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With the economic and social development and population growth, as three basic interconnected resources, water, energy and food are gradually deficient and inharmonious. This research selected 31 provinces of China as the study area and collected data of 16 years' time series. The temporal and spatial synergetic change of water, energy and food was quantitatively described by wavelet analysis and MK test methods. The results show that water consumption for energy in 2001–2016 has the first main period of 12 years and the temporal synergetic change of water and energy would not be obvious in the future. According to the results, the resources consumption of water energy and food can be optimized to implement the sustainable utilization. Also, this paper proposed the adjustment strategy for the country. [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]

This paper uses statistical learning theory and big data analysis to study the energy consumption structure of China from qualitative and quantitative aspects during COVID-19. According to the domestic and foreign scholars' research on the optimization of energy consumption structure, the carbon emission factor is considered in the optimization of energy consumption structure. Taking the minimum energy consumption cost and carbon dioxide emission as the objective function, the carbon dioxide emission is taken as the objective function, and the total energy consumption and various energy consumption proportions as the constraint conditions, the multi-objective planning method is used to evaluate the energy consumption structure of China. The optimization model of source consumption structure is analyzed, and the medium and long-term energy transformation path and optimization model under low-carbon constraints are studied. Combined with the experimental algorithms related to big data, it is concluded that China's economic development mainly depends on a large amount of energy consumption during the COVID-19 period. On this basis, some suggestions are put forward to realize the sustainable development of China's economy and energy. [ABSTRACT FROM AUTHOR]

The heating requirements for district heating systems decrease sharply during the summer in China, which leads to the heating capacity of these systems remaining idle. To make full use of district heating systems, a novel approach for application of these thermal systems to cooling is proposed in this paper. The proposed system is based on a distributed absorption cooling (DAC) system driven by heat from the combined heat and power system. To investigate its energy-saving effects, the energy efficiency of the proposed DAC system was researched using the primary energy saving ratio (FESR) method. To assess the economic feasibility of the proposed system, the equivalent heating price for this DAC system was derived using economic analysis methods. The weight analysis method was used to analyse the factors affecting the energy efficiency of the DAC system. The research results showed that the energy efficiency and the economic feasibility of the proposed DAC system can be improved by increasing the heating-driven cooling efficiency. A new DAC system (IDAC) was then proposed based on integration of DAC with a heat-driven liquid desiccant dehumidifier (LDD), and the results show that the new system can increase the heating-driven cooling efficiency. [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 uses the super-efficiency DEA model to study the super-efficiency energy efficiency values of 30 provinces in China from 2006 to 2018, compares the differences between different regions, and verifies the impact of different environmental regulatory tools on energy efficiency. The results show that the regions with the highest energy efficiency in China's provinces are, in order, the eastern region, the central region, and the western region. At the same time, the impact of different environmental regulatory tools on energy efficiency is quite different. The number of environmental administrative penalties has a negative impact on China's energy efficiency, that is, increased number of environmental administrative penalties will reduce China's energy efficiency; market-encouraging environmental regulations tools impact on China's energy efficiency show a positive correlation, which means that market-encouraging environmental regulation tools are conducive to achieving a win-win goal of environmental regulation and energy efficiency in China. The voluntary environmental regulation tool has a negative correlation with energy efficiency, but it is not statistically significant, indicating that it is not the main factor affecting energy efficiency. In terms of other influencing variables, the level of economic development and technological progress are positively related to energy efficiency. The proportion of the secondary industry in regional GDP is positively related to energy efficiency, the relationship between energy consumption structure and energy efficiency is negative correlation, the degree of opening to the outside world has a negative correlation to China's energy efficiency. [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]

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]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [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 objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

Due to the ever-increasing quantity of produced and sold automobiles in China, many side effects such as resource depletion, energy shortages and air pollution have emerged. Remanufacturing, as the highest form of the recycling economy, has been promoted by the Chinese government as a major measure to save resources and energy. The remanufactured products, however, get very low market recognition from Chinese consumers. Thus, understanding how to cultivate consumers potential behavior of purchasing remanufactured products is the first step and also very important for developing the remanufacturing industry. This paper, focusing on heavy truck engines due to their short life expectancy and repair frequency, aims to identify the factors influencing remanufactured heavy truck engine (RHTE) potential purchase and analyze the relationship among those factors and potential purchasing behavior. Based on 301 questionnaires from Chinese heavy truck drivers, this paper develops a conceptual model to hypothesize how the influencing factors affect RHTE potential purchasing behavior. Hierarchical regression results show that individual factors (including product knowledge, product trust and environmental values) mediate the relationship between environmental factors (including product attribute and advertisement) and RHTE purchasing intention. Contextual factors (including incentive policy and purchasing convenience) moderate the relationship between RHTE purchasing intention and potential purchasing behavior. Our results indicate that individual factors are essential in cultivating RHTE purchasing intention and environmental factors are helpful for improving individual factors. Contextual factors can motivate the transformation from RHTE purchasing intention to potential purchasing behavior. [ABSTRACT FROM AUTHOR]

This study explores how an institutional innovation in the 20th Century – Coasean bargaining - could contribute to build a low carbon China in the 21st Century. China has surpassed all nations and become the world's largest emitter of CO 2 since 2007. A time-series analysis has revealed that crude oil and coal consumption, inter alia, are the primary factors contributing to the variations in CO 2 emissions in China. To honour China's commitments in the Paris Agreement 2015, this paper, with reference to the empirical results, estimates the impacts on various sources of energy consumption before 2030. Developed upon the Coasean bargaining framework (1960), the cap-and-trade (CAT) markets have contributed to reduce the pollutants and greenhouse gas emissions in the US and EU. This paper will illustrate how the CAT market can be complementary to administrative measures for CO 2 reduction in China. It will also discuss the institutional settings and constraints of the 7 pilot CAT markets in China, and also the national one to be rolled out in 2017. [ABSTRACT FROM AUTHOR]

Reform of energy prices in China has stepped into a crucial stage. It has become a controversial issue after the reform of increasing block tariffs (IBTs) for household electricity, followed by a time-of-use (TOU) pricing policy. Using ELES model, this paper estimates the price elasticity of residential electricity demand; based on perceived price and price elasticity, a power structure model demand response for nonlinear electricity price is proposed; taking Anhui province as a case, this paper analyzes the attainment situation of such policy objectives as electricity saving, consumer welfare, equity improvement and peak shaving, with the introduction of TOU pricing into IBTs for household electricity. The results show that IBTs helps reduce electricity consumption by 0.74%–0.93%, with minor energy effect；IBTs may lead to a maximum 1.57CNY increase of electricity expense per household per month, which is acceptable for residents. It also may reduce cross-subsidy to some extent. After introducing TOU pricing, the efficiency of peak shaving is only 2.25%–2.78%, and the load decrement at peak periods is far lower than the increase at valley periods; while the effect of electricity conservation and cross-subsidy reduction have been alleviated. In other words, peak-valley price is not only difficult to achieve its own objective effectively, but also prohibits the effect of IBTs. Based on the above conclusions, some policy recommendations are provided to improve the price reform of residential electricity, natural gas and other public resources in various regions of China and foreign regions with similar electricity market. [ABSTRACT FROM AUTHOR]

Summary: The consumption of fossil fuel has resulted in global warming, environmental pollution, and many other crucial problems. Replacing fossil fuel with renewable energy has become an important issue over the recent decades. As a renewable clean energy, wind power is a relatively well‐developed and promising energy method for current technology development in China. Under the background of growing demand for electricity and enhancing awareness for environmental, the “Internet+ wind power” concept has emerged based on both the wind power's characteristics that renewable and non‐polluting, and the rapid development of the Internet in China. Through querying an amount of literature and information, this paper reveals the resource endowment and policy environment about wind power and energy Internet at first. Then, the PEST‐SWOT strategy analysis model is used to analyze the internalities (strengths and weaknesses) and the externalities (opportunities and threats) of “Internet+ wind power”. According to these results, the paper puts forward some measures (development and utilization, business mode) for wind power accommodation. Then some policy recommendations have been proposed. The government should provide favorable conditions for wind power grid with the “Internet+” technology innovation. [ABSTRACT FROM AUTHOR]

At the phase of 13-th five-year plan in China, natural gas will play an important role in energy revolution. With the growth of consumption, natural gas infrastructures will become hot spots of future investment and pipeline network construction will also usher in a period of rapid development. Therefore, it is of great theoretical and practical significance to study layout methods of transport pipeline network. This paper takes natural gas transport pipeline network as a research object, introduces dominance degree to analyse benefits of pipeline projects. Then, this paper proposes Dominance Degree Model (DDM) of transport pipeline projects based on Potential Model (PM) and Economic Potential Theory (EPT). According to DDM of gas transport pipeline projects, layout methods of pipeline network are put forward, which is simple and easy to obtain the overall optimal solution and ensure maximum comprehensive benefits. What's more, construction sequences of gas transport pipeline projects can be also determined. Finally, the model is applied to a real case of natural gas transport pipeline projects in Zhejiang Province, China. The calculation results suggest that the model should deal with the transport pipeline network layout problem well, which have important implications for other potential pipeline networks not only in the Zhejiang Province but also throughout China and beyond. [ABSTRACT FROM AUTHOR]

Considering both regional heterogeneity and industrial heterogeneity, this paper proposes a three-hierarchy meta-frontier data envelopment analysis (DEA) to decompose energy efficiency and energy-saving potential into three components, i.e., industrial structure, regional balance development, and management. Based on this approach, the paper then analyses the historical evolution and current status of energy efficiency in China. The results show the following. (1) From 2001 to 2015, Mainland China's energy efficiency increased by a factor of 2.48, primarily because of technological progress and the optimization of its industrial structure. (2) Nonetheless, the current energy efficiency in Mainland China remains very low and energy inefficiency is as high as 0.5922, indicating that 59.22% of total energy consumption is invalidly used. Severe industrial structure inefficiency and regional balance development inefficiency are the two main factors responsible for the very low energy efficiency. (3) By promoting industrial restructuring, regional balance development, and management improvement, Mainland China is expected to save, respectively, 13.67%, 24.54%, and 61.73% of its current total invalid energy consumption. Based on the estimation results, this paper formulates strategies to improve energy efficiency and save energy for China's provinces based on their specific situations, considering not only the direction of industrial restructuring in both the short and long terms but also the path to improved energy efficiency. In addition, a brief discussion about the applicability and the preconditions for an application of the multi-hierarchy meta-frontier approach is given at the end of the paper. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

This paper explores the salient factors driving the changes in energy consumption in China's nonferrous metal industry during the 2000–2014 period. We employ the logarithmic mean Divisia index (LMDI) method to decompose the change in energy consumption into the energy structure effect (Δ E ES ), the energy intensity effect (Δ E EI ), the industrial structure effect (Δ E S ), the labour productivity effect (Δ E G ) and the industrial scale effect (Δ E L ). The main results revealed the following: (1) from 2000 to 2014, China's nonferrous metal industry's energy consumption increased by approximately 69.08 million tons of coal equivalent (tce); (2) Δ E G increased energy consumption in all years and was the largest contributor to the increase in energy consumption (followed by Δ E L ), whereas Δ E EI was the dominant factor in reducing energy consumption over the same period, accounting for 104.07% of the change in the absolute value of total energy consumption; and (3) Δ E ES and Δ E S contributed 0.24% and 1.45% to the change, respectively. At present, the decline in Δ E EI cannot completely offset the increases resulting from the other four effects. This paper then provides several policy recommendations based on these results. [ABSTRACT FROM AUTHOR]

Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

To find an efficient and economic way to convert wave energy, a one-base multi-buoy offshore floating wave energy converter Sharp Eagle Wanshan is designed, consisting of four absorbing buoys, one semi-submersible barge, and other components. The working principle of the device is described in this paper. An experiment of a 1:13.78 model machine was carried out to test the hydrodynamic performance of the device and make an initial evaluation for the design The influence of wave period, wave height, work load and wave direction was tested. After construction, two-stage open sea tests have been finished in the waters near Wanshan Islands from November 2015 to June 2016. The device showed great power generation capacity with total generated output of 30530.57 kWh, and largest daily generation of 1847.09 kWh. During the open sea tests, the energy conversion efficiency was measured, and results show that capture width ratio of Wanshan remains higher than 20% in the wave period between 4 and 6.5 s and wave height range of 0.6–1.8 m. After operating in a wide range of conditions, including a tropical storm on May 27, amounts of tests data, experiences and lessons have been obtained and will be summed up and presented in the paper. [ABSTRACT FROM AUTHOR]

A comprehensive review of the thermal power industry and the accurate forecasting of carbon emissions can provide valuable information to improve energy efficiency and act as a tool for policy makers to realize sustainable and low-carbon emissions from the thermal power industry. In this paper, we study the low-carbon development of China's thermal power industry based on an international comparison from three perspectives: review, analysis and forecast. Initially, we review both the international and national energy consumption of China; although gaps in energy efficiency still exist between China and countries with advanced thermal power technology, China's thermal power industry is gradually following a low-carbon development route. Then, we analyze low-carbon technologies for thermal power units, including ultra-super-critical technology, integrated gasification combined cycle technology, and carbon capture and storage technology and present a design for environmental protection technology for thermal power units. Carbon emissions should be effectively and successfully handled to improve the prospects of China's thermal power industry. Therefore, this paper forecasts carbon emissions by using a hybrid grey model that is optimized by the firefly algorithm and adjusted by weakening buffer operator based on the calculated carbon emissions. If China's carbon emissions from the thermal power industry increase according to the present rate, China will have difficulty in realizing its carbon reduction target by 2020. Finally, related future policies for the 13th Five-Year Plan of China are proposed based on low-carbon policies around the world with regard to financial, technological and industrial aspects to help the thermal power industry achieve healthy and low-carbon development. [ABSTRACT FROM AUTHOR]

Remanufacturing is a critical tool for solving resource depletion and environmental deterioration by reducing raw material and embedded energy consumption. The Chinese government, like many other countries, has been keenly interested in remanufacturing during the past ten years, because of its potential material and energy usage reductions. However, the development of the remanufacturing industry has been unsatisfactory because of little knowledge of its key industry indices. Many potential customers of remanufactured products do not trust the quality of remanufactured products. The major objectives of this paper are to classify the key industrial indices of the remanufacturing industry and to suggest future directions for improvements. To achieve these objectives, this paper used a combined method of grey incidence analysis and grey clustering, which are suitable for distinguishing critical industry indices that can measure the status of development situation of the remanufacturing industry. This approach was successfully applied to a case in Jiangsu Province, China, and consequently developed useful governmental and industrial policy recommendations for remanufacturing enterprises to promote that industry. The research results identified the “total number of employees with a master's degree or above”, the “total number of engineering and technical staff” and the “number of intermediate technicians” as the most appropriate industry indices to reflect the development situation of the remanufacturing industry in China. There are two more important findings. The first is that remanufacturing talents are the most important internal impetus of the remanufacturing industry and should be paid more attention to. The second is that investment in the remanufacturing industry does not have a strong positive correlation with industry characteristics. The “annual revenue of the remanufacturing industry” and huge investment have not played an effective role in promoting this industry so far. The main contribution of this paper is to provide an effective decision-making tool for defining key industry indices that have an important effect on the remanufacturing industry. The tool provides decision-makers a scientific basis for developing and implementing appropriate industry policies and improvement measures to expand the size and scope of the remanufacturing industry in the future. [ABSTRACT FROM AUTHOR]

National Development and Reform Commission and National Energy Administration have launched a series of policies on closing down small coal-power units, in order to reduce energy consumption and pollutant emissions. However, it is hard to change current situation in the short term since coal is still the domain source of power generation in China. Aiming at efficiently closing down the small power units, to create a power generation planning model with minimized costs needs to take both economic and technical aspects into account. In this paper, eight types of coal-fired generators are classified into three categories: Inefficient units; Efficient units; and Low-carbon units. This paper has developed a power generation planning model under multiple constraint conditions such as coal-power demand, total installed capacity, and carbon capture etc. Also, the model involves variable costs of CCS technology and contingency payments at the same time. This paper has applied the power generation planning model into China’s coal-fired power industry research during the period from 2016 to 2030. The results show that because the coal-power demand ends up with a drop following a rise, the total costs thereby shows a same trend. During the planning period, the fuel costs and the operation and maintenance costs decrease most obviously. Given the installed capacity, compared with the increase in the number of efficient units, the number of inefficient units shows a gradual decrease. The number of low-carbon units displays a slight increase. Since low-carbon units can capture and store 90% of their carbon emissions, the total carbon emissions from coal-fired power industry have significantly been reduced in their operation year. Thus, it is imperative to develop high efficiency and low-carbon units as they will be the major contributors to the sustainable development of the coal-fired power industry. [ABSTRACT FROM AUTHOR]

Dependency on coal consumption to maintain energy security is common to the majority of developing countries where the coal is found in abundance. China and India are the leaders in coal consumption from the developing countries group, so establishing a relationship between the coal consumption and the economic growth for these two will derive useful lessons for policy-makers. This paper re-examines the causal relationship between coal consumption and economic growth in China and India for the period 1969–2013, for the first time using a frequency domain–based Granger causality test proposed by Brietung and Candelon (2006). The empirical results support unidirectional causality running from coal consumption to economic growth for both China and India. The findings of this paper provide important policy implications for energy policies and strategies for these two countries under study. [ABSTRACT FROM PUBLISHER]

China has been plagued by hazy weather for a long time. Adjusting the energy consumption structure and reducing fossil energy consumption proportions are key to solving environmental problems. The "Electricity substitution" development strategy advocates "substituting electricity for coal, oil, and gas." To establish an efficient energy consumption structure, the strategy is conducive to an increase in the proportion of electricity in the terminal energy consumption market. Therefore, it is important to comprehensively compare the economic and environmental substitution benefits of electricity and other fossil energies when promoting the electricity substitution strategy. In this paper, the energy substitution cost evaluation model is established to compare economic benefits, and a life cycle assessment calculation method is used to obtain the environmental benefits of electricity substitution. Based on the calculation results, the environmental benefits are quantified as the economic cost with an environmental value standard. The comprehensive economic-environmental evaluation results obtained reveal that in the three substitution directions, the effect of substituting electricity for fuel oil is the most obvious. The substitution index considering the economic and environmental cost is 5.25%. "Substituting electricity for oil" can be used as a priority area to promote the electricity substitution strategy. The sensitivity analysis results reveal that reducing the proportion of coal-fired power generation, improving the proportion of clean electricity, and making strict financial penalties for creating pollution, can play strong roles in promoting electricity substitution. This paper provides a new research perspective for the comparison between electricity and fossil fuels. The results from this study can provide references for electricity substitution implementation and relevant policy formulation. [ABSTRACT FROM AUTHOR]

As an important energy base of China, Xinjiang is the key part of the “Silk Road” economic belt development strategy and is in an superior position. This paper analyzes the problems exist in the sustainable energy industry based on the distribution status of sustainable resources of Xinjiang. The evaluation index system of the application level of Renewable Energy Systems (RESs) is discussed using the wind farm as an example. Besides it investigates the advantages and disadvantages of the development process of each node in the “Silk Road” economic belt areas according to the current situation of the resources, economic and social development. Suggestions for the development of each area are proposed in the end. This paper will contribute to the sustainable development of renewable energy industry and economy in Xinjiang. [ABSTRACT FROM AUTHOR]

Whether industrial agglomeration can promote an increase in energy efficiency is of great importance to not only China’s energy conservation and emissions reduction plans, but also China’s future sustainable development. This paper uses statistical data from 285 cities, from 2004 to 2013, to analyze the effect of industrial agglomeration on energy efficiency. The spatial autocorrelation tests show that there is significant spatial autocorrelation and spatial heterogeneity in urban energy efficiency. Although dynamic spatial econometric results show that industrial agglomeration can promote an increase in energy efficiency from a country level, there are significant differences at a regional level. In the east, the effect of industrial agglomeration on energy efficiency has a threshold effect, but in central and western areas, industrial agglomeration can promote the increase of energy efficiency, with the positive effect in western areas greater than that in central areas. Finally, based on the research, this paper puts forward concrete suggestions to enhance energy efficiency. [ABSTRACT FROM AUTHOR]

Energy demand in China has risen rapidly and reached an unprecedented level due to the high-speed economic growth and modern development. As a result, the Chinese government faces a growing pressure to address the energy shortage and environmental deterioration, mainly resulting from an over-dependence on fossil energy. China has become both the largest energy consumer and CO 2 emitting country in the world in 2015. Utilization of potential for renewable energy is necessary for changing inappropriate energy consumption structure, protecting environment and achieving sustainable economic and social development. In view of such mentioned situation, this paper firstly introduces the energy structure as well as the development status of renewable energy in China, which includes hydropower, wind power, solar power, biomass power and other renewable energy. Besides, based on the current situation in China, the paper makes a preliminary prediction of the development of renewable energy in the country for the future decades, and proposes targeted countermeasures and suggestions. [ABSTRACT FROM AUTHOR]

Atmospheric reactive nitrogen (Nr) has been a cause of serious environmental pollution in China. Historically, China used too little Nr in its agriculture to feed its population. However, with the rapid increase in N fertilizer use for food production and fossil fuel consumption for energy supply over the last four decades, increasing gaseous Nr species (e.g. NH3 and NOx) have been emitted to the atmosphere and then deposited as wet and dry deposition, with adverse impacts on air, water and soil quality as well as plant biodiversity and human health. This paper reviews the issues associated with this in a holistic way. The emissions, deposition, impacts, actions and regulations for the mitigation of atmospheric Nr are discussed systematically. Both NH3 and NOx make major contributions to environmental pollution but especially to the formation of secondary fine particulate matter (PM2.5), which impacts human health and light scattering (haze). In addition, atmospheric deposition of NH3 and NOx causes adverse impacts on terrestrial and aquatic ecosystems due to acidification and eutrophication. Regulations and practices introduced by China that meet the urgent need to reduce Nr emissions are explained and resulting effects on emissions are discussed. Recommendations for improving future N management for achieving 'win-win' outcomes for Chinese agricultural production and food supply, and human and environmental health, are described. This article is part of a discussion meeting issue 'Air quality, past present and future'. [ABSTRACT FROM AUTHOR]

In recent years, the environmental problems caused by excessive carbon emissions from energy sources have become increasingly serious, which not only aggravates the climate change caused by the greenhouse effect but also seriously restricts the sustainable development of Chinese economy. An attempt is made in this paper to use energy consumption method and input-output method to study the carbon emission structure of China's energy system and industry in 2015 from two perspectives, namely China's energy supply side and energy demand side, by taking into account the two factors of energy invest in gross capital formation and export. The results show that neglecting these two factors will lead to underestimation of intermediate use carbon emissions and overestimation of final use carbon emissions. On energy supply side, the carbon emission structure of China's energy system is still dominated by high-carbon energy (raw coal, coke, diesel, and fuel oil, etc.), accounting for more than 70% of total energy carbon emissions; on the contrary, the natural gas such as clean energy accounts for only 3.45% of total energy carbon emissions, indicating that the energy consumption structure optimization and emission reduction gap of China's energy supply side are still substantial. On energy demand side, the final use (direct consumption by residents and government) produces less carbon emissions, while the intermediate use (production by enterprises) produces more than 90% of the total energy carbon emissions. Fossil energy, power sector, heavy industry, chemical industry, and transportation belong to industries with larger carbon emissions and lower carbon emission efficiency, while agriculture, construction, light industry, and service belong to industries with fewer carbon emissions and higher carbon emission efficiency. This means that the optimization of industrial structure is conducive to slowing down the growth of energy carbon emissions on the demand side. [ABSTRACT FROM AUTHOR]

Driving cycles provide a basis for vehicle development and calibration and also serves as the foundation for energy consumption and emissions certification of vehicles. This paper presents the China Light-Duty Vehicle Test Cycle (CLTC) developed by the China Automotive Technology & Research Center (CATARC). First, the important steps and technical routes toward the CLTC development process are summarized. Second, the specific CLTC development process is presented in detail, including the data acquisition and data analysis procedures, weighting factor development and driving cycle construction. Then, the main driving characteristics of the New European Driving Cycle (NEDC), the Worldwide Harmonized Light-Duty Vehicles Test Cycle (WLTC), the Federal Test Procedure (FTP-75), the CLTC and the actual collected data are compared. The CLTC has low average speed, a high idle speed ratio and more frequent acceleration and deceleration characteristics. Finally, 70 vehicles are tested based on the NEDC, WLTC, and CLTC according to their legislative procedures in the vehicle emission laboratories of the CATARC and the manufacturers. The results show that the CLTC's fuel consumption is much higher than that of the NEDC and WLTC, and CLTC can effectively reflect the actual fuel consumption of users. [ABSTRACT FROM AUTHOR]

Energy consumption monitoring technology plays a very important role in the realization of intelligent building energy saving, but it is not accepted widely in China. The main reasons for this are the low public energy-saving awareness and incomplete informational policy instruments; thus, studying how informational policy instruments affect the adoption of energy consumption monitoring technology and the impact of energy-saving awareness is of great significance to the widespread acceptance of energy consumption monitoring technology and its role in the realization of intelligent building energy saving. This paper introduces informational policy instruments and energy-saving awareness into technology acceptance model and builds an extended technology acceptance model. A questionnaire survey of 298 respondents who related to the operation and management of public buildings was used to explore the effect mechanism of informational policy instruments on adopting energy consumption monitoring technology. The results show that (1) informational policy instruments have no direct impact on the acceptance of energy consumption monitoring technology (2) and energy-saving awareness, attitudes, perceived usefulness, and perceived ease of use can mediate the relationship between informational policy instruments and behavioral intention of adopting energy consumption monitoring technology, namely, informational policy instruments can affect behavioral intention through six paths which are informational policy instruments ➔ energy-saving awareness ➔ behavioral intention, informational policy instruments ➔ energy-saving awareness ➔ attitudes ➔ behavioral intention, informational policy instruments ➔ attitudes ➔ behavioral intention, informational policy instruments ➔ perceived ease of use ➔ behavioral intention, informational policy instruments ➔ perceived ease of use ➔ perceived usefulness ➔ behavioral intention, informational policy instruments ➔ perceived usefulness ➔ behavioral intention. Finally, relevant policies and suggestions are put forward based on the results. [ABSTRACT FROM AUTHOR]

The current study proposed the improved non-linear multi-variable Grey Bernoulli model and predicted the CO2 emissions in China. Firstly, the paper presents an improved multivariate grey Bernoulli model (INGBM(1, N)) that considers the nonlinearities of the system characteristic data and related factors in establishing the grey model. Secondly, the influence of the relevant factors on the grey model's forecast accuracy has been considered. The more the number of relevant factors, the higher the relative level with the system characteristic data, the higher the calculation accuracy. However, predictive accuracy began to decrease again after the number of relevant factors more than a specific value. Thirdly, we selected the number of relevant factors as 4 (coal energy consumption, urbanization rate, crude oil, population) and carried out compared analysis with other grey models and non-grey models. The results show that the proposed model has the best forecasting accuracy. The proposed model is a generalization of several other grey forecasting models. China's COz emissions for 2019-2021 is forecasted. It estimated that the value would continue to increase over the next three years and reach 9958.57Mt by 2021. Finally, several measures have briefly mentioned reducing COz emissions based on the influence of relevant factors. [ABSTRACT FROM AUTHOR]

By coupling algorithmic optimization with parametric modeling and performance simulation, the building design process becomes a series of informed decision-making. Algorithmic optimization helps architects find high-performance design choices which balance complicated tradeoffs among various performance objectives. Although algorithmic-optimization aided design is more competent than the traditional manual method, due to complexities in building design, optimization frameworks are not easy to formulate. Focusing on the correlation between energy efficiency, visual comfort, and construction material cost, the current author formulates a bi-phase optimization framework to search for facade fenestration geometries. Afterwards, this optimization framework is applied to one representative office building in China. Optimal design choices are found to have much lower thermal loads and construction cast, but higher visual comfort. This paper highlights how the optimization framework regarding facade fenestration is formulated and how it performs during the building design process. [ABSTRACT FROM AUTHOR]

This paper has used a stirpat model to investigate the synergistic effect of CO2 emission, energy consumption, energy intensity, economic growth, population, urbanization and trade openness to demonstrate growthenvironment nexus in four selected developing Asian economies. Taking a panel data set from Bangladesh, China, India and Indonesia this study applies Autoregressive Distributed Lag (ardl) model and vec Granger Causality/Block Exogeneity Wald Tests. The empirical results show that energy intensity, urbanization, population, and per capita gdp growth are the raison d'être of CO2 emissions whereas trade openness is found to be negatively related to CO2 emissions. Conversely, energy consumption, urbanization, population and trade openness are positively related to per capita gdp. In addition, it also investigates the Environmental Kuznets Curve (ekc) hypothesis and the findings substantiate an inverted Ushaped relationship. Cross-section short-run coefficients of country-level data are inquired into to check the robustness of the panel outcomes. [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]

China is rich in crop straw resources, but straw burning is serious and resource utilization is not high. To solved the ecological pollution and resource waste caused by straw burning, and let straw carbonization equipment market promotion. The orthogonal experiment of carbonization process was designed according to the literature and the results of preliminary experiment. The straw biochar produced by process test was analyzed. The thermal characteristic parameters and combustion characteristic parameters were calculated. Straw biochar yield, fuel ratio, hydrocarbon atomic ratio, alkalinity index, high calorific value and dimensionless comprehensive combustion index Z were used as quality evaluation indexes for high quality straw biochar. Grey correlation analysis method and comprehensive quality score method were used to analyze the evaluation indexes and influencing factors, and the response surface method designed by CCD experiment was used to optimize the production process of straw biochar directional regulation. The experiment provides a theoretical basis for improving the energy utilization rate of straw and provides a large number of data support for the popularization and application of continuous straw carbonization equipment. The results showed that temperature was the primary factor affecting the quality of straw biochar. The five evaluation indexes of straw biochar quality except the yield of straw biochar were ranked as follows: Z > H/C >FR >AI >HHV, the quality of straw biochar produced by the equipment is stable and close to the burning quality of bituminous coal. In the orthogonal experiment, the experiment in group 16 and group 12 obtained a higher comprehensive score, and the optimal process parameter combination was A3B4C1. CCD test results after response surface optimization, in the balance of the two response values to meet the maximum, the predicted optimal process parameters are: cut after the corn straw, after 600 ℃ thermal carbonization for 50 min, the production of straw biochar output is 53.05%, its combustion index Z is 0.726 6. The empirical test showed that the difference between the experimental value and the predicted value was less than 0.2%, the fitting model and the response surface optimization method were accurate and feasible, and the combustion quality of straw biochar produced by the optimal carbonization process was greatly improved. The C content and H/C of straw biochar produced under the best technological conditions are increased by nearly 2 times, which is closed to the combustion quality of bituminous coal and anthracite, and far better than the barbecue biochar purchased in the market. Through the carbonization process in this study, the utilization quality of straw biochar can be controlled directionally, forming a reproducible and generalized quasi-directional regulation method of high quality fuelized straw biochar. The analysis methods greatly reduce the experiment times, choose the appropriate fuel straw biochar quality evaluation index, and on the premise of saving the cost of raw materials and energy, quick understanding of high quality energy straw biochar production process parameters, facilitate continuous piecewise uniform crop straw carbonization market-oriented all-round production system of rapid popularization and application.In addition, the experimental design and data analysis method in this paper can also provide data support for the production of straw carbonization process using straw as raw material for adsorption and fertilizer carbon. [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 method of combining DesignBuilder and jEplus + EA is proposed. • The best configuration form of windows and shading system is investigated. • Four-objective optimization about energy consumption and thermal comfort is solved. • A typical high-rise office building with large area glass is used as case study. • The research is conducted in four typical climatic regions of China. As a large energy-consuming part of the envelope, windows and shading system play a significant role in building savings. Once established in the primary design stage, it is difficult to make changes later, especially for high-rise buildings with large areas of glass. Moreover, strongly influenced by solar radiation, the configuration of windows and shading system conflicts with each other in terms of energy consumption and indoor comfort, the optimal configuration of windows and shading system under different climatic regions has not been well solved at yet. This paper proposes an easy-operation, useful, and efficient multi-objective optimization method, using a smart optimization algorithm NSGA-II in combination with DesignBuilder energy simulation software, especially beneficial for non-programming designers. In this research, a typical high-rise office building with a large area window has been selected as a case study. Building orientation, the configuration of windows and shading system, including materials for each layer of the double-layer window, installation angle and depth of overhangs have been taken into consideration, aiming to minimize the heating, cooling, lighting energy consumption and discomfort hours, and to find the mutual relationship between each other. A set of Pareto solutions can be obtained after optimization, and the most recommended variable parameters of windows and shading system in four cities representing severe cold climate, cold climate, hot summer and cold winter climate, and hot summer and warm winter climate can be identified, respectively. Besides, Pareto optimal solutions can give designers different scheme choices based on preferences, which are of great significance to provide guidance and suggestion for designers in the early design of buildings. [ABSTRACT FROM AUTHOR]

With the depth increasing and the improvement of mining mechanization of the coal mine, heat hazard is becoming more and more serious, the ice cooling system is gradually promoted and applied in China for recent years, but the cooling capacity and energy efficiency ratio (EER) test and analysis for such system is seldom reported. The cooling capacity and EER of the refrigerating equipment of an ice cooling system of a coal mine are tested and analyzed in Shandong Province in this paper. The test result indicates that the refrigerating capacity and EER are lower and both the pre-cooling units and the ice making system have a large variable range. It points out that it should not evaluate the ice cooling system by the test data only in this mine but expect more test data and analysis of the ice cooling system in other coal mines to get a more scientific conclusion. And the test, analysis and comparison for different kinds of cooling system are also expected to explore suitable cooling system while a full consideration of the geological conditions and other factors of the mine are taken into consideration. [ABSTRACT FROM AUTHOR]

Under the trend of global low-carbon development, reasonable and accurate prediction of electricity consumption plays an essential role in vigorously adjusting power system structure, promoting electrification, and other energy-saving and emission reduction measures. Considering the development trend of energy consumption, this paper introduces the Logistic model of energy structure into the system structure, and establishes a novel grey prediction model with system structure. According to the division of energy factors with similar attributes, this model seeks the internal relationship of the development of electricity consumption and describes the interaction between related factors and multiple main factors in the form of equations, which makes the model have better applicability and stability. In the validation part, the ten types of energy are divided according to their attributes, and the main factor group and the related factor group are distinguished. The model proposed in this paper is used for simulation and prediction, and is compared with the three types of models (six models). In the two cases, the simulation error of the new model is as low as 3.9790%, and the prediction error is 0.5645%. Compared with other models, the new model has shown good performance in the case of electricity consumption forecasting in China. The effectiveness of the optimization of the model in structure, background, and application is verified. At the same time, based on the analysis and prediction of China's consumption data, this paper gives relevant policy suggestions for developing China's power structure. • A novel model based on energy background (EPMGM(1,M,N)) is established. • The relationship of factors in the system are characterized by the equations. • A Logistic model based on energy structure is introduced to the new model. • China's electricity consumption is effectively predicted by the model. [ABSTRACT FROM AUTHOR]

Facing the challage of energy conservation and emission reduction in the building sector, most energy saving strategies of central heating only focus on the performance improvement of building envelope, ignoring the impact of energy use behavior. This paper proposed a building energy conservation strategy based on energy use behavior analysis, which provides a perspective for in-depth exploration of building energy conservation. After investigating a typical university in the northern China, the energy use behaviors were characterized and two different DeST energy consumption models before or after considering energy use behavior were established. By comparing the results calculated by these two models, the impact of energy use behavior analysis on building energy consumption was quantitatively analyzed. The results show that the heating energy consumption and carbon emission can be reduced by 23.28% and 23% respectively through the proposed strategy based on energy use behavior. Therefore, the analysis of energy use behavior can provide a theoretical basis for heating operators to make decisions on energy supply regulation. With central cooling and heating further popularizing in the future, the research methodology of this paper has more extensive reference value for energy conservation and emission reduction strategies in the building sector. [ABSTRACT FROM AUTHOR]

China has launched energy quota right trading system, as one of the sustainable operations, since 2016 to cap the total energy consumption, however the economic and energy saving effect of this new policy is unclear. Based on the input and output panel data of China's 29 manufacturing sub-industries, this paper constructs the non-parametric optimization model under the command-and-control and the energy quota right trading scenario, to compare their potential economic gains and energy savings of these two polices for Chinese manufacturing industries. Results show that, whether at overall level or at the sub-industries level, the economic potential and energy-saving potential from energy quota right trading are higher than those from command-and-control. However, a part of energy-saving potential will be squeezed out due to the negative externality of the energy market trading. We suggest the well integration of both command-and-control and the market mechanism to achieve a Win–Win development. [ABSTRACT FROM AUTHOR]

The rapid urbanization in China has been associated with a growing hunger for energy consumption and steadily-increasing CO2 emissions. In this paper, an integrated system dynamics model composed of four sub-models is developed to simulate the urbanization and energy consumption in China from 1998 to 2050. Three scenarios are provided: accelerated economic development, emission reduction constraint, and low-carbon oriented. The result reveals that rapid economic growth and sufficient energy supply will foster China's urbanization in all three scenarios. Under the low carbon transition scenario, China's urbanization rate is expected to reach 76.41% in 2050, both reducing carbon emissions and promoting eco-friendly development. All three scenarios witness a dramatic growth of residential energy consumption and a steady increase of industrial energy consumption. China still has a long way to achieve the low-carbon transition goal. China should promote renewable resources and energy, pursue a low-carbon lifestyle, and reduce energy intensity over the next few decades. [ABSTRACT FROM AUTHOR]

This paper analyzes energy-related CO 2 emissions and production water use as the constrictions for energy development in northwestern China. By two period division methods such as one-year one-period and multi-year phased period, CO 2 emissions per unit of GDP and production water use are decomposed with a temporal decomposition technique. By compared with the average national level, carbon intensity and water intensity in 2016 are decomposed with a cross-regional decomposition technique. After a pairwise comparison of each influence factor between studied regions, what causes the variations in both intensity indicators among these five northwestern provinces is distinguished. Then the restrictions of energy development could be studied within an integrated framework of decomposing CO 2 emissions and water use in two dimensions such as time and space. Besides, the secondary industry is divided into non-energy industry and energy industry for the analysis of the effects of energy industry development. Moreover, renewable energy substitution factor is newly added to the decomposition of CO 2 emissions per unit of GDP, which is acted as an influence factor for the reduction of CO 2 emissions by the change of energy consumption structure. Finally, policy suggestions for sustainable development of energy industry in northwestern China are proposed. • Carbon intensity and production water use are decomposed by a temporal LMDI technique with two methods of period division. • Carbon intensity and water intensity in 2016 are decomposed by a multi-region decomposition approach. • Renewable energy substitution factor has been added into the spatial-temporal decomposition of carbon intensity. • The secondary industry is divided into energy industry and non-energy industry. • Renewable energy should be promoted during energy development in northwestern China. [ABSTRACT FROM AUTHOR]

Crop straw is a valuable biomass energy resource and raw material for livestock forage, organic fertilizer and industrial use. However, the comprehensive utilization level of straw resources in China is not high due to various reasons including agricultural intensification, capital shortage and farmers’ cognition. Regional, seasonal and structural surplus of crop straw is common in China and a lot of straw is discarded and burned casually, especially in rural areas. It is not only a huge waste of resources, but also leads to serious atmosphere and soil environment pollutions. Thus, it is of great importance to improve the straw utilization rate. That take regional planning as a whole and realize full utilization of the regional total straw resources is a good strategy. Assessment of regional straw resources’ quantity, type, and distribution pattern is the prerequisite to achieve regional straw resources full utilization. In addition, the utilization modes and levels of straw resources are also restricted by many other factors including the social and economic development status. Thus, to make better use of straw resources and optimize utilization structure, it is necessary to take all the above factors into comprehensive consideration, carrying out scientific layout and rational planning. Hunan province is an important agricultural province and also a main producing area of double cropping rice in China. The present study estimated the straw quantity and amount per capita of the main crops in Hunan province. The spatial distribution patterns of straw resources in Hunan province were also analyzed. In addition, the paper also analyzed the potential of full utilization of the total straw resources in the province through comparing the current straw utilization structure and quantities with their corresponding competitive straw demands. The results showed that the theoretical and collectable amount of the main crop straw resources in Hunan province in 2018 were 4 021.7× 104 t and 3 039.1×104 t, respectively. The mean amount per capita of straw resource is only 0.68 t, which is much lower than the national average level. The straw of rice, rape, maize and vegetables accounted for 64.7%, 16.0%, 6.1% and 7.5% of the total straw resources of the Province, respectively. The various types of crop straws exhibited different spatial distribution patterns. The amount of rice, rape and vegetable straw increased from west to east and south to north in the province, whereas corn straw displayed an opposite distribution trend. Through estimating the potential utilization ways of straw resources, the competitive demand of straw in Hunan province included 887.3×104 t for fertilizer, 885.1×104 t for fodder, 65.7×104 t for raw material and 83.2×104 t for stroma material. The remaining amount of straw for potential energy utilization was 1 117.9×104 t. Considering the current straw utilization structure and the results as above, the overall trend of realizing full utilization in the province should be to improve the ratio of fodder and energy utilization and slightly reduce fertilizer utilization on the basis of maintaining the amount for stroma and raw material utilization. [ABSTRACT FROM AUTHOR]

• Energy transitions are a trend that is reshaping the global energy system • Renewables deployment through electrification is fundamental for decarbonization • Electrification tendency upraises power system's security as a policy priority • Geography and geopolitics do shape strategies towards a sustainable power system • The Energiewende represents the most comprehensive energy transition strategy Energy transitions have placed the power system in the center of the energy agenda, since electricity constitutes a bridge between renewable resources and the decarbonization of the global economy. Therefore, due to stochasticity of renewable sources, guaranteeing a secure supply of electricity is crucial for achieving sustainable development, which has led energy security to become a priority within energy policy. This paper presents a review of four national security strategies focused in the power sector. The covered countries are the leaders in terms of electricity generation in their region, namely China, the United States, Germany and France, thus different approaches in the matter are contrasted and discussed. The analyzed countries tend to develop strategies focused on exploiting their indigenous energy resources. Nations possessing conventional fuels are willing to use them for enhancing their energy security under an all-of-the-above strategy, which implies also the expansion of renewable energy installations, as in the cases of the United States and China, while those ones that lack of fossil resources tend to compensate this hardship by relying deeper on renewable energy and reducing their energy consumption, as the European countries do. A frame for evaluating the effectiveness of these strategies on procuring energy security would be convenient for policy makers in order to strengthen security of the power sector. [ABSTRACT FROM AUTHOR]