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Energy consumption has promoted a continuous development for economy and society, but it has also brought serious environmental pollution problems which endanger public health. In order to focus on the impact of PM 2.5 emissions from future energy consumption on human health better, this paper estimated PM 2.5 emissions caused by energy consumption in Beijing in 2020,2025 and 2030 by setting the baseline scenario, emission reduction scenario, intensified emission reduction scenario and the data of the base year 2015, which will be 162.6 thousand tons, 195.9 thousand tons and 235.9 thousand tons in the baseline scenario, 143.1 thousand tons, 151.8 thousand tons and 160.9 thousand tons under the emission reduction scenario, and 132.6 thousand tons, 130.2 thousand tons, 127.9 thousand tons under the intensified emission reduction scenario. Finally the paper measured the number of different health effect ends caused by PM 2.5 emissions and the economic loss. The results showed that there was a rapid increase, a mild increase and a moderate decrease in energy consumption and PM 2.5 emissions in Beijing under the three scenarios from 2015 to 2030. Besides, under the same scenario and the same concentration level baseline, the number of the internal medicine (over the age of 15) was the largest, and the economic loss caused by total death rate was the biggest. This article provides suggestions to reduce PM 2.5 emissions and public health effect ends for Beijing in the future. [ABSTRACT FROM AUTHOR]

Plug-in electrical vehicles (PEVs) are introduced as a compatible transportation system for the environment. Manufacturing technology of electric vehicles (EVs) could bring an opportunity to implement them as energy storages. By expanding the use of renewable energy sources (RESs), the role of energy storage system is highlighted to overcome power generation fluctuations. Integrating PEVs and RESs could be profitable for both PEV and RESs owners. In this paper, a structure of renewable energy sources based micro grid (RMG) is considered. The proposed RMG has been equipped with a parking lot in order to control and aggregate PEVs. This paper investigates the optimal energy management problem of the RMG with the presence of PEVs. The objective of the RMG owner is to minimize the cost through generating power with its local generators and trading energy with the power market considering the market price. Also, the RMG could incentive PEV owners to take part in the demand response (DR) programs as a flexible load. It could bring profit for both PEVs and RMG owners. The existence uncertainties are modeled in the scenario-based framework. Three case studies are analyzed to display the effectiveness of the proposed model. As a result, utilization of the parking lot has decreased the cost of RMG about 40%. Additionally, implementing DR program during the charging process of PEVs could bring extra profit for both RMG and PEVs owners. The results have shown the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Transport is one of the sectors of the energy consumption where the presence of renewable energies is lower and its increase is hard to achieve especially in countries that import all the fuels that they consume. This paper addresses the progress that Portugal is making toward a more sustainable transport sector. A near- and medium- term scenario analysis is performed, based on the energy consumption in the past and on a detailed evaluation of the trends for renewable energy in the transport sector. The near-term scenarios aim at portraying the conditions that allow the country to fulfill the target of 10% renewable share in transportation established by the European Union. The medium-term scenarios highlight the implications, in terms of emission reduction and of energy independence, deriving from the use of electric vehicles and natural gas, synthetic and fossil, as alternatives to liquid fuels. The results show that electric vehicles would substantially reduce the total energy consumption and the greenhouse gas emissions, while the promotion of routes for synthetic natural gas would contribute to taking advantage of local resources. The paper also provides some insights about the design of future policies to build a more sustainable transport sector. [ABSTRACT FROM AUTHOR]

Coal preparation is an indispensable stage in coal production, during which run-of-mine coal is transformed into products (clean coal) suitable for the market. By-products (coal gangue, coal slime, and middlings) are also produced during this process, which are complex mixtures containing small amounts of coal and many impurities (minerals). However, in recent years, against a background of rising energy demand and growing yield of by-products, the Chinese Government has successively promulgated a series of policies to encourage and support comprehensive utilization of coal by-products. As a result, the comprehensive utilization of coal by-products has attracted considerable research interest and resulted in the publication of many academic articles (mostly written in Chinese). However, few previous studies have addressed the problems and negative effects of comprehensive utilization of by-products. Consequently, the purpose of this paper is to provide a comprehensive literature review and analysis of the comprehensive utilization of coal-preparation by-products in China. The key focus of the review is on revealing problems during processing and giving indications of potential solutions. In addition, the paper also gives recommendations for future work in the field. To this aim, this study reviews the body of knowledge on the topic, through a systematic review of the literature. After searching for publications in four databases (Elsevier, Springer Link, CNKI, and ACS) and a standard Internet search engine, 203 studies (published from 1982 to 2017) have been included in the review due to their relevance for the stated aims. This study makes a significant contribution to the literature because it interprets the comprehensive utilization of coal-preparation by-products from a new viewpoint. Despite its advantages, the comprehensive utilization of by-products is associated with negative impacts that cannot be ignored, so it is very important to consider environmentally benign methods of utilizing these by-products. The findings of the present study can provide valuable information for researchers interested in the field, and hopefully motivate and promote relevant research and policy-making in the near and long-term. [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]

As one of the most widely used power sources in the engineering field, compressed air is especially common in industrial applications. In a traditional pneumatic circuit, a three-position five-way valve is used to control the air inlet and exhaust with a single pressure, which has low efficiency. This paper proposed a novel bridge-type circuit with variable pressure control using four on-off valves to improve the energy efficiency of compressed air for pneumatic actuators. The key idea of the method was to use air expansion energy to do work. Reducing the volume of consumed air was the goal, and a numerical method was presented to calculate the optimal on-off time sequence of the four valves using nonlinear dynamic optimization. The sequence was obtained based on the combination of a finite element polynomial configuration method and a reduced space sequential quadratic programming algorithm. Then, experimental validation was conducted to illustrate the energy efficiency, including pneumatic cylinder motion test under different conditions. Compared with the traditional circuit, the experimental results show that the bridge-type circuit put forward by this paper can significantly improve the energy efficiency of pneumatic driving systems by 50–70%. Additionally, the bridge-type circuit allows the piston to move smoothly to the end of the stroke, which can take the place of the function of cushion component and speed control valve of the traditional circuit. [ABSTRACT FROM AUTHOR]

Electricity consumption and material wastage of manufacturing industries have directly or indirectly influenced the environment. Many manufacturing enterprises are committed to improving energy and material efficiencies. To achieve this goal, one of the high-efficiency ways is to optimize the scheduling. In this study, a multi-object optimization model is constructed for a particular kind of batch processing scheduling problem existed in flexible flow shops, where the objects include makespan, electricity consumption and material wastage. First, the models for electricity consumption and material wastage are built, based on which a mathematic model for scheduling problem is built afterwards. Finally, a hybrid non-dominated sorting genetic algorithm II (NSGA-II) method is employed to solve the multi-object optimization scheduling model. A case study based on a real-world paper mill industry is presented to demonstrate the effectiveness of the method and its application in practice. Moreover, a real-life scheduling problem is investigated, and the result shows that the proposed method is more efficient than manual scheduling in energy and material saving. In fact, many tissue paper mills or other manufacturing industries schedule by manual labor in China, indicating that the proposed method has a significant potential in improving energy and material efficiencies in the studied flexible flow shop, and in energy and material saving in similar industries. [ABSTRACT FROM AUTHOR]

Behaviour, practices and culture constitute a powerful human factor in the energy system; in particular the interactions between technologies, practices and norms lock individuals in to certain patterns of (often inefficient) energy use. Consequently, behaviour change has gained traction amongst policymakers as a key area of intervention given the impact energy-related behaviours have on climate change. Given the increasing emphasis within policy perspectives in the European Union, it is surprising that a gap in understanding of the success factors of behaviour change initiatives remains. This paper addresses this gap by identifying and characterising behaviour change initiatives across five European countries (the UK, Ireland, France, Italy, and Spain). The paper provides insights into the success factors and commonly encountered barriers to behaviour change initiatives. Initiatives are classified into 6 broad categories (community-based interventions; information and awareness based interventions; eco-districts; show-case events; energy switching; and smart-technology focused interventions). The results suggest that there are significant knowledge gaps between what is known to work to engage individuals in behavioural change and what is currently being applied in practice. An over-reliance on education and awareness-raising projects is evident, illustrating that such projects do not sufficiently aim for sustained behavioural changes. A dearth of projects incorporating fiscal measures, regulations or legislation to drive behaviour change reflects reluctance on behalf of decision-makers to engage widely with diverse approaches to foster lifestyle change. This paper contributes understandings of the different models and delivery tools employed to change energy-related behaviours; insights into the critical success factors that underpin best practice and the barriers to action; and a ‘what works in practice’ overview of the meaningful approaches to change behaviour. [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]

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]

This paper presents a simple computational model for determining whether additive manufacturing or subtractive manufacturing is more energy efficient for production of a given metallic part. The key discriminating variable is the fraction of the bounding envelope that contains material – i.e. the volume fraction of solid material. For both the additive process and the subtractive process the total energy associated with the production of a part is defined in terms of the volume fraction of that part. The critical volume fraction is that for which the energy consumed by subtractive manufacturing equals the energy consumed by additive manufacturing. For volume fractions less than the critical value, additive manufacturing is more energy efficient. For volume fractions greater than the critical value, subtractive manufacturing is more efficient. The model considers the entire manufacturing lifecycle – from production and transport of feedstock material through processing to return of post-production scrap for recycling. Energy consumed by processing equipment while idle is also accounted for in the model. Although the individual energy components in the model are identified and accounted for in the expressions for additive and subtractive manufacturing, values for many of these components may not be currently available. Energy values for some materials' production and subtractive and additive manufacturing processes can be found in the literature. However, since many of these data are reported for a very specific application, it may be difficult, if not impossible, to reliably apply this data to new process-material manufacturing scenarios since, very often, insufficient information is provided to enable extrapolation to broader use. Consequently, this paper also highlights the need to develop improved knowledge of the energy embodied in each phase of the manufacturing process. To be most valuable, users of the model should determine the energy consumed by their manufacturing process equipment on the basis of energy-per-unit-volume of production for each material of interest – considering both alloy composition and form. Energy consumed during machine idle per unit time should also be determined by the user then scaled to specific processing scenarios. Energy required to generate feedstock material (billet, plate, bar, wire, powder) must be obtained from suppliers. [ABSTRACT FROM AUTHOR]

Within the urban water cycle, energy issues have been mostly studied for wastewater treatment plants, ignoring that drinking water treatment plants (DWTPs) also consume a significant quantity of energy. Knowing the real energy consumption of DWTPs is the starting point for any energy-saving initiative. This paper benchmarks the energy efficiency measures of a sample of real DWTPs using the data envelopment analysis methodology. Subsequently, whether these facilities are affected by economies of scale is investigated. This issue is essential for planning new DWTPs that minimize energy consumption. In the second stage of analysis, some structural and managerial variables affecting energy efficiency are explored. The results showed that most of the DWTPs analysed have a suitable size but can greatly improve in terms of saving energy. It was found that the age of the plants and the water company operating them significantly affects its energy efficiency. The approach applied in this paper is of great interest for water regulators and company managers since it enables them to learn from the best practices for reducing energy consumption in DWTPs and contributes to improving the sustainability and efficiency of the urban water cycle. [ABSTRACT FROM AUTHOR]

Cities are suggested as being the key level for shifts towards more sustainable modes of production and consumption. The building sector with its significant carbon footprint plays an important role in urban climate change adaptation strategies. Using the case study of Brisbane (Australia), the paper examines the place-specific contextualisation of green building transitions by analysing the co-evolution and interplay of building practices, policy making and involved actors. Drawing on theoretical approaches of Transition Studies and Evolutionary Economic Geography, we trace back and analyse policy and economic trajectories focusing on formative and hindering processes. The paper discusses ambivalent pathways and 'regime resistance' caused by local economic and political specificities. The analysis illustrates how crucial the continual support from both policy makers and industry actors can be when economic market mechanisms do not drive sustainability transitions. Regime actors can play a powerful role as 'transition detractors' and can determine the dynamics and the scope of sustainability transitions. [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 presents a green one-to-one pickup and delivery problem including a set of new features in the domain of green vehicle routing. The objective here is to enhance the traditional models for the one-to-one pickup and delivery problem by considering several important factors, such as explicit fuel consumption (which can be translated into emissions), variable vehicle speed and road categorization (i.e., urban, non-urban). Accordingly, the paper proposes a mixed integer programming model for the problem. A case study from the Netherlands shows the applicability of the model in practice. The numerical analyses show that the investigated factors has a significant impact on operational-level logistics decisions and the selected key performance indicators. The results suggest that the proposed green model can achieve significant savings in terms of total transportation cost. The total cost reduction is found to be ( i ) 3.03% by the use of explicit fuel consumption estimation, ( ii ) up to 10.7% by accounting for variable vehicle speed and ( iii ) up to 10.5% by considering road categorization. As total cost involves explicit energy usage estimation, the proposed model has potential to offer a better support to aid sustainable logistics decision-making process. [ABSTRACT FROM AUTHOR]

During its operation, a photovoltaic (PV) panel is exposed to various and in general, stochastic thermal and wind conditions, which have a significant influence on the PV panel operating temperature. The increased PV panel operating temperatures normally have an unfavorable effect on the PV panel performance and lifetime, thus various cooling methods were proposed in order to increase the photovoltaic energy conversion efficiency. A reasonable step before the consideration of a specific cooling strategy is to obtain a PV panel performance analysis with respect to its surroundings (specific geographical micro location) for various operating conditions. This paper presents such a study, which was conducted through an experimentally validated numerical model. Numerous CFD simulations regarding heat and fluid flow around a monocrystalline PV panel coupled with a heat flow simulation inside the PV panel elements were conducted. The aim of the paper was to investigate an effective heat transfer field and the variations in the PV panel temperatures with respect to various wind velocities and heat source conditions. A detailed study regarding pressure, viscous and body (buoyancy) forces as well as their effects on flow separation was also conducted. The study also investigated the changes in the effective heat transfer near the PV panel. The gained results in this study turned out to be useful for the consideration of a specific cooling strategy for PV panels, which can ultimately lead to an increase in PV panel efficiency and lifetime. Additionally, the conducted study could be used to improve the delivered electricity prediction from the PV system at a selected location defined by specific wind velocities and solar insolation distributions. [ABSTRACT FROM AUTHOR]

This paper reviews the literature on smart cities. Offering a critical synthesis of the material, it advances a Triple Helix inspired account of smart cities as future internet-based developments. In particular, as future internet-based developments covering the digital infrastructures, data management systems, renewable energies and cloud computing of a regional innovation in the Internet of Things (IoT). More specifically, as a regional innovation in the IoT that covers the morphology of urban extensions, infill and mass retrofits, which smart cities call for the development of. Focusing on the metrics of mass retrofit proposals, the paper also serves to demonstrate how the urban morphology of such regional innovations matter in the sense they tell us that being aware of the considerable energy savings and CO 2 reductions, which IoTs offer cities to be smart, is not enough. Not enough, because without knowing whether the costs and benefits under-gridding the sustainability of city-districts are shared equally, it is impossible to say if the 65% energy saving and 78% reduction in CO 2 , attributed to the data collection, information processing and smart (micro) grids of mass retrofits is socially just. The paper suggests that in order to verify this, it is necessary for smart cities to first baseline the social-demographic structure of retrofit proposals. Then draw upon the environmental profile this evaluation generates to assess whether the regional innovation creates the wealth needed to under-grid the sustainability of city-districts. Under-grid the sustainability of city-districts as the energy efficient-low carbon zones of an inclusive growth strategy seen to be socially just. Seen to be socially just, because the costs and benefits underlying the 1.5 ha ecological footprint that surfaces from this regional innovation are equally appropriated as the proceeds of a wealth creation, which contributes to the resilience of city-districts as energy efficient-low carbon zones. As energy efficient-low carbon zones, whose inclusive growth strategy also emerges as a post-carbon economy claiming to be climate neutral. [ABSTRACT FROM AUTHOR]

To reduce the water footprint of a cement plant is one of the most important clean production performance indicators of the manufacturer. This paper proposes a comprehensive model for evaluating water footprint of cement production based on the type of energy consumption, transportation and human effects using a system boundary analysis. A cement plant located on western Iran is analysed to demonstrate the application of the proposed model and a sensitivity analysis is conducted to show the effects of different parameters on the performance of the model. The paper shows that the total water footprint of the selected cement plant accounts for 3.614 × 10 6 m 3 in 2016 with water consumption intensity of 2.126 m 3 per each ton of cement production indicating the risk of surviving cement industry in dry regions. The paper also shows that in the selected cement plant virtual water consumption contributes to the 90 percent of the total water footprint value. In addition, the paper demonstrates that the majority of the virtual water consumption is related to the energy sources which is 9.3 times more than the direct water consumption of the case study plant. Furthermore, the paper shows that water footprint can be most effectively reduced by shifting to greater contributions of wind and solar energy. This paper will be of interest to academics and practitioners interested in cleaner production of cement plants. It provides an understanding of water consumption of the cement industry broader than is currently available. [ABSTRACT FROM AUTHOR]

Under the policy of energy saving and emission reduction, technological innovation has become the key power-driver to improve energy utilization efficiency. By using the panel data of 21 industrial segments between 2000 and 2015, this paper investigates the driving effect of technological innovation on energy-utilization efficiency in strategic emerging industries and analyzes the critical factors influencing the driving effect of technological innovation by the stochastic frontier analysis method. The empirical result shows that technological innovation between 2000 and 2015 has had a significant positive driving effect on the energy utilization efficiency of strategic emerging industries and exhibits a development trend of year-by-year steady-state growth on the whole. The greater the value of the development expenditure of new green products and the investment in environmental pollution treatment, the greater the technological efficiency; the greater the value of the transformation expenditure of energy-saving technology, the greater the technological inefficiency. Finally, the paper proposes the countermeasures and suggestions for the driving effect of technological innovation on energy utilization efficiency in strategic emerging industries. An empirical study is made to analyze the driving effect of technological innovation on energy utilization efficiency, the positive and negative factors of technological innovation are forgotten. Strategic emerging industries can select optimal innovation behavior to improve quality and efficiency of energy utilization based on the results. [ABSTRACT FROM AUTHOR]

The allocation of carbon emission quotas is recognized as a fundamental and critical step towards the establishment of an effective nationwide carbon emissions trading (CET) market in China. This paper aims to examine the quota allocation pertaining to China's east coastal areas. These regions are pioneers in reformation and the domestic heavy emitters. In this paper, a multi-criteria decision analysis model is proposed. This model is based on the principles of efficiency and equity. In order to reflect the true efficiency of carbon emissions, a weighted Russell direction distance model is employed. Three criteria, namely capacity, responsibility and potential, are used to evaluate the degrees of equity. Furthermore, different situations are set to evaluate the related indicators. The results indicate the following: (1) Industrial provinces have less carbon emission quota increments. (2) The Yangtze River Delta Economic Zone has notably improved energy efficiency, and future quota increments correspond with the zone's current carbon emissions. (3) Circum-Bohai Sea Economic Zone will be a major buyer of carbon emission quotas, while Pan-Pearl River Delta Economic Zone currently receives surplus quota. (4) The overall allocation of quotas converts from uneven to even as a result of GDP growth. These results provide a reference for collaborative regional reductions in carbon emissions and for the construction of a CET market. [ABSTRACT FROM AUTHOR]

One-third of global energy demand as well as CO 2 emissions is accounted to industrial processes. In particular, over 30% of total industrial energy consumption is attributed to the iron and steel, cement and refining industry. The aim of the present paper is to review crosscutting technologies and measures adopted to improve energy efficiency in the main Italian industrial sectors regulated by the recent EU legislation on integrated pollution prevention and control (IPPC-IED). In fact, 2010/75/EU Directive on industrial emissions, a general improvement on the entire environmental performance of the industrial installations is pursued by taking into account relevant environmental issues, such as emissions into water, air, soil as well as energy efficiency, waste production, recovering and recycling, restoration of the site upon definitive cessation of activities. Moreover, according to 2010/75/EU Directive, IPPC permits should be based on Best Available Techniques (BAT) aimed to reach an adequate level of environmental protection and should establish all the necessary measures including operating conditions, emission limit values for relevant polluting substances as well as monitoring requirements. Thus, in the present paper an assessment of Best Available Techniques (BAT) related to energy efficiency in the main Italian industrial installations is carried out on the base of the analysis on the IPPC permits released by the Italian Ministry for the Environment, Land and Sea, and made available on its web site. As a result a significant improvement in energy efficiency was assessed. In fact, many process units were upgraded, by major revamping or even by replacing the process completely with one showing better performances. Finally, since energy efficiency is at its best at the beginning of the life cycle of the plant, operators, whenever necessary, periodically monitor and measure the actual energy performance of their own installations for process control and maintenance purposes. [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]

This paper presents a novel research work on the potential benefits of using, a unique and sustainable energy source - the human-power. The paper discusses the benefits and the practicality of using human-power as a domestic energy source to power electrical and electronic devices and explores the benefit of its use in a more diverse perspective for possible change in behaviour and energy savings for improved sustainability in the society. The economic and sustainability gains of using Human-Powered Products (HPPs) are investigated. Two studies have been conducted, the first is a study which involves assessing the environmental impact of a human-powered products via Life Cycle Assessment (LCA); and the second is a case study called Home User Study (HUS), where the technology is experimentally tested. The human-powered system is used to explore the real benefits and life-cycle analysis towards assessing the sustainability of such products. The Home User Study (HUS) has been conducted to explore the in-situ use of human-powered systems using a new prototype that has been built and deployed. The study has used a monitoring device to measure the outcome of the interaction between the user and human-powered products. The results interestingly have revealed various other forms of benefits beyond renewable energy that could add extra motives for using human-powered products, such as health benefits. The paper also puts an emphasis on the opportunity of using Human-Powered Products which can be perceived as a great viable solution against counter measuring social issues such as physical inactivity and increasing sedentary behaviour. The results of the theoretical study indicate that Human-Powered Products (HPP) do not offer significant financial savings. The results of the HUS indicate that using human-powered products for health prospective outweigh the benefit gained from the prospective of energy savings and renewable energy. Based on the findings of this study, the paper suggests an approach that shows how the implementation of Human-powered systems could provide the opportunity to sustainable energy generation and energy savings, but in all cases they can be retained through a motivational drive in improving the health benefit via encouraging physical activities. [ABSTRACT FROM AUTHOR]

Coal mining activities have caused serious environmental problems; however, almost 30% of global primary energy demand is met using coal, making it difficult to replace in the near future. Under these circumstances, as it is not possible to completely cease coal mining activities, coal mines need to invest in cleaner production techniques to reduce environmental damage. To achieve pollution emissions and energy reductions, this paper proposes a dynamic multi-objective mixed 0–1 model based on ecological coal mining, in which environmental technological investment and production adjustments are integrated into a dynamic system to seek ecological and economic equilibrium, and emissions reductions and energy conservation are controlled using double dynamic transfer equations. Different from previous papers, this model considers the effect of production adjustments and energy conservation on the environment and the economy with the aim of achieving global optimization through integrated planning. To solve the proposed model, a hybrid algorithm with a standard and an antithetic method-based Particle Swarm Optimization (PSOs) is developed. A case study from Chaohua Colliery is presented to demonstrate the practicality and efficiency of the optimization model. The results and comparison analyses showed that as the dynamic adjustments strengthened the production and investment coordination for global optimization, integrated production and environmental investment planning provided coal mines with a superior method to solve conflicts between the ecology and the economy. [ABSTRACT FROM AUTHOR]

The industrial area layout can influence the economic benefit, safety and surrounding environment of an industrial area to a large extent, especially the length of piping and safety. Every year, the construction of new industrial areas requires thousands of tons of steel pipes, resulting in a high consumption of natural resource of iron and high emission of carbon dioxide. Additionally, the long pipeline will increase the energy consumption for material transportation. Meanwhile, accidents in industrial areas can usually result in serious damage to the local environment. So the optimization of industrial area layout holds great significance for natural resource, energy saving, and environment protection. But up to now, very few papers have been reported to consider the use of pipes and safety simultaneously to optimize the layout in industrial area level. Most works only focus on safety aspects, and the impact of connection is ignored. Accordingly, this paper proposes a methodology to optimize the relative position of each plant, whose objective function consists of piping cost and safety cost. In this paper, despite conventional consideration of material piping, steam piping, which features multiple-branches connected pipeline network, is also considered. For safety issues, it is firstly analyzed by qualitative principles to limit position for some specified plants. Then quantitative analysis, including explosion and toxic release, are optimized simultaneously with connection cost. A genetic algorithm is used to solve the proposed model. Kruskal algorithm and Arrangement & Combination are used to calculate the length of steam piping. Finally, a case study illustrates the effectiveness and applicability of the proposed methodology. [ABSTRACT FROM AUTHOR]

As an important part of smart grid optimizations, optimal dispatch of microgrid is of great significance to reduce energy consumption, environmental pollution and user's electricity costs. The development objective of microgrid is not only to meet the basic demand of power supply, but also to improve its economic efficiency and environmental protection. In this regard, this paper proposes a multi-objective optimal dispatch model for microgrid under grid-connected mode, which comprehensively considers the operation cost and the environmental protective cost of the microgrid system. Distribution generators in the microgrid system include photovoltaic array, wind turbine, diesel engine, micro turbine and electric vehicle. The batteries of the accessed electric vehicles are treated as a kind of mobile distributed energy storage device in the model. In order to solve the proposed model effectively, according to the configuration and characteristics of the model, this paper proposes an improved particle swarm optimization algorithm to solve the optimization model. Two different operation scheduling scenarios under grid-connected mode are researched, and the dispatch results of different optimization goals are discussed in this paper. The simulation results show that the effectiveness and superiority of the proposed model, which can effectively reduce the user's electricity costs and environmental pollution, promote the optimal operation of microgrid and achieve the economic management of the batteries of electric vehicles. [ABSTRACT FROM AUTHOR]

Electricity consumption in cities is steadily increasing. Using a life cycle approach and fuel mix data from power companies’ sustainability reports, this paper analyzes greenhouse gas (GHG) emissions from electricity consumption in Hong Kong. The results show that coal contributed on an average 74.3 percent, liquefied natural gas 25.1 percent, and oil 0.6 percent of the thermal energy consumed for generating electricity in Hong Kong between 2002 and 2015. Besides, Hong Kong imported an average of 7.96 billion kWh per year net electricity from a nuclear power plant in Shenzhen. During this period, GHG emissions from annual electricity consumption ranged between 27.0 and 34.1 million tons (MT) and the emission factor ranged between 702 and 792 g CO 2 -eq/kWh. Hong Kong’s gross domestic product (GDP) increased steadily from USD 176 billion in 2002 to USD 297 billion by 2015. As a result, Hong Kong’s electricity productivity increased from 4.62 to 6.75 USD/kWh while GHG emission from electricity consumption per GDP decreased from 0.153 to 0.104 MT CO 2 -eq/USD billion. Hong Kong’s annual electricity consumption was predicted over the short-term period (2016–2020) and medium term (up to year 2030). Electricity consumption is likely to increase to 44.63 billion kWh by 2030 while GHG emissions from electricity consumption would increase to 33.92 MT of CO 2 -eq. The implications are discussed at the end of the paper. [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]

The purpose is to analyse and explain factors determining whether conventional trade with stores or e-commerce with home delivery is more energy-efficient. The findings from previous studies are compared in order to identify more general patterns of energy consumption, describe which energy consumption factors (product waste and product returns, buildings, packaging, passenger transport and freight transport) are considered and what assumptions are made. In this comparison, we analyse product characteristics and product classes, discuss the energy factors with the greatest impact and the contextual impact of each factor on the energy consumption. The paper is based on a structured literature review and a content analysis, which helped us to synthesise current knowledge and explain consistent and inconsistent findings across individual studies of energy consumption in conventional sales channels versus e-commerce channels. Our literature search identified 11 studies, with 16 cases, that compared the energy efficiency. The results show the following: 1) The net effect of energy consumption was in the majority of the cases positive for the e-commerce channel, 2) The proportion of unsold products and product returns seem to have a major impact on the energy efficiency of different sales channels, 3) Buildings had only a minor effect on the energy consumption difference. It was slightly lower in the home delivery systems, 4) Packaging contributed considerably to the energy consumption difference for some products. The e-commerce channel consumed generally more energy from packaging, but indirect effects (e.g. volume efficiency) were not considered, and 5) The total energy consumption from transportation was greater in the conventional supply chains, as the additional energy in passenger transport generally outweighed the increased energy in freight transport in e-commerce. The paper points out directions for future research and discusses implications for research, policy-making and practice. [ABSTRACT FROM AUTHOR]

The sustainability transition of electricity sectors is a matter of competition between multiple emerging renewable systems and dominant, established conventional systems. These transitions are multi-dimensional and are featured with non-linear and causal interactions between social, technical, economic and political components. Understanding the dynamic of transitions, i.e. how transitions unfold, can inform effective policy interventions. This paper aims to present a narrative-modelling approach to improve the understanding and description of transition dynamics in electricity sectors. The central ideas of the paper are: (1) the use of qualitative transition narratives helps to capture the co-evolving nature of society and technology which are simplified in modelling approaches; (2) narratives, with concepts from the sustainability transitions field, also guide the development of a model structure; and (3) computational models, in return, reproduce the complexity of transition dynamics, i.e. feedback loops, non-linearity, and time delays—the features which are impracticable to analyse with transition narratives alone. We use the historical transition of India's electricity sector to demonstrate the implementation of our proposed approach. First, an overview of the transition narratives is presented and the model structure, developed based on the narratives, is explained. Then, it is argued how the coupling of the narratives and model improves our understating of the positive impacts as well as the side-effects of stable feed-in tariffs and accelerated depreciation on the penetration levels of wind and solar electricity. [ABSTRACT FROM AUTHOR]

The paper explores the nexus between greenhouse gas, financial development, energy consumption, trade and urbanization in 34 upper middle income countries from Asia, Europe, Africa and America (South and North) by using panel data from 2001 to 2014. Vector error correction model explored different results for different regions such as the causality of greenhouse gas for Europe and America; financial development for Asia; trade openness for Asia, Europe and America; and urbanization for Africa and America. The causality of greenhouse gas emission was bi-directional with urbanization in America and trade in Europe. The bi-directional causality of trade was observed with financial development in Asia and urbanization in Africa. The generalized method of moment and fully modified ordinary least square explored a direct association of per capita greenhouse gas emission with financial development in Europe; energy consumption in all panels, and renewable energy in Africa and America. But, the relationship of per capita emission was reciprocal with financial development in Asia, Africa and America; renewable energy in Europe; trade in Europe, Africa and America; and urbanization in Asia, Europe and America. The relationship of variables changes from region to region and country to country. A country-based reciprocal effect on per capita greenhouse gas was observed for financial development, renewable energy, trade openness and urbanization for different countries. This paper provides an insight to policy makers to re-structure the financial system, energy usage pattern, trade and urbanization in accordance with the cleaning of environment at country and regional level. [ABSTRACT FROM AUTHOR]

Energy consumption is a major sustainability focus in the metal cutting industry. As a result, process planning is increasingly concerned with reducing energy consumption in machine tools. The relevant literature has been categorized into two research areas. The first includes energy prediction models, which characterize the relationships between cutting parameters – the main outputs of process planning - and energy consumption. The second involves energy-consumption optimization, which uses the prediction models to find the cutting parameters that minimize energy use. However, previous energy prediction models are limited to predict energy for tool paths coded in a Numerical Control (NC) program. Previous energy optimization methods typically do not use online optimization, which enables fast optimization decision-making for supporting on-demand process planning and real-time machine control. This paper presents a component-based energy-modeling methodology to implement the online optimization needed for real-time control. Models that can predict energy up to the tool path-level at specific machining configurations are called component-models in this paper. These component-models are created using historical data that includes process plans, NC programs, and machine-monitoring data. The online optimization is implemented using a dynamic composition of component-models together with a divide-and-conquer technique. The feasibility and effectiveness of our methodology has been demonstrated in a milling-machine example. [ABSTRACT FROM AUTHOR]

Residential sector has been one key sector for reducing its greenhouse gas emissions due to its significant contribution to global warming. Researchers in different countries have studied household energy consumption patterns and greenhouse gas emissions in order to promote low-carbon lifestyles. However, few review papers have been published in this regard, leading to a lack of systematic understanding on the related research achievements. Hence, by using a bibliometric approach, this paper aims to review the existing literature and examine the evolution of such a field so that the research trends can be uncovered, including popular research methods. Citation analysis is performed to assess the influence of most productive journals, countries/territories, and authors. Network analysis is also conducted to evaluate the relationship among different countries/territories, authors, and keywords. Research outcomes of this paper present a comprehensive research picture on residential energy consumption and corresponding greenhouse gas emissions (REE) related papers published from 1997 to 2016. The most productive journals, countries/territories, authors are also analyzed based on citation analysis and network analysis. In addition, results also revealed that behavioral analysis, input-output analysis, life cycle assessment, and cost-benefit analysis are the most commonly used methods in this field. Results obtained from this study can provide valuable information for researchers interested in the REE-related field. [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]

Energy poverty has attracted widespread attention from the government and researchers for its close relationship with human well-being and resident health. Estimating the energy poverty line is essential in understanding energy poverty and alleviating it. However, there is no consensus on the measurement of energy poverty. This paper defined the energy poverty line as the threshold at which energy consumption ceases to change significantly as household income increases, which is based on the household minimum energy demand. Considering the environmental endowment in Qinghai, this paper established new scenarios to examine the feasibility of replacing biomass with clean electricity. The findings show that 31.6% of rural households are energy poor in Qinghai. Basic energy demand has been met in Qinghai, but there are difficulties in shifting to a more efficient energy structure. Income, residents' consumption habits and technical issues with clean energy equipment continue to limit the energy choices of rural households. Therefore, improving the actual performance of clean energy devices is critical in the clean energy transition. In addition, local governments can increase incentives for clean energy utilization by setting reasonable subsidies for clean energy. [Display omitted] • Estimating household energy poverty is essential to regional sustainable development. • Defining the energy poverty line based on the minimum energy demand. • The clean energy transition is limited by income and behavioral habits in rural Qinghai. • Technical renovation of clean energy appliances is crucial to solving the energy crisis. [ABSTRACT FROM AUTHOR]

The paper aims at investigation of the nexus between Industry 4.0 (I4.0) and environmental sustainability in addition to exploring the long-run and short-run effects of Industry 4.0 on CO 2 emissions. For this end, energy consumption, internet and communication technology (ICT) exports, research and development (R&D), artificial intelligence (AI), ICT technology patents and bitcoin are taken as control variables of Industry 4.0 for a panel of 9 countries that contribute to 62% of the total CO 2 emissions in the world. For this purpose, the paper follows two approaches. First, the paper proposes utilization of AI and ICT technology patents, technology-related R&Ds and ICT exports as variables of I4.0 in addition to investigating the effects of economic growth, energy consumption and bitcoin. Second, to control structural changes and nonlinearity in the cointegrating relations and existence of degenerate cointegration, Fourier panel bootstrap autoregressive distributed lag model (FPBARDL) is utilized. Afterwards, FPBARDL based long, short and strong causality analyses are conducted. The empirical findings revealed positive impacts of all I4.0-related variables on emissions in the long-run. Though I4.0 related AI and ICT innovation has no direct effect in the short-run, its effects are determined through increased energy consumption towards emissions. The strong positive effects of energy consumption and positive effects of economic growth, ICT exports and R&D are observed both in the short and long-run. In addition to positive impacts of I4.0 on environment, the findings favor insufficiency of policies focusing on lowering emissions in I4.0 context.Policy recommendations include strong commitment to energy efficiency and renewable energies and trade policies with environmental concerns. [ABSTRACT FROM AUTHOR]

Renewable energy plays an important role in reducing global carbon (CO 2) emission. This paper builds a RER (renewable energy consumption rate) index to represent the energy structure of a country and proposes a U-shaped RKC (renewable energy Kuznets Curve) hypothesis between RER and economic growth. We also examine the dynamic relationship between RER and the Environmental Kuznets Curve (EKC) hypothesis using two panel data sets of 17 major developing and developed countries as well as six geo-economic regions of the world during 1990–2014. Panel co-integration tests indicate that a long-run relationship exists among economic growth, RER and carbon emission. We employ the fully modified ordinary least squares (FMOLS) and the dynamic ordinary least squares (DOLS) techniques to estimate the co-integration coefficients of the panels and individual countries/regions respectively. The results verify both the EKC and RKC hypotheses, indicating that a 10% rise in RER would to a 1.6% carbon emission reduction. It is also found that the RKC turning points of individual countries and the entire samples in general take place before the turning points of the respective EKCs. It suggests that promoting renewable energy consumption to make RKC cross its turning point earlier can accelerate EKC to reach its turning point more quickly. This finding has important policy implications with respect to the development and utilization of renewable energy and environmental protection. The dynamic relationship between EKC and RKC. Image 1 • We examined the relationship between renewable energy and GDP. • A U-shaped curve exists between GDP and renewable energy consumption. • The turning points of RKCs take place earlier than that of the EKCs. • Promoting RKC arrive its turning point in advance can accelerate EKC to reach its turning point more quickly. [ABSTRACT FROM AUTHOR]

A sustainable hydraulic system is proposed to cool the slurry manure and mitigate the ammonia emissions of livestock buildings, a major source of environmental pollution. In this paper, analytical and numerical methods are used to evaluate the energy efficiency and the mitigation capability of the hydraulic cooling system. Results show that annual primary energy use of only 6.08 kWh per animal can reduce 5.87 kg of ammonia per animal per year. The system is most efficient for manure with less than 12% total solids content. Results also show that the liquid region above the cooling pipes features one-dimensional transient heat transfer formed by unique flow patterns. A simplified analytical model is derived to predict the surface temperature of liquid manure. The analytical solution shows that the manure surface temperature can be reduced by 7.4 and 12 °C after 2 and 5 h, respectively. The temperature reduction results in up to 37.3% decrease in ammonia emissions with only 0.8% of the total energy use in livestock buildings. • An energy efficient cooling system is proposed to reduce emissions from buildings. • Using primary energy of only 6.08 kWh can reduce 5.87 kg NH3 per animal per year. • The cooling system uses only 0.8% of the total energy use in a livestock building. • The cooling system can reduce up to 37.3% NH3 emissions from livestock buildings. • An analytical model is derived to predict the surface temperature of liquid manure. [ABSTRACT FROM AUTHOR]

Wind energy is an important renewable source with promising development perspectives worldwide. Multi-criteria assessment studies can effectively assist the decision-making process for a profitable implementation of wind energy projects. This paper presents a new comprehensive process for assessing wind power generation based on a multidimensional analysis covering energetic, exergetic, economic and environmental aspects. For comparison purposes, the wind power plant is investigated for two Moroccan coastal zones with substantially different outdoor meteorological conditions. The three-bladed horizontal axis commercialized wind turbine Enercon-48 with a rated power of 800 kW is considered in the analysis. The developed computation tool can predict hourly energy/exergy flows and efficiencies of wind power generation at any location. The Levelized Cost of Electricity and its sensitivity to key financial and operational parameters was investigated as well. A geometrical technique applied to wind power generation was for the first time established to determine the combination of meteorological variables leading to the best compromise between energy efficiency maximization and exergy destruction minimization. Site comparison elucidated that the southern Moroccan zone (Dakhla) allows a higher sustainability index of 1.74 (a 7.4% higher than the predicted value for Tangier) with an LCOE value of 13.42 c$/kWh against 20.95 c$/kWh for Tangier. Environmentally, wind power generation operating in Dakhla has the potential to mitigate up to 42.73 tonnes CO 2 -eq/kW compared to 23.31 CO 2 -eq/kW in Tangier. • 4 E assessment of wind power generation in two Moroccan coastal regions. • Determination of climatic conditions leading to the best energy/exergy efficiencies. • Performance indices are parametrically investigated. • Southern coastal region has a sustainability index of 1.74 for a capacity factor of about 40%. [ABSTRACT FROM AUTHOR]

Existing studies pay little attention to when or under which conditions foreign direct investment (FDI) can spill energy-saving technologies. From a perspective of energy-biased technical change and using a two-layer nested constant elasticity of substitution (CES) production function, this paper investigates the energy-saving spillover effect of FDI on technical change (i.e., energy-saving spillovers) in China between 2002 and 2015. In particular, we consider the conditions of marketization, industry, technology, and labor mobility to examine whether and when FDI has energy-saving spillovers. The results indicate no income inequality effect, i.e., there is no evidence supporting that FDI flowing into low- and middle-income regions increases energy consumption, while FDI flowing into high-income regions conserves energy. However, there is a condition effect: FDI can improve (support the halo effect) or deteriorate (contradict the halo effect) the environmental performance under different conditions. Moreover, there is a threshold effect: the direction of FDI spillovers varies with the different levels of the threshold variables. An increasing marketization motivates enterprises to select energy-biased technologies. It is more likely to generate energy-saving spillovers in the regions with a lower specialized agglomeration level. FDI will have energy-biased spillovers when domestic technological level is relatively high with an evident energy-biased technology. In addition, a moderate labor mobility is beneficial to the energy-saving spillovers of FDI. [ABSTRACT FROM AUTHOR]

The industrial sector is characterized by high energy consumption and high carbon emissions. It is of great significance to clarify the determinants of industrial CO 2 emissions for emissions abatement policy making. For this purpose, a comprehensive decomposition framework that can quantify the impacts of both oriented technologies and economic factors on CO 2 emissions is developed. By applying the proposed decomposition framework, this paper investigates the determinants of China's industrial CO 2 emissions. The main findings show that, during the study period, (1) investment scale expansion was the leading factor promoting emissions growth; (2) against our expectations, efforts for energy structure adjustment failed to curb emissions but had marginal promoting effects on emissions growth; (3) energy-oriented and output-oriented technologies were indispensable contributors to emissions mitigation, followed by decreases in investment efficiency, potential energy intensity, and the CO 2 emission coefficient; and (4) energy use efficiency and production efficiency changes usually exerted moderate influences on industrial CO 2 emissions, and their influencing directions were sensitive in different sub-industries and Five-Year Plan periods. In most situations, the inhibiting effects could not counteract the promoting effects. Based on these empirical findings, policy recommendations to further reduce industrial CO 2 emissions are provided. • Empirical analysis was conducted at sub-industries and different FYPs levels. • Investment scale was the leading factor promoting industrial CO 2 emissions. • The technology progress contributed most to emission mitigation. • Driving effects distinctly differed among sub-industries and FYP periods. [ABSTRACT FROM AUTHOR]

In recent years, the profit growth of wind power enterprises in China is generally weak, and the phenomenon of "wind curtailment" in some areas is relatively common. The comprehensive evaluation of wind power performance in various regions of China and the study of the driving forces of wind power performance differences in different regions are of great significance for scientific planning and layout of wind power investment. Based on the panel data, this paper combines Data Envelopment Analysis (DEA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to establish an evaluation model to evaluate the wind power performance of China's 29 provinces and cities from 2011 to 2018. Then uses the evaluation results as input data of Adaptive Neuro-Fuzzy Inference System (ANFIS) prediction model to predict the wind power performance of 2019 in various regions of China under the current policy and environment. Finally, the main factors affecting the performance of China's wind power generation are explored by establishing a regression model. The research results show that at present, the main factors affecting the performance of China's wind power generation are local power consumption capacity, economic development degree and the rate of wind abandonment. On the premise of solving the problem of wind curtailment, appropriately promoting power consumption and renewable energy policy reform, from Feed-in-Tariff (FiT) to a Renewable Portfolio Standard (RPS), are effective means to promote the development of wind power generation in China. Image 1067 • In wind-intensive areas, wind power performance levels are relatively low. • Power consumption capacity and wind curtailment rate are the main influencing factors. • Current policy cannot effectively solve the problem of wind curtailment. • Renewable energy policies with regional differences should be adopted. [ABSTRACT FROM AUTHOR]

Hydraulic press machines (HPMs) are often preferred in metal processing for their high power-to-mass ratio, stiffness, and load capacity. Unfortunately, they are also known for their high energy consumption and low energy efficiency. The mismatch between installed and demanded power is the primary cause of low energy efficiency among HPMs. This paper proposes an energy-saving hydraulic drive system based on the flywheel energy storage system (FESS) to reduce the installed power and improve the energy efficiency. The FESS is used to store redundant energy when the demanded power is less than the installed power. During pressing with slow falling, the stored energy is recycled in combination with an AC motor to work against the heavy load. Furthermore, unlike traditional FESS's, the variable frequency drive (VFD) and specific control algorithm are adopted to improve the energy storage capacity of the FESS, as well as the operation and lifetime of the hydraulic drive system. The proposed method presents the first integration of both VFD and FESS into a hydraulic drive system. Using this method, the low energy efficiency caused by high installed power can be significantly improved, and the negative effects caused by mismatches between the installed and demanded power can be largely mitigated. Finally, a test platform is set up to verify the effectiveness of the proposed hydraulic drive system. The results show that the installed power and energy consumption are reduced by approximately 30% and 40%, respectively, based on the working characteristics of a traditional drive system. • An energy-saving hydraulic drive system based on the flywheel energy storage system and variable frequency control is developed. • The installed power and average energy consumption of the traditional hydraulic press machines can be reduced by 30% and 40%, respectively. • The proposed hydraulic drive system has the same working characteristics and processing properties as the traditional drive system. [ABSTRACT FROM AUTHOR]

Sectors tend to generate pressure on the environment due to its large amounts of emissions. The aim of this study is to identify critical betweenness sectors and transactions that play an important intermediate role in the supply chain, which can provide additional insights for CO 2 emissions. Based on the input-output and energy consumption data in China, the notion of network centrality and structural path analysis method are employed in this paper to identify critical betweenness sectors and transactions, and then the evolutionary trends of betweenness sectors and transactions are analyzed from 2005 to 2015. The results show that some critical betweenness sectors, such as Metal products sector and Electrical equipment sector, have huge potential for carbon emission reduction, which fail to receive sufficient attention from the perspective of production or consumption. Some critical transactions, such as the transaction from Nonmetal products sector to Construction sector, have a large amount of CO 2 emissions. The transaction from Metallurgy sector to Electrical equipment sector became increasingly important in China from 2005 to 2015. Additionally, the evolutionary trends of different transactions are significantly different. The findings reveal that special attention should be paid to these critical betweenness sectors and transactions and policy development should be dynamic to respond to changes in CO 2 emissions that are generated by different betweenness sectors and transactions. • Critical betweenness sectors and transactions for CO 2 emissions in China are identified. • Input-output relationships are converted into a supply chain network. • Edge betweenness and SPA are used to identify critical transactions in China. • The intermediate effect of Metal products sector is significant. [ABSTRACT FROM AUTHOR]

Research on energy-saving retrofits of the existing industrial systems can effectively improve the systems' energy-saving level and increase company revenue. The energy-saving bottleneck diagnosis for systems is the foundation of the energy-saving retrofit design. The diagnosis also aims to yield a more targeted energy-saving retrofit, thus ensuring the energy-saving effect and investment income of the transformation project. Therefore, this paper proposes a new method to diagnose the energy-saving bottleneck of the existing industrial systems. First, the energy-saving bottleneck diagnosis is decomposed into two parts: the diagnosis of energy-saving bottleneck units and the diagnosis of energy-saving bottleneck factors. Then, the energy density decomposition method is improved and a multi-mode energy efficiency density decomposition method is proposed. Next, an energy-saving bottleneck diagnosis method for industrial systems based on multi-mode energy efficiency density decomposition and an orthogonal test method is proposed. The proposed method can analyze the energy-saving potential of existing systems, accurately locate energy-saving bottlenecks, and avoid the dependence on a large amount of expert experience or complete production data in the existing methods. Finally, the proposed method is applied to an actual circulating cooling water system and the system energy-saving bottleneck diagnosis is realized, thus verifying the practicability of the method. • Energy-saving bottlenecks in industrial systems are analyzed and decomposed. • A method for energy-saving bottleneck diagnosis from two directions is proposed. • An improved energy efficiency density decomposition method is proposed. • The diagnosis of energy-saving bottlenecks in industrial systems is achieved. • The verification is performed for an industrial circulating cooling water system. [ABSTRACT FROM AUTHOR]

The household sector of China is responsible for 11.7% of national energy consumption and 12.6% of carbon dioxide (CO 2) emissions in 2015. Thus, revealing the determinants of household CO 2 emissions (HCE) is extremely important for national efforts towards emissions mitigation. In this context, this paper investigates the driving forces behind national and regional HCE changes employing a temporal Logarithmic Mean Divisia Index (LMDI) model. It also analyses interregional discrepancies in HCE using a spatial LMDI model. This study decomposes the changes or discrepancies of national and regional HCE from 2000 to 2015 into seven key factors. The temporal analysis indicates that household income is the predominant determinant explaining the increase of HCE, whereas energy intensity is the crucial determinant contributing to the mitigation of HCE. The spatial analysis reveals that the number of households and energy intensity are primary driving forces accountable for growing discrepancies in HCE, followed by household income, energy structure and carbon emission coefficient. The analysis also suggests that resourceful and economically developed regions generally have larger potential for mitigation of HCE. The study concludes with some policy recommendations based on the results. [ABSTRACT FROM AUTHOR]

Pinch Analysis (PA) and Exergy Analysis have been used, either independently or in combination, for energy integration of process plants. This paper discusses a methodology to apply PA and Exergy Analysis during design of a new process plant to make it energy efficient, using Diesel Hydrotreating Unit (DHT) as an example. PA has been used to estimate the Minimum Energy Requirement (MER), to select utilities and to design the optimal Heat Exchanger Network (HEN). Exergy Analysis is then performed to pinpoint the sources of energy inefficiency in the whole plant and suggest improvements. The application of these two techniques has helped in energy integration of the plant during the design phase itself. Two common layouts of diesel hydrotreating unit—the 'hot separator layout' and the 'cold separator layout'—have been studied. The minimum Total Annualized Cost (TAC) is ∼7.6 M€/y and ∼10 M€/y for the hot separator layout and the cold separator layout respectively. Exergy destroyed is 27.15 MW (7.9% of exergy input) and 50.18 MW (6.7% of exergy input) respectively for the hot separator layout and the cold separator layout. Exergy Analysis reveals that the energy efficiency can be improved for air coolers, fired heaters and letdown valves. • Pinch and exergy analysis carried out on design of new DHT. • HEN with minimum TAC obtained by pinch analysis. • Sources of energy inefficiency identified by exergy analysis. • Modifications for improving energy efficiency provided. • Equipment modifications resulted in higher exergetic efficiency. [ABSTRACT FROM AUTHOR]

Even though renewable energy development has gained momentum in China, thermal power generation still accounts for approximately 70% of the county's total power generation serving as the major source of carbon dioxide (CO 2) emissions in China. Facing the challenges of meeting 2030 peak target of CO 2 emission and realizing the coordinated development of thermal power generation in Beijing-Tianjin-Hebei region, this paper applies generalized Divisia Index Method (GDIM) to decompose the dynamics in the relevant CO 2 emission. The effects of five factors including electricity demand, energy consumption, technology, energy efficiency and energy-mix are considered. The decomposition suggests that electricity demand is the primary factor driving the CO 2 emission up, whereas technology effect decreases CO 2 emission the most. Given the significant roles of technology, energy-mix and energy efficiency in CO 2 emissions reduction, seven scenarios are designed to identify the optimal coordinated development pathway for thermal power generation in Beijing-Tianjin-Hebei region. Through upgrading energy structure and/or enhancing energy efficiency, the thermal power generation in Beijing-Tianjin-Hebei region can achieve coordinated development and realize the 2030 peak target under four scenarios. The detailed development pathways for CO 2 emissions and specific policy implications for Beijing, Tianjin and Hebei are provided to further govern CO 2 emissions and maintain sustainable development. • Proposed a five-factor Generalized Divisia Index Model (GDIM) for CO 2 emission analysis. • Analyzed the CO 2 from thermal power generation in China's Beijing-Tianjin-Hebei region. • Electricity demand and technology contributed the most to the positive and negative changes of CO 2 , respectively. • Designed seven thermal generation development scenarios to study the CO 2 change until 2030. • The 2030 CO 2 peak target can be achieved under four scenarios. [ABSTRACT FROM AUTHOR]

Modern manufacturing enterprises are consuming a considerable amount of energy every year. Improving energy efficiency will not only benefit the enterprises economically, but also help the world to overcome various problems such as energy crisis and air pollution. To achieve this, an accurate energy consumption model is essential. The main objective of this paper is to develop an improved cutting power-based energy consumption model for general end milling process. The proposed model consists of an idle part due to auxiliary components and spindle rotation, and an additional part due to cutting workpiece materials. The first part is modelled as a function of spindle rotation speed, and the other part is considered proportional to the cutting power. Experiments under various milling conditions have demonstrated the effectiveness and efficacy of the proposed model. Comparative studies show that the proposed model is more accurate than other models. Although calibrated from slotting experiments when cutting aluminium alloy, the proposed model is applicable for general milling process. Partial-immersion milling experiments show that the prediction error of the proposed model is as low as 1.74%. When workpiece material changes to titanium alloy, its performance remains decent, with low prediction error of 2.81%. This reveals its capability to provide reliable estimation for different workpiece materials. As such, it could help avoid tedious model calibration, thus saving time, material, and energy. Finally, the energy efficiency of general end milling process is investigated through numerical experiments with the proposed model. By revealing the relationship between energy consumption and various cutting parameters, the proposed model could serve as an excellent platform towards energy-efficient manufacturing/cleaner production. • A new energy consumption model (ECM) for general end milling is proposed. • The ECM's accuracy and reliability is validated by general milling experiments. • The ECM significantly improves the prediction accuracy than other major models. • Energy efficiency can be analyzed with the ECM via numerical experiment. • The ECM contributes to cleaner production by saving time, material, and energy. [ABSTRACT FROM AUTHOR]

Enhanced ultrafiltration process as the cleaner treatment of cutting oil wastewater has been presented in this paper. Twisted tapes as turbulence promoters were used for fouling mitigation and the enhancement of cutting oil wastewater ultrafiltration for the first time. The response surface methodology was used for modelling and analysis of the most important effects, particularly an aspect ratio of twisted tape and cross-flow rate, on the flux and specific energy consumption as responses. The improved maximal flux under minimal specific energy consumption has been obtained by the optimization of twisted tape dimension alongside the working conditions. The application of twisted tapes remarkably increases the flux. The linear effects of the cross-flow rate and the aspect ratio have a dominant positive influence on the flux. The linear effect of cross-flow rate has a positive dominant effect on the specific energy consumption. The squared effect of the aspect ratio is statistically significant and allows for optimization. The optimal flux of 201 L m−2 h−1 can be reached under specific energy consumption of 1.34 kWh m−3 with a twisted tape of the aspect ratio of 1.55 and 2% w/w oil concentration. The optimized process has the desirability of 0.81 what is beyond commercially available. Image 1 • The ultrafiltration of cutting oil wastewater was enhanced by application of twisted tapes. • Response surface methodology was used for the effects analysis and optimization of the process. • An aspect ratio of twisted tape has statistically significant linear and quadratic effects on flux. • Cross-flow rate has bigger influence on the specific energy consumption than twisted tape. • The proposed optimized process has desirability beyond commercially available. [ABSTRACT FROM AUTHOR]