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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]

In this paper, a 1 kW-class Solar-Ocean Thermal Energy Conversion integrated Air-Conditioning (S-OTEC/AC) experimental system, which can provide both electrical energy and cooling energy without any pollution, is constructed for the first time. Based on the experimental data, the system's overall performance was comprehensively evaluated in terms of energy, exergy, economy, and environment (4 E). Furthermore, the performance difference between the system using solar energy (i.e., S-OTEC/AC) and the system without solar energy (i.e., OTEC/AC) was compared. The experimental results revealed that the maximum thermal efficiency of the S-OTEC/AC system could reach 2.10%, which was 1.91 times higher than the OTEC/AC system. For the OTEC/AC and S-OTEC/AC systems, the maximum cold energy utilization efficiency was 4.12% and 10.09%, and the maximum isentropic efficiency was 18.81% and 76.84%, respectively. The minimum payback period for the S-OTEC/AC system was 13.90 years, which was much lower than the 18.40 years of the OTEC/AC system. Additionally, the maximum primary energy saving achieved by the OTEC/AC system was 0.53 kW, while the S-OTEC/AC system reached a higher value of 1.56 kW. From the results, the superiority of the S-OTEC/AC system over the OTEC/AC system was confirmed. This work not only provides data references for the actual operating characteristics of the S-OTEC integrated system, but also provides a new technical way for comprehensive utilization of ocean temperature difference energy. • 1 kW class S-OTEC/AC experimental system was built for the first time. • The first 4 E analysis was used to characterize S-OTEC/AC with experimental data. • The S-OTEC/AC system has a thermal efficiency of up to 2.10%. • The S-OTEC/AC system achieves a cooling energy utilization of 10.09%. • The S-OTEC/AC system is superior to the OTEC/AC system in all aspects. [ABSTRACT FROM AUTHOR]

The train generates regenerative braking energy (RBE) during braking. When the RBE generated by the braking train is too large to be absorbed and utilized, the OCS voltage will rise rapidly. It may even exceed the rated voltage threshold, resulting in hidden dangers for driving safety. How to use RBE efficiently and reasonably has become a hot issue in recent years. This paper presents a metro timetable optimization method for multi-train operation to improve the RBE utilization efficiency of trains. Firstly, an energy-saving multi-objective model for multi-train operation is established, which takes the total energy consumption and travel time as the objective functions and the dwell time and departure interval as the constraints. Then, the genetic algorithm (GA) is used to generate the composition sequence of dwell time and departure interval, and the multi-node nonlinear model is used to calculate the total energy consumption of the metro line. Finally, Guangzhou metro line 7 is selected as an example to illustrate the effectiveness of the developed optimization model. The results show that the energy consumption of the whole line can be effectively reduced by adjusting the dwell time and departure interval. Meanwhile, the timetable optimization model with GA has better energy-saving effects by comparative analysis. • A metro timetable optimization method based on improved genetic algorithm is developed. • The multi-node nonlinear model is developed to calculate the total energy consumption. • The developed optimization model has better energy-saving effects than previous methods. [ABSTRACT FROM AUTHOR]

Two economic activities have been integrated in southern Brazil: olive cultivation and sheep farming. The favorable edaphoclimatic conditions in the southern region for cultivating olive trees and cultural preferences for the consumption of sheep meat make this integration a valuable strategy. Considering that every activity causes environmental impact and the exploitation of natural resources, new systems that promote sustainable development and the efficient use of these resources become necessary. This paper presents the first study of the carbon footprint of the life cycle of integrating of sheep and olive farming, with the objective to build an inventory based on primary data collected on olive and sheep farms in Brazil, determine the carbon footprint of the conventional and integrated system and estimate the potential for mitigating GHG emissions. The evaluation was performed using the life cycle assessment (LCA) methodology. The study focuses on the detailed analysis of the processes and activities that are responsible for GHG emissions, including enteric methane emissions, methane emissions from manure management, emissions from nitrogen fertilizer use and limestone application and energy consumption. For this, two major scenarios were considered, the first centered around on the traditional olive cultivation and sheep farming systems individually, and the second involved their synergistic integration. The findings indicate that the conventional system is associated with a global warming impact of 6.8 kg CO 2 eq per liter olive oil and kg live weight. In contrast, the integrated system demonstrates a significant mitigation potential of 27.7%, resulting in a reduced global warming impact of 4.92 kg CO 2 eq. This advantage is a consequence of the synergy between the systems, as they now occupy the same area, which allows the sharing of agricultural activities and agrochemical inputs, in addition to optimizing nutrient recycling and complementing each other. Additionally, the results of a sensitivity analysis showed that enteric methane from sheep and the application of limestone to the soil are the most influential parameters on the carbon footprint, indicating that they are key parameters for the development of GHG mitigation strategies, some of which were discussed in the article. • First life cycle assessment of integration between olive and sheep farming in Brazil. • The inventory was constructed with primary data collected in situ. • The study assesses the carbon footprint of the olive and sheep farming system. • The results show environmental advantages of the integration of olive and sheep farming systems. [ABSTRACT FROM AUTHOR]

With the rapid expansion of computational infrastructure, the electricity consumption of geographically dispersed Internet Data Centers (IDCs) has imposed a substantial influence on the power grid. Geographically distributed IDCs, which present a versatile electricity demand with significant operational flexibility, hold potential for mitigating cost issues and balancing regional supply and load demand. To exploit this flexibility, this paper has developed a dual-drive coordinated operational strategy, which integrates locational electricity prices and unit carbon emission costs based on the dynamic carbon emission intensity (DCEI) of various regions as interaction signals to improve coordination effectiveness. The upper-level determines the consumption behaviour of IDCs, the lower-level provides feedback on dual-drive signals factoring in IDCs' involvement in grid operation, whilst an iterative algorithm is suggested to solve the bi-level model. Case studies based on real-world datasets demonstrate that the proposed operation strategy can achieve arbitrage through multi-regional carbon-electricity markets, significantly reduce operating costs, and support the rapid development of IDCs. Additionally, this strategy facilitates optimal matching of power load in IDCs with renewable energy sources, thereby mitigating imbalances in regional renewable energy supply and demand. • Analysing the necessity of integrating IDCs into the carbon market. • Proposing a dual-drive coordination to activate spatiotemporal flexibility of IDCs. • An iterative algorithm for solving the bi-level model is designed. • Comparing impacts of carbon policies in IDC costs and renewable energy accommodation. [ABSTRACT FROM AUTHOR]

- The integration of multi-energy sources in microgrids offers a promising approach to address the challenges of energy efficiency and bolster environmental stewardship. This paper presents a novel optimization scheduling model for multi-energy microgrids (MEMG) with carbon capture and storage (CCS) technology in various renewable energy scenarios. The model effectively coordinates integrated demand response (IDR) and the flexible operation of waste heat utilization, enhancing energy utilization efficiency while ensuring user satisfaction. Furthermore, introducing flexible operation combined with ladder-type carbon trading minimizes operating costs and carbon emissions. The improved particle swarm optimization (PSO) algorithm is employed to solve the eco-economic economic scheduling model. Simulation analysis shows that integrating CCS into MEMG can reduce carbon emissions by 74.4%, while lowering the overall cost by 37.9%. These findings not only improve MEMG's low-carbon and economic efficiency but also pave the way for environmentally responsible energy management practices. [ABSTRACT FROM AUTHOR]

Based on 196 prefecture-level cities in China from 2006 to 2021, this paper constructs a weight matrix of urban economic geography and uses the spatial differential model to verify the impact of smart city policies on urban green energy efficiency. The results show that the efficiency value of green energy fluctuates in Chinese cities. Different test results show that smart city policies can effectively improve urban green energy efficiency, but mainly from the time effect rather than the individual effect. It means the improvement in urban green energy efficiency comes more from the fast-growing of the Chinese economy and urban construction in this period than from the country's smart city pilot policy. In addition, from the spatial spillover effect result, China needs to design a better urban spatial development plan to improve the capacity of smart city energy services and vigorously develop intelligent technology represented by information and communication science. [ABSTRACT FROM AUTHOR]

Traditional methods of polymers joining for industrial applications are limited to lasers, induction, or conduction heating. It is difficult to achieve precision and efficiency in large-scale applications simultaneously. In this paper, we report a precise microwave welding method induced by localized surface plasmons of metallic macro-gaps under microwave excitation. The proposed method uses energy from well-developed commercial microwaves and benefits from the precision of localized surface plasmons, an oscillating electron cloud excited by electromagnetic waves, which is currently under investigation only at the micro or nanoscales. This method is employed in plastic microwave welding, and the numerical analyses and experimental results reveal that, in comparison to traditional microwave heating methods, this process effectively focuses microwave energy to achieve precision area heating of a diameter of 4 mm or less; this results in a temperature increase at a rate of 333.8 °C/s, and the maximum tensile strength of the welded samples reaches as high as 668 N, which is comparable to that of the base material. The results demonstrate that the processing method is an environmentally friendly approach characterized by high quality, efficiency, and low energy consumption. [Display omitted] • Develop a novel plasmon local field enhancement assisted microwave welding method. • Achieve focused microwave energy and precise polymer heating. • Welded samples exhibit excellent mechanical properties. • Method offers high quality, efficiency, cleanliness, and low consumption advantages. [ABSTRACT FROM AUTHOR]

With the increasing number of integrated energy system (IES) construction, a multi-agent system group composed of multiple IESs would be formed in a certain region. Moreover, complex uncertainties gradually existed in the IES which affect the system optimal situation and optimization results. In order to take full use of each agent's advantages and improve the performance of the whole region under uncertainty, this paper focuses on the multiple energy types' interaction of multi-agent IESs within the region to realize the stable operation, economic and environmental improvement of each agent and the whole region. To this aim, a multi-objective multiple energy types' multi-agent interactive optimization model considering energy demand and renewable energy output uncertainties was built. The model was based on Nash bargaining cooperative game theory and took economy, flexibility and carbon emission as objectives. Moreover, energy interaction scheduling and its corresponding price can be optimized through the model. The results of non-cooperative operation mode without interaction and cooperative operation mode with interaction were compared to analyze the superiority of interaction from the cost, carbon emission and flexibility aspects. The overall regional carbon emission and the economic cost has been reduced by 13.84% and 9.94%, for each IES, the carbon emission and economic cost could reduce by up to 41.5% and 44.5%. Moreover, the flexibility of the IES was correspondingly increased by nearly 47%. These results denoted that after multi-agent interaction, not only the overall region's energy, economic and environmental performance are improved, but also that of each agent are significantly improved. In addition, different energy types among multiple agents could be effectively used and regional joint energy storage is realized, improving the region flexibility level and resilience. • A multi-objective integrated energy systems interaction model is established. • The interaction model considers multiple energy types and uncertainties. • The model can improve economy and flexibility of each system agent and the region. [ABSTRACT FROM AUTHOR]

At present, the energy and environmental crisis is increasingly prominent, and how to solve the global energy and environmental problems is one of the challenges facing the world today. China is a major producer and consumer of organosilicon, so it is necessary to explore the stage of high energy consumption and high pollution in the organosilicon industrial chain. In 2022, the proportion of submerged arc furnaces of 25000 kVA and higher in China reached 40%. Further expansion of these furnaces in the future is inevitable. However, research on the life cycle assessment of organosilicon manufactured using large-capacity submerged arc furnaces is still blank.Therefore,in this paper, the life cycle assessment method is used to evaluate the synthesis process of chemical grade silicon-organosilicon monomer prepared by large capacity (33000 kVA) submerged arc furnace, and the dominant process in various environmental impacts is defined.At the same time, the measures to improve the production process of organosilicon monomer were put forward. In the production process of 1000 kg organosilicon monomer, global warming potential (GWP) contributed the most (73.43%) to the comprehensive environmental impact, followed by chronic public health impact (HTI, 10.55%). Energy consumption (EN) accounted for 8.50%, while resource consumption (RU) accounted for 7.43%. The contributions of other environmental factors were relatively small (0.09%).The energy consumption and environmental pollution in the production of organosilicon monomer can be reduced by strictly controlling the quality of raw materials into the furnace, using heat pump technology in the distillation unit, and comprehensively utilizing the heat of reaction by-products and steam condensate. [Display omitted] • This study is the first one in China to conduct LCA for the preparation of chemical grade silicon-organosilicon monomer synthesis process in 33000 kVA submerged arc furnace. It provides the best improvement suggestions for reducing the environmental load of the product life cycle process and achieving cleaner production. • In response to the national development policy of large-scale submerged arc furnace, the dominant process of preparing organosilicon monomer based on 33000 kva submerged arc furnace in various environmental impacts was clarified. • The main technical improvement directions are: Strictly control the quality of raw materials for submerged arc furnace; Strictly control the sulfur content and nitrogen content of carbonaceous reductant, and adopt the most suitable flue gas treatment technology route; Smelt with large submerged arc furnace; Use heat pump technology for distillation unit; Optimize the monomer synthesis device. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

The operation of solar photovoltaic installations for many years may lead to problems such as reduced energy efficiency and aging of components. Under this framework, replacing certain components in the facility to extend the service life of the power plant is viewed, in some cases, as a feasible strategy. However, despite its enormous strategic interest for the solar PV industry, we find that revamping PV installations has been the focus of very few scientific publications, and even less so when it comes to analyzing real facilities. Thus, this paper performs a techno-economic analysis of three revamping strategies at a real PV power plant located in the south-east of Spain. The strategies consist of substituting, in each case, the PV modules, the inverter, and both components. The simulated results show that the highest production value by installed power is obtained when both the modules and the inverter are replaced. In the same vein, the economic analysis reveals this scenario as the most favorable in terms of profitability. Based on the results obtained, an interesting future line of research would be focused on the extension of the analysis at country level to study the joint impact of numerous revamping actions. • Techno-economic analysis of revamping projects of a real solar PV power plant. • Replacing modules and inverter emerges as the most feasible strategy. • Study's applicability extends to other revamping initiatives and geographical regions. • Economic outcomes allow the most cost-effective alternatives to be determined. • This research can contribute to efficient and sustainable energy planning. [ABSTRACT FROM AUTHOR]

With the comprehensive progression of China's electric power reform, the participation of hydropower in the spot market has become inevitable. For hydropower-dominated power grids, the tight hydraulic and electric coupling relationship between cascade hydropower plants and the policy requirement of clean energy consumption greatly increase the challenge of optimal scheduling. Based on the market characteristics and actual demand of the hydropower-dominated power grids, this paper discusses the day-ahead spot market trading mechanism to promote the guaranteed consumption of renewable energy. On this basis, a day-ahead optimal scheduling model is established which aims to minimize the comprehensive power purchase cost of the power system. The nonlinear factors in the scheduling model, such as the relationship between the water level and storage capacity of hydropower plants, the relationship between the water level and water consumption rate, and the constraints on the start-up and shutdown durations of thermal power units, are linearized through multiple linearization techniques. The original nonlinear model is transformed into a mixed integer linear programming (MILP) model and is then solved using a CPLEX solver. The developed model is verified by taking 10 thermal power plants and 22 hydropower plants in Yunnan Power Grid as a case study. The calculation time is 183.6s, the comprehensive power purchase cost of the system is 155.35·million CNY, and no abandoned water is generated in the three basins. The simulation results show that the proposed model has high solution accuracy and efficiency, and maximizes the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost. The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grids. [Display omitted] • A day-ahead spot market trading mechanism to promote consumption of renewable energy. • Day-ahead optimal scheduling of hydropower-dominated power grids under a spot market environment. • A novel MILP approach is employed to solve the model. • Proposed model has high solution accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Energy quota trading is critical to both energy conservation and the achievement of dual-carbon goals. However, little remains to be done on total factor productivity and economic potential for Chinese industry. The purpose of this paper is to counterfactually model and explore the effects of energy quota trading on total factor productivity and economic potential in industrial sector. We propose a command-controlled DEA model and an energy quota trading DEA model through non-parametric linear programming based on two policy strategies of energy consumption control. We then assess total factor productivity and its growth sources for 35 two-digit industrial sector in China, as well as examine economic potential and optimal path forecasts for carbon peaking. The results show that total factor productivity and economic potential for energy quota trading are higher than those for command-controlled energy policy. Energy-saving effect can be achieved for energy quota trading because the total energy input is lower. Additionally, the sources of productivity growth differ in timing. The average economic potential and total factor productivity of different industries differ due to the heterogeneity of the production conditions and scale of development of individual market players. Moreover, the catch-up emission reduction path with an increase of 8% in output and 4.76% in energy consumption is the optimal carbon peaking path under energy quota trading. Our findings shed valuable light on China's efforts to expand energy quota trading for high-quality development in the context of carbon peaking. • Propose a command-controlled DEA model and an energy quota trading DEA model. • Assess TFP and its growth sources for industrial sector in China. • Compare the impact of different energy policies on economic potential and TFP. • Estimate the energy saving and emission reduction potential of energy quota trading. • Examine the optimal energy-saving and emission-reduction path forecasts for carbon peaking.. [ABSTRACT FROM AUTHOR]

The efficient removal of organic impurities in waste salts is significant for their recycling and environmental protection. The pyrolysis process of organic impurities in waste salt was investigated by thermogravimetric experiment to analyze the reaction kinetics characteristics. The results indicate that the pyrolysis reaction temperature range for the present waste salt is between 641.15 K and 726.22 K. The activation energy is 177.59 kJ mol−1, and the pre-exponential factor is 2.98 × 1011 s−1. Based on this, a numerical model was established to investigate the pyrolysis performance of organic impurities in practical tubular reactor. The effects of configuration and operating parameters on reaction performance and energy consumption were revealed. It was discovered that increasing the heating rate and wall temperature can accelerate pyrolysis rate but results in higher energy consumption. To balance reaction time and energy consumption, the heating rate of 15 K/min and heating temperature of 773.15 K are recommended. The content of organic impurities and bed porosity have minimal impact on the reaction rate and energy consumption, indicating that the tubular reactor has wide applicability in various working conditions. Additionally, reducing bed porosity can improve the processing rate and daily processing capacity. This paper provides a method to analyze the pyrolysis performance of organic impurities in waste salt, which is significant for designing and selecting working conditions of practical reactor for waste salt treatment. [Display omitted] • Pyrolysis kinetics characteristics of organic impurities were investigated. • Reaction temperature is between 641.15 K and 726.22 K. • Activation energy and pre-exponential factor are 177.59 kJ/mol and 2.98 × 1011 s−1. • Numerical model for pyrolysis process of organic impurities was established. • Effects of parameters on reaction rate and energy consumption were investigated. [ABSTRACT FROM AUTHOR]

The present study explores net carbon-neutral road transport options in the EU27 in 2050 from a well-to-wheel (WtW) perspective. To this aim, three scenarios have been developed regarding the evolution of the road vehicle fleet composition in terms of the degree of electrification of powertrains, and technical measures such as vehicle efficiency improvements, transport flow, and transport volumes have been considered. The fleet scenarios are further combined with four scenarios deploying different mixes of alternative fuels in 2050, including electricity, e-fuels, liquid/gaseous advanced biofuels and remaining fossil fuel components. Two different electricity production pathways are considered, as well, one of them assuming fully renewable electricity production, and an alternative one including residual shares of nuclear and natural gas power plants plus carbon capture and storage. The Joint Research Centre's DIONE model was used for the scenario calculations. From a tank-to-wheel (TtW) perspective, each scenario reduces energy consumption, mainly due to powertrain electrification, with EU27 TtW road vehicle energy consumption in 2050 ranging from roughly 650 to 1650 TWh, which is 20%–53% of that of 2019. For the most strongly electrified fleet scenario with optimistic assumptions on measures to improve vehicle efficiency, transport flow and transport volumes and renewable electricity production, well-to-tank (WtT) energy consumption is around 110–160 TWh, depending on the fuel scenario. If a moderately electrified fleet is propelled with e-fuels, even when assuming fully renewable electricity and optimistic measures, the WtT energy consumption increases ten times or more, to 1300 TWh (2150 TWh with pessimistic measures). The results show that fleet electrification is the strongest lever for WtW transport energy consumption reduction among the options considered. Other efficiency measures contribute significantly to energy savings, but their benefit decreases with increasing fleet electrification. The production pathways of fuels make a substantial difference for WtW fleet energy requirement if the fleet is moderately electrified, in which case e-fuels require significant amounts of additional renewable electricity. Nevertheless, fuel production pathways become irrelevant from an energetic point of view under very ambitious electrification scenarios since fuel volumes become marginal. The economic feasibility and the societal acceptability of different pathways towards WtW carbon-neutrality of road transport is out of scope of this paper and requires further investigation. • The study examines well-to-wheel scenarios for 2050 carbon neutral road transport. • Electrification is the strongest driver in transport energy consumption reduction. • Vehicle efficiency and activity impacts decrease with fleet electrification. • With high fleet electrification fuel production barely impacts energy consumption. • E-fuels require particularly large amounts of additional renewable electricity. [ABSTRACT FROM AUTHOR]

Battery electric industrial vehicles (BEIVs) offer significant environmental protection and decarbonization potential for rapidly growing logistics and transportation sectors in China. However, the limited driving range remains a major obstacle to the widespread adoption of BEIVs. Eco-driving is an effective solution that can improve energy efficiency and extend the driving range of vehicles by controlling driving behavior and speed. Therefore, this paper introduces an energy efficient speed planning method for BEIVs, in which data-driven models are developed to estimate energy consumption. Real-world driving data collected from a BEIV are used to model the energy consumption by curve fitting, random forest, and LSTM. The speed planning process is considered a Markov Decision Process, which is solved using Dynamic Programming and Q-learning, respectively. The case study of a battery electric forklift shows that speed planning can reduce energy consumption by 13%–27% compared to time-optimal speed, while only increasing the driving time by 10%–20%. • Energy efficient speed planning methods for electric industrial vehicles are proposed. • The speed planning method uses data-driven vehicle energy consumption models. • The energy consumption models are developed using random forest and LSTM. • The speed planning problem is formulated as a Markov decision process. • The speed planning problem is solved by Dynamic Programming and Q-learning. [ABSTRACT FROM AUTHOR]

The energy crisis caused by climate change is the most significant challenge of the 21st century. Single-objective and multi-objective optimization studies for buildings often only consider the building itself, without considering the impacts of climate change. However, in the future, energy-efficient design and appropriate operating parameters will be crucial considerations in the face of global climate change. This paper aims to discuss the impact of climate change in the humid-hot region over the past 60 years on the energy consumption of office buildings and propose countermeasures. Firstly, the meteorological data of Guangzhou from 1960 to 2020 is statistically analyzed, and four typical meteorological years and corresponding air conditioning design days are established. Secondly, Energyplus is used to simulate the building's energy consumption, and the energy consumption factors are analyzed for sensitivity using jEplus. Finally, a multi-objective optimization is performed using jEPlus + EA with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The results found that climate change led to a significant increase in the duration of high outdoor temperatures during summer. Specifically, the daily dry-bulb temperature for air conditioning design increased by 0.4–0.7 °C, and due to climate change, the energy consumption of the office building increased by about 4.6 %. The main factor affecting the cooling energy consumption in summer was the indoor cooling set point (8.29%–30%), infiltration air volume (1.0%–8.6%), fresh air volume (3.2%–16.06%), the glazing solar transmission rate (1.25%–9.0%), building orientation (0%–1.43%), and relatively small influence of envelope insulation performance. The operation scheme determined by multi-objective optimization can reduce the cooling energy consumption of the building by 10.6%–16.8%, which can mitigate the rise in energy consumption resulting from climate change to a greater extent. [Display omitted] • Discuss the impact of climate change over the past 60 years on the energy consumption of office buildings. • There was a significant increase in the duration of high outdoor temperatures during the summer. • Multi-objective optimization is performed using jEPlus + EA. • Climate change caused energy consumption to increase by about 4.6 %. • Optimal solutions can reduce the cooling energy consumption of the building by 10.6%–16.8%. [ABSTRACT FROM AUTHOR]

The flexibility of power systems is critical to cope with the variability and uncertainty caused by the integration of renewable energy resources. Incorporating district cooling systems (DCSs) into power systems is an emerging approach to provide flexibility for renewable energy utilization. However, the existing models of DCS components, such as ice-storage cooling sources, cooling pipelines, and cold warehouses, are simplified, failing to fully utilize that flexibility, which brings difficulties for renewable energy utilization. Therefore, this paper proposed a coordinated operational strategy for an integrated power and cooling system combining detailed operating characteristics of DCSs to exploit the potential flexibility of DCSs for better integration of renewable energy. The primary cooling source components, including the chiller, ice storage tank, pump, and cooling tower, are established to model a detailed process of cooling generation and storage. The thermal inertial of district cooling networks (DCNs) is formulated as a quasi-dynamic model by considering dynamical temperature characteristics and transmission delay to exploit the virtual energy storage capacity of the cooling water pipeline. Moreover, the thermal inertia of the demand side, such as buildings and cold warehouses, is considered to utilize thermal storage capacity. The objective function of the proposed optimization model is to minimize the overall operating cost of the integrated power and cooling system. Numerical simulations show that the proposed method could reduce the operating cost by 15.4% and the wind curtailment rate by 86.2%, indicating better performance of the proposed method in improving economic benefits and reducing renewable energy curtailment. • We proposed a coordinated operational strategy combining flexible resources of DCSs. • We established a detailed model of cooling source including chiller, ice storage tank, pump, and cooling tower. • The thermal inertial of district cooling networks is formulated as a quasi-dynamic model. • The combined cooling and power system can reduce the costs and wind curtailment. [ABSTRACT FROM AUTHOR]

Acid gas enrichment (AGE) is a new method to increase the H 2 S conversion in conventional Clause process. In this paper effect of methyl diethanolamine (MDEA) flow rate, MDEA temperature, acid gas flow rate, and AGE tower pressure on the outlet H 2 S and CO 2 concentration and energy consumption have been studied. A novel procedure based on enthalpy of combustion in the reaction furnace and incinerator is conducted for energy consumption calculations. By changing MDEA and inlet acid gas flow rates, a maximum H 2 S concentration in the enriched stream could be attainable. Increasing MDEA temperature will decrease maximum H 2 S concentration and enriched acid flow rate; also, CO 2 concentration in off-gas will be decreased. By increasing AGE pressure, maximum H 2 S concentration in the enriched stream will be diminished. At higher MDEA flow rates, lower AGE pressures will bring higher H 2 S concentration in enriched acid gas stream. According to flame temperature simulation in the reaction furnace, energy consumption is directly related to H 2 S concentration in the sulfur recovery unit (SRU) feed stream. Results show that maximum H 2 S concentration in the enriched acid gas stream has the best conditions from energy point of view. At optimum conditions, H 2 S concentration in enriched acid gas is 62.45 mol%, which has been increased by 24.8%, compared with existing plant conditions, and energy consumption has been decreased by 25.05 GJ/h, and CO 2 concentration in off-gas is 94.94 mol%. • Study the effect of process variables on the AGE streams by ProTreat software. • Determine the relation between reaction furnace temperature and H 2 S concentration. • Generate an EES procedure for heat of combustion in reaction furnace. • Evaluate the fuel gas consumption and therefore energy consumption. • Multi-objective optimization based on the TOPSIS method. [ABSTRACT FROM AUTHOR]

Despite the growing interest, a thorough explanation of how geopolitical and energy security risks relate to carbon emissions is still missing. To fill this gap, this paper investigates the impact of these factors, both individually and jointly, on carbon dioxide emissions in European Union countries from 1990 to 2021, also accounting for the effects of per capita final energy consumption and real income. Empirical findings from the augmented mean group and novel dynamic common correlated effects mean group estimator reveal that the strongest long-term escalation in carbon dioxide emissions is attributable to final energy consumption, followed by energy security risk. Geopolitical risk, however, has a mild short-term mitigating effect on carbon emissions. In the long run, this effect is statistically insignificant. The joint effect of energy security and geopolitical risks indicates that they may reinforce each other and lead to even higher carbon dioxide emissions in the long run. Therefore, policies aimed at reducing carbon emissions need to address both risks simultaneously, while also considering the causal relationships observed between the variables under study. • Examined the individual, joint, and causal geopolitical and energy security risks effects on CO 2 emissions. • Energy consumption and energy security risks were identified as the main drivers of CO 2 emissions. • Energy security risk's effect on CO 2 emissions was escalating, gradual, and long-lasting. • Geopolitical risk's effect on CO 2 emissions was mild, short-term, and mitigating. • Found significant long-term joint effect of geopolitical and energy security risks. [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]