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A growing research interest currently exists in the use of paper as a building material. This work aims to present the results of a measurement campaign developed on innovative waste paper-based building components. The research was carried out in Southern Italy and used some local by-product aggregates. Three different mixture designs were developed in the laboratory by adding three kinds of biomass to a pulp paper blend: fava bean residues (FB), sawdust powder (SP) and coffee grains (CG) extracted from exhausted chaffs. A physical characterization was carried out measuring the bulk density and bulk porosity. Scanning Electron Microscopy (SEM) analysis of the single aggregates was followed by a microstructure analysis of the final components. Bulk density evaluation showed a range between 200 and 348 kg·m−3. Furthermore, thermal performances were measured; the thermal conductivity of the experimented samples ranged from 0.071 to 0.093 W·m−1·K−1, thus it is possible to classify the tested materials as thermal insulators. Moreover, the acoustic properties were evaluated and tested. The normal incidence sound absorption coefficient was measured by the impedance tube on cylindrical specimens. In general, a different behavior was observed between the upper and lower base of each specimen due to the manufacturing process and the shrinkage caused by the different interactions occurring between the aggregates and the pulp paper waste; for example, the presence of sawdust reduced shrinkage in the final specimens, with consequent smaller physical variations among the two faces. The correlation existing between the manufacturing process and the microstructural properties was also investigated by the estimation of the non-acoustical parameters using the inverse method and taking into account the JCA (Johnson, Champoux and Allard) model as a reference. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) offers unique capabilities in terms of design freedom and customization, contributing to sustainable manufacturing. However, energy efficiency remains a challenge in the widespread adoption of AM processes. In this paper, we present a comprehensive review of the current research on energy efficiency in AM, addressing challenges, opportunities, and future directions. Our analysis reveals a lack of standardization in the measurement and reporting of energy consumption, making it difficult to evaluate and compare the energy performance of various systems. We propose a holistic framework to address energy efficiency throughout the entire life cycle of the AM process, highlighting the importance of design optimization, material selection, advanced control systems, and energy management strategies. The paper also emphasizes the need for further research on the interactions between process parameters, along with the potential of integrating renewable energy sources into AM systems. This review offers valuable insights for both academics and industry professionals, calling for standardized methodologies and a focus on energy management to optimize energy efficiency in AM processes, ultimately enhancing competitiveness and sustainability in modern manufacturing. [ABSTRACT FROM AUTHOR]

The demand for low-carbon and energy-efficient building designs is urgent, especially considering that building energy consumption constitutes a significant part of global energy usage. Unlike small to medium-sized buildings such as residential and office spaces, large public buildings, like sports facilities, have unique usage patterns and architectural forms, offering more significant potential for energy-saving strategies. This review focuses on sports buildings, selecting 62 high-quality papers published in building science over the past 30 years that investigate low-carbon and energy-efficient research. Summarizing and synthesizing these papers reveals that current studies predominantly concentrate on four main areas: indoor air quality, ventilation, thermal environment, and energy consumption. Notably, many studies emphasize improving indoor thermal comfort and reducing energy consumption in sports buildings through measurements and evaluations of indoor thermal environments, temperature distributions, heat transfer phenomena, and energy consumption analyses. Key outcomes indicate that green technology innovations, such as energy substitution technologies, significantly enhance energy efficiency and reduce CO2 emissions. However, present research emphasizes singular energy-saving approaches, suggesting future directions could integrate comprehensive green technologies, life-cycle assessments, and applications of intelligent technologies and the Internet of Things (IoT). These enhancements aim to provide more effective and sustainable solutions for implementing green, low-carbon energy practices in sports buildings. The review emphasizes that in order to accomplish sustainable urban growth and achieve global carbon neutrality targets, a comprehensive approach involving technical innovation, legislative assistance, and extensive preparation is crucial. [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]

The excessive use of energy from fossil fuels, which corresponds to population, industrialisation, and unsustainable economic growth, is the cause of carbon dioxide production and climate change. The Water–Energy–Food (WEF) nexus is an applicable conceptual framework that helps manage the balance between human development and natural resource constraints, and it becomes a valuable tool to address the challenges of resource depletion and clean energy. This article aims to analyse the relationship between the WEF nexus and clean energy through a statistical analysis and a systematic review of knowledge on energy sustainability. The methodology involves the selection of bibliographic information databases such as Scopus and Web of Science (WoS), a statistical analysis, specifically the Scientometrics applied to the information obtained, and the identification of 179 scientific publications related to the study variables through a screening process called Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The interaction of green energy and sustainability with the WEF nexus has been approached mainly by developed countries such as China (10%), the United States (9.49%), India (7.26%), and Brazil (5.02%). The review of 55 scientific papers identified strategies that balance economic growth and environmental impact, applying clean energy systems (e.g., solar and wind), and the importance of adaptation to the subsystems of the WEF nexus. This study also highlights adaptability to climate change in rural and urban communities. Therefore, it is consistent with the four pillars of sustainable development (Economic: 7 papers, Environmental: 22, Social: 18, and Cultural: 8). This study highlights the following: (a) the importance of the use of renewable energy either in mixed systems and consumption, energy storage, and seeking energy efficiency in systems adapted to diverse environments and (b) the relevance of community participation in the decision-making process for the use of clean energy, such as a strategy for climate change adaptation. [ABSTRACT FROM AUTHOR]

A prerequisite for decreasing the intensification of energy in buildings is to evaluate and understand the influencing factors of building energy performance (BEP). These factors include building envelope features and outdoor climactic conditions, among others. Based on the importance of the influencing factors in the development of the building energy prediction model, various researchers are continuously employing different types of factors based on their popularity in academic literature, without a proper investigation of the most relevant factors, which, in some cases, potentially leads to poor model performance. However, this can be due to the absence of an adequate comprehensive analysis or review of all factors influencing BEP ubiquitously. Therefore, this paper conducts a holistic and comprehensive review of studies that have explored the various factors influencing energy use in residential and commercial buildings. In total, 74 research articles were systematically selected from the Scopus, ScienceDirect, and Institute of Electrical Electronics Engineers (IEEE) databases. Subsequently, by means of a systematic and bibliometric analysis, this paper comprehensively analyzed several important factors influencing BEP. The results reveals the important factors (such as windows and roofs) and engendered or shed light on the application of some energy-efficient strategies such as the utilization of a green roof and photovoltaic (PV) window, among others. [ABSTRACT FROM AUTHOR]

Turning ships in port turning basins is an important and responsible operation, mainly involving the ship itself and the port tugboats. Such operations involve many maneuvers that consume a lot of energy (fuel) and emit a lot of emissions. Turning basins in harbors and quay approaches are, in most cases, relatively shallow. This paper examines the turning of ships in port turning basins using harbor tugboats, the effect of shallow depth on ship turning, energy (fuel) consumption and the generation of emissions during such maneuvers of harbor tugboats. This paper presents the developed theoretical models, and the experimental results on theoretical models that were verified on real ships and using calibrated simulators. Discussions and conclusions were prepared on the basis of the research results. The use of the developed methodology makes it possible to increase shipping safety, optimize maneuvers and reduce energy (fuel) consumption when turning ships in the port and, at the same time, reduce the amount of fuel consumed by port tugboats and reduce the number of emissions of tugboats during such operations. [ABSTRACT FROM AUTHOR]

Sustainable smart cities (SSCs) target decarbonisation by optimising energy consumption through the emerging capabilities of technology. Nevertheless, the energy consumption behaviour of end users has the potential to compromise the effectiveness of technological interventions, reflecting the importance of active social engagement in realising decarbonisation goals. Although extensive research exists on energy consumption behaviour, little is known about how technology engagement affects it, the nature of these technologies, and their role in SSC. The paper aims to identify, categorise, and investigate the smart technologies that impact household energy consumption behaviours and their integration into the larger SSC system. Following a systematic review of 60 articles from the Scopus database (2013–2023), the study found 45 smart technologies cited, with 49% affecting efficiency behaviour and 51% affecting curtailment behaviour. While these technologies inform the city administration level in the SSC framework, the role of end users remains unclear, suggesting a technocratic approach. The study proposes the Sustainable Smart City Network to facilitate a grassroots approach, identifying five key domains: government policies, smart technology adoption, smart technology engagement, smart city infrastructure, and urban sustainability. The study provides an original contribution to knowledge by unveiling the key technologies affecting energy consumption behaviour and outlining the pragmatic requirements for achieving decarbonisation through a grassroots approach. [ABSTRACT FROM AUTHOR]

The paper presents an innovative concept of the fluidization of an adsorption bed carried out under low-pressure conditions. Additionally, different bed mixes were used to test the effects of the bed composition on fluidization. Fluidization was caused by the pressure difference and the velocity of the flowing water vapor. These features make the research presented in this article significantly different from other studies known in the literature and constitute the main novelty of the paper. Silica gel with a particle diameter of 200–250 µm (Geldart group B) with aluminum and carbon nanotube additives was fluidized under reduced pressure (10–25 mbar). The pressure difference results in the flow of water vapor and, consequently, induces fluidization. The pressure in the evaporator was approx. 10 mbar, while in the reaction chamber it was approx. 25 mbar. The pressure difference of about 10–15 mbar allows for a flow of water vapor between the evaporator and the reaction chamber. During the tests, the pressures, temperatures and mass were measured. The pressure drop in the bed was closely related to the mass change in the fluidized bed. [ABSTRACT FROM AUTHOR]

In this paper, the challenges inherent in the development of a decarbonized transportation system are thoroughly examined. Sustainable transportation practices that can contribute to the limitation of greenhouse gas emissions and overall sustainability are identified. Furthermore, the most effective and innovative research avenues being pursued by the research community to enhance transportation sustainability are reviewed and discussed. The review framework has been designed to facilitate the identification of key areas of interest through the implementation of a systematic literature review approach. Firstly, an in-depth analysis is provided concerning the main barriers encountered in the realization of sustainable transportation. These barriers are categorized into five dimensions, namely regulatory, technological, financial, organizational, and social. Subsequently, attention is directed towards the emerging approaches that actively support the implementation of sustainable transportation. Lastly, the primary policy measures intended to promote sustainable mobility are the subject of discussion. The findings unveiled in this paper possess the potential to provide managers and policy makers with a comprehensive understanding of transportation sustainability issues. Furthermore, they carry practical implications that can contribute to the construction of sustainable transportation systems. [ABSTRACT FROM AUTHOR]

Buildings are an important part of worldwide efforts to reduce energy consumption and mitigate greenhouse gas emissions that contribute to climate change. Despite recent technological developments in the area of energy consumption reduction, energy use is on the rise, highlighting the significance of considering occupant behavior with regard to controlling energy consumption and supporting climate resilience. Energy performance of residential buildings is a function of various aspects such as properties of the building envelope, climatic location characteristics, HVAC system, and, more importantly, occupant behavior and activities towards energy utilization. This study carries out a comprehensive review of the impact of occupant behavior on reducing the energy performance gap in residential buildings since residential buildings account for 70% of building floor area around the globe. Findings have revealed that a dearth of literature on occupants' behavior scholarship leads to inaccurate simplifications in building modeling and design. Thus, there is a strong need to obtain appropriate occupant behavioral data to develop strategies to close the energy performance gap as much as possible to achieve better energy efficiency in residential buildings to contribute to resilience and sustainability. Findings have also revealed a lack of objective and subjective data on occupants' behavior towards energy efficiency in residential buildings. In response to these gaps, the current paper has proposed a conceptual framework for occupant behavior toward a modification of thermal comfort to reduce energy use. Based on the findings of this paper, understanding the variety of factors influencing occupants' behavior should be considered a major influential factor in the design and retrofit of residential buildings with a view toward long-term resilience and sustainability. [ABSTRACT FROM AUTHOR]

More energy is consumed by domestic appliances all over the world. By reducing energy consumption, sustainability can be improved in domestic contexts. Several earlier approaches to this problem have provided a conceptual overview of green and smart buildings. This paper aims to provide a better solution for reducing energy consumption by identifying the fields of abnormal energy consumption. It creates a better environment-friendly smart building to adopt the various lifestyles of people. This paper's main objective is to monitor and control the energy efficiency of smart buildings by integrating IoT sensors. This paper mainly analyzes various prime factors that can help to improve energy efficiency in smart buildings. Factors impacting energy consumption are analyzed, and outliers of energy consumption are predicted and optimized to save energy. Various parameters are derived from IoT devices to improve energy efficiency in lighting and HVAC controls, energy monitoring, building envelope and automation systems, and renewable energy. The parameters used in water, network convergence, and electrical and environmental monitoring are also used for improving energy efficiency. This paper uses various IoT devices for monitoring and generating data in and around a smart building and analyzes it by implementing an intelligent Information Communication Technology (ICT) model called the Dynamic Semantic Behavior Data Analysis (DSBDA) Model to analyze data concerning dynamic changes in the environment and user behavior to improve energy efficiency and provide better sustainable lifestyle-based smart buildings. From the analyzed output, the outliers of the power consumption and other abnormalities are identified and controlled manually or automatically to improve sustainability regarding energy use in smart buildings. [ABSTRACT FROM AUTHOR]

The focus of this paper is the relationship between sustainable energy sources and financial development. The main research hypothesis assumes a positive link between these areas, with inevitable differences across countries and business sectors. The following research questions were asked: Is the impact of financial development on sustainable energy resources the same in different EU countries advanced in green transition processes? How is transition towards renewable energy sources progressing in different economic sectors? Does financial development influence sectoral transition in particular countries? This study uses the TOPSIS method and 25 variables for EU countries from 2013 to 2021. Key findings reveal that the link between sustainable energy sources and financial development varies across EU countries, country size affects energy autonomy, and the transition also differs by business sector. Surprisingly, higher financial development correlates with less progress in sustainable energy initiatives. The results of our research may be useful for government decision-makers in the process of designing and controlling the country's transition to sustainable energy. The original contribution of the study is expressed in its the diagnosis of the relationship between financial development and sustainable energy sources, while most studies have focused on the relationship between the energy market and financial development. [ABSTRACT FROM AUTHOR]

Wastewater Treatment Plants (WWTPs) play a crucial role in maintaining ecological balance, a cornerstone of environmental health for thriving biodiversity and undisturbed natural processes. This balance is crucial for the sustainability of ecosystems, directly influencing human health, biodiversity, and the overall quality of our natural environment. WWTPs contribute to this equilibrium by efficiently removing pollutants and harmful substances from wastewater, thus averting the degradation of water bodies that are essential for numerous ecological processes. WWTPs encompass multiple stages of wastewater and sludge treatment and are significant energy consumers globally, especially in secondary treatment, particularly the activated sludge method which is the most common method. With an upcoming directive from the European Union aiming to reduce energy consumption in WWTPs, this paper focuses on a literature review examining global practices implemented across all stages of WWTP treatment processes. It summarizes the key points of each study, focusing primarily on the outcomes of each application. This document concludes with an in-depth review of each study and provides general conclusions for each group of studies. The objective is to identify methods that have effectively reduced energy consumption and enhanced the overall energy efficiency of WWTPs. The main conclusions indicate that the studies encompass a wide range of applications that achieve significant reductions in energy consumption. However, additional testing of these applications in more diverse operating environments through trials could further enhance their reliability and increase acceptance among WWTP operators. [ABSTRACT FROM AUTHOR]

Buildings consume 30% of the total energy consumption around the globe and 29% of the energy consumption in Egypt, which in 2022 had a total population of 102 million, out of which 43% live in urban areas. The operation of buildings contributes to around 30% of global CO2 emissions due to their high energy consumption. Among the efforts made towards improving the energy efficiency of buildings are Advanced Energy Design Guides (AEDGs), building rating systems, codes, and standards. Furthermore, numerous research studies that are either literature review studies, experimental studies, or computational studies addressed the topic of energy efficiency in buildings. In this paper, 124 articles are systematically reviewed with the purpose of identifying the research gap in available research with a focus on Egypt. The identified gap is the development of a prescriptive path for the Egyptian Green Pyramid Rating System (GPRS) energy efficiency category based on whole building energy simulations. Furthermore, recommendations for future research are given based on gaps in the existing literature. [ABSTRACT FROM AUTHOR]

Optimizing path planning for energy efficiency is critical for achieving sustainable vehicular transportation. This paper presents a novel framework for evaluating the impact of path planning algorithms (PPAs) on energy consumption within a simulated environment. We leverage the CARLA simulator to conduct a comparative analysis between the widely used A* and a Hybrid Genetic Algorithm (HGA) across diverse vehicular scenarios. This investigation aims to quantify the influence of PPA selection on vehicle energy expenditure, enabling data-driven optimization for energy minimization. We leverage an offline energy estimation model to further streamline the comparison of the two PPAs. Extensive simulations are employed to demonstrate the efficiency and adaptability of the proposed framework. The findings contribute to the development of energy-efficient path-planning strategies, promoting advancements toward sustainable transportation systems. [ABSTRACT FROM AUTHOR]

In the contemporary era, conventional energy sources like oil, coal, and natural gas overwhelmingly contribute 89.6% to global CO2 emissions, intensifying environmental challenges. Recognizing the urgency of addressing climate concerns, a pivotal shift towards renewable energy, encompassing solar, wind, and biofuels, is crucial for bolstering environmental sustainability. Bioethanol, a globally predominant biofuel, offers a versatile solution, replacing gasoline or integrating into gasoline–ethanol blends while serving as a fundamental building block for various valuable compounds. This review investigates the dynamic landscape of biomass generations, drawing insightful comparisons between the first, second, third, and fourth generations. Amid the drive for sustainability, the deliberate focus on the initial generation of biomass, particularly corn, in bioethanol production is grounded in the current dependence on edible crops. The established utilization of first-generation biomass, exemplified by corn, underscores the necessity for a comprehensive examination of its advantages and challenges, allowing for a nuanced exploration of existing infrastructure and practices. To produce bioethanol from corn feedstock, various milling methods can be employed. Thus, this paper delves into a comparative assessment of dry-milling and wet-milling processes scrutinizing their efficiency, environmental impact, and economic feasibility. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of the potential benefits and feasibility of integrating Building Energy Management Systems (BEMSs) with Building Information Modeling (BIM) in, but not limited to, the construction and building management sectors. By examining advantages, challenges, and real-world case studies, this study offers valuable insights into the impact of BEMS-BIM integration on building operations. The research methodology includes a literature review and bibliometric analysis to understand the subject domain and identify prevalent keywords. Additionally, case studies demonstrate the effectiveness of BEMS-BIM integration in real-world scenarios. This study investigates the possibilities and challenges of BIM to the BEMS methodology for energy-efficient industrial buildings, emphasizing the importance of addressing uncertainties and enhancing software interoperability. This research highlights the potential of BEMS-BIM integration to revolutionize building performance, enhance sustainability, and contribute to a greener and more efficient future for the construction and building management industries. [ABSTRACT FROM AUTHOR]

The scientific community has shown considerable interest in Industry 4.0 due to its capacity to revolutionise the manufacturing sector through digitalisation and data-driven decision-making. However, the actual implementation of Industry 4.0 within complex industrial settings presents obstacles that are typically beyond the scope of mainstream research articles. In this paper, a comprehensive case-study detailing our collaborative partnership with a leading medical device manufacturer is presented. The study traces its evolution from a state of limited digitalisation to the development of a digital intelligence platform that leverages data and machine learning models to enhance operations across a wide range of critical machines and assets. The main business objective was to enhance the energy efficiency of the manufacturing process, thereby improving its sustainability measures while also saving costs. The project encompasses energy modelling and analytics, Fault Detection and Diagnostics (FDD), renewable energy integration and advanced visualisation tools. Together, these components enable informed decision making in the context of energy efficiency. [ABSTRACT FROM AUTHOR]

It is well known that buildings have a sizeable energy and environmental footprint. In particular, in environments like university campuses, the occupants as well as occupancy in shared spaces varies over time. Systems for cooling in such environments that are centrally controlled are typically threshold driven and do not account for occupant feedback and thus are often relying on a reactive approach (fix after identifying problems). Therefore, having a fixed thermal operating set point may not be optimal in such cases—both from an occupant comfort and well-being as well as an energy efficiency perspective. To address this issue, a study was conducted which involved development and deployment of an experimental Internet of Things (IoT) prototype system and an Android application that facilitated people engagement on a university campus located in the UAE which typically exhibits hot climatic conditions. This paper showcases data driven insights obtained from this study, and in particular, how to achieve a balance between the conflicting goals of improving occupant comfort and energy efficiency. Findings from this study underscore the need for regular reassessments and adaptation. The proposed solution is low cost and easy to deploy and has the potential to reap significant savings through a reduction in energy consumption with estimates indicating around 50–100 kWh/day of savings per building and the resulting environmental impact. These findings would appeal to stakeholders who are keen to improve energy efficiency and reduce their operating expenses and environmental footprint in such climatic conditions. Furthermore, collective action from a large number of entities could result in significant impact through this cumulative effect. [ABSTRACT FROM AUTHOR]

Currently, studies on the energy efficiency of manufacturing systems usually lack synthetic and systematic techniques. In this paper, a holistic framework is demonstrated in order to achieve more sustainable manufacturing, which covers machine-level, system-level and life-cycle-level energy efficiency techniques. Based on these, the mechanism of how energy consumption is affected by machining processes and system operation is analyzed to achieve a comprehensive decision on energy efficiency optimization. Four main topics are included in this paper: (1) Hierarchical sustainability goals and metrics for energy-efficient manufacturing; (2) Machine-level machining processes optimization for energy efficiency enhancement; (3) System-level innovations for efficient consumption management; (4) Life-cycle level energy flow modeling and energy recycling strategy. An automotive engine manufacturing system is taken as an example to build a concrete understanding of the application of the framework. Moreover, this holistic framework establishes the theoretical basis for promoting the energy efficiency of automotive engine manufacturing systems. Furthermore, the proposed techniques can provide decision-making support for achieving sustainable manufacturing in a wider scope of mechanical manufacturing. [ABSTRACT FROM AUTHOR]

Buildings represent the largest potential for carbon reduction worldwide. This highlights the need for a simulation and optimization method for energy management. The early design stage of buildings represents an important phase in which choices can be made to optimize design parameters. These parameters can focus on multiple areas, including energy and thermal comfort. This paper introduces the optimization of early-stage sustainable building design considering end-user energy consumption. It proposes an optimization model that integrates multiple layers, which consist of a parametric energy simulation, artificial neural network, and genetic algorithm. The proposed optimization model considers a single objective function to obtain the optimal design. The targeted goal is to obtain minimal energy consumption for residential buildings during the early design stages. Key design parameters of the building were identified for optimization and feasible ranges for them were obtained using genetic algorithms. Finally, the results of this paper include the identification of the optimal building design for the thermal comfort analysis and optimal energy performance. The model was applied to a case study in Egypt and the results showed that using the developed optimization model can lead to a 25% reduction in energy consumption. [ABSTRACT FROM AUTHOR]

Automated machine learning (AutoML), which aims to facilitate the design and optimization of machine-learning models with reduced human effort and expertise, is a research field with significant potential to drive the development of artificial intelligence in science and industry. However, AutoML also poses challenges due to its resource and energy consumption and environmental impact, aspects that have often been overlooked. This paper predominantly centers on the sustainability implications arising from computational processes within the realm of AutoML. Within this study, a proof of concept has been conducted using the widely adopted Scikit-learn library. Energy efficiency metrics have been employed to fine-tune hyperparameters in both Bayesian and random search strategies, with the goal of enhancing the environmental footprint. These findings suggest that AutoML can be rendered more sustainable by thoughtfully considering the energy efficiency of computational processes. The obtained results from the experimentation are promising and align with the framework of Green AI, a paradigm aiming to enhance the ecological footprint of the entire AutoML process. The most suitable proposal for the studied problem, guided by the proposed metrics, has been identified, with potential generalizability to other analogous problems. [ABSTRACT FROM AUTHOR]

The concept of sustainability, with a focus on energy, has emerged as a central tenet in addressing the mounting global challenges of environmental degradation and resource depletion. Indicators of sustainability focusing on energy are crucial tools used to assess and monitor progress toward achieving a more sustainable energy system. These indicators provide valuable insights into the environmental, social, and economic dimensions of energy practices and their long-term impacts. By analyzing and understanding these indicators, policymakers, businesses, and communities can make informed decisions, formulate effective policies, and steer their efforts toward a more sustainable energy future. These indicators serve as navigational guides, steering the world toward energy practices that support both present needs and the well-being of future generations. In this paper, the concept of sustainability and measurement indexes used are reviewed, focusing on energy factors. The focus of the discussion presented here is related to an assessment of the possibilities for improving energy efficiency and evaluating the indicators that are used to measure whether the desired levels of sustainability are being achieved. [ABSTRACT FROM AUTHOR]

In recent years, the importance of energy efficiency in the agricultural sector has become increasingly apparent. As the world faces challenges such as climate change, resource scarcity, and population growth, the need for sustainable and efficient agricultural practices has intensified. Energy plays a crucial role in agricultural production, from powering machinery and irrigation systems to processing and transportation. Therefore, understanding the scientific advancements and collaborative efforts in the field of energy efficiency in agriculture is essential for devising effective strategies, promoting innovation, and achieving global sustainability goals. The aim of this study is to provide insight into and a comprehensive overview of global publications on energy efficiency in agriculture and examine its scientific productivity. The paper explores the research areas and trending topics within the field, as well as the extent of collaboration among authors, institutions, and countries involved in this scientific domain. This investigation is crucial in order to address the current energy shocks and the numerous problems they generate, highlighting the importance of a holistic approach and the need for multiple regions to work together. Only by offering rapid and viable solutions can we effectively overcome this situation. [ABSTRACT FROM AUTHOR]

This article reviews the accomplishments of studies in which optimization tools were used to develop energy-efficient and sustainable construction schedules. With the increase in global awareness of environmental issues, the construction industry has been forced to explore innovative techniques to make the building process more energy-efficient and sustainable. Project managers can use optimization tools in their scheduling procedures to address these issues in the early stages of the project. Therefore, this paper examines different optimization-based construction scheduling methods and their impact on schedule energy efficiency and the three key sustainability goals: economic viability, social equity, and environmental protection. Such a review has not yet been conducted to the best of our knowledge. This research aims to fill the gap and contribute to understanding advanced optimization tools that can pave the way to energy-efficient and sustainable scheduling practices. After a brief introduction, the background of optimization-based construction scheduling techniques that aim to improve construction management and incorporate these aspects into the decision-making process is explained. Then, these approaches are addressed in detail. It is determined for each study whether it adopted energy efficiency goals and which sustainability dimensions it considered within the proposed optimization model. The results of this study indicate a wide heuristic algorithms application for complex scheduling problems. Meanwhile, mathematical programming is still quite unexplored, especially methods that utilize algebraic modeling languages. This study provides a foundation for further research by addressing the current reach in development and possible knowledge gaps that could be researched in future studies. The paper also discusses the advantages and limitations of different approaches and illustrates the potential for utilizing these methods. Supported by the main review findings, conclusions and recommendations for further research are provided. [ABSTRACT FROM AUTHOR]

In this paper, a review of the adoption status of energy efficiency and renewable energy technologies is presented, specific to US residential buildings. Various technologies are reviewed and categorized as either their relative "higher adoption" or "lower adoption" rates within the US housing stock. More importantly, the review analysis investigates the main factors associated with their high or low adoption rates. Specifically, the paper provides a background of the historical progression of energy efficiency programs as well as sustainability certifications and standards for buildings. The review then analyzes specific building energy efficiency and renewable energy technologies applied to US residential buildings and their adoption rates. The review analysis indicates that building technologies are more frequently adopted for multiple reasons including requirements by codes and standards, incentives through green certifications, low implementation costs, and acceptance and popularity by the public. In contrast, technologies with low adoption rates have higher payback periods, are not required or highly incentivized through codes and certifications, have limited promotion about their benefits, or are not compatible with existing systems. By determining the reasons for the high and low adoption rates, mitigation options can be identified to increase the application of sustainable energy technologies in designing and retrofitting buildings. [ABSTRACT FROM AUTHOR]

The rapid growth of sustainability has created a plethora of options for expanding zero-energy buildings (ZEBs) and energy efficiency in all aspects of life. In recent years, there has been a rise in interest in ZEBs, and many countries have adopted ZEBs as future energy targets to promote the sustainable development paradigm. The primary goal of this paper was to conduct a bibliometric review of current research on ZEBs and energy efficiency. The first part of this paper identifies new knowledge gaps as well as practical demands in the field of sustainable development. Furthermore, bibliometric analysis was performed using the Scopus database (i.e., 2592 articles) and a screening process was undertaken, with the result being 252 papers. This study draws attention to a body of knowledge by reviewing trends and patterns, major research topics, journals, countries, new approaches, emerging trends, and future directions for sustainable development. This study is unique in that it provides a comprehensive, updated review of ZEBs and energy efficiency trends. Moreover, this study could help identify limitations for future policymakers, practitioners, and academics. The empirical section of this paper, through a case study, presents an example of a low-energy single-family building located in Poland. [ABSTRACT FROM AUTHOR]

Featured Application: To date, the 'values' associated with 'heritage buildings' have received little attention in designing technical interventions for energy efficiency. This may be due to a fear that modern interventions for improving energy performance clash with heritage conservation, especially conservation of original features. We argue that energy efficiency interventions and heritage conservation can co-exist if an in-depth understanding of people's heritage values and attitudes is obtained. This paper adds to our limited knowledge of residents' approaches to heritage conservation and energy efficiency. It does so by presenting the first study of its kind in Mexico's City Historic Centre (a World Heritage Site since 1987). The results reveal the type of heritage values that residents assigned to their buildings when seeking to achieve thermal comfort and energy efficiency in heritage buildings. With building construction representing one of the largest sectors responsible for the use of natural resources, retrofitting existing heritage buildings becomes a necessity, albeit a challenging one. The emergence of specific guidance on retrofitting heritage buildings has unveiled more than never the need to understand how residents negotiate, thermal comfort, energy efficiency, and heritage conservation decisions. The paper reports the complexity of the decision-making process of residents of heritage buildings in the Historic Centre of Mexico City regarding energy efficiency, intending to improve thermal comfort and reduce energy consumption while preserving heritage values. The study involved in-depth semi-structured interviews with users of heritage buildings that were thematically analysed, complemented by the monitoring of internal environmental conditions and system dynamics analysis. The results show that although the residents perceived the buildings' temperature as poor, passive thermal comfort actions (e.g., wearing more clothes and closing windows) were preferred against invasive retrofitting solutions for thermal comfort due to residents' resistance to a potential loss in the buildings' values and the high cost of changes. The degree of change necessary for maintenance, renovation, and actions for improving the thermal comfort of a heritage building is related to values and to their preservation for future generations. The users' changes were limited to small-scale interventions in floors and ceilings while avoiding touching what they consider essential to preserve and protect (i.e., social and cultural values). Integrating the user into the decision-making process would enhance the long-term continuity and sustainability of retrofitting policies and guidelines, thus avoiding losing heritage-built stock. [ABSTRACT FROM AUTHOR]

The EU's energy transition strategy highlights the significance of developing innovative energy models to encourage the utilization of renewable energy sources in urban areas. Utilizing local urban biomasses, including food waste, sewage, and green waste, can contribute to the establishment of energy systems that harness bio-waste for energy generation, thereby promoting circular economy principles and urban metabolisms. This paper proposes using a pre-design tool (based on soft computing approaches) that incorporates an initial analysis of the multidisciplinary feasibility of such systems as an effective strategy and valuable support for preliminary studies. It focuses on validating three "biomass ratio" parameters, integrating urban morphology and district characteristics with the amount of bio-waste in a peri-urban district comprising multifamily buildings. These parameters can be incorporated into a pre-design tool that facilitates multi-criteria decision analyses, aiding the design of innovative models that promote renewable energy sources in urban areas. The findings suggest that synthetic parameters can guide initial considerations, but they may overestimate the energy potential and should be further investigated. Hence, future research should explore complementary strategies for estimating biomass energy potential and extend the application of this methodology to other types of districts. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of traffic signal control in general intersections by applying a recent reinforcement learning technique. Nowadays, traffic congestion and road usage are increasing significantly as more and more vehicles enter the same infrastructures. New solutions are needed to minimize travel times or maximize the network capacity (throughput). Recent studies embrace machine learning approaches that have the power to aid and optimize the increasing demands. However, most reinforcement learning algorithms fail to be adaptive regarding goal functions. To this end, we provide a novel successor feature-based solution to control a single intersection to optimize the traffic flow, reduce the environmental impact, and promote sustainability. Our method allows for flexibility and adaptability to changing circumstances and goals. It supports changes in preferences during inference, so the behavior of the trained agent (traffic signal controller) can be changed rapidly during the inference time. By introducing the successor features to the domain, we define the basics of successor features, the base reward functions, and the goal preferences of the traffic signal control system. As our main direction, we tackle environmental impact reduction and support prioritized vehicles' commutes. We include an evaluation of how our method achieves a more effective operation considering the environmental impact and how adaptive it is compared to a general Deep-Q-Network solution. Aside from this, standard rule-based and adaptive signal-controlling technologies are compared to our method to show its advances. Furthermore, we perform an ablation analysis on the adaptivity of the agent and demonstrate a consistent level of performance under similar circumstances. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) nodes get deployed for a variety of applications and often need to operate on batteries. This restricts their autonomy and/or can have a major ecological impact. The core idea of this paper is to use a unmanned aerial vehicle (UAV) to provide energy to IoT nodes, and hence prolong their autonomy. In particular, the objective is to perform a comparison of the total energy consumption resulting from UAV-based recharging or battery replacement versus full provisioning at install time or remote RF-based wireless power transfer. To that end, an energy consumption model for a small license-free UAV is derived, and expressions for system efficiencies are formulated. An exploration of design and deployment parameters is performed. Our assessment shows that UAV-based servicing of IoT nodes is by far more beneficial in terms of energy efficiency when nodes at distances further than a few meters are serviced, with the gap increasing to orders of magnitude with the distance. Our numerical results also show that battery swapping from an energy perspective outperforms recharging in the field, as the latter increases hovering time and the energy consumption related to that considerably. The ecological aspects of the proposed methods are further evaluated, e.g., considering toxic materials and e-waste. [ABSTRACT FROM AUTHOR]

The growing demands for food with high quality standards and high nutritional value have caused agriculture to evolve towards agricultural innovation go hand in hand with technological development, as is the case of vertical farming (VF) development. VF is a competitive system for sustainable food production, reducing space, and natural and human resources for agricultural production, and it is a system that can be developed anywhere in the world and at any time, without seasonality being a factor that influences production. Light is the most important factor to consider when it comes to vertical farming, replacing sunlight with artificial light has had great advances in improving productivity, especially when using LED lighting. Despite the exponential growth of the system, there is a paucity of analysis on the research that has been carried out to date using a VF system, and on information on the most relevant parameters to be considered for optimum production. This review is a bibliometric analysis of 318 scientific articles taken from the SCOPUS database, where information from 109 papers published in relevant journals was used. During the last 10 years, the number of publications that have been carried out in a VF system has increased by 195%, with China standing out as the geographical location where field experiments are carried out. Lettuce crop predominates in the investigations, with a light intensity of 200 μmol∙m−2∙s−1 and with a photoperiod of 16 h·day−1, using spectra between 450 and 495 nm, and a combination of blue and red (450–495 and 620–750 nm). The use of the research in the VF system for fresh, quality, local produce has increased in recent years, and has proven to be highly effective in productivity and quality. Conditions and management have been generalized, with more than 50% of researchers deciding to perform this cultivation method with similar photoperiod, spectrum, and intensity. Among the conclusions obtained by each researcher, it is also agreed that it is a potentially sustainable and controllable system that can be developed in urban locations, benefiting the social economy, food security, and the environment, while the conclusions on the cent per cent utilization of natural resources (such as energy from sunlight) in the system remain open and improving. [ABSTRACT FROM AUTHOR]

The aim of this paper was to examine whether the COVID-19 epidemic has slowed the fulfilment of one of the core tasks of the energy sector "Ensure Access to Affordable, Reliable, Sustainable and Modern Energy for All" (SDG7) taking into account corporate social responsibility. Four research questions and hypotheses were posed, relating to the perspectives of local authorities, the activities of large energy companies, the impact of the epidemic on the implementation of the SDG7 and, in addition, to the understanding of CSR principles from the point of view of ordinary entrepreneurs. A qualitative descriptive analysis based on two reliable databases and a survey procedure (Question 4) was used to answer the research questions posed. The goal was achieved by positively confirming three hypotheses and testing one negatively, relating to COVID-19's slowing role in SDG7 implementation. The analysis showed that the 2020–2021 epidemic in Poland has led to more initiatives in this area, contrary to expectations. However, they were linked to the simultaneous implementation of other SDGs, which distorted their importance for achieving Goal 7. In summary, although energy companies were more active than expected during the epidemic, they had a low contribution to SDG 7. This also applies to local authorities. An analysis of the knowledge about CSR in a group of entrepreneurs from the Lublin district (case study) confirmed the opinion appearing in the literature about the lack of understanding of the concept and the need for its application. [ABSTRACT FROM AUTHOR]

The quality of human nutrition has acquired significant improvements thanks to the opportunity to store food in suitable temperature conditions. Refrigeration has allowed the slowing of chemical and biological degradation and hence the waste of foodstuff, but at the same time increases energy consumption. These effects impact the environment and the sustainability performance of the cold chain, and drive consumers' choices. The stakeholders of the chain are, therefore, constantly looking for improvement actions to reduce environmental impacts. This paper aims to provide a methodology for prioritizing and assessing the energy efficiency measures for cold chains in terms of quality losses and specific energy consumption, distinguishing between technological, maintenance, and managerial opportunities. This analysis is based on the cold supply chain tool, developed under the H2020 project ICCEE ("Improving Cold Chain Energy Efficiency") which focuses on a holistic approach, not looking only at the individual stages of the cold chain. Furthermore, an economic evaluation has been proposed considering cost savings and the investment needed. [ABSTRACT FROM AUTHOR]

In this paper, the characteristics of the Excellence in Design for Greater Efficiencies (EDGE) green building certification system in terms of the scope of certification, and environmental and social strategies focused on 6024 units in the 17 EDGE-certified residential buildings in South Africa was investigated. This research analyzed the efficiency of energy, water, embodied energy in materials, and annual CO2 emissions and their contribution to solving housing issues in the given context. This research revealed that the design of EDGE-certified buildings focuses on the "efficiency first" approach and reduced energy and water demand more than on-site energy production. In energy-saving strategies, energy-saving solutions are three times (69.2%) higher than energy-generating solutions (23.1%). The results on resource savings showed that, on average, embodied energy in materials (54%) is the most reduced resource, followed by water (31%) and energy (29.7%). The statistical analysis indicated that there is no statistically significant correlation between energy, water, embodied energy in materials, and CO2 savings with floor areas of the buildings. In addition, this research highlighted how EDGE certification has positively contributed to solving South Africa's resource shortage and affordable housing scarcity problems. [ABSTRACT FROM AUTHOR]

Sustainability improvements in industrial production are essential for tackling climate change and the resulting ecological crisis. In this context, resource efficiency can directly lead to significant advancements in the ecological performance of manufacturing companies. The application of Artificial Intelligence (AI) also plays an increasingly important role. However, the potential influence of AI applications on resource efficiency has not been investigated. Against this background, this article provides an overview of the current AI applications and how they affect resource efficiency. In line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this paper identifies, categorizes, and analyzes seventy papers with a focus on AI tasks, AI methods, business units, and their influence on resource efficiency. Only a minority of papers was found to address resource efficiency as an explicit objective. Subsequently, typical use cases of the identified AI applications are described with a focus on predictive maintenance, production planning, fault detection and predictive quality, as well as the increase in energy efficiency. In general, more research is needed that explicitly considers sustainability in the development and use phase of AI solutions, including Green AI. This paper contributes to research in this field by systematically examining papers and revealing research deficits. Additionally, practitioners are offered the first indications of AI applications increasing resource efficiency. [ABSTRACT FROM AUTHOR]

Room occupancy prediction based on indoor environmental quality may be the breakthrough to ensure energy efficiency and establish an interior ambience tailored to each user. Identifying whether temperature, humidity, lighting, and CO2 levels may be used as efficient predictors of room occupancy accuracy is needed to help designers better utilize the readings and data collected in order to improve interior design, in an effort to better suit users. It also aims to help in energy efficiency and saving in an ever-increasing energy crisis and dangerous levels of climate change. This paper evaluated the accuracy of room occupancy recognition using a dataset with diverse amounts of light, CO2, and humidity. As classification algorithms, K-nearest neighbors (KNN), hybrid Adam optimizer–artificial neural network–back-propagation network (AO–ANN (BP)), and decision trees (DT) were used. Furthermore, this research is based on machine learning interpretability methodologies. Shapley additive explanations (SHAP) improve interpretability by estimating the significance values for each feature for classifiers applied. The results indicate that the KNN performs better than the DT and AO-ANN (BP) classification models have 99.5%. Though the two classifiers are designed to evaluate variations in interpretations, we must ensure that they have accurate detection. The results show that SHAP provides successful implementation following these metrics, with differences detected amongst classifier models that support the assumption that model complexity plays a significant role when predictability is taken into account. [ABSTRACT FROM AUTHOR]

This paper explores and ranks the key performance indicators of multi-criteria decision-making in the process of selecting renewable energy sources (RES). Different categories of factors (e.g., political, legal, technological, economic and financial, sociocultural, and physical) are crucial for the analysis of such projects. In this paper, we apply the fuzzy analytic hierarchy process (fuzzy AHP) method--a mathematical method--in order to analyze the main criteria for such projects, which include the environment, the organizational management structure, project participants, and participants' relationship with the performance indicators. In order of ranking, the indicators are the following: time, costs, quality, monitoring the project's sustainability, user feedback, and users' health and safety. The aim of this paper is to point out the necessity of creating an adjustable model for renewable energy projects in order to proceed with the sustainable development of the southeast part of Serbia. This model should lead the creation process for such a project, with the aim of increasing its energy efficiency. [ABSTRACT FROM AUTHOR]

Currently, sustainability is considered a priority by society, with the household appliances being one of the economic sectors involved in achieving sustainability. However, the existence of several issues (e.g., energy and water consumption, reliability, initial cost, and illuminance, among others) together with the diversity of brands and models on the market, make the consumer's decisions regarding sustainable options difficult, according to their concerns and related to each sustainability dimension (economic, environmental, and social). By combining evolutionary algorithms (EA) with multicriteria techniques, it is possible to achieve sustainable solutions for the consumer based on their requirements. In this paper, a method is presented to support the consumer by obtaining a set of sustainable household appliances on the market that suit their preferences, concerns, and needs. By using a case study to apply the approach developed here, a set of sustainable appliances from the market is obtained, where several benefits are achieved (e.g., energy and water consumption savings, avoidance of CO2 emissions) during the lifecycle of each appliance, chosen from the appliance's industry. [ABSTRACT FROM AUTHOR]

The US manufacturing sector faces critical challenges: improving sustainability, reducing energy consumption, and reducing greenhouse gas emissions. Energy Treasure Hunt (ETH) training, a service provided by the US Department of Energy's Better Plants program, offers a compelling solution. Although ETHs have traditionally focused on energy and cost savings, data indicate that ETHs can be used to identify opportunities to reduce emissions and water use and to support a sustainable and circular operation. These 3-day on-site events engage employees in a collaborative search for operational and maintenance efficiency improvement opportunities. The success of ETHs lies in a comprehensive methodology. Each phase in an ETH uses various tools and resources to empower employees to identify practical solutions. This study presents data from 13 ETHs conducted between 2023 and 2024 across diverse manufacturing subsectors in the United States and demonstrates that the events can help create a pragmatic decarbonization pathway. Through the events, a total of 234 energy and emissions reduction opportunities were identified, and the potential impact is significant. Implementing the recommendations could translate to annual savings of 497,299 MMBtu of energy, 64,374 kgal of water, and 4.85 million tCO2e of emissions. The fiscal savings from the proposed recommendations translate into nearly $5 million annually. This study identifies the opportunities by energy system type and by the specific actions recommended, while also analyzing the identified opportunities, presenting the most established sustainability recommendations. Case studies from participating partners are presented to further demonstrate that ETHs provide a practical and impactful approach to reducing energy consumption, emissions, and operating costs and promote a more sustainable future for the industrial sector. [ABSTRACT FROM AUTHOR]

The energy sector is essential in the transition to a more sustainable future, and renewable energies will play a key role in achieving this. It is also a sector in which the circular economy presents an opportunity for the utilisation of other resources and residual energy flows. This study examines the environmental and social performance of innovative energy technologies (which contribute to the circularity of resources) implemented in a demonstrator site in Luleå (Sweden). The demo-site collected excess heat from a data centre to cogenerate energy, combining the waste heat with fuel cells that use biogas derived from waste, meeting part of its electrical demand and supplying thermal energy to an existing district heating network. Following a cradle-to-gate approach, an environmental and a social life cycle assessment were developed to compare two scenarios: a baseline scenario reflecting current energy supply methods and the WEDISTRICT scenario, which considers the application of different renewable and circular technologies. The findings indicate that transitioning to renewable energy sources significantly reduces environmental impacts in seven of the eight assessed impact categories. Specifically, the study showed a 48% reduction in climate change impact per kWh generated. Additionally, the WEDISTRICT scenario, accounting for avoided burdens, prevented 0.21 kg CO2 eq per kWh auto-consumed. From the social perspective, the WEDISTRICT scenario demonstrated improvement in employment conditions within the worker and local community categories, product satisfaction within the society category, and fair competition within the value chain category. Projects like WEDISTRICT demonstrate the circularity options of the energy sector, the utilisation of resources and residual energy flows, and that these lead to environmental and social improvements throughout the entire life cycle, not just during the operation phase. [ABSTRACT FROM AUTHOR]

Hydrogen mobility embodies a promising solution to address the challenges posed by traditional fossil fuel-based vehicles. The use of hydrogen in small heavy-duty road vehicles based on internal combustion engines (ICEs) may be appealing for two fundamental reasons: Direct electrification seems less promising in heavy-duty transport systems, and fuel cell-based hydrogen vehicle implementation may not proceed at the expected pace due to higher investment costs compared to ICEs. On the other hand, hydrogen combustion is gaining attractiveness and relies on robust and cheap technologies, but it is not the only renewable solution. In this framework, this work presents a methodology to assess the Well-to-Wheel primary energy consumption and CO2 emissions of small heavy-duty vehicles. The methodology is applied in a real case study, namely a passenger coach traveling on a 100 km mission in non-optimized conditions. Therefore, the suitability of hydrogen is compared with standard diesel and other alternative diesel-type fuels (biodiesel and synthetic diesel types). Hydrogen shows competitivity with standard diesel from the point of view of CO2 emission reduction (−29%) while it hides a higher primary energy consumption (+40%) based on the current power-to-hydrogen efficiency declared by electrolyzer manufacturers. Nonetheless, HVO brings the highest benefits both from the point of view of primary energy consumption and emission reduction, namely −35% and 464–634 kgCO2/100km avoided compared to hydrogen. Moreover, the availability of HVO—like other biofuels—does not depend on carbon from CO2 capture and sequestration systems. [ABSTRACT FROM AUTHOR]

Biomimicry applications in different domains, from material science to technology, have proven to be promising in inspiring innovative solutions for present-day challenges. However, biomimetic applications in the built environment face several barriers including the absence of biological knowledge of architects and planners and the lack of an adequate common means to transfer biomimetic concepts into strategies applicable in the urban context. This review aims to create a multidimensional relational database of biomimetic strategies from successful precedent case studies in the built environment across different city systems and on different application scales. To achieve this, a thorough systematic search of the literature was implemented to map relevant biomimetic case studies, which are analyzed to extract biomimetic strategies that proved to be applicable and successful in an urban context. These strategies are then classified and documented in a relational database. This will provide a guide for architects and planners on how to transfer biomimetic strategies to strategies applicable in the urban context, thus bridging the gap of their lack of biological knowledge. The resulting matrix of strategies provides potential strategies across most of the different city systems and scales with few exceptions. This gap will be covered in a future work, currently in progress, to expand the database to include all city systems and scales. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between artificial intelligence (AI), industrial robots, and renewable energy consumption, driven by the rapid technological advancements and widespread adoption of AI tools in various industries. This research aims to evaluate the environmental implications of these technologies, specifically their impact on renewable energy usage. Employing a comprehensive analytical framework, this study utilizes advanced methodologies, including regularization factors, to accurately estimate the effects of these variables. Through a thorough data analysis, the research quantifies how AI and industrial robots influence the shift towards renewable energy sources. The findings reveal that investments in AI significantly enhance renewable energy consumption, as demonstrated by both conventional estimation techniques and those that integrate regularization factors. Conversely, the use of industrial robots is found to have a detrimental effect on renewable energy consumption. These results have important implications for policymakers, industry leaders, and sustainability researchers. This study encourages policymakers and investors to prioritize funding for AI solutions that promote renewable energy adoption, while it advises industry managers to strategically modify their use of industrial robots to reduce their environmental impact. Ultimately, this research lays a critical foundation for future inquiries and policy initiatives aimed at aligning technological advancements with sustainable energy practices. [ABSTRACT FROM AUTHOR]

Energy efficiency is widely recognized as the foundational and most critical strategy for decarbonizing the manufacturing sector. Misconceptions surrounding energy efficiency measures often hinder their widespread adoption. This article aims to debunk five common myths and provides data and resources to help implement efficiency projects faster and more effectively to achieve greater decarbonization. First, the article challenges the myth that organizations have exhausted all possible energy efficiency opportunities by achieving voluntary energy intensity goals or energy performance certification. Second, it also addresses the misconceptions that efficiency projects are capital-intensive, require many qualified specialists, and have long investment return periods. By presenting real-world case studies and referencing commonly found efficiency opportunities, the article illustrates that energy-savings opportunities are ubiquitous. Organizations can use various contracting mechanisms as well as financial and technical resources from utility companies and government programs to lessen their burden. The notion that efficiency measures can be implemented solely in proprietorship facilities is dispelled. This article emphasizes the importance of green leases and explains that aligning decarbonization goals between the lessor and lessee can help drive savings for both parties. Finally, using unbundled renewable energy certificates as the sole pathway to decarbonization is strongly discouraged. By debunking these prevalent myths, this article aims to foster a deeper understanding of energy efficiency's potential as a cornerstone of decarbonization efforts and to embrace it as a critical pathway toward a sustainable future. [ABSTRACT FROM AUTHOR]

This comprehensive systematic review explores the multifaceted impacts of electric vehicle (EV) adoption across technological, environmental, organizational, and policy dimensions. Drawing from 88 peer-reviewed articles, the study addresses a critical gap in the existing literature, which often isolates the impact of EV adoption without considering holistic effects. Technological advancements include innovations in the battery technology and energy storage systems, enhancing EV performance and mitigating range anxiety. The environmental analysis reveals substantial reductions in greenhouse gas emissions, with lifecycle assessments showing significant reductions for EVs compared to internal combustion engine vehicles, particularly when charged with renewable energy sources. Key comparisons include lifecycle emissions between mid-size battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs), and global average lifecycle emissions by powertrain under various policy scenarios. The organizational implications are evident, as businesses adopt new models for fleet management and logistics, leveraging EVs for operational efficiency and sustainability. Policy analysis underscores the crucial role of government incentives, regulatory measures, and infrastructure investments in accelerating EV adoption. The review identifies future research areas such as efficient battery recycling methods, the potential impact of EVs on grid stability, and long-term economic implications. This study offers insights for stakeholders aiming to foster sustainable transportation and achieve global climate goals. [ABSTRACT FROM AUTHOR]

Oil refineries play a crucial role in meeting global energy demands, and optimizing the efficiency of critical processes is vital for economic feasibility and environmental sustainability. Simulation is an essential tool for the optimization of valuable products. This work presents the rigorous simulation of a vacuum distillation unit (VDU) based on actual data from the vacuum distillation processes using Aspen HYSYS V10. The Peng–Robinson fluid package is used in this simulation, and an input assay with a standard density of 29 API_60 (879.8 kg/m3) is employed. True boiling point (TBP) assay data are the type that is being used. Methane, ethane, propane, i-Butane, n-Butane, i-Pentane, and n-Pentane are the components listed in the simulation. The research determines that achieving a yield capacity of 685 tons/h requires thirty stages in the atmospheric distillation unit and twelve stages in the vacuum distillation unit while operating at 420 °C temperature and 9 kPa pressure. Adjustments in the flash section temperature (FST) and steam flow rate (SFR) are proposed to enhance operational efficiency. Increasing the FST from 370 °C to 400 °C and adjusting SFR from 10 tons/h to 26 tons/h increases the Light Vacuum Gas Oil (LVGO) yield by 7.2% while elevating the FST from 400 °C to 430 °C and adjusting SFR from 10 tons/h to 26 tons/h enhances the High Vacuum Gas Oil (HVGO) yield by 7.4%. These optimization strategies offer a practical and effective approach for refineries to improve the economic benefits of vacuum distillation units. The implications of this research can act as a computational thinking exercise for higher education students considering the case study where only through changing the operational strategies can the yield be enhanced by 10.81% in the vacuum distillation unit of the oil refinery. [ABSTRACT FROM AUTHOR]

The pursuit of energy efficiency in machining processes is a critical aspect of sustainable manufacturing. A significant portion of global energy consumption is by the industrial sector; thus, improving the energy efficiency of machining processes can lead to substantial environmental and economic benefits. The present study reviews the recent advancement made for improving the energy efficiency of machining processes. First the energy consumption of the machining processes was explored and then the key areas and developments in their energy consumption modeling were identified. Following this, the review explores various strategies for achieving energy savings in machining. These strategies include energy-efficient machine tools, the accurate modeling of the energy consumption of machining processes, the implementation of optimization techniques and the application of artificial intelligence (AI). Additionally, the review highlights the potential of AI in further reducing energy consumption within machining operations and achieving energy efficiency. A review of these energy-saving strategies in machining processes reveals impressive potential for significant reductions in energy consumption: energy-efficient design can achieve up to a 45% reduction, optimizing cutting parameters may minimize consumption by around 40%, optimizing tool paths can reduce consumption by approximately 50%, optimizing non-cutting energy consumption and sequencing can lead to savings of about 30% and employing AI shows promising energy efficiency improvements of around 20%. Overall, the present review offers valuable insights into recent advancements in making machining processes more energy-efficient. It identifies key areas where significant energy savings can be achieved. [ABSTRACT FROM AUTHOR]

The energy design of museums in developing countries is a subject that has been poorly studied, despite its significant implications for heritage preservation, human comfort, energy efficiency, and environmental sustainability. This study introduces a comprehensive framework of Energy Performance Indicators tailored to air-conditioned museums in tropical regions, which represent the most prevalent museum type. These indicators are particularly important as international standards may not be applicable in these contexts. A comprehensive review of the factors and their design implications is provided at the building, system, and component levels. Efficient integration of lighting and air conditioning systems can optimize energy use while maintaining appropriate conditions for both artefact preservation and visitor comfort. Parameters such as average illuminance, uniformity of lighting, lighting power density and lighting energy use intensity are critical in balancing visual quality and energy efficiency. Recommended values and strategies, such as the use of LED lighting and daylight harvesting, help to minimize energy consumption. In addition, parameters such as power density and energy use intensity of air conditioning systems are essential for assessing their efficiency. Techniques such as the integration of solar-assisted, optimized performance indices can effectively reduce energy consumption. Synthetic indicators for assessing lighting quality and overall energy performance are (i) Average Illuminance Ratio, which assesses the adequacy of lighting in a space by comparing the average measured illuminance with the recommended illuminance levels for that space, and (ii) Energy Use Intensity, which represents the total annual energy consumption per unit area of conditioned space. By adopting these indicators, tropical museums can advance energy efficiency and broader sustainability objectives, taking a significant step towards a more energy-conscious and sustainable future. [ABSTRACT FROM AUTHOR]