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Although recycling is considered the core of a circular economy for returning materials to the supply chain, its procedures are poorly understood. Waste recycling is considered a big source of energy saving and a promoter of CO2 recovery. Besides that, it generates jobs and changes markets worldwide. The Brasilian National Policy on SolidWaste (PNRS) recognizesWaste Pickers as the major social agent in the recycling process responsible for putting Brasil among the ten largest paper-recycling countries in the world. This paper presents an analysis of Brasilian recycling chains of paper and plastics and the main challenges for expanding recycling from Municipal solid waste. The research data were obtained from primary and secondary source related to the recycling supply chain of paper and of the following plastics--High Density Polyethylene (HDPE), Low Density Polyethylene (LDPE), Polypropylene(PP), Polyethylene Terephthalate(PET) and Polystyrene(PS). Enterprises of various sizes, including informal ones and WPs associations/cooperatives, were visited, in the five Brasilian geographic regions, during the years of 2013 and 2014. A nomenclature was defined for the various enterprises that operate in the Brasilian recycling chain. Each node of the plastic and paper recycling chain was described. The main bottleneck observed in these chains is the lack of continuous programs of selective collection with an emphasis on environmental education processes in the 5570 Brasilian municipalities. Several possibilities not only to promote waste recycling but also to increase the productivity of the sorting process are discussed. [ABSTRACT FROM AUTHOR]

In the context of global climate change, energy conservation and greenhouse effect gases (GHG) reduction are major challenges to mankind. The forestry-pulp and paper industry is a typical high energy consumption and high emission industry. We conducted in-depth research on the energy flows and carbon footprint of the forestry-pulp paper industry. The results show that: (1) The main sources of energy supply include external fossil fuel coal and internal biomass fuel black liquor, which supply 30,057,300 GJ and 14,854,000 GJ respectively; in addition, the energy produced by diesel in material transportation reaches 11,624,256 GJ. (2) The main energy consumption processes include auxiliary engineering projects, material transportation, papermaking, alkali recovery, pulping and other production workshops. The percentages of energy consumption account for 26%, 18%, 15%, 10% and 6%, respectively. (3) The main sources of carbon include coal and forest biomass, reaching 770,000 tons and 1.39 million tons, respectively. (4) Carbon emissions mainly occur in fuel combustion in combined heating and power (CHP) and diesel combustion in material transportation, reaching 6.78 million tons and 790,000 tons of carbon, respectively. (5) Based on steam and electricity consumption, the indirect carbon emissions of various thermal and electric energy production units were calculated, and the key energy consumption process units and hotspot carbon flow paths were further found. This research established a theoretical and methodological basis for energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

Time-of-use pricing of electric energy, as an important part of the national policy of energy conservation and emission reduction, requires accurate electric energy data as support. However, due to various reasons, the electric energy data are often missing. To address this thorny problem, this paper constructs a CNN and GRU-based recovery model (RCNN-BiGRU) for electric energy data by taking the missing data as the output and the historical data of the neighboring moments as the input. Firstly, a convolutional network with a residual structure is used to capture the local dependence and periodic patterns of the input data, and then a bidirectional GRU network utilizes the extracted potential features to model the temporal relationships of the data. Aiming at the difficult selection of network structure parameters and training process parameters, an accelerated adaptive differential evolution (AADE) algorithm is proposed to optimize the electrical energy data recovery model. The algorithm designs an accelerated mutation operator and at the same time adopts an adaptive strategy to set the two key parameters. A large amount of real grid data are selected as samples to train the network, and the comparison results verify that the proposed combined model outperforms the related CNN and GRU networks. The comparison experimental results with other optimization algorithms also show that the AADE algorithm proposed in this paper has better data recovery performance on the training set and significantly better performance on the test set. [ABSTRACT FROM AUTHOR]

Smart meters for measuring electricity consumption are fast becoming prevalent in households. The meters measure consumption on a very fine scale, usually on a 15 min basis, and the data give unprecedented granularity of consumption patterns at household level. A multitude of papers have emerged utilizing smart meter data for deepening our knowledge of consumption patterns. This paper applies a modification of Okoli’s method for conducting structured literature reviews to generate an overview of research in electricity customer classification using smart meter data. The process assessed 2099 papers before identifying 34 significant papers, and highlights three key points: prominent methods, datasets and application. Three important findings are outlined. First, only a few papers contemplate future applications of the classification, rendering papers relevant only in a classification setting. Second; the encountered classification methods do not consider correlation or time series analysis when classifying. The identified papers fail to thoroughly analyze the statistical properties of the data, investigations that could potentially improve classification performance. Third, the description of the data utilized is of varying quality, with only 50% acknowledging missing values impact on the final sample size. A data description score for assessing the quality in data description has been developed and applied to all papers reviewed. [ABSTRACT FROM AUTHOR]

Smart grids generate an immense volume of load data. When analyzed using intelligent technologies, these data can significantly improve power load management, optimize energy distribution, and support green energy conservation and emissions reduction goals. However, in the process of data utilization, a pertinent issue arises regarding potential privacy leakage concerning both regional and individual user power load data. This paper addresses the scenario of outsourcing computational tasks for regional power load forecasting in smart grids, proposing a regional-level load forecasting solution based on secure outsourcing computation. Initially, the scheme designs a secure outsourcing training protocol to carry out model training tasks while ensuring data security. This protocol guarantees that sensitive information, including but not limited to individual power consumption data, remains comprehensively safeguarded throughout the entirety of the training process, effectively mitigating any potential risks of privacy infringements. Subsequently, a secure outsourcing online prediction protocol is devised, enabling efficient execution of prediction tasks while safeguarding data privacy. This protocol ensures that predictions can be made without compromising the privacy of individual or regional power load data. Ultimately, experimental analysis demonstrates that the proposed scheme meets the requirements of privacy, accuracy, and timeliness for outsourcing computational tasks of load forecasting in smart grids. [ABSTRACT FROM AUTHOR]

With the increasing global focus on energy efficiency and environmental sustainability, intelligent building materials such as thermochromic glazing have emerged as a hot topic of research. The intent of this paper is to explore the utilization of gel-type thermochromic glazing within the realm of architectural energy conservation calculations. It conducts an exhaustive examination of the material's attributes, its capacity for energy savings, and the obstacles encountered in real-world applications. Through simulation studies and case analyses, this paper assesses the energy efficiency of gel-type thermochromic glazing across various climates and suggests strategies for optimization. The study revealed that the incorporation of gel-based thermochromic glazing leads to a marked reduction in energy usage within buildings, an improvement in indoor comfort levels, and significant environmental advantages. [ABSTRACT FROM AUTHOR]

This work investigates the interaction between water waves and multiple ice shelf fragments in front of a semi-infinite ice sheet. The hydrodynamics are modelled using shallow water wave theory and the ice shelf vibration is modelled using Euler–Bernoulli beam theory. The ensuing multiple scattering problem is solved in the frequency domain using the transfer matrix method. The appropriate conservation of energy identity is derived in order to validate our numerical calculations. The transient scattering problem for incident wave packets is constructed from the frequency domain solutions. By incorporating multiple scattering, this paper extends previous models that have only considered a continuous semi-infinite ice shelf. This paper serves as a fundamental step towards developing a comprehensive model to simulate the breakup of ice shelves. [ABSTRACT FROM AUTHOR]

Energy saving is an important measure to promote social green transformation. The traditional energy-saving ideas usually only focus on a specific loss, and seldom consider the possible relationship and influence among various losses. In relatively complex energy-using systems, there are often many kinds of losses, and each loss may have many influencing factors. There may be some relationship between these losses and the influencing factors. To solve this problem, this paper presents an analysis method of the variable association in multi-variable systems. First, the basic relationships between variables and the representation methods are discussed. The basic concept of a path between variables is given, and the analysis method of variable association based on path statistics is provided. This paper focuses on the analysis of the influencing factors and paths of the observed variables, as well as which observed variables will be affected by a control variable. Then, based on the correlation matrix, the quantitative analysis method of the influence between variables is given. Variable correlation analysis is innovatively applied in the field of energy saving to determine the correlation of losses through variable associations, guiding the preliminary screening of energy-saving measures and analyzing the collateral effects of these measures. Based on the correlations between energy losses, a scientific process for formulating energy-saving measures is proposed. The variable correlation analysis method proposed in this paper is a generalized method, which can judge the correlation between variables from the perspective of theoretical analysis and avoid the dependence on data. In addition to good applications in the field of energy conservation, it can also be widely used in construction, transportation, climate change, and other fields. The proposed energy-saving ideas take into account the intensity of influencing factors on loss and the correlation between loss, which improves the effectiveness of energy saving measures. [ABSTRACT FROM AUTHOR]

Due to the extensive use of fossil fuels, energy conservation and sustainable transportation have become hot topics. Electric vehicles (EVs), renowned for their clean and eco-friendly attributes, have garnered considerable global attention and are progressively being embraced worldwide. However, disorganized EV charging not only reduces charging station efficiency but also threatens power grid stability. In this low-carbon era, photovoltaic storage charging stations offer a solution that accommodates future EV growth. However, due to the significant instability in both the charging load and photovoltaic power generation within charging stations, it is critical to maximize local photovoltaic power consumption and minimize the impact of disorganized EV charging on the power grid. This paper formulates an intelligent scheduling strategy for electric heavy trucks within charging stations based on typical photovoltaic output data. The study focuses on a photovoltaic storage charging station in an industrial zone in Xinjiang. While considering the electricity procurement cost of the charging station, the aim is to minimize fluctuations in the electricity procurement load. A simulation analysis was conducted using MATLAB 2021a software, and the results indicated that, compared to an uncoordinated charging strategy for electric heavy trucks, the proposed strategy reduced electricity procurement costs by CNY 1348.25, decreased load fluctuations by 169.45, and improved the utilization efficiency of photovoltaic energy by 30%. A statistical analysis was also used to support the reduction in electricity procurement costs and load variations. Finally, a sensitivity analysis of the weight factors in the objective function was performed, proving that the proposed strategy effectively reduces electricity procurement costs and improves the utilization efficiency of photovoltaic energy. [ABSTRACT FROM AUTHOR]

In Europe, it is estimated that 14% of existing buildings were built before 1919, whereas 26% were built before 1945. In Romania, about 31% of the buildings date from before 1961, contributing to the current stock of old buildings with historic and architectural value in the country. This paper illustrates the current state of buildings with historic and architectural value in Romania, alongside a case study of a representative administrative building in Câmpulung, Romania. The analysis of the Town Hall building in Câmpulung, Romania, demonstrates that potential energy savings of up to 47.53% can be achieved by implementing interventions such as upgrading windows, insulating the attic, and installing photovoltaic panels. The highest energy reduction is obtained by replacing the window glass with a value of 18.16% with attic insulation with a value of 16.1%. This paper also presents indoor measurements of temperature and humidity in different offices positioned in the north and the south. The study conducted on the south façade office revealed consistent temperatures ranging from 21.7 °C to 24.4 °C, with an average of 23.31 °C. However, the humidity levels fluctuated considerably, ranging from 17.1% to 39.1%, with an average of 26.89%. The sun-exposed section of the building saw relatively stable temperature conditions, but the varying humidity levels could have a detrimental impact on the quality of the indoor atmosphere and potentially decrease the effectiveness of the workforce. By contrast, the north façade office exhibited lower and more fluctuating temperatures, ranging from 19.8 °C to 23.6 °C, with an average of 21.74 °C. Additionally, it had higher and more stable humidity levels, ranging between 19.5% and 41.7%, with an average of 29.83%. A thermographic analysis was performed on the north façade of the Câmpulung Town Hall, utilizing thermal imaging technology to detect areas of heat loss, and thus identifying the energy inefficiency problems of the building's exterior. The investigation found notable variations in temperature, especially around the windows, where temperatures could be as high as 14.1 °C, highlighting the insufficiency of the building's antiquated timber-framed windows in preventing energy loss. [ABSTRACT FROM AUTHOR]

The building sector, which is responsible for a significant amount of total global energy consumption, provides substantial opportunities for energy efficiency studies. In the context of historic and traditional buildings, this matter becomes more crucial, as energy efficiency is more complex and challenging. The complexity partly derives from the multiple and diverse values with which the buildings are associated. These values are dynamic. In this paper, we chose historic houses in Gaziantep as our focal point. They provide an indicative example of houses with architectural features that help residents deal with the adverse effects of the hot climate. These specific features are significant for the users not only in terms of thermal comfort but also in terms of heritage values. The value that users attribute to the neighbourhood and their attitude towards buildings change over time. It is seen that thermal comfort plays a key role in energy efficiency and heritage conservation. Hence, understanding the role of thermal comfort perceptions and the ways in which they dictate certain energy efficiency and heritage conservation actions is critical. In this context, this paper addresses these dynamic, complex, and changing interrelationships over time. Drawing upon the dynamic analysis of in-depth, semi-structured interviews with three dwellings in Gaziantep's Bey neighbourhood, we will discuss how residents of historic houses perceive thermal comfort and how they negotiate and prioritise energy efficiency and heritage conservation. [ABSTRACT FROM AUTHOR]

Large public buildings (LPBs) are the main energy consumers in cities, and the air conditioning system contributes a large part. Supply air allocation by partition can avoid excessive regulation of the system. In spatially interconnected LPBs, thermal coupling relationships exist between different subzones. The convective heat transfer to the non-occupied zone increases the actual cooling/heating capacity of the air conditioning area. This paper applies the air curtain as an airflow barrier indoors, and the air curtain grid system (ACGS) is created by the combined operation of multiple air curtains, which aims to reduce the convective heat exchange between adjacent subzones. The computational fluid dynamics (CFD) model is established and simulated. The main conclusions are as follows: (1) For the scenarios addressed in this paper, the combination of a 60° diffuser air supply angle and 2 m/s air curtain velocity can reduce the convective load from the adjacent space by more than 50%. (2) It is recommended to install incomplete air curtains indoors, and a 50% air curtain coverage ratio can reduce 52% of the heat exchange. (3) The mathematical model of air infiltration/exfiltration under the combined operation of multiple air curtains is established and verified in ACGS. This paper provides a new approach to the air conditioning partition control of LPBs. [ABSTRACT FROM AUTHOR]

Electricity consumption in buildings is one of the major causes of energy usage and knowledge of this can help building owners and users increase energy efficiency and conservation efforts. For Pacific Island countries, building electricity demand data is not readily accessible or available for constructing models to predict electricity demand. This paper starts to fill this gap by studying the case of schools in Fiji. The aim of the paper is to assess the factors affecting electricity demand for grid-connected Fijian schools and use this assessment to build mathematical models (multiple linear regression (MLR) and artificial neural network (ANN)) to predict electricity consumption. The average grid-connected electricity demand in kWh/year was 1411 for early childhood education schools, 5403 for primary schools, and 23,895 for secondary schools. For predicting electricity demand (ED) for all grid-connected schools, the stepwise MLR model shows that taking logarithm transformations on both the dependent variable and independent variables (number of students, lights, and air conditioning systems) yields statistically significant independent variables with an R2 value of 73.3% and RMSE of 0.2248. To improve the predicting performance, ANN models were constructed on both the natural form of variables and transformed variables. The optimum ANN model had an R2 value of 95.3% and an RMSE of 59.4 kWh/year. The findings of this study can assist schools in putting measures in place to reduce their electricity demand, associated costs, and carbon footprint, as well as help government ministries make better-informed policies. [ABSTRACT FROM AUTHOR]

In recent years, global attention to carbon emissions has increased, becoming one of the main drivers of global climate change. Accurate prediction of carbon emission trends in small and medium-sized countries and scientific regulation of carbon emissions can provide theoretical support and policy references for the effective and rational use of energy and the promotion of the coordinated development of energy, environment, and economy. This paper establishes a grey prediction model using the classical Logistic mathematical model in a determined environment to investigate the carbon emission system. At the same time, we use the basic principle of fractional-order accumulation to establish a grey prediction model with fractional-order Logistic and obtain the parameter estimation and time-response equation of the new model by solving the model through the theory related to fractional-order operators. The particle swarm optimization algorithm is used to complete the optimization process of the order of the fractional order grey prediction model and obtain the optimal model order. Then, the new model is applied to predict carbon emissions in five medium-emission countries: Ethiopia, Djibouti, Ghana, Belgium, and Austria. The new model shows better advantages in the validity analysis process, and the simulation results indicate that the new model proposed in this paper has stronger stability and better simulation and prediction accuracy than other comparative models, proving the model's validity. Finally, the model is used to forecast the carbon emissions of these five countries for the five years of 2021–2025, and the results are analyzed, and relevant policy recommendations are made. [ABSTRACT FROM AUTHOR]

The simplification of complex networks is a research field closely related to graph theory in discrete mathematics. The existing methods are typically limited to simplifying the series sub-networks, parallel sub-networks, diagonal sub-networks, and nested simple sub-networks. From the current perspective, there are no available methods that can handle complex sub-networks and nested complex sub-networks. In this paper, we innovatively propose an efficient and automatic equivalence simplification method for arbitrary complex ventilation networks. The method enables, for the first time, the maximum possible equivalence simplification of nested simple sub-networks and nested complex sub-networks. In order to avoid the NP-hard problem caused by the searching of simplifiable sub-networks, it is necessary to analyze the intrinsic topology relationship between simplifiable sub-networks and spanning sub-graphs to optimize the searching process. One of our main contributions is that we present an efficient searching method for arbitrarily nested reducible sub-networks based on the bidirectional traversal process of a directed tree. The method optimizes the searching process for simplifiable node pairs by combining the characteristics of a directed tree with the judgment rules of simplifiable sub-networks. Moreover, by deriving the formula of an equivalent air resistance calculation for complex sub-networks, another one of our main contributions is that we present an equivalent calculation and simplification method for arbitrarily complex sub-networks based on the principle of energy conservation. The basic idea of the method is to calculate the equivalent air resistance using the ventilation network resolution of the constructed virtual sub-networks. We realize the simplification method of arbitrarily complex mine ventilation networks, and we validate the reliability of the simplification method by comparing the air distribution results using the network solution method before and after simplification. It can be determined that, with appropriate modifications to meet specific requirements, the proposed method can also be applicable to equivalent simplification instances of other types of complex networks. Based on the results analysis of several real-world mine ventilation network examples, the effectiveness of the proposed method is further verified, which can satisfactorily meet the requirements for simplifying complex networks. [ABSTRACT FROM AUTHOR]

This paper proposes, for the first time, the research concept of comparing energy and economy between transcritical cycle high-temperature heat pumps and subcritical cycle high-temperature heat pumps with new refrigerants. Experiments and simulations are conducted to compare the system performance and economy of two heat pumps, and the effects of different factors on the performance of two heat pumps are analyzed. The results show that R744/R1234yf (90/10) and R515-1 are the preferred refrigerants for transcritical cycle heat pumps and subcritical cycle heat pumps, respectively. The COP of the R744/R1234yf (90/10) transcritical heat pump is generally higher than that of the R515B-1 subcritical heat pump, and compared to the R515B-1 subcritical heat pump, the cost recovery period of the R744/R1234yf (90/10) transcritical heat pump is about 9–15 years. Therefore, it is recommended that users who use heat pumps for a long time choose transcritical cycle heat pumps. Meanwhile, with the change of evaporation temperature, the system COP of the R515B-1 subcritical heat pump and R744/R1234yf (90/10) transcritical heat pump increases by 61.11% and 65.91%, respectively. In addition, the optimal charge amount for the R515B-1 subcritical heat pump is 81.8% of that of the R744/R1234yf (90/10) transcritical heat pump. [ABSTRACT FROM AUTHOR]

The thermal performance of windows is an important area of research to reduce the energy consumption of buildings and improve indoor comfort. The application of innovative glazing technologies can improve the energy performance of windows and transparent facades, resulting in significant energy savings. This paper presents research results on the energy performance of electrically heated windows. A comprehensive CFD and experimental analysis of the heat transfer processes in a window space depending on the size, power, and location of an electric heater was performed. The convective gas flows in the gas gaps and in the boundary layer were also analysed, and it is shown that a window with an electric heater can reduce the energy consumption of a room by 10–12%. This study is a pilot study to assess the feasibility and cost-effectiveness of electric local heating of a window or facade to minimise heat loss before full-scale implementation. The results of numerical modelling and experimental studies confirm the potential of the new technologies. [ABSTRACT FROM AUTHOR]

Featured Application: The work in this paper provides some basic theoretical and practical reference value for the energy and exergy analysis, calculation, process optimization, and energy conservation research of the hydrogen-based direct reduction shaft furnace process, which is helpful for promoting its further industrial application. The traditional production mode using coal as the main energy source is not conducive to the sustainable development of the iron and steel industry (ISI). The hydrogen-based direct reduction shaft furnace (HDRSF) process is a feasible technical route for promoting the green development of the ISI. However, there is a lack of comprehensive analysis with respect to the energy utilization and process flow of the HDRSF method. To address these issues, a systemic material–energy–exergy model of HDRSF is established. An improved HDRSF process incorporating waste heat recovery is also proposed, and energy consumption intensity and exergy intensity are used as assessment metrics. This study's findings indicate that the proposed waste heat recovery can considerably lower gas demand and energy consumption intensity, but exergy intensity has little effect. The reducing gas demand drops from 2083 m3 to 1557 m3, the energy consumption intensity drops from 2.75 × 107 kJ to 1.70 × 107 kJ, and the exergy intensity drops from 1.08 × 107 kJ to 1.05 × 107 kJ when the reducing gas temperature is 900 °C, H2:CO = 1:1; meanwhile, the recovery rate of waste heat reaches 40%. This study can serve as a reference for actual HDRSF process production. [ABSTRACT FROM AUTHOR]

Improving China's high-quality development efficiency represents a key lever for the development of new productivity and successfully achieving the "dual carbon" goal. Starting from the nonparametric production theory, this paper addresses the issues of infeasible solutions and technical heterogeneity by employing the total-factor non-radial directional distance function and a metafrontier non-radial Malmquist model. The static total-factor high-quality development efficiency index (THEI) and its dynamic metafrontier non-radial Malmquist high-quality development efficiency index (MNMHEI) are measured for 31 provinces in China from 2008 to 2021. Given that high-quality development efficiency is led and driven by talent, we use labor of different ages and levels of education as four inputs instead of single labor for the study of THEI. The MNMHEI is divided into three indices for measuring efficiency change (EC), best-practice gap change (BPC), and technology gap change (TGC). The empirical results demonstrate that labor with higher education is the main lever of static high-quality development efficiency; there is a 5.3% decrease in China's dynamic high-quality development efficiency as a whole, and a lack of technological innovation remains a significant constraint on its improvement. The results of the heterogeneity analysis, which classified all provincial areas into low-carbon and high-carbon regions, indicate that the former exhibits a higher dynamic high-quality development efficiency than the latter, which still lacks innovation and technology leadership. It is recommended that the Chinese government consider the talent management system, investments in upgrading technologies, energy conservation, and emission reduction for high-carbon regions to improve their high-quality development efficiency. [ABSTRACT FROM AUTHOR]

Nonintrusive load monitoring (NILM) is an important technique for energy management and conservation. In this paper, a deep learning model based on an attention mechanism, temporal pooling, residual connections, and transformers is proposed. This article presents a novel approach for NILM to accurately discern energy consumption patterns of individual household appliances. The proposed method entails a sequence of layers, including encoders, transformers, attention, temporal pooling, and residual connections, offering a comprehensive solution for NILM while effectively capturing appliance-specific energy usage in a household. The proposed model was evaluated using UK-DALE, REDD, and REFIT datasets in both seen and unseen cases. It shows that the proposed model in this paper performs better than other methods stated in other papers in terms of F1-score and total error of the results (in terms of SAE). This model achieved an F1-score equal to 92.96 as well as a total SAE equal to −0.036, which shows its effectiveness in accurately diagnosing and estimating the energy consumption of individual home appliances. The findings of this research show that the proposed model can be a tool for energy management in residential and commercial buildings. [ABSTRACT FROM AUTHOR]

As the criteria of energy conservation, emission reduction, and environmental protection become more important, and with the development of wet-end papermaking, developing excellent retention aids is of great significance. Spherical polyelectrolyte brushes (SPBs) bearing polyelectrolyte chains grafted densely to the surface of core particle have the potential to be novel retention aids in wet-end papermaking not only because of their spherical structure, but also due to controllable grafting density and molecular weight. Such characteristics are crucial in order to design multi-functional retention aids in sophisticated papermaking systems. This review presents some important recent advances with respect to retention aids, including single-component system and dual-component systems. Then, basic theory in papermaking is also briefly reviewed. Based on these advances, it emphatically describes spherical polyelectrolyte brushes, focused on their preparation methods, characterization, conformation, and applications in papermaking. This work is expected to contribute to improve a comprehensive understanding on the composition, properties, and function mechanisms of retention aids, which helps in the further investigation on the design of novel retention aids with excellent performance. [ABSTRACT FROM AUTHOR]

In many different industrial domains, hydraulic control systems are extensively utilized. This paper examines the current state of research and the trajectory of energy-efficient hydraulic control system development. Initially, a quick introduction to the control principles of hydraulic control systems is given. Secondly, hydraulic control systems are classified, the factors affecting the energy consumption of hydraulic control systems are analyzed, and the method of reducing its influence on hydraulic control systems is given. Subsequently, research concerning energy conservation is compiled based on the classification of hydraulic control systems. In this paper, the circuit structure of two control modes of a hydraulic control system (valve control system and pump control system) and their related control algorithms (fuzzy PID control, adaptive robust control) for reducing system energy consumption are studied. In summary, the evolution of energy-efficient hydraulic control system approaches is forecasted and projected, offering some pointers for advancing hydraulic control system study and implementation in the industrial future. [ABSTRACT FROM AUTHOR]

As awareness of climate change increases, diverse initiatives such as subsidies for remanufactured products and take-back programs for end-of-life products have been taken to conserve energies and materials. This paper explores how the subsidy program affects manufacturer's take-back activity in a closed-loop supply chain and also analyzes how a coalition between a retailer and a remanufacturer affects the equilibrium decisions. Major findings of this paper reveal that (i) when a take-back program is implemented, the government imposes a high penalty on products that are not collected, thereby encouraging manufacturers to collect more used products, (ii) implementing a take-back program in conjunction with a subsidy program results in a greater reduction in environmentally negative impacts and an enhanced social welfare compared to implementing them separately, and (iii) a coalition between a retailer and a remanufacturer results in lowering the penalty imposed to a manufacturer, which leads to lowering the quantity of the collected and remanufactured products. [ABSTRACT FROM AUTHOR]

Computational methods play a significant role in reducing energy consumption in cities. Many different sensor networks (e.g., traffic intensity sensors, intelligent cameras, air quality monitoring systems) generate data that can be useful for both efficient management (including planning) and reducing energy usage. Street lighting is one of the most significant contributors to urban power consumption. This paper presents a summary of recent attempts to use computational methods to reduce energy usage by lighting systems, with special focus on graph-based methods. Such algorithms require all the necessary data to be integrated, in order to function properly: this task is not trivial, and is very time-consuming; therefore, the second part of the paper proposes a novel approach to integrating urban datasets and automating the optimisation process. In two practical examples, we show how spatially triggered graph transformations (STGT) can be used to build a model based on the road network map, sensor locations and street lighting data, and to introduce semantic relations between the objects, including utilisation of existing infrastructure, and planning of development to maximise efficiency. [ABSTRACT FROM AUTHOR]

A collection of twelve papers published in Energies, in a Special Issue on "Building Energy Audits-Diagnosis and Retrofitting", was bound together and published in 2021, focusing on the built environment. The aim was to systematically collect and analyze relevant data for obtaining adequate knowledge on the energy use profile of buildings, and was extended for the sustainability assessment of the built environment. To date, all papers have been very well received, attaining a total of 97 citations and over 15,300 views. The papers addressed historic and various building types, baselines for non-residential buildings from energy performance audits and from in-situ measurements, monitoring and data analysis, assessment of indoor environmental quality, model calibration and verification of energy savings, along with an urban audit and rating method for assessing the sustainability of the built environment. Following on from the success of this Special Issue, the decision was made to reopen and extend it to include papers related to decarbonization and sustainability, at building, city, region, and national scales. This Editorial reviews the performance of the first Special Issue and outlines the second volume on Building Energy Audits-Diagnosis and Retrofitting Towards Decarbonization and Sustainable Cities, as a Special Issue in Energies. [ABSTRACT FROM AUTHOR]

With the background of rural revitalization, the urgent demand for energy conservation and improved living quality arises alongside the issues of high energy consumption and low comfort in residential buildings. Located in a region with a hot summer and cold winter climate, Hanzhong faces significant energy consumption for heating and cooling throughout the year, considering both winter insulation and summer heat insulation. Based on the energy consumption simulation and analysis of folk dwellings in Hanzhong, this paper employs a single-objective optimization method to explore the optimization of building envelope structures, including the window-to-wall ratio, bay width, number of floors, orientation, and floor height. Additionally, it investigates building layout, spatial organization, regional design methods, and energy acquisition. Through energy consumption simulation and validation of thermal comfort evaluation index PMV-PPD, design strategies such as building scale, layout organization, indoor and outdoor buffer space design, and building material selection are proposed to effectively improve indoor thermal comfort during the winter and summer seasons. This research provides insights and references for the low-carbon design and optimization of residential buildings. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative cooperative model for energy efficiency retrofitting that incorporates carbon emission rights, addressing critical financial constraints in Energy Performance Contracting (EPC). By employing the fuzzy analytic hierarchy process (F-AHP) to evaluate risk assessment indicators and stakeholder contributions and utilizing the enhanced Shapley method for equitable benefit distribution, the model demonstrates significant improvements in financing and efficiency for energy conservation projects. The findings are as follows: (1) the energy efficiency retrofit model, which integrates carbon emission rights, effectively alleviates the financial constraints and fosters energy conservation and emission reduction in guaranteed-savings EPC projects; (2) the enhanced Shapley method is deemed appropriate for the equitable distribution of energy-saving benefits among stakeholders; (3) when compared with the traditional model and the benefit allocation-absent carbon rights, the energy-saving benefits of the energy efficiency retrofit model incorporating carbon emission rights are higher in individual and overall terms. The findings of this study offer a viable solution to financing challenges faced by stakeholders in such projects and delineate a pragmatic approach for enterprises to enhance energy efficiency and reduce emissions. [ABSTRACT FROM AUTHOR]

Diverse demands have promoted the rapid development of the cold chain logistics industry. In the paper, a novel approach for calculating the comprehensive carbon emission cost was proposed and the front warehouse mode was analyzed under the background of energy conservation and emission reduction. To solve the two-echelon low-carbon location-routing problem (2E-LCLRP), a mathematical model considering operating cost, total transportation cost, fixed cost, refrigeration cost, cargo damage cost, and comprehensive carbon emission cost was proposed to determine the minimum total cost. A hybrid ant colony optimization (HACO) algorithm based on an elbow rule and an improved ant colony optimization (IACO) algorithm was proposed to solve the 2E-LCLRP. According to the elbow rule, the optimal number of front warehouses was determined and an IACO algorithm was then designed to optimize vehicle routes. An adaptive hybrid selection strategy and an optimized pheromone update mechanism were integrated into the HACO algorithm to accelerate convergence and obtain global optimal solutions. The proposed model and algorithm were verified through the case study of the 2E-LCLRP in Nanjing, China. The HACO algorithm outperformed the original ant colony optimization (ACO) algorithm in terms of convergence rate and solution quality. This study provides significant insights for enhancing heuristic algorithms as well as valuable research methods. Furthermore, the results can help cold chain logistics companies in balancing economic costs and environmental benefits and address cold chain distribution of agricultural products. [ABSTRACT FROM AUTHOR]

In advanced manufacturing, optimizing mixed-model synchronous assembly lines (MMALs) is crucial for enhancing productivity and adhering to sustainability principles, particularly in terms of energy consumption and energy-efficient sequencing. This paper introduces a novel approach by categorizing sequence-dependent setup times into bipartite categories: workpiece-independent and workpiece-dependent. This strategic division streamlines assembly processes, reduces idle times, and decreases energy consumption through more efficient machine usage. A new mathematical model is proposed to minimize the intervals at which workpieces are launched on an MMAL, aiming to reduce operational downtime that typically leads to excessive energy use. Given the Non-deterministic Polynomial-time hard (NP-hard) nature of this problem, a genetic algorithm (GA) is developed to efficiently find solutions, with performance compared against the traditional branch and bound technique (B&B). This method enhances the responsiveness of MMALs to variable production demands and contributes to energy conservation by optimizing the sequence of operations to align with energy-saving objectives. Computational experiments conducted on small and large-sized problems demonstrate that the proposed GA outperforms the conventional B&B method regarding solution quality, diversity level, and computational time, leading to energy reductions and enhanced cost-effectiveness in manufacturing settings. [ABSTRACT FROM AUTHOR]

A special vibration damper is proposed for Young's modulus and hardness identification through a scratching process on extruded aluminum. This paper presents the design and working principle of a scratching damper based on a scratching device. A non-contact electromagnetic shaker is used to generate the shaking force for test sample vibration. The required forces on the scratched material during the scratching process are generated by an adjustable compression spring. The proposed damper is designed and tested on an extruded aluminum 3004 sample for the determination of its Young's modulus and hardness, and validation is performed using the standard test instruments. The physical dimensions of the scratching tracks are measured using a microscope and utilized to compute the scratching energy factor. Load curves are obtained at different divisions of the scratching process. The loop energy during the scratching process of the tested object is measured and used for the determination of sample material properties. Furthermore, the energy conservation law, scratch energy release rate of semi-conical scratch head, and loop energy release rate are established to determine the Young's modulus and hardness of the sample. Their estimation accuracies are evaluated. The proposed method has several advantages over the traditional methods, including low cost, directness, and high repeatability. The results suggest this to be used as an alternative to the standard modulus and hardness tester. [ABSTRACT FROM AUTHOR]

Urban building energy modeling (UBEM) is a practical approach in large-scale building energy modeling for stakeholders in the energy industry to predict energy use in the building sector under different design and retrofit scenarios. UBEM is a relatively new large-scale building energy modeling (BEM) approach which raises different challenges and requires more in-depth study to facilitate its application. This paper performs a systematic literature review on physics-based modeling techniques, focusing on assessing energy conservation measures. Different UBEM case studies are examined based on the number and type of buildings, building systems, occupancy schedule modeling, archetype development, weather data type, and model calibration methods. Outcomes show that the existing tools and techniques can successfully simulate and assess different energy conservation measures for a large number of buildings. It is also concluded that standard UBEM data acquisition and model development, high-resolution energy use data for calibration, and open-access data, especially in heating and cooling systems and occupancy schedules, are among the biggest challenges in UBEM adoption. UBEM research studies focused on developing auto-calibration routines, adding feedback loops for real-time updates, future climate data, and sensitivity analysis on the most impactful modeling inputs should be prioritized for future research. [ABSTRACT FROM AUTHOR]

Saving energy is an important strategy to address the current energy crisis and environmental degradation. Regarding the pilot policy of the energy quota trading as a quasi-natural experiment by employing a difference-in-differences method, the purpose of this paper is to investigate the effect of this pilot policy on energy saving and its mechanisms based on city-level data in China from 2006 to 2020. We find that the energy quota trading policy can reduce the total energy consumption and energy consumption intensity of pilot cities, and the effect of the policy can gradually strengthen over time. The market-oriented reform of energy factor allocation can effectively promote energy saving and economic growth. These results are convincing through a series of robustness checks. The heterogeneity test shows that the energy quota trading has a significant energy saving effect on economically developed cities, densely populated cities and southern cities, but not in economically underdeveloped cities, sparsely populated cities and northern cities. Further mechanism inspection suggests that the pilot policy of energy quota trading mainly achieves energy conservation through industrial structure upgrading and green technology innovation. Our findings provide a valuable insight for China to control energy consumption and promote the high-quality development of the energy economy. [ABSTRACT FROM AUTHOR]

The thermal effect and heat dissipation have a significant impact on three-dimensional stacked chips, and the positional layout of the chip's three-dimensional layout directly affects the internal temperature field. One effective way is to plan the overall layout of three-dimensional integrated circuits by considering the thermal effect and layout utilization. In this paper, an ant colony algorithm is used to search for the most planned paths and achieve the overall layout optimization by considering the effects of power, temperature, and location on the thermal layout and using feedback optimization of pheromone concentration. The simulation results show that the optimization of the thermal layout of 3D integrated circuits can be well realized by adjusting the algorithm parameters. The maximum temperature, temperature gradient, and layout scheme verify reliability and practicability. It improves the utilization rate of chips, optimizes the layout, realizes energy conservation, and reduces resource waste. [ABSTRACT FROM AUTHOR]

The present study offers a thorough scientometric analysis of the practice of bioclimatic retrofitting in commercial buildings, which is considered a crucial approach for mitigating energy consumption and addressing the challenges posed by climate change. Since Scopus offers advanced tools for literature search and analysis, its database was used to acquire bibliographic data for nearly 400 published papers using a bibliometric search, a scientometric methodology, and an in-depth qualitative analysis. The scientometric procedure utilizes various quantitative dimensions, such as the number of intermediate citations, occurrences, average publication year, and general connection power. A retrospective examination of research publication patterns spanning 2008 to May 2022 has unveiled an upward trajectory in scholarly investigations pertaining to commercial buildings during this 15-year period. Nevertheless, research on the topics of bioclimatic design, retrofitting strategies, and green building practices in the context of commercial buildings exhibits a more gradual incline, displaying an almost linear trend between the years 2016 and 2020. Additionally, the study provides qualitative perspectives on the research environment. The paper delineates various focal points of research within the field, encompassing thermal comfort in the context of energy management and climate control, ventilation systems, sustainable development as it pertains to architectural designs and green buildings, retrofitting strategies in commercial buildings to enhance energy efficiency, the interplay between carbon dioxide levels and energy resources, the utilization of solar energy, the relationship between energy conservation and atmospheric temperature, and the application of building energy simulation techniques. [ABSTRACT FROM AUTHOR]

Today, HVAC (heating, ventilation, and air conditioning) systems have become an integral part of modern buildings and are designed to provide comfortable indoor environments while conserving energy and reducing carbon emissions. With advancement in technology, HVAC systems have a variety of sensors that are used to detect the occupants within a controlled environment. Advancements in computer control systems and the use of smart technology have made HVAC systems even more sophisticated, allowing for approximate temperature control and energy management. This paper will review the historical development of technology and the current state of HVAC systems. With the proper data, development of artificial intelligence models can, in theory, improve the overall optimization and reduce energy consumption This paper will provide a review of HVAC history and the key concepts around the usefulness of using AI from previous research conducted in this field of study. [ABSTRACT FROM AUTHOR]

In this paper, the optimization of the flow channel structure of the U-shaped air distributor is proposed. Fluent meshing was used to mesh the multipatch meshing of the original model of the grid air distributor, and then the CFD numerical simulation was carried out by using Fluent 2022R1 to obtain the internal air flow state of the air distributor flow channel. Through the orthogonal experimental design and a comprehensive analysis method, the optimal size structure for resistance performance is obtained as S = 60 mm, RL = 125 mm, L = 160 mm, D = 100 mm, the resistance coefficient of the new structure as 1.375, and the pressure loss as 56.87 Pa, by using 3D modeling software (SOLIDWORKS 2015) and Fluent. Compared with the initial scheme, the resistance coefficient and pressure loss are reduced by 3.03% and 6.29%, respectively. To summarize, the research in this paper offers a substantial contribution to the realm of energy conservation and emission abatement in ship air conditioning systems, simultaneously furnishing invaluable guidance for the design of air distributors. [ABSTRACT FROM AUTHOR]

In this paper, an experimental study of a system for heating an air-conditioned bed during a 2 h lunch was carried out. The results show that the power consumption of heat conduction heating was only 0.34 kW·h and that the average heat dissipation was 81.3 W, while the power consumption of convection heating was 1.43 kW·h, accompanied by an average heat dissipation of 748.7 W. Regardless of the power consumption or the heat dissipation, the convection heating was significantly higher than the heat conduction heating. As a result, the room air temperature increased from 12.3 °C to 17.3 °C under convection heating, but only increased from 14.4 °C to 15.2 °C under heat conduction heating. The study results indicate that when using heat conduction heating, water temperatures in the range of 38~40 °C could meet the thermal comfort needs of the human body; however, a higher temperature range was required when using convection heating. In contrast, the grade of the hot water required for heat conduction heating was lower. It was also found that the temperature under convection heating rises faster, but it tends to lead to a dry feeling after a long time, while the conductive heating showed a slower temperature rise. There was a cool feeling for 20 min when the heating started, and then the thermal comfort improved. The air-conditioning system in this paper was investigated in a heating experiment in the winter lunch break mode and compared with convection heating. The heat conduction heating resulted in better thermal comfort and higher energy efficiency. It is suggested to adopt the heat conduction heating mode in the winter heating operation of this system. [ABSTRACT FROM AUTHOR]

In the last decades, increasing energy prices and growing environmental awareness have driven engineers and scientists to find new solutions for reducing energy consumption in manufacturing. Although many processes of a high energy consumption (e.g., chemical, heating, etc.) are considered to have reached high levels of efficiency, this is not the case for many other industrial manufacturing activities. Indeed, this is the case for robotic and automatic systems, for which, in the past, the minimization of energy demand was not considered a design objective. The proper design and operation of industrial robots and automation systems represent a great opportunity for reducing energy consumption in the industry, for example, by the substitution with more efficient systems and the energy optimization of operation. This review paper classifies and analyses several methodologies and technologies that have been developed with the aim of providing a reference of existing methods, techniques and technologies for enhancing the energy performance of industrial robotic and mechatronic systems. Hardware and software methods, including several subcategories, are considered and compared, and emerging ideas and possible future perspectives are discussed. [ABSTRACT FROM AUTHOR]

(1) Background: The decoupling of energy consumption from economic growth in the construction industry is crucial to the sustainable development of the global construction industry. The existing studies focus on the advancements in energy efficiency by designers for building monoliths or construction techniques, involving no exploration of energy efficiency management from a regional perspective, which is unfavorable for the formulation of energy efficiency policies and systematic control of the construction industry by local governments. (2) Methods: From the perspective of regional management, this paper constructs an integrated analysis and application framework of "spatio-temporal characteristics + matching evaluation + policy design" based on the decoupling model and GIS tools. It studies the spatio-temporal characteristics of energy consumption in the construction industry in 30 provinces of China from 2010 to 2019, and its decoupling relationship with the economic development of the construction industry, and proposes an optimal zoning and recommendations for energy consumption in the construction industry, providing a reference for energy conservation management in the construction industry in China. (3) Results: First, the change of energy consumption amount (ECA) in the construction industry in the provinces was dominated by ascent, while the energy consumption intensity (ECI) predominantly decreased, and most provinces are still in a period of growth or plateau in energy consumption. Second, ECA and ECI had prominent spatial heterogeneity and aggregation. High-energy-consuming regions are concentrated along the coast and along the Yangtze River, while low-energy-consuming regions are mainly clustered in remote areas, such as the northeast, northwest, and southwest of China. Energy consumption shows a clear north-south difference in intensity, with high-intensity regions clustered in the north compared to low-intensity regions in the south. Third, most of the provinces were in strong negative decoupling, expansive coupling, and weak decoupling, and better decoupling regions were mainly gathered in south and central China. Nearly one half of these provinces showed decoupling degradation and only a few achieved evolution, with evolutionary regions clustered mainly in central and southern China. The northeast and northwest were the key problem areas of energy-saving transformation in China's construction industry. (4) Conclusion: The 30 provinces were divided into three types: leader, intermediate, and laggard, and the development goals and suggestions on low energy consumption in the construction industry for three zones were put forward, significantly improving the precision of policy design and implementation. The study in this paper expands the research perspective on energy saving management in the construction industry and provides a methodology and basis for developing energy efficiency policies and plans for the construction industry in China and similar developing countries. [ABSTRACT FROM AUTHOR]

With the electrification and connectivity of vehicles in transportation, traditional vehicles with single drivetrains are being replaced by pure electric or hybrid electric vehicles (HEVs). This evolution has given rise to diverse electromechanical coupling drivetrains. There is a pressing need to update simulation software to assess the economic performance of vehicles in various environments, and promote sustainable development and energy conservation. This paper presents a unified framework for the construction and automated operation of large-scale automated vehicle simulations with multiple drivetrain types, facilitating synchronous information exchange among vehicles. Central to the framework is the development of a plug-and-play vehicle model based on a modular component design, facilitating the rapid assembly of vehicles with varied drivetrain configurations and standardizing simulation file management. Additionally, a standardized simulation process construction is established to accommodate the automated operation of simulations. Furthermore, a data scheduling method among vehicles is introduced to achieve multi-vehicle interconnection simulation. Finally, the effectiveness of the framework is demonstrated through a case study involving queue-following control for HEVs. This framework aims to provide a comprehensive solution for quickly establishing automated simulation environments for multi-vehicle interaction, enhancing model reusability and scalability. [ABSTRACT FROM AUTHOR]

In the era of widespread edge computing, energy conservation modes like complete power shutdown are crucial for battery-powered devices, but they risk data loss in volatile memory. Energy autonomous systems, relying on ambient energy, face operational challenges due to power losses. Recent advancements in emerging nonvolatile memories (NVMs) like FRAM, RRAM, MRAM, and PCM offer mature solutions to sustain work progress with minimal energy overhead during outages. This paper thoroughly reviews utilizing emerging NVMs in microcontroller units (MCUs), comparing their key attributes to describe unique benefits and potential applications. Furthermore, we discuss the intricate details of NVM circuit design and NVM-driven compute-in-memory (CIM) architectures. In summary, integrating emerging NVMs into MCUs showcases promising prospects for next-generation applications such as Internet of Things and neural networks. [ABSTRACT FROM AUTHOR]

This paper presents the findings of fifteen energy audits conducted on industrial sites in Canada's Greater Toronto Area (GTA). The audits covered a range of industries including food processing, packaged goods, and finishing processes (powder-coating). The primary focus of the audits was to analyze the natural gas consumption and the performance of major-gas-consuming equipment. The audits identified natural-gas-consuming equipment that could be optimized to yield energy and operational cost savings and greenhouse gas (GHG) reduction opportunities. Food production plants' energy intensity ranges from 5.59 m3/ft2 to 17.73 m3/ft2. Therefore, there is a significant opportunity to improve energy consumption through better technology integration. The results of the audits indicate a trend of an increase in the percentage of non-productive consumption with non-productive time. The proposed energy-saving measures include reducing non-productive natural gas consumption, gas-fired equipment tune-up, optimizing boiler loads, and reducing oven exhaust by using variable frequency drives (VFDs). The findings of this study could be used to develop a demand-side management program specifically for small- and medium-sized industrial facilities in the Greater Toronto Area and other parts of Canada. [ABSTRACT FROM AUTHOR]

The built environment is a significant contributor to global energy consumption and greenhouse gas emissions. Advancements in the adoption of environmentally friendly building technology have become crucial in promoting sustainable development. These advancements play a crucial role in conserving energy. The aim is to achieve an optimal design by balancing various interrelated factors. The emergence of innovative techniques to address energy conservation have been witnessed in the built environment. This review examines existing research articles that explore different metaheuristic optimization techniques (MOTs) for energy conservation in buildings. The focus is on evaluating the simplicity and stochastic nature of these optimization techniques. The findings of the review present theoretical and mathematical models for each algorithm and assess their effectiveness in problem solving. A systematic analysis of selected algorithms using MOT is conducted, considering factors that influence wellbeing, occupant health, and indoor environmental quality. The study examines the variations among swarm intelligence MOTs based on complexity, advantages, and disadvantages. The algorithms' performances are based on the concept of uncertainty in consistently providing optimal solutions. The paper highlights the application of each technique in achieving energy conservation in buildings. [ABSTRACT FROM AUTHOR]

Opportunistic mobile networks, as an important supplement to the traditional communication methods in unique environments, are composed of mobile communication devices. It is a network form that realizes message transmission by using the opportune encounter of these mobile communication devices. Consequently, mobile communication devices necessitate periodic contact detection in order to identify potential communication opportunities, thereby leading to a substantial reduction in the already limited battery life of such devices. Previous studies on opportunistic networks have often utilized geographic information in routing design to enhance message delivery rate. However, the significance of geographic information in energy conservation has been overlooked. Furthermore, previous research on energy-efficient routing has lacked diversification in terms of the methods employed. Therefore, this paper proposes a dynamic co-operative energy-efficient routing algorithm based on geographic information perception (DCEE-GIP) to leverage geographic information to facilitate dynamic co-operation among nodes and optimize node sleep time through probabilistic analysis. The DCEE-GIP routing and other existing algorithms were simulated using opportunistic network environment (ONE) simulation. The results demonstrate that DCEE-GIP effectively extends network service time and successfully delivers the most messages. The service time of DCEE-GIP increased by 8.05∼31.11%, and more messages were delivered by 14.82∼115.9%. [ABSTRACT FROM AUTHOR]

The relativistic Doppler effect comes from the fact that observers in different inertial reference frames experience space and time differently, while the speed of light always remains the same. Consequently, a wave packet of light exhibits different frequencies, wavelengths, and amplitudes. In this paper, we present a local approach to the relativistic Doppler effect based on relativity, spatial and time translational symmetries, and energy conservation. Afterwards, we investigate the implications of the relativistic Doppler effect for the quantum state transformations of wave packets of light and show that a local photon is a local photon at the same point in the spacetime diagram in all inertial frames. [ABSTRACT FROM AUTHOR]

Studies on regional low-carbon development are essential for reducing air pollution, protecting human life and health, and environmental sustainability. In this article, after sorting the connotations of low-carbon development, the low-carbon development evaluation indicators system was constructed, and the entropy weighting method and improved analytic hierarchy process were applied to evaluate the low-carbon development level between 2007 and 2021 about Jiangsu Province, China. Also, the system dynamics model was constructed to simulate the low-carbon development process. The research findings show the following: (1) Low-carbon development in Jiangsu Province obtained some achievement; (2) "Coordination force" played the most crucial role in low-carbon development, while "growth force" and "transformation force" performed better; (3) The simulation results showed that the economic development type would be the most beneficial in the long run; the energy conservation type would be steadily developing and improving every year; and the green transformation type had a clear drive for low-carbon development at an early stage and the impact was rapid. The novelty of this paper includes the following: (1) The dimension division of the index system is novel; (2) The measurement method is novel. The weights of indicators are determined by a combination of the entropy weighting method and improved analytic hierarchy process; (3) The low-carbon development pathways of Jiangsu Province are studied by the system dynamics model. Different strategy conditions are innovatively designed, and simulations of the scenarios are carried out. [ABSTRACT FROM AUTHOR]

In this paper, a second-order operator splitting method combined with the barycentric Lagrange interpolation collocation method is proposed for the nonlinear Schrödinger equation. The equation is split into linear and nonlinear parts: the linear part is solved by the barycentric Lagrange interpolation collocation method in space combined with the Crank–Nicolson scheme in time; the nonlinear part is solved analytically due to the availability of a closed-form solution, which avoids solving the nonlinear algebraic equation. Moreover, the consistency of the fully discretized scheme for the linear subproblem and error estimates of the operator splitting scheme are provided. The proposed numerical scheme is of spectral accuracy in space and of second-order accuracy in time, which greatly improves the computational efficiency. Numerical experiments are presented to confirm the accuracy, mass and energy conservation of the proposed method. [ABSTRACT FROM AUTHOR]

The development and utilization of marine renewable energy is an important measure for achieving energy conservation, emissions reduction and carbon neutrality. Ocean thermal energy is the most stable energy among all the types of marine renewable energy. This paper built a simulation model of an ocean thermal energy conversion system based on actual device specifications by Aspen and MATLAB and put forward a corresponding control strategy. The opening control signal of the control valve at the turbine inlet was the condenser inlet pressure in this paper, and the frequency control of the working fluid pump depended on the evaporating pressure and flow rate of the working fluid. This paper analyzed the key operating parameter changes of the system under different working conditions. According to the analysis results, the turbogenerator in this system was able to generate 50 kW power for about 8 months per year. The highest net output power of the Organic Rankine Cycle was 47.3 kW; the highest cycle thermal efficiency was 3.2%. [ABSTRACT FROM AUTHOR]

City size expansion in China creates substantial economic circulation, which impacts CO2 emissions. Since CO2 production primarily comes from human activities, CO2 emissions are mainly in cities. To achieve China's carbon neutrality and provide specific implementation guidance for future carbon-reduction policies, it is worth assessing China's pressure on carbon reduction in the urban aspect. Highly developed social productivity and a market economy lead to a dramatic increase in the interconnection between cities, and the spatial distribution of CO2 emissions emerges in a spatial association. Therefore, it is of great significance to investigate the interaction of CO2 emissions with spatial effects. Taking the Yangtze River Delta urban agglomeration (YRDUA) as the research target area, this paper utilizes city-size indices to construct spatial-association networks of CO2 emissions for the first time. It employs social network analysis to explore the structures of whole networks, clusters, and city nodes. The main results show that: (1) the spatial associations of CO2 emissions in the YRDUA's cities have become tighter over time. (2) The networks of CO2 emissions in the YRDUA's cities have noticeable spatial-spillover effects, and the interaction of CO2 emissions between cities is dominant. (3) Nanjing is the paramount "bridge" node in the networks. (4) Nanjing, Hangzhou, Wuxi, Shanghai, Changzhou, Suzhou, Nantong, and Hefei will be the decisive cities for efficient CO2 emission control in the future. Overall, this paper reveals the role of carbon reduction in the YRDUA's cities and proposes suggestions for establishing a transboundary energy-saving mechanism to improve the efficiency of energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

This review paper provides a comprehensive overview of the phenomenon of superlubricity, its associated material characteristics, and its potential applications. Superlubricity, the state of near-zero friction between two surfaces, presents significant potential for enhancing the efficiency of mechanical systems, thus attracting significant attention in both academic and industrial realms. We explore the atomic/molecular structures that enable this characteristic and discuss notable superlubric materials, including graphite, diamond-like carbon, and advanced engineering composites. The review further elaborates on the methods of achieving superlubricity at both nanoscale and macroscale levels, highlighting the influence of environmental conditions. We also discuss superlubricity's applications, ranging from mechanical systems to energy conservation and biomedical applications. Despite the promising potential, the realization of superlubricity is laden with challenges. We address these technical difficulties, specifically those related to achieving and maintaining superlubricity, and the issues encountered in scaling up for industrial applications. The paper also underscores the sustainability concerns associated with superlubricity and proposes potential solutions. We conclude with a discussion of the possible future research directions and the impact of technological innovations in this field. This review thus provides a valuable resource for researchers and industry professionals engaged in the development and application of superlubric materials. [ABSTRACT FROM AUTHOR]