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In the context of the global potential energy crisis and aggravating regional environmental pollution, Chinese photovoltaic power generation still faces the key problems of sustainable development, even given its favorable background in large-scale exploitation. Scientific evaluation of the comprehensive efficiency of photovoltaic power generation is of great significance because it will improve investment decision-making and enhance management level, evaluate the development conditions of photovoltaic power generation and then promote sustainable development capability. The concept of “comprehensive efficiency” is proposed in this paper on the basis of the resource development of solar energy and exploitation of photovoltaic power generation. A system dynamics model is used to study the conduction mechanism of the comprehensive efficiency of photovoltaic power generation. This paper collects data from 2005 to 2015 as research models, establishes the evaluation model of the comprehensive efficiency of photovoltaic power generation and conducts empirical analysis based on a super-efficient data envelopment analysis (SE-DEA) model. With the evaluation results, this paper puts forward political suggestions as to the optimization of the comprehensive efficiency of photovoltaic power generation. The research results may provide policy-oriented references on the sustainable development of photovoltaic power generation and give theoretical guidance on the scientific evaluation and diagnosis of photovoltaic power generation efficiency. [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]

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

Household energy consumption accounts for almost one third of global primary energy demand and significantly affects the environment. As such, it has served as a classic and compelling theme in the literature, with a range of studies having analyzed various aspects of household consumption, including energy conservation, energy poverty, and energy efficiency. Nonetheless, overall trends and frontiers in this research area have not been characterized and are poorly understood. This study aims to assess the current status, evolution, and emerging topics in this area through a bibliometric and network analysis of 1134 extracted publications from 1983 to 2018. This systematic review shows that nearly half the studies on household energy consumption were published in just three journals (namely, Energy Policy; Energy; and Energy Economics) with a focus on three areas (Environmental Sciences and Ecology; Energy and Fuels; Business and Economics). The findings also show that among contributing countries, the USA and China have the closest ties and wield the most academic influence. Furthermore, emerging and pioneering studies on behavioral interventions, energy conservation, and energy poverty and those pertaining to climate and electricity consumption may constitute the research frontier. [ABSTRACT FROM AUTHOR]

Nearly zero-energy-consumption buildings are the inevitable trend of future buildings. There have been a large number of studies on nearly zero building technology issues. However, there is no detailed study on how to effectively promote the development of nearly zero-energy consumption buildings according to China's national conditions. Here, by establishing an evolutionary game model, this paper discusses the dynamic game scheme selection and stability strategy of three stakeholders, namely local government, real estate companies, and construction consumers, related to the development of nearly zero-energy-consumption buildings in the development process. The conditions required for evolutionary stabilization strategies were identified. Finally, Matlab data simulation analysis is used to further illustrate the stability and equilibrium strategies of each subject and the sensitivity analysis of the main influencing factors at various stages in the development process of nearly zero-energy-consuming buildings. The research results show that the government plays a leading role in the early stage of the development of nearly zero-energy consumption buildings, and as the market matures, government intervention gradually withdraws from the market; furthermore, if the cost of supervision is prohibitively high, the government's willingness to supervise the market will be reduced. This will hinder consumers and developers from choosing nearly zero-energy-consuming buildings and if the penalties and subsidies are too low, it will be meaningless to the evolution of the optimal solution of the three parties. On this basis, targeted promotion programs are established to realize the rapid development of China's nearly zero-energy-consumption building sector. Our research results can provide important scientific basis for the development of the nearly zero-energy building industry in China. [ABSTRACT FROM AUTHOR]

China has pledged that it will strive to achieve peak carbon emission by 2030 and realize carbon neutrality by 2060, which has spurred renewed interest in hydrogen for widespread decarbonization of the economy. Hydrogen energy is an important secondary clean energy with the advantage of high density, high calorific value, rich reserves, extensive sources and high conversion efficiency that can be widely used in power generation, transportation, fuel and other fields. In recent years, with the guidance of policies and the progress of technology, China's hydrogen energy industry has developed rapidly. About 42% of China's carbon emissions comes from the power system and Shenzhen has the largest urban power grid in China. Bringing the utilization of hydrogen energy into Shenzhen's power system is an important method to achieve industry transformation, achieve the "double carbon" goal and promote sustainable development. This paper outlines the domestic and international development status of hydrogen energy, introduces the characteristics of Shenzhen new power system, the industrial utilization of hydrogen energy and the challenges of further integrating hydrogen energy into Shenzhen new power system and, finally, suggests on the integration of hydrogen energy into Shenzhen new power system in different dimensions. [ABSTRACT FROM AUTHOR]

Global climate change has caused governments worldwide to take actions to improve their energy efficiency. This paper investigates how China's Top-1000 program, a command-and-control type of energy-saving mandate, has affected the operational choices of firms, and in turn, their profitability. We apply the propensity score matching method to find "identical twins" for the participants in the Top- 1000 program, then conduct a difference-in-differences analysis on the matched sample. Our findings suggest that the profitability of the enterprises targeted for energy savings decreased by one-third, mainly due to increased production costs. The targeted enterprises tended to increase their fixed assets per capita, which was associated with improvements in energy efficiency. Furthermore, compared to similar untargeted enterprises, there was a significant slowdown in the production growths of the targeted enterprises, raising concerns about carbon leakage due to increased production by less efficient producers. [ABSTRACT FROM AUTHOR]

Building a new type of power system is an important guarantee to support China's "dual carbon" goal. Due to the inseparable relationship between industrial and agricultural production and electric energy utilization, there must be interdisciplinary integration to achieve the goal of "dual carbon". The disciplines of horticulture and electric power are taken as examples in this paper to analyze the feasibility of carbon emission reduction through coordinating agricultural photovoltaic (PV) greenhouse and electric vehicle (EV) energy storage. Firstly, the mechanism of carbon emission difference caused by electric energy supplementing during EV charging is analyzed. Secondly, in the context of the contradiction between the reduction of battery life caused by discharging (increasing carbon emission) and the increase in PV output consumption by orderly charging and discharging (reducing carbon emission), an optimization model for the synergistic operation of EV clusters and greenhouse PVs (with the objective of minimizing carbon emissions) is proposed. Finally, the effectiveness of the proposed model is verified through simulation cases. The energy storage characteristics of EVs is capable of realizing the transfer of PV power generation in the time dimension, and the coordinated operation of greenhouse PVs and EVs' charging and discharging can effectively reduce carbon emission during the EV operation period. In a typical summer scenario of PV output, the carbon emission of EVs in V2G (vehicle to grid) mode was reduced by 69.13% compared to disorderly charging. It is shown that the adequacy of PV generation and the orderly dispatching of the charging and discharging of EVs are the key factors in reducing carbon emission throughout the life cycle of EVs. [ABSTRACT FROM AUTHOR]

In coastal cities, a large amount of cold energy is released into the nearby seawater during the process of regasification of liquefied natural gas (LNG) at the receiving terminal, and meanwhile, a large amount of exported and/or imported foods need to be frozen by bulk cold energy near the sea. In this paper, a new multistage cold energy recovery/utilization system is investigated to link the LNG cold energy directly to supply the coastal cold store. This design uses a realistic case in Ningbo LNG receiving station in China, and for the very first time considers how to utilize the LNG cold energy in an efficient manner regarding the technical, economic, and environmental benefits. A three‐stage LNG cold energy utilization system is designed and evaluated by considering different temperatures, pressures, and heat exchange parameters. Compared to conventional electric‐driven cold stores, the proposed multistage cold energy recovery/utilization system has a much cheaper capital cost during the initial investment stage, and also avoids the utility power consumption during the daily operation period. In the case study, from Ningbo LNG receiving station to a 10 MW class cold store, the proposed multienergy system can save the energy of 20.05 kilotons of standard coal, and the carbon emission reduction is up to 1.49 × 108 kg per year. [ABSTRACT FROM AUTHOR]

As China reaffirms its commitments to limit the climate change risk and improve air quality, a combination of new policy and technology opportunities is presenting itself. A national emission trading scheme (ETS) begun in 2017 and is showing great promise, creating decentralized incentives for cost effective pollution mitigation. At the same time, sustained energy sector innovation is driving the costs of renewable electric power generation below those of fossil fuel substitutes. Early economic evidence of ETS measured pollution reductions, but has not addressed important economy-wide net benefits. This paper focuses on technology and energy cost savings and is the first to account for three multiplier effects—shifting consumption patterns, job growth, and the benefits of induced productivity growth—that would result from accelerated renewable electricity deployment in China. Results from a dynamic recursive computable general equilibrium model for 2017 to 2030 show that expanding renewable deployment can interact with the ETS to slash GHG emissions, as well as energy costs, stimulating significant long-term economic growth. These results suggest that China should accelerate its clean energy transition, not only for the air-quality and climate benefits, but to fulfill the energy sector's potential to promote innovation, employment, and economic growth. [ABSTRACT FROM AUTHOR]

Enhancing carbon emission mitigation and carbon utilization have become necessary for the world to respond to climate change caused by the increase of greenhouse gas concentrations. As a result, carbon capture, utilization, and storage (CCUS) technologies have attracted considerable attention worldwide, especially in China, which plans to achieve a carbon peak before 2030 and carbon neutrality before 2060. This paper proposed six priorities for China, the current world's largest carbon emitter, to achieve its dual carbon strategy in the green energy transition process. We analyzed and summarized the challenges and potentialities of conventional carbon utilization (CU), carbon capture utilization (CCU), and CCUS. Based on the current development trend, carbon dioxide capture, circular utilization, and storage (CCCUS) technology that integrates carbon circular utilization and partial sequestration, with large-scale underground energy storage were proposed, namely biomethanation. Technically and economically, biomethanation was believed to have an essential contribution to China's renewable energy utilization and storage, as well as the carbon circular economy. The preliminary investigation reveals significant potential, with a corresponding carbon storage capacity of 5.94 × 108 t~7.98 × 108 t and energy storage of 3.29 × 1012 kWh~4.42 × 1012 kWh. Therefore, we believe that in addition to vigorously developing classical CCUS technology, technical research and pilot projects of CCCUS technology that combined large-scale underground energy storage also need to be carried out to complete the technical reserve and the dual-carbon target. [ABSTRACT FROM AUTHOR]

Atriums play an irreplaceable role within the plan of modern commercial buildings. However, the presence of skylights makes the atrium suffer from unfavorable conditions such as overheating, high energy consumption, and glare, which can be partially reduced by the sun-shading design of skylights. In this paper, we conducted a field test and questionnaire survey on the daylight quality of commercial buildings in cold zones in China to find out the current problems of daylight quality in atriums and to establish a model of commercial atrium. After the dynamic daylight and energy consumption simulation, the sensitivity analysis of daylight and energy performance is performed for the skylight and shading (SAS) design parameters under three shading types. Finally, the Pareto front solution set of optimized commercial atrium daylight, visual comfort, and energy performance for the three shading types has been obtained using a multi-objective search tool. The results show that SRR has the greatest effect on sDA, DGP, and EUI in all shading cases; while SGT has a greater effect on EUI than on daylight quality; FC has a greater effect on EUI than FV on EUI; and LS and LI have a more significant influence on daylight and visual comfort. The optimal SAS values of no shading, fabric shading and louvered shading were screened as SRR is 0.4–0.5, SGT is Double silver Low-E insulating glass; SRR is 0.5–0.6, SGT is Double silver Low-E insulating glass, FV is 0.5–0.7, FC is 0.5–0.6; SRR is 0.6–0.7, SGT is Double silver Low-E insulating glass, LS is 100 mm/125 mm, and LI is 60–70°. It is expected that this study will provide some information and reference for the design of commercial atriums in cold zones in the future. [ABSTRACT FROM AUTHOR]

China's rare earth export trade has developed so rapidly since 1990s that China has gradually occupied a leading position in the international market. However, this fast development was proceeding at the cost of the rare earth energy consumption and environmental devastation. Now China begins to attach great importance to environmental protection, which attracts many researchers. This study aims to analyze the influence of environmental regulation on China's rare earth export trade. And the original study is amongst the few to examine the relationship between environmental regulation and China's rare earth export with the product-level data. Different from previous studies, this paper selects China's rare earth export data from 1995 to 2015 and introduces product heterogeneity based on the rare earth production process. Moreover, this study uses the entropy weight method to measure the intensity of environmental regulation. The core conclusions are as follows: (1) Environmental regulation significantly promotes rather than restrains China's rare earth export. (2) According to the rare earth production process, this paper divides rare earth products into 3 kinds, that is, rare earth raw materials, rare earth useful components and rare earth end-use applications. Then, it is found that rare earth useful component export in processing and smelting is positively affected by environmental regulation. Rare earth raw materials and end-use applications in China's export are hardly affected. (3) Technological innovation has a mediating effect on the impact mechanism of environmental regulation on China's rare earth export, which means that environmental regulation significantly promotes technological innovation of enterprises, and thereby the rare earth export is increased. The findings are helpful for policymakers to resolve the issue of environmental devastation. [ABSTRACT FROM AUTHOR]

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

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

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

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

Despite market-oriented reforms, China's energy sector is subject to energy price distortions, which are believed to be a crucial determinants of energy efficiency in China. This paper investigates the impact of energy price distortions on energy efficiency in China from the perspective of spatial correlation. Using the nonradial directional distance function approach, we first estimate the provincial-level energy efficiency in China. Paying attention to spatial correlation among the provinces of China, in stage two, we identify the determinants of energy efficiency. Our empirical results suggest that price distortions have a significant impact on energy efficiency in China. This impact holds when the cross-region effect is considered, i.e., besides its own energy price distortion, a region's energy efficiency is also correlated to the adjacent provinces' energy price distortions. Furthermore, we found that the levels of energy efficiencies in adjacent provinces are highly correlated. This spatial relationship can be decomposed into the 'spillover effect' and 'warning effect'. These two effects work together, determining the spatial relationship among the province-level energy efficiencies. [ABSTRACT FROM AUTHOR]

The introduction of the new round of electricity reform policies has made the electricity sales companies' trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China's current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market. [ABSTRACT FROM AUTHOR]

This paper explores the nonlinear effect of outward foreign direct investment (ODI) and Export Trade Structure on CO2 emissions in China. A national panel of 30 provinces and two sub-national panels for the time span 2003 to 2016 have been estimated by using SGMM estimator and panel threshold regression model. The results indicate that GDP has a positive and significant impact on carbon emissions and that the scale effect of ODI will increase the CO2 emissions. Additionally, ODI and Export Trade Structure are generally conducive to the reduction of carbon emission intensities, except that the impact of Export Trade Structure is not significant the in northern region. Moreover, GDP, ODI, and Export Trade Structure contribute to the reduction of CO2 emissions via the technical effects of energy efficiency, and ODI will help reduce CO2 emissions even as the output of energy-intensive industries grows. Therefore, regions should develop a more effective opening-up strategy based on their industrial distribution characteristics and development stages against the background of trade protectionism affecting the evolution of global value chains, use the spillover effects generated by various channels to effectively mitigate CO2 emissions, and seek sustainable economic growth accompanied by clean technologies and faster development of energy efficiency. [ABSTRACT FROM AUTHOR]

The copper demand and production in China are the largest in the world. In order to obtain the trends of the energy consumption and GHG emissions of copper production in China over a number of years, this paper uses a life cycle analysis method to calculate the above two indexes, in the years between 2004 and 2017. The life cycle energy consumption ranged between 101.78 and 31.72 GJ/t copper and the GHG emissions varied between 9.96 and 3.09 t CO2 eq/t copper due to the improvements in mining and smelting technologies. This study also analyses the influence of electricity sources, auxiliary materials consumption, and copper ore grade on the life cycle performance. Using wind or nuclear electricity instead of mixed electricity can reduce energy consumption by 63.67–76.27% or 64.23–76.94%, and GHG emissions by 64.42–77.84% or 65.08–78.63%, respectively. The GHG emissions and energy consumption of underground mining are approximately 2.97–7.03 times that of strip mining, while the influence of auxiliary materials on the above two indexes is less than 3.88%. [ABSTRACT FROM AUTHOR]

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China's aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies. [ABSTRACT FROM AUTHOR]

Promoting crop residue-based bioenergy (CRB) is a strategy for mitigating climate change and ensuring water-energy-food security. Although China has abundant crop residues, CRB is not well developed, and several policy targets are not being reached. These implementation gaps need critical examination as CRB development mainly relies on policy support. This examination provides a framework to assess the feasibility of this policy that covers several cross-cutting issues. By reviewing national policies, this paper analyzes the horizontal coherence of multisectoral CRB policies during the last two decades. Based on 55 semi-structured interviews, conducted with stakeholders, civil servants and experts, we analyzed the vertical coherence among policy implementation to further explore the causes of the limited success of CRB policies. The priority given to the cultivation and livestock sectors (particularly for soil improvement) in crop residue utilization policies and the development of energy policy targets resulted in horizontal policy incoherence. Furthermore, financial limitations were shown to be the most significant obstacle to CRB policy implementation. Successful CRB policy implementation requires a debate about the crop residue utilization for either energy or fertilizer to determine the more sustainable application. Appropriate incentives and increased technological quality of bioenergy projects are also recommended. [ABSTRACT FROM AUTHOR]

China's extensive economic growth has been accompanied with high levels of pollution, and excessive energy consumption has brought serious pollution problems. The use of financial resources to regulate green production modes and encourage high‐quality economic development has become a major focus in academia. At the same time, growth enterprise market (GEM) enterprises, which mainly operate in technology‐intensive industries, are assumed to have a simulating effect on regional innovation. Therefore, this paper utilizes the capital return differences of 4437 listed companies and 920 GEM companies based in 30 provinces of China from 2008 to 2018 to quantitatively analyze the levels of financial misallocation. With two‐stage regression method, the direct effect of financial misallocation on regional green total factor energy efficiency (GTFEE) and the indirect impact observed when taking regional innovation as an intermediary variable are discussed. Furthermore, dynamic threshold panel regression and heterogeneity analysis are used to verify the above nonlinear relationship. The empirical findings indicate that financial misallocation enhances innovation capability and further restrains GTFEE. With an improved degree of marketization and environmental regulation, the inhibitory effect of financial misallocation on GTFEE is more significant. [ABSTRACT FROM AUTHOR]

Combined decomposition of relative productivity growth and absolute changes in input/output variables helps to identify the driving forces of energy conservation and emission reduction. This paper proposes a framework based on the Luenberger productivity indicator (LPI) and the logarithmic mean Divisia index (LMDI) approach to analyze the energy–economy–environment nexus. The empirical case of the China's industrial sector for 2006–2014 is analyzed. Following this approach, we present a variable‐specific decomposition framework which attributes the overall productivity change and its sources to individual input/output variables. Empirically, we examine the relationships between the productivity growth and energy consumption within the LPI–LMDI framework across China's province‐level regions. The results show important spatial variation in the productivity measures. The LPI–LMDI decomposition implies that the industrial energy consumption increased with productivity growth appearing as the only mitigating factor. As regards the industrial SO2 emission, the individual productivity growth effect and the efficiency change effect remained as suppressing factors for emission abatement. These results can be used for evidence‐based decision making. [ABSTRACT FROM AUTHOR]

With the promotion of the pilot development of distributed whole county roof photovoltaics in China, problems such as power consumption, energy regional balance, and grid stability have become prominent. In this paper, an application mode of electric vehicle (EV) charging network and distributed photovoltaic power generation local consumption is studied. The management idea of two-layer and four model has been established, including the regional distributed photovoltaic output model, electricity consumption model, EV consumption model, and regional grid load dispatching model, which can realize the scheduling of the energy flow formed by photovoltaic, induce the charging of EVs, and make the photovoltaic consumption in office building areas and residential building areas complementary. Firstly, according to the randomness of photovoltaic power generation and EV charging, the dynamic response capability, power support capability, effective convergence time, system stability, system failure rate, and other characteristics of regional loads are comprehensively analyzed, and the grid energy management model of EV charging network and distributed photovoltaic is proposed. Secondly, according to certain statistical characteristics, the distributed photovoltaic will be concentrated, and EV charging will be prioritized to achieve nearby consumption. Finally, different scenarios are described, and the scenarios of charging in the park, community life, and power supply service are selected for analysis. This mode is intended to guide the consumption of new energy through economic leverage, which can realize the unified regulation of distributed energy convergence, consumption and storage. [ABSTRACT FROM AUTHOR]

Since the emergence of the COVID-19 pandemic, people all around the globe have seen its effects, including city closures, travel restrictions, and stringent security measures. However, the effects of the COVID-19 pandemic extend beyond people's everyday lives. It impacts the air, water, soil, and carbon emissions as well. This article examines the effect of energy and the COVID-19 pandemic on China's carbon dioxide emissions in light of the aforementioned context, using the daily data from 20 January 2020 and ending on 20 April 2022. Using the nonlinear autoregressive distributed lag model for empirical analysis, the findings indicate that COVID-19 pandemic confirmed cases and renewable energy advance environmental sustainability due to their negative effects on carbon dioxide emissions, whereas fossil fuel energy hinders environmental sustainability due to its positive effect on carbon dioxide emissions. Moreover, these results are also supported by the results of the frequency domain causality test and the Markow switching regression. In light of these results, there are several policy implications, such as vaccination, renewable energy utilization, and non-renewable energy alternative policies, which have been proposed in this paper. [ABSTRACT FROM AUTHOR]

With the continuous uptick in world energy consumption, green energy plays an increasingly significant role in alleviating energy depletion and promoting economic development. Due to regional differences, transportation restrictions, national policies and other reasons, there is a mismatch between green energy needs and resources across regions in China, which leads to misallocation of capital and labor between heavily polluting and nonpolluting enterprises. In this context, this paper first proposes a new measurement method: namely, the capital and labor mismatch index. Panel data of 30 Chinese provinces from 2008 to 2018 are utilized to calculate the index. The results show significant resource mismatch across provinces in China. In addition, we extend the green Solow model by combining capital mismatch, technological progress and environmental regulation into a dynamic analysis framework of economic growth. The empirical results show that all three factors have significant spatial spillover effects. Specifically, capital misallocation exerts a strong negative impact on economic growth, while the other factors increase it. [ABSTRACT FROM AUTHOR]

As low-carbon and sustainable manufacturing becomes the mainstream development direction of the current manufacturing industry, the traditional heavy industry manufacturing enterprises in China urgently need to transform. For the heavy cement equipment manufacturing enterprise investigated here, there is a large amount of energy waste during the manufacturing operation due to scheduling confusion. In particular, the multispeed, multi-function machining and the transportation of multiple automated guided vehicles (multi-AGV) are the main influencing factors. Therefore, this paper addresses a novel low-carbon scheduling optimization problem that integrated multispeed flexible manufacturing and multi-AGV transportation (LCSP-MSFM & MAGVT). First, a mixed-integer programming (MIP) model is established to minimize the comprehensive energy consumption and makespan in this problem. In the MIP model, a time-node model is built to describe the completion time per workpiece, and a comprehensive energy consumption model based on the operation process of the machine and the AGV is established. Then, a distribution algorithm with a low-carbon scheduling heuristic strategy (EDA-LSHS) is estimated to solve the proposed MIP model. In EDA-LSHS, the EDA with a novel probability model is used as the main algorithm, and the LSHS is presented to guide the search direction of the EDA. Finally, the optimization effect and actual performance of the proposed method are verified in a case study. The experimental results show that the application of the proposed method in actual production can save an average of 43.52% comprehensive energy consumption and 64.43% makespan, which effectively expands the low-carbon manufacturing capacity of the investigated enterprise. [ABSTRACT FROM AUTHOR]

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China's energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future. [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]

Most of the crude oil produced in China is highly viscous and easy to condense, and the pipeline transportation method is mostly heated. At present, frequency conversion technology is gradually applied to oil pump units. In order to find the best pipeline operation scheme, this paper is based on MATLAB programming software and established a corresponding mathematical model of oil pipeline energy consumption. This model innovatively takes the rotational speed of the variable frequency pump as one of the model optimization variables, calculating the pressure change and temperature change between stations of the pipeline, predicting the energy consumption of the pipeline and can guide the optimized operation of the pipeline, which has a high popularization and application value. An example of Qingtie Fourth‐line crude oil pipeline shows that among the genetic algorithm, particle swarm optimization, and simulated annealing algorithms for solving the optimization model, the particle swarm optimization algorithm has fast convergence speed, short optimization time, obtains the most optimal scheme, and can reduce energy consumption by 7.84%, which proves the practicability and creativity of the optimization model. [ABSTRACT FROM AUTHOR]

This paper proposes an extended Solow decomposition framework with a finite mixture model, which is incorporated to account for heterogeneous regimes. The model decomposes green economy into two different components, namely, green total factor productivity and factor endowment. Then, we reestimate the growth sources of green economy and especially the importance of energy consumption in China's provincial industries over 2000-2015. The empirical results suggest that there are three green growth regimes across Chinese provinces for overall economy and different industries. Specifically, some provinces switch regime over time, while the others maintain the same regime. Furthermore, when controlling for regime heterogeneity, the contribution of factor endowment decreases and that of green total factor productivity increases. With respect to energy consumption, traditional methods overestimate its importance in the primary and tertiary industries and underestimate that in the secondary industry. In addition, the reliance of China's overall economy and the secondary and tertiary industries on energy consumption decreases as economy develops. [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]

The current legal and policy system of renewable energy in China has set up a framework of policy instruments, which provides an important foundation for dealing with climate change and promoting the healthy development of the renewable energy industry with the goal of "carbon neutrality" and "emission peak". However, the current policy instruments cannot meet the needs for rapid development of the renewable energy industry. This paper investigates, analyzes, and concludes the status of renewable energy development along with related policy instruments in different renewable energy sources by literature and points out the problems of current policy instruments, and puts forward corresponding countermeasures. Moreover, from the perspective of energy consumption market transformation, the authors carried out an analysis of China's challenges of policy instruments, pointing out that China's renewable energy policy instruments have the potential to take one step further in the areas of the regulatory system, legal system and legal security system. [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]

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Northern China is vigorously promoting cogeneration and clean heating technologies. The accurate prediction of building energy consumption is the basis for heating regulation. In this paper, the daily, weekly, and annual periods of building energy consumption are determined by Fourier transformation. Accordingly, a period-based neural network (PBNN) is proposed to predict building energy consumption. The main innovation of PBNN is the introduction of a new data structure, which is a time-discontinuous sliding window. The sliding window consists of the past 24 h, 24 h for the same period last week, and 24 h for the same period the previous year. When predicting the building energy consumption for the next 1 h, 12 h, and 24 h, the prediction errors of the PBNN are 2.30%, 3.47%, and 3.66% lower than those of the traditional sliding window PBNN (TSW-PBNN), respectively. The training time of PBNN is approximately half that of TSW-PBNN. The time-discontinuous sliding window reduces the energy consumption prediction error and neural network model training time. [ABSTRACT FROM AUTHOR]

The building sector accounts for over 40% of global energy consumption. The utilization of renewable energy systems such as the solar-assisted heat pump (SAHP) in buildings has been shown to improve building energy efficiency and achieve carbon neutrality. This paper presents a review of the research and development of solar-assisted heat pumps for buildings in China. It firstly introduces the different stages of solar-assisted heat pump research. Secondly, the research on different types of heat pumps, the core components of heat pumps, the computer software used, and the economic feasibility evaluation of solar-assisted heat pumps are presented. Thirdly, the application of SAHPs in practical projects is examined and relevant regulations, standards, and policies for solar-assisted heat pump development in China are highlighted. Finally, recommendations for the future development of solar-assisted heat pumps in China are suggested. [ABSTRACT FROM AUTHOR]

Based on the panel data from 30 provinces in China from 2010 to 2020, this paper employs the panel vector autoregression (PVAR) model to investigate the dynamic relationship between a green economy and energy utilization level. The results show that: (1) the green economic development level and energy utilization level of 30 provinces in China have been continuously enhancing in recent years, the increase in green economic development level is higher than energy utilization level, and the geographical characteristics of both levels are significant, decreasing from East to West; (2) the causal relationship between the green economy and the energy utilization level has passed the Granger test; the two have formed a relatively high-level balanced relationship over a long period, showing a benign and orderly development trend; (3) the green economy generates a positive pulse response on energy utilization level in the initial period, but the impulse response weakens in the period of lag 1, entailing the relationship needs to be further strengthened in the long term; (4) in the process of continuous enhancement of energy utilization level, it is difficult to drive economic benefits due to high input costs in the initial stage, but it can form a two-way interaction relationship with a green economy as time goes by. [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]

As one of the most significant carbon emission departments in China, the power industry will gradually become the core hub of reducing carbon emissions in the process of undertaking carbon emissions transferred from other industries. Therefore, it is of vital importance to predict the power consumption in China's end energy consumption to achieve the carbon peak goal on time. This paper firstly uses the gray relational analysis model to study the relationship between power consumption indicators of the three major industries and some social and economic indicators and obtains the influencing factors with the greatest correlation with the power consumption of the three industries. Then, based on the analysis of socio-economic factors, considering different growth rates, the GMCN(1,N) model of electricity consumption in China's three major industries is established. Forecast data under different scenarios have important practical significance for formulating active and effective energy policies. The data indicate that the secondary and tertiary industries consume the greatest amount of electricity. It is estimated that the power consumption of China's three major industries will reach 10.15 trillion kWh (kilowatt hours) by 2030. [ABSTRACT FROM AUTHOR]

Energy saving is one of the main technique routes for net zero carbon emissions. Air compressor systems take up a large part of energy consumption in the industrial field. A pre-cooling air compressor system was proposed for energy saving by cooling the air before it flows in a compressor. The energy efficiency of the proposed system was analyzed. As additional energy consumption is required for air cooling, the feasibility of the pre-cooling method for energy saving was analyzed. As the efficiency of the pre-cooling air compressor system is mainly influenced by the environment temperature and humidity, applicability of the system in different regions and at different seasons was discussed. A pilot project was performed to verify the technical feasibility and economics of the proposed system. When the precooling temperature of the pilot system was set to 2 °C, the annual pneumatic-electrical ratio of the system can be increased by approximately 2% in several regions of China. This paper shows the pre-cooling air compressor system is feasible for energy saving. [ABSTRACT FROM AUTHOR]

A great abundance of rural houses lacking design guidance exists in the cold regions of China, often accompanied by huge energy loss. Particularly, a courtyard-style dwelling (CSD) has more complex and diverse building elements than a common house, rendering the design optimization extremely costly. Sensitivity analysis (SA) can screen the significant parameters of energy consumption for prediction and optimization. In this paper, (1) the design variables related to CSDs and their data details were extracted; (2) a ranking of parameters sensitive to energy demand was formulated; (3) an energy prediction model was trained and (4) dual-objective optimization was carried out. Using the survey data from 150 units in nine villages, 25 control variables were extracted for sequential global sensitivity analysis (GSA). Thus, the ranking of sensitivity parameters was formulated with the two-stage-and-three-sort GSA method. Furthermore, an energy prediction model was then trained with Gaussian Process Regression (GPR) and compared with the other four high-precision models. Based on the obtained prediction model, optimization was then carried out on energy and economic concerns. Consequently, a GSA-based workflow for CSD optimization was proposed to help architectural designers figure out the most efficient energy-saving parameter strategy. [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]

Distribution centers are quite important for logistics. In order to save costs, reduce energy consumption and deal with increasingly uncertain demand, it is necessary for distribution centers to select the location strategically. In this paper, a two-stage model based on an improved clustering algorithm and the center-of-gravity method is proposed to deal with the multi-facility location problem arising from a real-world case. First, a distance function used in clustering is redefined to include both the spatial indicator and the socio-economic indicator. Then, an improved clustering algorithm is used to determine the optimal number of distribution centers needed and the coverage of each center. Third, the center-of-gravity method is used to determine the final location of each center. Finally, the improved method is compared with the traditional clustering method by testing data from 12 cities in Inner Mongolia Autonomous Region in China. The comparison result proves the proposed method's effectiveness. [ABSTRACT FROM AUTHOR]

The foundation of the national economy is agriculture, agricultural modernization is the symbol of national modernization and agricultural mechanization is an important symbol of agricultural modernization. In this paper, the authors conducted an analysis of the agricultural mechanization levels of 31 provincial areas in China. In order to assess the agricultural mechanization levels of the provincial areas in China as accurately as possible, the authors adopted indicators in the year 2005, the year 2010 and the year 2015, and used the comparative static analysis method to observe the dynamic changes in the data over the three years. Eight items, including total agricultural mechanization power/grain output (10 million watts/10 k tons), number of large and medium-sized tractors/grain output (pcs/10 k tons), tractor plowing area/grain output (k hectares/10 k tons), total input of agricultural mechanization business operation/grain output (million yuan/10 k tons), total income of agricultural mechanization business operation/grain output (million yuan/10 k tons), and fuel consumption for agricultural production/grain output (hundred tons/10 k tons), were used as assessment indicators. With the gray weighted cluster assessment instrument, 31 provincial areas of China were classified into five gray categories at high development level, relatively high development level, medium development level, medium to low development level and low development level. An objective, scientific and comprehensive assessment of the cluster results was conducted in an effort to better provide references for the authorities to draft relevant policies and measures. [ABSTRACT FROM AUTHOR]

India and China are the biggest developing economies in the world apart from being the most populous nations. The population of China is expected to increase over 1.4 billion by 2050, and India may over take China and become the most populous nation at around 1.6 billion populace. These two nations are home to about 40 % of the total population in the world. Apart from this, India and China have attained remarkable success in the economic growth denoted by higher gross domestic product (GDP). The two nations together contribute about one-fifth of the world GDP. This paper discusses about the changes in the energy consumption pattern of developing countries like China and India aiming towards the sustainable development. Furthermore, this paper also analyses the most important drivers adding to the ecological problems, and gives a further glance at the ecological impacts of these in India and China. Over the last 50-60 years we have been emitting carbon dioxide at an accelerated pace. This has had an effect on the carbon dioxide concentration and other GHG gas concentrations, in the atmosphere. The paper also discusses about the effect of pollutants like NOx, SOx, Particulate matter and Mercury on the environment. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of the automotive industry has brought about several environmental and energy issues worldwide. Many countries have established fuel consumption regulations. Among them, fuel consumption regulations based on the curb weight or footprint have been put forward in China and the US. This paper mainly compares the effect of the application of footprint-based and curb weight-based regulations in China. To compare the effect of these two different benchmarks, a Chinese footprint-based fuel consumption regulation is designed based on the principles of the American footprint regulations and the actual conditions of the Chinese passenger car market, and fuel consumption data from 14 enterprises are also used. It is found that regulations help maintain market neutrality if the target value is separated into two curves according to the type of vehicle. Additionally, footprint regulations are more conducive to vehicle lightweighting than curb weight regulations. Finally, policy recommendations are drawn: to maintain market neutrality, there should be two target value curves in the fifth stage of the weight regulation: one for sedans and one for SUVs. Meanwhile, footprint regulation adaptation should be considered in the future to promote vehicle lightweighting in the Chinese market. [ABSTRACT FROM AUTHOR]