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Aerogels, with their exceptional properties such as high insulation performance, lightness, and eco-friendliness, present immense potential for use in the construction industry. This paper reviews the progress in research and application of various types of aerogels in construction, highlighting notable case studies demonstrating energy efficiency gains and sustainability impacts. It delves into the lifecycle of aerogels, discussing environmental implications at each stage. Despite their potential, aerogels face certain limitations including production complexity, brittleness, and high cost which hinder their widespread adoption. The paper further discusses these challenges and highlights the need for continuous research and development efforts to overcome them, with a view to achieving more scalable production, enhanced mechanical properties, and cost reduction. Looking forward, the paper discusses the expansive horizon of aerogel research, emphasizing the potential of smart aerogels, their integration with renewable energy systems, and exploring the possibility of recycling or creating bio-based aerogels to enhance their overall sustainability. While still in early stages, aerogels promise to be a major contributor to the future of construction, leading to more sustainable and efficient built environments. [ABSTRACT FROM AUTHOR]

Measuring the sustainability performance of an organisation is a rather complex task. This study aims at analysing a broad number of performance indicators related to the economic, environmental, and social pillars of the Triple Bottom Line (TBL) framework and evaluates their applicability toward the development of a sustainable performance measurement system (SPMS) of projects. To this purpose, an analysis of the annual sustainability reports of the listed EURO STOXX Sustainability 40 companies was conducted, identifying the sustainability indicators incorporated in each individual report, and classifying them according to the three pillars of the TBL framework. The analysis of the reports yielded 67 economic indicators, 109 environmental, 130 social, and 38 additional ones, mainly combining the latter two categories, giving 344 unique indicators in total. The proposed system, based on empirical evidence, recommends that selected indicators for an SPMS for projects should relate to predefined subcategories. These are costs, efficiency, and shareholder return for the economic dimension; emissions, energy, paper, resource consumption, waste, and water for the environmental dimension; diversity & equality, ethical behaviour, external commitment, health & safety, training & development, and working conditions for the social dimension. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, achieving both energy efficiency and robust security in Cyber-Physical Systems (CPSs) presents a significant challenge because of the resource requirements and complexity of these systems. This paper presents a novel method to integrate energy efficiency and robust security measures in CPSs. We propose the integration of anomaly detection techniques into the CPSs, to facilitate self-adaptation to changing conditions and threats, thereby enhancing system flexibility and reliability while also optimizing energy consumption. Our approach enhances the flexibility and reliability of CPSs by integrating Deep Reinforcement Learning (DRL) into the MAPE-K (Monitor-Analyze-Plan-Execute with Knowledge) control loop. This integration not only streamlines anomaly detection but also optimizes energy consumption, ensuring efficient and effective management of critical system functions. The outcome is a marked improvement in the adaptive decision-making capabilities of CPSs, leading to heightened security and better energy efficiency across various sectors and applications. This study significantly advances sustainable industrial practices within the Industry 4.0 paradigm, emphasizing the development of CPSs that excel in both energy efficiency and robust security. [ABSTRACT FROM AUTHOR]

Museums environment is complicated and defined by indoor air quality, thermal and lighting comfort. Artifacts deterioration is factored by extreme conditions of thermal exposure or excessive lighting. With high control required for exposed old monuments and visitor comfort, museums energy systems reach extreme levels. In this paper, we aim to find the gap in museums high energy loads and reach solutions through architectural design. The paper studies comparison results for different techniques in fifty recent case studies to identify the specific factors that matter most to museum buildings. These factors are implemented simultaneously on one base model in three climatic states by multi-objective optimization. The best option will showcase each climate optimum conditions. The paper introduces optimum architectural procedures optimizing sDA and ASE to minimum 70% and maximum 10% respectively while decreasing thermal load. The results help architects and policy makers achieve daylighting and energy optimization in museums through architecture. [ABSTRACT FROM AUTHOR]

Recently, the widespread adoption of artificial intelligence, particularly generative AI technology, has surged across various industries. However, a notable drawback of this technology is its significant energy consumption during model training and operation, which poses challenges to sustainability goals and the environment. Consequently, various initiatives have emerged to promote what is termed "green artificial intelligence," aiming to mitigate these environmental impacts. Nevertheless, research discussing these initiatives remains scarce. Hence, this study aims to identify green artificial intelligence initiatives that contribute to environmental friendliness. This paper has comprehensively reviewed the existing literature, professional websites, and expert blogs to identify and analyze available green AI initiatives. This paper has identified 55 such initiatives, broadly categorized into six themes: cloud optimization, model efficiency, carbon footprinting, sustainability-focused AI development, open-source initiatives, and green AI research and community. This study discusses the strengths and limitations of each initiative to offer a comprehensive overview. The findings provide valuable insights, particularly for industries interested in green artificial intelligence and green technology in general. While some tools have been recognized and studied, comprehensive research and analysis are still required to empirically evaluate the majority of other tools due to their early stages of development in this field. • Study explores the growing awareness and concern about environmental impact of AI. • It investigates development of tools and approaches to address Green AI. • Significance of collaboration, open-source initiatives, in Green AI development. • Examine importance of ethical considerations in green AI development. • Provide insights for industries in green AI and green technology in general. [ABSTRACT FROM AUTHOR]

Extant research has highlighted the pros and cons of the use of (a) competition and (b) positive (peer) pressure as two mechanisms for invoking peer effects to bring about long-term behavior change. However, these mechanisms have been studied separately and in different contexts. In this paper, we compare the differential impacts of competition versus positive pressure-induced pro-environmental behavior change in the same target population. This study spans a seven-year horizon between 2013 and 2019 (pre-COVID) during which the workforce of about 2500 employees in the Stephan P. Clark Government Center in Miami, Florida, was split into four groups - one control and three treatment groups. Each treatment group was subjected to (a) a healthy inter-group competition through tracking, benchmarking, and comparing monthly group level electricity saving, and (b) positive pressure through the appointment of champions who encouraged pro-environmental behavior among their group members. Studying these mechanisms concurrently in the same population allows for a nuanced comparison of their differential impacts on pro-environmental behavior change. • In this paper, we compare the differential impacts of competition-induced spillover and supervision-induced peer pressure in affecting pro-environmental behavior change in the same target over a seven-year analysis horizon. • The study spans 2013-2019 during which the workforce of about 2500 employees in a building was split into four groups (one control and three treatment) and was subjected to both peer pressure and healthy competition. • The study spans 2013-2019 during which the workforce of about 2500 employees in a building was split into four groups (one control and three treatment) and was subjected to both peer pressure and healthy competition. • These results have implications for the design of pro-environment campaigns that could leverage peer effects through fostering an environment of intragroup pride and healthy inter-group rivalry sprinkled with intermittent supervisory interventions for making long-term impacts. [ABSTRACT FROM AUTHOR]

This study investigates the impact of human activities on environmental degradation, focusing on the roles of urbanization, economic growth, energy intensity and renewable energy within the STIRPAT framework. To this end, the study adopts the ecological footprint (EF) as the environmental indicator. Employing Panel Quantile Regression, the study analyzes data from 31 OECD countries spanning the period 2000–2021. The findings reveal that renewable energy consumption and urbanization exert significant negative influences on the EF, with urbanization proving more effective than renewable energy usage across all quantiles. Both economic growth and energy intensity contribute to environmental degradation, and the impact on the EF escalates with higher quantiles. Additionally, the causality test results demonstrate a two-way causal link among urbanization, economic growth, energy intensity, renewable energy use, and EF. Finally, based on the empirical results, this paper suggests that an energy revolution should be carried out to promote the sustainable use of energy. Meanwhile, the high-level urbanization is suggested to reduce the EF through the aggregation of living production to achieve sustainable development. [Display omitted] • Sustainable use of energy can help curb environmental degradation. • Urbanization more effective than renewable energy consumption in suppressing EF. • Economic growth inhibits environmental quality. • This study employed the quantile regression method. [ABSTRACT FROM AUTHOR]

This research addresses the critical necessity for energy-efficient solutions in port operations. The primary objective of this paper is to introduce and assess the viability of an innovative infrastructure termed Underground Reefer Container Storage (URCS) devised to mitigate the significant and increasing energy demand posed by reefer containers in ports. This study employs a discrete-event simulation (DES) model to evaluate the feasibility, environmental implications, and cost-effectiveness of three distinctive URCS infrastructure designs. These designs are compared against conventional storage methods to ascertain their capacity for minimizing energy usage and greenhouse gas emissions. The analysis reveals that the best scenario for a specific case study involves a multi-block layout comprising two underground yards, capable of accommodating 39% of the overall refrigerated container capacity at a port. This layout cuts CO 2 emissions by 61% from the 2.704 GWh/year energy used by refrigerated containers, yielding around 1.4 million USD/year cost savings. Further analyses using weighted searches to prioritize URCS container slotting led to shorter container dwell times at ports, rendering energy savings 23% higher than in similar unplanned settings. Moreover, this study presents URCS as an eco-friendly alternative for port-based reefer container storage, offering practical alignment with sustainability goals and regulations. The innovative design and its successful application provide holistic insights, paving the way for enhanced port energy management and environmental care. In addition, the implementation of URCS has the potential to reshape port procedures, yielding economic and ecological benefits. This initiative contributes to diminishing the carbon footprint of ports, aligning with global endeavors towards greener and more responsible practices. [Display omitted] • Conventional stacking at ports consumes high energy for reefer containers, risking the cold chain. • Underground reefer container storage (URCS) reduces heat exchange by storing reefers in a colder underground deposit. • Multi-level block storage is preferred in URCS, according to a multi-criteria assessment. • Simulation recommends energy savings with proper stacking in multi-level block storage. • URCS enables environmentally responsible port operations, improving standards feasibly. [ABSTRACT FROM AUTHOR]

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

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

This paper explores the viability of utilizing agricultural biomass-based energy potential, employing mathematical, engineering, and economic modeling techniques. Moreover, the potential of a biogas-based co-digestion (CD) system, integrating its techno-economic performance and environmental sustainability in terms of electricity generation, has also been studied. In this investigation, the categorization of 25 different plant species into two groups: arable field crops (AFCs) and horticultural plants (HPs), was performed. Data was collected during the 2021‐–2022 cropping season in Bangladesh from various sources, including literature reviews, governmental, and non-governmental organizations. The findings revealed that the available agricultural biomass residues, totaling 1,02,585.75 KT, have the capacity to generate 1,33,815 million m3/year of biogas. This energy potential corresponds to 291,125.85 TJ/year or 9231.60 MW of electricity, which can fulfill 88% of the national total energy demand. In terms of levelized cost, the proposed approach is more competitive and shows a greater promise compared to other technologies. Furthermore, it demonstrates environmental friendliness by reducing CO 2 emissions by 156 tons at a cost of $7/ton while earning $1092 annually from the potential carbon-credit market. This approach presents a potential solution to address Bangladesh's energy crisis. The payback period of the system ranged from 2.93 to 3.75 years, with and without the inclusion of a slurry, respectively. The recommended methods hold significant promise for meeting national energy demands. A case study was provided as a proof-of-concept (PoC) to validate the approach. This study is the first of its kind, providing valuable insights into the renewable energy potential in Bangladesh. The results will assist policymakers in formulating sustainable energy policies. • Mathematics, engineering, economics and environmental modeling explored renewable energy. • Techno-economics and environmental sustainability validated the proposed methodology. • Bioenergy-based electricity could supply 88% of the national energy demand of Bangladesh. • A case study was provided as a proof-of-concept (PoC) to validate the approach. [ABSTRACT FROM AUTHOR]

The evaluation of urban energy internet (UEI) is crucial for the establishment of low-carbon cities. This paper aims to present a hybrid decision-making framework to address UEI evaluation problems from a sustainability perspective. First, the Fermatean fuzzy Aczel-Alsina power aggregation operators are proposed to aggregate evaluation information, and the remarkable properties of these operators are explored. Then, the combined weight of the criteria is determined through the decision-making trial and evaluation laboratory method and the Shannon entropy-based power weighted method within the Fermatean fuzzy circumstance. Moreover, the classic multiobjective optimization by ratio analysis plus the full multiplicative form method is extended using the proposed aggregation operators. Finally, an index system was constructed from a sustainability perspective, and the level of development of the four UEI projects is assessed using the proposed method. The experimental results demonstrate that the proposed method can provide beneficial guidelines for the construction and development of the UEI. Furthermore, the reliability and effectiveness of the proposed decision-making framework are validated through sensitivity analysis and a comparative study with existing MCDM methods. [ABSTRACT FROM AUTHOR]

• Urgent sustainable alcohol production via a photoelectrochemical pathway is studied. • MXene-modified graphene enhances light absorption and expands graphene surface. • Synthesized nanohybrid enables efficient production of methanol and formic acid. • Synergy between MXene and graphene improves charge transfer and utilization. • Results hold promise for ambient alcohol production via methane conversion. In the pursuit of efficient ambient methane (CH 4) conversion, we introduce a novel MXene combining with a nitrogen-doped graphene (MX@NG) hybrid as a photoelectrocatalyst for CH 4 oxidation under ambient conditions with light and external bias. Through electrostatic assembly, graphene nanosheets are incorporated between MXene sheets, effectively preventing MXene nanosheet restacking and increasing interlayer spacing. This enhances ion diffusion of electrolyte, increasing access to electroactive sites. Using Ti 3 CN as MXene and nitrogen-doped graphene (NG) as catalyst supports, our research demonstrates the superior performance of the MX@NG composite over pure NG and MXene for methane oxidation. After a 4-hour reaction with a 2 × 2 cm2, 10 mg sample-loaded carbon paper, it produces 17 µmol/ml of CH 3 OH and 14.5 µmol/ml of HCOOH at 0.8 V vs. Ag/AgCl. This enhanced performance results from the synergy between MXene and graphene, improving charge transfer and promoting efficient utilization of photoexcited charges. Additionally, excellent electrical conductivity of NG facilitates the transfer of photo-generated electrons to surface reaction sites, promoting free radical formation. The incorporation of MXene extends visible light absorption and improves charge separation, thereby enhancing solar energy utilization. Overall, this study highlights the potential of MX@NG composite in solar light-based electrocatalytic methane oxidation. [ABSTRACT FROM AUTHOR]

Soil contamination is a growing concern for sustainable development worldwide. Conventional remediation approaches, such as using ordinary Portland cement (OPC) or lime are limited due to high CO 2 emissions, energy consumption, and natural resource consumption. This paper proposes a sustainable method using CO 2 and a waste from steel production (ladle slag, LS) for rapid remediation of Cr and Zn-contaminated soils. Contaminated soils spiked by Cr and Zn with various initial concentrations were treated with 10% LS and subjected to conventional and CO 2 curing for different periods. The results demonstrated that LS with conventional curing could reduce leaching concentrations of Cr and Zn in contaminated soils. However, it necessitated 28 days to meet the criteria of inert waste and drinking water standards. In contrast, LS with CO 2 curing required significantly less time (32 h for Cr and 8 h for Zn) to achieve lower leaching concentrations of Cr and Zn than those with 28-day conventional curing. After CO 2 curing for 152 h for Cr- and 80–120 h for Zn-contaminated soils, leaching concentrations of Cr and Zn were 1.5–4 times and 6–72 times lower than those with 28-day conventional curing, respectively. Simultaneously, carbon capture was increased from 10.6% to 17.5% and 19.9%, respectively, with the initial Cr and Zn concentrations increased from 0 to 8000 mg/kg. The strength of Cr- and Zn-contaminated soils with CO 2 curing also effectively enhanced up to around 3.3–3.6 times and 1.3–3.3 times higher than those with 28-day conventional curing, respectively. [Display omitted] • Chromium (Cr) and zinc (Zn) are rapidly immobilized in soil by ladle slag and CO 2. • CO 2 is rapidly sequestered and chemically stored. • Strength of contaminated soils are enhanced. • Binder cost, LS landfilling, and use of nature resources and energy are reduced. [ABSTRACT FROM AUTHOR]

[Display omitted] • Identifying recent developments in thermal-driven dehumidification technologies. • Evaluating critical characteristics including dehumidification efficiency, energy consumption and cost. • Assessing the desiccant properties for thermal driven dehumidification technologies. • Directing future research to address environmental concerns via innovative sustainable humidity control mechanisms. As we navigate an era marked by significant environmental concerns and technological advancements, the search for energy-efficient and ecological friendly solutions is more critical than ever. One area of growing significance is the control of indoor humidity levels, which not only impacts human comfort and health but also the structural integrity and air quality within buildings. The challenge is to control these levels while lessening energy consumption and environmental impact. A feasible solution lies in the use of thermal-driven dehumidifiers, a promising technology that offers a sustainable approach to humidity control. Thermal-driven dehumidifiers have emerged as promising solutions for humidity control in various applications, owing to their energy-saving and eco-friendly features. Thus, the focus of this review paper is to explore the most recent advancements and enhancements in thermal-driven dehumidification technologies. This includes systems based on solid desiccant, liquid desiccant, and thermoelectricity. The study aims to fill the existing literature gaps, providing a thorough analysis of the current state of these technologies, their performance indicators, and their potential for future development. The study also explores the suitability of these technologies for different ambient conditions and humidity loads. It addresses critical characteristics such as dehumidification efficiency, cooling capacity, regeneration heat, and energy consumption. Each technology is thoroughly examined, including its suitability for various ambient conditions and humidity load scenarios. Specific real-world examples are examined to highlight these technologies' practical importance and possible influence in tackling humidity management concerns. [ABSTRACT FROM AUTHOR]

Given the significant energy consumption and carbon emissions associated with buildings, there is increasing interest in improving sustainability of building operations to reduce impact on climate change. A common goal is to operate buildings as "net-zero" energy users in which all energy consumed by the building is balanced against renewable energy purchased from the grid or produced on site. To achieve net-zero status, many buildings will require significant retrofit so as to both reduce energy consumption in the absolute sense and provide the remainder without consuming fossil fuels. Thus, multi-year planning is required to ensure that goals can be met on time. In addition, due to the inherent uncertainty associated with energy consumption and generation, actually achieving net-zero energy use may require discretionary curtailment actions to be taken, and deciding whether such actions are necessary can be challenging. To address these challenges, we propose in this paper a design optimization and operational planning strategy to make the decisions needed to achieve sustainability goals in buildings. The strategy can be applied to schedule design changes over a long horizon to meet annual targets, and it can also be applied in closed loop on a shorter horizon to determine whether curtailment is needed to stay on track. We discuss the formulation of the optimization problem, solution methods, and modeling approaches for key parameters. Application of the strategy is illustrated via examples. Overall, this approach will help automate planning that is often done manually, allowing buildings to take a significant leap forward toward achieving their sustainability goals. • Achieving sustainability goals in buildings requires multi-year planning. • The required design and operational decisions can be made via optimization. • Key problem parameters can be obtained from data-driven modeling. • The strategy allows sustainability goals to be met at minimum cost. [ABSTRACT FROM AUTHOR]

Degrowth and post-growth economics has emerged as a particularly fruitful approach in the debates about the reorientation of economies in the Global North towards environmental sustainability, equality, need satisfaction and democracy. This perspective promotes a planned reduction of energy and resource use in the Global North to limit environmental pressures and global inequalities and improving well-being. Yet, the specifics of this "design" are not precisely delineated. On the one hand, there is a wide acceptance, at the abstract, most general, even definitional level, that degrowth involves planning or amounts to a planned transition. On the other hand, there is strikingly little explicit engagement with, debate on, and research into what exactly "planning beyond growth" could look like. This gap urgently needs to be addressed. By exploring the degrowth-planning nexus, this paper seeks to lay a foundation for this effort. First, it identifies in the degrowth/postgrowth literature the obstacles and the opportunities for further engagement with planning. Second, it advances an agenda-setting framework, delineating problems relative to democratic ecological planning beyond growth along three axis: elaboration, implementation and multilevel dynamics. • Laying the ground for an engagement between research on democratic planning and degrowth/postgrowth. • Identifying the obstacles to a more substantial engagement with debates on planning in the degrowth/postgrowth literature. • Delineating the key requirements and challenges for democratic planning beyond growth. • Advancing a bridging framework from the current economic institutional setting towards planning beyond growth. [ABSTRACT FROM AUTHOR]

[Display omitted] • Energy-Water-Food security nexus of mung bean production in Iran is analyzed. • Non-renewable cumulative energy demand is estimated at 27.4 MJ/kg of beans. • Total water footprint is estimated at 1.55 m3/kg of beans. • On-farm production concentrates the largest environmental impacts (40% to 96%). • Cooking accumulates over 50% of the carbon footprint. Mung bean is a very important crop in Iran in both socio-economic and nutritional terms. However, although discussions on food and food security increasingly include sustainability issues, there are no precedents in academic literature that analyze in depth the nexus between energy, water use and food security in relation to this crop in Iran from an agri-food system approach. Therefore, our main objective is to assess the energy-water-food security (EWFs) nexus and the environmental impact of mung bean production in Iran from a "cradle to fork" approach using different nutritional units (1 kg of beans, 1 kg of proteins, and 1000 kcal) and load allocation criteria. In addition, an economic analysis of the farms is carried out. The results show that the on-farm production of mung beans is the phase where the largest environmental impacts are concentrated (between 40 % and 96 % of them, including those related to water and energy use), while cooking accounts for more than 50 % of the carbon footprint. The non-renewable cumulative energy demand (NR CED) and total water footprint (TWF) per kilogram of beans ("cradle to fork") is estimated at 27.4 MJ and 1.55 m3 and the farm Net Margin (NM) is estimated at 3,677 USD per ha. The paper discusses whether mung bean is a low-impact option for protein production, especially when compared to animal products and the importance of using different functional units and load allocation criteria to address the issue of EWFs and sustainability. In this regard, further research is needed to improve the environmental efficiency of bean production, which is critical for promoting sustainable diets in line with food security goals. [ABSTRACT FROM AUTHOR]