body that devises environmental performance standards, reviews procedures, and ensures that they get implemented on all CPEC projects. The Belt and Road Initiative increases emissions among participating countries. China and corridor economies need to adopt strict policy reforms that increase transparency, expand trade, improve debt sustainability, and mitigate environmental, social, and corruption risks. [ABSTRACT FROM AUTHOR]

In recent years, with the gradual implementation of the central government's policy of expanding domestic demand, the living standards of urban residents have been greatly improved. With the increasing level of urban living consumption, residents' living consumption situation has attracted more attention and attention. In order to further increase the consumption income of households, it is necessary to conduct corresponding analysis on households in various regions. Based on SPSS statistical simulation software, this paper uses factor analysis and clustering methods often used in modern multivariate economic statistical analysis to establish multivariate statistical models and calculate and establish various analysis models suitable for my country's household consumption expenditure structure (2020) and analyze the parameters, accordingly. From the perspectives of politics, economy, geography, etc., this paper reveals the changes in energy consumption in China's family and social life and its possible implied related information, laws, directions, and the overall development level of society. Through empirical analysis and research, this paper can finally conclude that the current consumption expenditure structure of Chinese households is affected by a combination of factors such as national policies, economic development and technical conditions, and geographical environment characteristics, and the effect is different in different cities. [ABSTRACT FROM AUTHOR]

To clarify whether there is a spatial correlation problem among China's provincial energy consumption, economic growth, and ecological environment, this paper adopts the panel data of 31 provinces in China from 2008 to 2019 and uses a spatial data analysis method. This work studies economic growth and the spatial distribution pattern of the ecological environment, as well as the spatial effects of its energy consumption and economic growth on the ecological environment. Moreover, the spatial autocorrelation model, spatial-temporal transition method, and generalized moment estimation method are adopted to conduct empirical analysis on the research object. The results show that (1) there are spatial correlations among energy consumption, economic growth, and the ecological environment in China's provinces, and there are obviously different agglomeration areas in spatial distribution; (2) energy consumption, economic growth, and the ecological environment level show different growth trends, and the differences between different provinces in provincial units are shrinking; and (3) regarding energy consumption, the spatial impact of economic growth on the ecological environment is obvious, and there are obvious "path dependence" characteristics in the spatial distribution and positive correlations. Finally, this paper puts forward research conclusions and relevant suggestions on the basis of empirical analysis. [ABSTRACT FROM AUTHOR]

The household energy consumption has been a hot field in the study of household energy consumption in recent years. With the increase of residents' income level and the pushing of urbanization, there is a complex nonlinear relationship between energy price and energy consumption. The purpose of this paper is to investigate the scenario effect of per capita income and regional differences in urbanization development on the relationship between electricity sales price and urban household electricity consumption. To this direction, based on the regional characteristics of economic development in China, with the residents' disposable income and the urbanization level as the conversion variables and the electricity sales price as the core explanatory variable, the panel smooth transition regression (PSTR) model of electricity sales price and urban household electricity consumption from the perspectives of income level and urbanization has been constructed in this paper. The empirical results show the following: (1) Under the consideration of regional difference of residents' income level, with the increase of residents' disposable income level, there is a significant negative correlation between electricity sales price and urban household electricity consumption in the whole country, the eastern region, and the central region, while such correlation is significantly positive in the western region. (2) Under the consideration of the difference of urbanization development level, the national regional electricity sales price and the urbanization level are positively related to the urban household electricity consumption, and the urbanization level in the western region plays the biggest role in promoting the urban household electricity consumption, followed by the eastern region and then the central region which plays the smallest role. This paper discusses the effect of electricity sales price on urban household electricity consumption from the perspective of regional difference in income and urbanization, which provides the decision-making basis and empirical support for developing regional electricity price policy and household energy consumption policy. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the mechanism and process of the dynamic evolution of the economy-energy-environment (EEE) system and study the variables that determine the speed of system evolution and development. The innovation is to overcome the defect of single index by constructing a system evaluation index and reveal the regional EEE system's evolution mechanism based on Haken's synergetic theory to supplement a systematic perspective's empirical evidence. It selects 30 provinces, municipalities, and autonomous regions in China to empirically analyse the evolution mechanism of the EEE system from 2005 to 2019. The empirical results show that economic development is the order parameter of the evolution and development of the EEE system. In the process of system evolution, the economic development subsystem is the decisive factor in EEE system evolution. In terms of the positive feedback mechanism of order parameter combination, the EEE system forms a positive feedback mechanism for increasing economic development in the stage of evolution and development. The negative feedback mechanism of decreasing environmental pollution emissions is formed in the EEE system. The increase in pollutant emissions has a certain inhibitory effect on economic growth. The improvement in the economic development level has no promoting effect on pollutants, and economic development, in turn, reduces environmental pollution. [ABSTRACT FROM AUTHOR]

The utilization efficiency of China's rural collective resource assets has always been at a low level, and excessive energy consumption and input have become the main limiting factor, which seriously affects the overall improvement of agricultural modernization and rural people's livelihood. In this paper, time measure and space measurement are adopted alternatively, and spatiotemporal vertical-horizontal progressive deduction is built with the improved model, so as to set up a perfect spatiotemporal dynamic effect evaluation system: First of all, improve the U-HDM-GML index model, study on the improvement strategy for input redundancy and unexpected output redundancy in the utilization efficiency of rural collective resources assets in various provinces of China, as well as the equilibrium rupture relation between the two from the perspective of global space and time, and at the same time of fulfilment of time measurement and estimation, provide support for better expressing the spatial effect in terms of improving approach and strategy; secondly, measure the improvement strategy of the total factor productivity of research samples with the spatial expletory ESDA test method, and it is also applicable to global spatial effect evaluation system; finally, apply FE-SDM to further analyze the difference of spatial effect of total factor productivity in rural resource asset utilization. Through analysis of the significant difference characteristics of the research samples with different geographical and spatial characteristics, the strategy deficiency in terms of difference discrimination is made up. Conclusions. This paper carries out the time and spatial effect measurement of total factor productivity for the performance of pilot strategies in various provinces of China in the last ten years and puts forward a more beneficial improved strategy and mechanism, preferentially selected according to the direction indicated by good research indicators, gets the redevelopment strategy for improving the utilization efficiency of areas at a low level of resources utilization currently, and indicates the direction for tapping the full potential of existing rural resources according to the practical conditions at local places, in the hope of establishing the trans-provincial cooperation supply and demand system based on the new rural collective economic organizations (cooperatives) after the reform experimentation and optimizing the spatial spillovers of rural resources assets, so as to make a breakthrough in the barrier due to growth of technical efficiency. [ABSTRACT FROM AUTHOR]

As a key means to elevate low-carbon energy transformation in China, multi-energy microgrid accelerates the construction of new power systems. In order to scientifically evaluate the benefits of multi-energy microgrids, we proposed a benefit evaluation index system from the dimensions of economy, reliability, low carbonization, and intelligence. Considering the relationship between the evaluation indicators, this paper innovatively proposed a multi-energy microgrid benefit evaluation model based on AHP-VWT-MEEM. In addition, this paper selected different multi-energy microgrid demonstration projects in the China Southern Power Grid Company Limited's region for example analysis. In the example analysis, through the comparison of the comprehensive benefits of the three projects, the comprehensive benefit of the project 3 is the best. On this basis, from the specific configuration plan of Project 3, it can be concluded that the configuration of larger capacity thermal storage can realize the "thermal decoupling" of cogeneration, thereby improving the flexible adjustment capability of the demonstration area, promoting the consumption of renewable energy, and obtaining more considerable comprehensive benefits. At the same time, it is pointed out that the comprehensive benefit evaluation result can be improved by appropriately reducing the investment cost of project 3. [ABSTRACT FROM AUTHOR]

Taking Hunnan District of Shenyang City as an example, this paper investigates 32 government agencies, 17 tertiary first-class hospitals, and 15 colleges and universities in Hunnan region and analyzes the energy consumption characteristics of three types of public institutions. Through the use of DeST energy consumption software to simulate the energy consumption of three types of public institutions, combined with the load density method to predict the total energy demand of hospitals, universities, and government agencies in Hunnan area and the MARKAL model coupling mechanism, the coupling model of active and passive energy suitable for public institutions is presented. According to the forecast results of energy demand, combined with the energy consumption structure and energy conversion efficiency, the energy supply of each subitem of the public institution was solved and the energy supply of the public institutions in Hunnan District was optimized in accordance with the relevant constraints. Through calculation, it is found that by 2020, the passive energy supply of public institutions in Hunnan District will account for 19.79% and active energy sources such as coal and petroleum will still be the main type of energy used by public institutions. Based on the research on the active and passive energy coupling supply of public institutions in Hunnan District, the active and passive energy coupling model and algorithm of public institutions constructed can provide a reference basis for the active and passive energy coupling utilization of public institutions in China. [ABSTRACT FROM AUTHOR]

Prefabrication is undergoing significant growth in the building and construction sector in China. Meanwhile, the integrated measurement and reduction solution for energy consumption is quickly becoming an important target of scientific efforts and research, especially in prefabricated buildings. Embedded energy consumption requirements can potentially be reduced during the manufacturing process of prefabricated components: the opportunity for its reduction can be significant. This paper aims to propose a BIM and LCA integrated approach that enables the energy consumption of prefabricated components in the manufacturing stage to be extracted and calculated in order to obtain a clear, precise understanding of the energy consumption management in prefabrication. To enhance the energy consumption description of prefabricated components, this paper clarifies the contents of energy consumption inventory and related calculation formula in raw material extraction and production, material transportation, and factorized production of prefabricated components, respectively. Specifically, considering that current Industry Foundation Classes (IFC) standard does not accommodate entities with energy consumption information or relationships, it applies the IFC extension method to connect the energy consumption inventory with the BIM model. The proposed approach is applied and verified in a case study from China. This study reveals that energy consumption control should be investigated in the element level considering the differences of various prefabricated components' requirements in the manufacturing stage. [ABSTRACT FROM AUTHOR]

As new energy vehicle (NEV) is the future of automobile development, it is of great significance to dig deeper into the technical topics and development trends of new energy vehicles for accurately understanding the technical trends of the new energy vehicle industry, grasping development opportunities, and scientifically formulating strategic plans. This paper takes the patent texts in the field of new energy vehicles from 2000 to 2020 in the patent database of CNKI as the data source, identifies 25 technical topics implied in the patent texts by using the LDA (Latent Dirichlet Allocation) topic model, analyzes the evolution trend of the 25 technical topics in terms of importance and popularity, and predicts the popularity and development trend of each technical topic in new energy vehicles from 2021 to 2025 by constructing the ARIMA model. The popularity and development trend of each technology topic of new energy vehicles in China from 2021 to 2025 are predicted by constructing ARIMA model. Drawing on quantitative evidence, the study found that there are top five technical topics in terms of importance in this field, namely, Topic 8 (Installation and Fixation), Topic 5 (Heat Dissipation), Topic 14 (Vehicle Data Monitoring), Topic 9 (Charging Pile), and Topic 15 (Damping). From 2014 to 2020, the importances of Topic 5 (Heat Dissipation), Topic 8 (Installation and Fixation), Topic 6 (Electric Drive System), Topic 9 (Charging Pile), and Topic 15 (Damping) are gradually rising. In terms of popularity of technical topics, from 2014 to 2020, the first to fifth topics are Topic 20 (Safety), Topic 8 (Installation and Fixation), Topic 3 (Cable Insulation Materials), Topic 15 (Damping), and Topic 10 (Pump Cooling). Based on the prediction of ARIMA model, it is found that the popularity of these five technical topics is steadily increasing from 2021 to 2025, among which the popularity of Topic 20 (Safety) will increase from 63.58 to 113.07, the largest increase in popularity among all technical topics. The paper provides implications for countries dedicated to developing the new energy vehicle industry. [ABSTRACT FROM AUTHOR]

Forecasting energy demand accurately is the basis for the formulation and implementation of energy planning. In this paper, energy demand influencing factors are mainly decomposed into scale economy effect, population size effect, energy structure effect, and residential consumption effect based on the Logarithmic Mean Divisia Index (LMDI). Then, the Cointegration and Granger Causality tests are used to discover the influencing factors of energy demand in China. On this basis, a hybrid optimization algorithm, the least-squares support-vector regression optimized by particle swarm optimization (PSO-LSSVR), is proposed to forecast the energy demand of China. Then, three scenarios are set up to analyze the further development of drive factors of energy demand. Finally, in accordance with the forecasting results, some suggestions related to China's energy development policy are given. The main results are as follows. First, gross domestic product (GDP), the total population at the end of the year (POP), the coal consumption ratio in energy (CCR), and residential consumption levels (RCLs) are dominant indicators of energy demand in China. Second, the improved PSO-LSSVR model has significant superiority than other models in energy demand forecasting, a complex and nonlinear system with small samples. Third, China's energy demand will peak in 2022, which is 4.9 million tce in all scenarios. [ABSTRACT FROM AUTHOR]

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

At present, with the development of wireless communication and microcomputer control system, the design and construction level of long-span bridges in China are also improving. How to improve the durability of bridge structure has become a major scientific and technological problem in bridge design and construction. This paper studies a microcomputer control system of bridge dehumidification based on energy consumption optimization and wireless communication. It compares three kinds of dehumidification and anticorrosion methods of bridge engineering, namely, freezing dehumidification system, rotary dehumidification system, and hybrid dehumidification system. In the hardware design of microcomputer control system of dehumidification system, ATmega128 bit main control chip and aluminum designer are used to draw the power circuit. Then, the MCU program of the air dehumidifier is written, and the power of the air dehumidifier is controlled by the PWM signal generated by the timer 0 of the MCU. The air dehumidifier is divided into three tap positions corresponding to three duty cycles, and the power of the air dehumidifier is changed according to the input tap position. [ABSTRACT FROM AUTHOR]

Under the situation of global low-carbon development, the contradiction among energy consumption, economic growth, and CO2 emissions is increasingly prominent. Considering the possible two-way feedback among the three, based on the panel data of 30 regions in China from 2000 to 2017, this paper establishes a spatial Durbin model including economic growth, energy consumption equation, and CO2 emissions and studies the dynamic relationship and spatial spillover among economic growth, energy consumption, and CO2 emissions effects. The results show that the economic growth can significantly improve carbon dioxide emissions, and China's economic growth level has become a positive driving force for carbon dioxide emissions. However, economic growth will not be significantly affected by the reduction of carbon dioxide emissions. There is a two-way relationship between energy consumption (ENC) and carbon dioxide emissions (CO2). Energy consumption and carbon emissions are interrelated, which has a negative spatial spillover effect on the carbon dioxide emissions of the surrounding provinces and cities. [ABSTRACT FROM AUTHOR]

This paper, based on the panel data, measures the comprehensive efficiency of green innovation, the economic output efficiency of green innovation, the social output efficiency of green innovation, and the environmental output efficiency of green innovation of listed energy companies in China by means of the window DEA model from the perspective of the triple bottom line. Moreover, the impacts of environmental factors and random factors on the green innovation efficiency are analyzed. It is found that firstly, green innovation efficiency of listed Chinese energy companies shows a V-shaped change trend without excluding environmental factors and random factors. Secondly, environmental factors and random factors are the primary factors to promote the green innovation efficiency of energy listed companies in China. Finally, after removing the interference of environmental factors and random factors, comprehensive efficiency of green innovation of the listed energy companies in China is relatively high and the distribution is relatively concentrated, but there is a downward trend during the research period. [ABSTRACT FROM AUTHOR]

Environmental issues caused by energy consumption have attracted increasing attention recently. Shanxi Province, a typical energy-dominated region in China, has long-term dependency on coal industry generating extensive economic growth, which is detrimental to green development. Distinguished from previous studies ignoring driving factors of energy consumption, this paper establishes a vector autoregression (VAR) model to dynamically identify the drivers of energy consumption based on STIRPAT model in Shanxi Province from 1990 to 2015. It can be obtained from the impulse response analysis that a positive shock in population, GDP, and urbanization level, respectively, positively affect energy consumption, and a positive change in technology negatively affects energy consumption in the long run. The variance decomposition results indicate that fluctuation in energy consumption explained by the innovation of the urbanization level accounts for 23.18%, which plays a prevailing role in increasing energy consumption. Meanwhile, the forecasting results of GM (1,1) model manifest that energy consumption in Shanxi Province generally has an increasing trend from 2016 to 2025. Consequently, Shanxi can achieve green development through optimizing energy structure, promoting the transformation of resource-based cities, and promoting low-carbon technological innovation. This paper can be available for other resource-based regions analogous to Shanxi. [ABSTRACT FROM AUTHOR]

With the continuous improvement in China's economy, the construction industry has developed and rampantly progressed. Besides the wastage of resources and energy, the development has caused serious pollution to the environment. This makes the construction industry a high energy-consuming and highly polluting industry. There is a pressing need to reduce the wastage of resources and to adequately manage consumption of energy throughout the life cycle of buildings. This paper explores an effective method of building life cycle energy management by appropriately utilizing information system and the emerging deep learning technology. To achieve energy saving in buildings, a feasible model is proposed for predicting, analyzing, and building energy consumption based on neural networks. By analyzing the massive data stored in the building information system, the operation of each subsystem in the building is guided and regulated to achieve energy deployment and build energy optimization. Focusing the key meters, the average generalization ability of the proposed model (R-Squared = 1.9, MSE = 1.02) is better than the other contemporarily used models, LightGBM, LSTM, and SVR. Moreover, the method can effectively predict the energy consumption of the whole life cycle of the building and has higher prediction accuracy. The method proposed has great significance in research related with improving building energy performance and designing decision support tool. [ABSTRACT FROM AUTHOR]

In order to achieve China's energy conservation and emission reduction goal of peaking carbon dioxide emissions around 2030, it is of great significance. An important means of building energy conservation and emission reduction is the fine management of building energy consumption, which is based on the accurate prediction of building energy consumption, so as to support the optimal management of building operation and achieve the goal of energy conservation and emission reduction. This paper puts forward the evaluation indexes of the results of the building energy consumption prediction model, uses MAPE and RMSE indexes to evaluate the accuracy of the prediction results of the model, and uses the prediction time and input parameter dimensions to evaluate the time cost of the prediction model. Then, using the three building energy consumption prediction models based on machine learning algorithm established above, the prediction of energy consumption of four types of public buildings in different seasons is completed, and the prediction results are evaluated and analyzed. According to the prediction results and the requirements of related work on the accuracy of building energy consumption prediction model, the adaptation relationship between different types of buildings and different machine learning algorithm prediction models is summarized. [ABSTRACT FROM AUTHOR]

While promoting the economic growth, energy has also brought pollution problems to the world environment, which has gradually become a bottleneck impeding sustainable economic development. In view of the rapid evolution of urbanization and industrialization, economic growth is increasingly dependent on the energy consumption, the development of the two is difficult to coordinate, and the internal contradictions are becoming increasingly serious, which hinders the sustainable development of economic growth. This study establishes the relationship between energy consumption and economic growth according to the energy Kuznets curve and studies the future trend of China's sustainable development through the comparative analysis of the energy Kuznets curve of the United States and Germany. The results show that, at the turning point of energy consumption, China's energy economic rate is higher than that of Germany and the United States. In addition, in terms of urbanization rate and industrial structure, although China's tertiary industry has made a breakthrough, it is still lower than that of the United States and Germany, but the level of urbanization rate has made significant progress. In short, China has obvious advantages in future economic development and has a late developing advantage compared with the United States and Germany. This paper makes an empirical analysis of the relationship between energy consumption and economic growth in OECD countries and finds out the turning point of energy consumption, so as to provide a theoretical basis for coordinating China's energy consumption and economic growth. [ABSTRACT FROM AUTHOR]

With the increase in the proportion of new energy resources being generated in the power system, it is necessary to plan the capacity configuration of the power supply side through the coordination of power generation, grid, load, and energy storage, to create a relatively controllable power generation output and ensure the safe and stable operation of the power system is a key problem that needs to be solved at present. Therefore, combined with national and regional policies and resource constraints in China, this paper firstly determines the requirements and boundary conditions of various power supply planning in the regional power system and proposes a "generation-grid-load-energy storage" coordination mode. Secondly, establish a regional power system coordination planning model considering the proportion of new energy consumption and low-carbon cost. Finally, in three scenarios with a high, medium, and low proportion of new energy resources, the new installed capacity configuration of regional power supply is optimized to verify the effectiveness of the proposed model and provides reference for regional power supply planning. [ABSTRACT FROM AUTHOR]

Reducing the total carbon emissions of the logistics industry is one of the basic requirements for the development of a low-carbon economy. Based on the AHP analytic hierarchy process and the 1-9 value scaling method, an evaluation index system for the low-carbon development of the logistics industry is constructed. At present, the development of low-carbon logistics requires the combination of low-carbon technology and low-carbon management to ensure the integrity and dynamics of low-carbon logistics control. The results of this study show that in the AHP index analysis of the development of logistics industry in Shandong Province, compared with 13 evaluation indexes of low-carbon logistics and traditional logistics, low-carbon logistics is significantly better than traditional logistics. Among them, the implementation of low-carbon logistics policy system has increased the energy utilization rate to 88.72%, the recovery rate of warehousing and logistics waste to 92.11%, and other relevant indicators have also been improved and optimized to varying degrees. Based on the EKC model curve, the total carbon emissions from 2015 to 2019 showed a downward trend month by month. The future development of low-carbon logistics mainly starts with reducing the total carbon emission of logistics transportation and improving energy utilization. Aiming at the main influencing factors of the development of low-carbon logistics, this paper puts forward specific measures for the development of low-carbon logistics, in order to promote the development of low-carbon logistics. [ABSTRACT FROM AUTHOR]

Today, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low-carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitious emission reduction goals. This paper attempts to explore the spatial relationships among cities from the perspective of carbon trading. A "multiscenarios across different spatial scales" analysis framework applied to the allocation and trading of CO2 emission quotas among cities in China is proposed. Based on this framework, the carbon trading networks of 182 cities in China are specifically simulated under four different scenarios, with a comparative analysis of the networks' complexity made from different perspectives. The results of the study are as follows: firstly, significant spatial network correlations exist between the cities' carbon trading under each scenario. Secondly, on a national scale, there are more inner connections in carbon trading networks, with stronger correlations and robustness, while the degree of connection of intercity carbon trading is higher overall on a regional scale. Thirdly, on a national scale, no obvious core nodes exist in the network, while core nodes do exist in the overall network and in each region under the regional scale. Fourthly, cities in the central region have the highest core position overall. Finally, based on the research results, practical guidance in using the framework for achieving carbon reduction, promoting economic growth, and balancing regional development, as well as the important inspiration for policy formulation, is further discussed. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy and with the increasing awareness of environmental protection, clean energy will become the ultimate solution of energy in the near future. In order to meet the future demands of clean energy, it is important to accurately predict the consumption of clean energy. This paper is based on the total consumption data of clean energy in China from 2000 to 2019, including natural gas, hydropower, nuclear power, and wind power consumption. The combined model is used to predict the clean energy consumption and achieves the optimal prediction with minimum variance. The results show that compared to the GM(1,1) and ARIMA model, the combined forecasting model has lower relative error when fitting and predicting the consumption demand of clean energy. It is observed from the prediction results that the clean energy consumption would have a rapid growth tendency, and the growth rate will be about 8.6% in the next five years. The consumption would be about 1.7 billion tons standard coal in the year of 2024. [ABSTRACT FROM AUTHOR]

Under the requirement of energy savings and emission reduction in China, building energy consumption, which occupies a rising proportion of the total energy consumption in society, has become the focus of energy conservation research. Public buildings with a high-energy consumption level have become the most important part of energy conservation research. It is of great practical significance and social value to study energy conservation in large public buildings. In this paper, a large office building is taken as an example. First, a simulation model is constructed by using the energy consumption simulation analysis method, and the reliability of the model is verified by a comparison with the actual energy consumption. Second, based on the model, the thermal design parameters of six building envelope structures, including the external wall heat transfer coefficient, are analyzed in the order of energy-saving sensitivity. Based on the results of the sensitivity analysis, suggestions for each factor are presented. Finally, considering the mutual influence of each parameter on the building energy consumption, the orthogonal design method is used to arrange the test, and the optimal scheme combination of the energy-saving effect is analyzed, which can provide decision support for the energy saving of public building envelopes. [ABSTRACT FROM AUTHOR]

Based on the dynamic characteristics of enterprises' competition and cooperation, this paper introduces the idea of ecology and synergy and constructs a dynamic coevolution model of financing allocation efficiency and financing niche based on improved Lotka-Volterra model. The parameters in the model are difficult to be given by the least square method and the maximum likelihood estimation method; the accelerated genetic algorithm is proposed to solve the parameters in the dynamic coevolution model, which makes the parameter estimation more accurate and reasonable. Finally, the data of new energy vehicle listed companies in China from 2009 to 2017 are given to validate the proposed model, and the dynamic process of coevolution of new energy vehicle enterprises, capital allocation efficiency, and financing niche is described. The results show that the minimum financing niche breadth of industry and market determines the location of the equilibrium point. With capital allocation efficiency as the core, adjusting the financing niche through financing market, industrial policy, enterprise development, and other factors will help to improve the coevolution balance between industrial capital allocation efficiency and financing niche and promote the coordinated development of strategic emerging industries. [ABSTRACT FROM AUTHOR]

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

Hospital buildings usually contain sophisticated facility systems and special medical equipment, strict security requirements, and business systems. Traditional methods such as BIM are becoming less capable of real-time updates of building status and big data volume. By proposing innovations both in technique and management—a "continuous lifecycle integration" method based on the concept of Digital Twin (DT) and "early movement" of the general contractor, this paper reported a successful project case in a large hospital in China. The case realized continuous, scheduled integration of static data and dynamic data of more than 20 management systems from the design, construction, pre-O&M phase up to the O&M phase. Then, a DT software system with real-time visual management and artificial intelligent diagnosis modules was developed and deployed in a newly built DT control center. Managers have the ability to grasp the detailed status of the whole hospital by visual management and receive timely facility diagnosis and operation suggestions that are automatically sent back from the digital building to reality. The case has been steadily running for more than a year in the hospital and achieved desired performance by reducing energy consumption, avoiding facility faults, reducing the number of requested repairs, and enhancing the quality of daily maintenance work. [ABSTRACT FROM AUTHOR]

The hilly farmland in China is characterized by small farmland areas and dense farmland distribution, and the working environment is three-dimensional topographic farmland, so the working conditions in the field are relatively complex. In this working environment, the coverage path planning technique of a farmland autonomous task is harder than that of 2D farmland autonomous task. Generally, the path planning problem of 2D farmland is to construct the path cost model to realize the planning of agricultural machinery driving route, while for the path planning problem of three-dimensional terrain farmland in the hilly region, this paper proposes a covering path planning scheme that meets the requirements of autonomous work. Based on the energy consumption model, the scheme searches the optimal driving angle of agricultural machinery, prioritizes solutions to the problem of covering path planning within the scattered fields in the working area, and then searches through the genetic algorithm for the optimal order of traversing the paths of each field to complete the coverage path planning in the working area. On the one hand, the scheme optimizes the planning route in the fields from the angle of optimal energy consumption; on the other hand, through the genetic algorithm, the fields are connected in an orderly manner, which solves the comprehensive problems brought by the unique agricultural environment and farming system in China's hilly areas to the agricultural machinery operation. The algorithm program is developed according to the research content, and a series of simulation experiments are carried out based on the program using actual farmland data and agricultural machinery parameters. The results show that the planned path obtained at the cost of energy consumption has a total energy consumption of 4771897.17J, which is 17.4% less energy consumption than the optimal path found by the path cost search; the optimization effect is evident. [ABSTRACT FROM AUTHOR]

The optimization of high-occupancy vehicle (HOV) lane management can better improve the efficiency of road resources. This paper first summarized the current research on HOV lane implementation and analyzed and identifies the threshold of setting road HOV lane dynamic control under the connected vehicle environment. Then, the HOV lane priority dynamic control process was determined, and the operating efficiency and energy consumption evaluation method was proposed. Moreover, a case study in Wuxi City, China, was carried out. The results showed that, after implementing the HOV lane priority dynamic control, the total mileage of road network vehicles was saved by 4.93%, the average travel time per capita was reduced by 4.27%, and the total energy-saving rate of road network travel was 21.96%. [ABSTRACT FROM AUTHOR]

The Sanxingdui Moon Bay City Wall, in China, is built of pale-yellow sand and yellow-brown clay, and the yellow-brown layers are suffering severely. In order to discuss the desiccation cracks in a section of this wall, this paper conducts evaporation tests in laboratory and observes the variations in the characteristics of the boundary conditions of the bottom surface of the sample. The results show that the boundary conditions of the bottom surface of the sample consist of two free boundaries, two sliding boundaries, and one fixed boundary from the outside to the inside. During the drying process, the free boundary extends, but the fixed boundary shrinks; the sliding boundary also remains basically stable. We obtain the surface tensile stress distribution under different boundary conditions through stress analysis and deduce that the tensile stress distribution has a trapezoidal pattern. Moreover, we calculate the lower limit on the crack spacing of the sample using the energy method, and the double of the sum of the maximum sliding boundary length and the free boundary length is the upper limit to the crack spacing. Maintaining the stability of the soil moisture content of the site is the main factor in the protection of the earthen archaeological site under the humid conditions of the museum above the site. In order to reduce the water evaporation rate of the soil, the surface of the site should be coated by a protectant, the main determining features of which are permeability, tensile strength, and compatibility with the earthen site. [ABSTRACT FROM AUTHOR]

Water pollution control is currently an important development strategy for China. Analysis and forecasting of wastewater discharge and the energy consumption are critical for this strategy. In this paper, we proposed the two time series models, namely, improved GM(0,n) model (IGM(0,n)) and optimized FGM(1,1) model (OFGM(1,1)). Two numerical experiments were used to test the validity of these models. It was indicated that the forecasting ability of two models had remarkably improved, compared to traditional FGM(1,1) and GM(0,n), respectively. We applied the two models to forecast wastewater discharge and energy consumption in China. The forecasting results have shown that the current growth rate in treated wastewater could meet the planning target of the 13th Five-Year Plan. The wastewater discharge and the energy consumption would reach 77.39 billion tons and 22.75 billion kWh, respectively, in 2020. [ABSTRACT FROM AUTHOR]

Effective supply of charging infrastructure is a necessary support for the development of electric vehicle and also an important strategic measure to promote energy consumption revolution and green development. The construction and operation of charging infrastructure in China is unfortunately not smooth, lagging behind the actual demand. Public-Private Partnerships (PPPs) may offer a promising way forward and accelerate the development of charging infrastructure by tapping the private sectors’ financial resources and professional skills. However, PPP has not been commonly adopted in this sector yet. This paper hence studied an illustrative case of Anqing Project in China to demonstrate how governments structure a PPP deal in the electric vehicle charging infrastructures. A content analysis was conducted on the important project documents to investigate key elements including the planning, construction, risk sharing, profit distribution, and supervision during the execution stage. Based on the illustration, some key lessons and recommendations were provided to offer a reference for future charging infrastructure PPP projects in China. [ABSTRACT FROM AUTHOR]

Because of increasing energy consumption and severe air pollution in China, solar photovoltaic power generation plants are being deployed rapidly. Owing to various factors such as technology, construction, and imperfection of construction standards, solar photovoltaic systems have certain fire risks. This paper focuses on the fire risks of building-integrated solar photovoltaic buildings, as well as temperature and heat flow density near a photovoltaic system in a fire. Based on FDS simulation results, the influence of different building fires on photovoltaic systems is analysed. It is found that the influence of fire on photovoltaic systems installed on a building with a flat roof is stronger than that on a system installed on a building with a sloping roof; the influence of fire on a photovoltaic system installed on a building with external wall thermal insulation is stronger than that on a system installed on a building without such insulation; and in the presence of a skylight, a photovoltaic system installed on a building with a sloping roof is more dangerous. [ABSTRACT FROM AUTHOR]

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

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

Electric vehicles (EVs) are widely regarded as a promising solution to reduce air pollution in cities and key to a low carbon mobility future. However, their environmental benefits depend on the temporal and spatial context of actual usage (journey energy efficiency) and the rolling out of EVs is complicated by issues such as limited range. This paper explores how the energy efficiency of EVs is affected and shaped by driving behavior, personal driving styles, traffic conditions, and infrastructure design in the real world. Tests have been conducted with a Nissan LEAF under a typical driving cycle on the Beijing road network in order to improve understanding of variations in energy efficiency among drivers under different urban traffic conditions. Energy consumption and operation parameters were recorded in both peak and off-peak hours for a total of 13 drivers. The analysis reported in this paper shows that there are clear patterns in energy consumption along a route that are in part related to differences in infrastructure design, traffic conditions, and personal driving styles. The proposed method for analyzing time series data about energy consumption along routes can be used for research with larger fleets of EVs in the future. [ABSTRACT FROM AUTHOR]

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

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

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

Energy recovery and hybrid power technology are new directions in construction machinery energy-saving research. Thus far, however, no uniform standard method exists to evaluate the efficiency of novel energy-saving concept systems in early stages of development. Efficiency assessment is valuable and credible only by relying on driving cycles that are consistent with actual data. As representative products of construction machinery, hydraulic excavators are multifunctional, object-uncertain, and heavily influenced by operator habits. It is therefore challenging to develop standard excavator driving cycles. Aiming at the energy efficiency evaluation of new energy-saving products characterized by energy recovery and power system optimization, taking medium-sized hydraulic excavator as an example, this paper proposes an evaluation method of energy-saving efficiency and a classification construction method of comprehensive driving cycle of hydraulic excavator based on actual operating data with load demand power and boom recoverable power as combined variables. First, based on the analysis of general driving cycle variables for excavators with different energy-saving schemes, a load demand power model and boom recoverable power model based on machine sensing data are established. Second, 10 excavators were selected at different locations in southern China, and 30 days of real-world working data were recorded. Third, according to the periodic characteristics of working data, a method for dividing microcycle operation structure is proposed. The microcycle sample space based on the data conversion of working data is constructed and classified via the clustering algorithm. Finally, a comprehensive excavator driving cycle based on the classification results is constructed through the Markov method. Results show that the energy-saving efficiency of the three classification driving cycles was 17.45%, 13.60%, and 11.88%, respectively; the comprehensive energy-saving efficiency was 15.76%. The deviations in maximum load demand power and maximum boom recoverable power between the constructed comprehensive cycle and the sample space were 7.81% and 8.61%; the average deviation of characteristic parameters was 4.26%. The comprehensive driving cycles can fairly reflect the general characteristics of real-world working conditions. The proposed construction method of comprehensive driving cycles based on sample space is therefore reliable and holds great promise for evaluating the energy-saving efficiency of new energy-saving concept systems. [ABSTRACT FROM AUTHOR]

Surface water environment in China was degraded rapidly in the last two decades, resulting in increasingly tighten criteria issued for municipal wastewater treatment plants (WWTPs). This paper reviewed the recent advances of process design and operational optimization for nutrients removal. Three major processes, as anaerobic-anoxic-oxic (AAO) process, oxidation ditch (OD), and sequencing batch reactor (SBR) occupied 65% of WWTPs amounts and 54% of treatment volumes of China in 2006. However conservative process designs and operational faults often impaired the process performances and energy efficiency. Therefore, typical processes were modified, combined, and innovated to meet the requirements of the diverse influent characteristics and lower energy consumptions. Furthermore, operational optimization techniques by modeling, simulation, and real-time control were also developed and applied in China to improve the process operation. Although great efforts had been contributed to improve the WWTPs performances in China, attentions should be continuously paid to the introduction, instruction, and implementation of advanced techniques. At last, the technical demands and appropriated techniques of WWTPs in China were briefly discussed. [ABSTRACT FROM AUTHOR]

Traditional method of forecasting electricity consumption based only on GDP was sometimes ineffective. In this paper, urbanisation rate (UR) was introduced as an additional predictor to improve the electricity demand forecast in China at provincial scale, which was previously based only on GDP. Historical data of Shaanxi province from 2000 to 2013 was collected and used as case study. Four regression models were proposed and GDP, UR, and electricity consumption (EC) were used to establish the parameters in each model. The model with least average error of hypothetical forecast results in the latest three years was selected as the optimal forecast model. This optimal model divides total EC into four parts, of which forecasts can be made separately. It was found that GDP was only better correlated than UR on household EC, whilst UR was better on the three sectors of industries. It was concluded that UR is a valid predictor to forecast electricity demand at provincial level in China nowadays. Being provided the planned value of GDP and UR from the government, EC in 2015 were forecasted as 131.3 GWh. [ABSTRACT FROM AUTHOR]

Following a dynamic nonlinear perspective, this study explores the relationship between urban innovation capability and energy utilization efficiency by employing the Panel Vector Autoregression (PVAR) and Dynamic Panel Threshold Regression (DPTR) methods. Using the 2003–2020 panel data of 281 prefecture-level cities in China, this study confirms that energy utilization efficiency improves owing to the improvement of urban innovation capability. Depending on the characteristics of the city, such as population density, industrial structure, and environmental pollution, high energy utilization efficiency in the early stages of city development may help or hinder the improvement of energy utilization efficiency in the later stages. The enhancement in urban innovation capability has failed to improve energy utilization efficiency and has adversely affected cities with a low population density or weak secondary industrial foundation. However, in cities with a high population density or proportion of secondary industry, the improvement in innovation capability significantly increases the efficiency of energy utilization. In addition, the positive effect that urban innovation capability has on energy utilization efficiency is higher in low-pollution cities than in high-pollution cities. [ABSTRACT FROM AUTHOR]

With the continuous development of Internet of Things technology, this technology is not limited to the laboratory but is more and more applied in the process of commercialization. Large-scale machine communication is one of the three most important scenarios for 5G applications. Its features include larger uplink access, smaller data packets, higher device energy consumption requirements, lower device transmission speed, higher latency, and bursty communication. With the development of the Internet of Things in the 5G era, interpersonal interaction experience has been further optimized and welcomed by the market and adopt Qt/embedded multilayer menu design mode to improve our computer system interaction to facilitate the operation and Maintenance system. The software function of the human-computer interaction system has reached the expected result. By constructing the application of a human-computer interaction system in the analysis of regional tourism competitiveness, we analyze the temporal and spatial changes of tourism competitiveness in four major economic regions in China and combine multiple linear regression and geographic detector models to analyze China's tourism competitiveness. On this basis, we propose to further enhance the tourism competitiveness of areas with weak tourism development infrastructure and encourage potential tourism development areas to complement each other with high-quality resources between regions. [ABSTRACT FROM AUTHOR]

The resource utilization of a circular economy should reflect both economic and environmental values. Resource utility can be measured by GDP in the short term, while environmental value is challenging to measure; that is, the improvement in air quality is not effectively evaluated. In order to examine this initiative, using China's pilot cities of circular economy as a quasi-natural experiment, we construct a difference-in-difference (DID) strategy for estimation. The results demonstrate the following: (1) the pollutant emissions of pilot cities decline by 2.92 percentage points (p < 0.01) compared to unpiloted cities, (2) the policies on pilot cities more rapidly enhanced air quality for central cities and those with a low level of economic development, and (3) pilot cities significantly enhance air quality by decreasing energy consumption per unit of GDP. We provide the first empirical evidence of the effectiveness of circular economy pilot cities in improving air quality. [ABSTRACT FROM AUTHOR]