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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]

Implementing sustainable or green strategies in warehouse management has become increasingly important. The environmental impact can be assessed by evaluating resource usage and productivity. A proper method for assessing the sustainability of internal processes can provide a valuable tool for companies to understand what is being done correctly and what needs to be improved to comply with new guidelines. For this paper, a case study at Arvato warehousing provider for end consumer products was conducted, and a rating mechanism model for warehouses was developed. Data on energy consumption and productivity were collected from output of 13 warehouse units (modules). From the collected data, a set of KPIs, an index system, an automation categorization system, and a ranking system were created to help with decision making, problem identification, and solving. As result, this paper demonstrates the impact of different material handling systems on energy consumption and found that a higher level of automation does not always translate into operating more efficiently in terms of sustainability. Instead of reporting absolute numbers, this study created an index that displays relative values, making it much easier to identify the most efficient modules. Additionally, this study takes the automation index a step further by creating three categories of automation levels in addition to the percentage that indicates how advanced the technology in a warehouse is, allowing for the creation of groups of warehouses and the comparison of their performance. • Increased automation does not always translate into sustainable operational efficiency. • In general, warehouse units employing less technology perform worse. • Supply chain transparency can increase by grouping and scoring warehouses efficiency. • Electricity and productivity index enable measuring environmental impact. • Energy performance and productivity are related at various levels of automation. [ABSTRACT FROM AUTHOR]

Environmental issues have become global challenges, so seeking an economic model to reach environmental sustainability is essential. As an emerging economic model, green finance is considered the most effective tool in promoting low-carbon economic transition. China, the largest economy among developing countries, faces environmental inferiority and increasing energy demand. This paper aims to discuss the effects of green finance on the low-carbon economic transition. This paper makes the policy of green financial reform and innovation pilot zones a quasi-natural experiment. It employs difference-in-differences (DID) model to analyze the impact of green finance on the low-carbon economic transition. This paper found that the low-carbon economic transition achieved good results within experimental zones after establishing a pilot zone for green finance reform and innovation. Furthermore, the parallel trend test results, complicatedly disturbing facts mitigating provincial differences, and placebo tests are still valid. Finally, we found that low-carbon economic transition solely takes effect significantly in eastern and central areas but is not significant in western areas. The paper suggests that green finance has played an apparent role in promoting low-carbon economic transition and provides essential reference and experimental evidence for future economic transition after analyzing the pilot zone for green finance reform and innovation policy. • Green finance is a crucial tool for achieving low-carbon economic transition. • Eastern and middle regions experienced significant effects. • The study provides valuable experimental evidence for future economic transition. [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]

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]

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

The 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]

[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]

Alternative fuels are the subject of growing interest among both researchers and practitioners. In this aspect, to properly handle the problem of proper evaluating alternative fuels, appropriate methods, and tools are undoubtedly needed. Since the evaluation of sustainable alternative fuels similarly, like most sustainability problems, has a multi-criteria character, multi-criteria methods have the potential to be employed here. Analysis of the alternative fuels domain indicates that classical multi-criteria methods are not exactly suitable for use in cases where, instead of a single matrix for evaluating alternatives, we have a set of them collected for particular periods. Therefore, developing a dedicated approach that considers the specifics of a given problem is necessary. For this purpose, the paper proposes a new Temporal Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) method for multi-criteria temporal evaluation. Hence, the presented method solves the limitations occurring in previously developed multi-criteria methods. In addition to the classical aspect of evaluating the options under consideration, the proposed method makes it possible to accurately grasp the dynamics of the outcomes and put them into an easy-to-interpret result. A practical contribution of the paper is applying the developed method to a multi-criteria temporal evaluation of sustainable consumption of alternative fuels in road transport. For this purpose, an assessment model was built based on the data for 32 European countries acquired from the European Union's statistical office (Eurostat). Preference imprecision modeling and model sensitivity analysis demonstrated the analytical potential of the developed sustainability assessment model and, simultaneously, the Temporal PROMETHEE method's superiority. The comparative analysis of the Temporal PROMETHEE II method clearly shows that the results are robust and reliable, and the developed method is suitable for evaluating various temporal sustainability problems. The research demonstrated that a model alternative fuel mix and its shape as well as progression is maintained by Scandinavian countries such as Norway and Sweden. [Display omitted] • A new temporal method for multi-criteria sustainability assessment. • Public available algorithm and code of method developed. • An evaluation of sustainable consumption of alternative fuels. [ABSTRACT FROM AUTHOR]

The growing awareness of climate change is constantly moving the attention of designers and policymakers from typical and current scenarios to future layouts. This new approach introduces a degree of uncertainty that should be accounted in the building design process. The multitude of possible scenarios suggests considering dynamic system that can adapt themselves to unpredicted operating conditions. The aim of this study is to test a new approach and a new flexibility metric analysing the behaviour of a high-performance dynamic internal curtain in current and future scenarios. The first part of the paper focuses on the optimization of the dynamic system in the current scenario; this preliminary analysis represents the traditional design approach and is considered the baseline for all the comparisons. Hence, defining a matrix of likely scenarios, this paper explores the behaviour of three different selected control strategies – always off (i.e., no curtain), fixed control, optimized control – in the different scenarios considering possible variations of i) climate, ii) urban context, iii) internal loads, and iv) building use. The main outcomes of the research are, on the one hand, the comparisons of the control strategies and the benefits of the dynamic system and, on the other hand, the definition of a new metric that can properly describe the flexibility of the building systems with reference to the future scenarios analysed. This metric is based on six classes – which describe the statistical distribution of the energy consumptions of all the scenarios simulated in the matrix – and an index called Energy Flexibility Index (EFI) that quantifies the flexibility of the technology considered. The case study analysed highlights how implementing a dynamic shading system, considering the same building use, can increase the EFI of nearly 21% for non-optimized control strategy and up to 23% when optimized. While changing the building use in residential reduces these values respectively, to 6% and 7%. [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]

Hemp-based building envelopes have gained significant popularity in developed countries, and now the trend of constructing houses with hemp-clay blocks is spreading to developing countries like Morocco. Investigating the hygrothermal behavior of such structures under actual climate conditions is essential for advancing and promoting this sustainable practice. This paper presents an in-depth experimental characterization of a commercial hemp-clay brick that has been exposed to the outdoor environment for four years, in addition to field measurements on a building scale demonstration prototype. Additionally, the study simulates 17 representative cities to assess the hygrothermal performance and energy-saving potential in each of Morocco's six existing climate zones, using the EnergyPlus engine. The experimental campaign's findings demonstrate excellent indoor air temperature and relative humidity regulation within the hemp-clay wall building, leading to satisfactory levels of thermal comfort within hemp-clay wall buildings. This is attributed to the material's good thermal conductivity and excellent moisture buffering capacity (found to be 0.31 W/mK and 2.25 g/m2%RH), respectively). The energy simulation findings also point to significant energy savings, with cooling and heating energy reductions ranging from 27.7% to 47.5% and 33.7% to 79.8%, respectively, as compared to traditional Moroccan buildings. [Display omitted] • Experimental characterization of thermal conductivity, sorption isotherm, and moisture buffering capacity of hemp bricks. • Assessment of indoor thermal comfort and energy demand in a hemp-based building across 17 cities in Morocco. • Hemp-clay bricks demonstrated excellent humidity regulation with a moisture buffer capacity of 2.25 g/m2%RH. • Hemp-clay walls can achieve energy savings ranging from 27.7%–47.5% for cooling and 33.7%–79.8% for heating in Morocco. [ABSTRACT FROM AUTHOR]

This paper reviews the published research pertaining to the use of superheated steam for carbon fibre reinforced polymer (CFRP) composite reclamation. Superheated steam has been used for this purpose for around a decade and was initially investigated to prevent the degradation of reclaimed fibres, which occurs during the oxidative char removal step of most pyrolysis-based reclamation techniques. The review evaluates the various methodologies employed with particular focus on the physical, mechanical, and chemical properties of the reclaimed fibres, and the environmental impact of using superheated steam for carbon fibre reclamation as determined by life cycle assessment. Superheated steam studies report recovering carbon fibres with retained tensile moduli of around 90%–100% and tensile strengths of 65%–100% when compared to virgin carbon fibres, however, when optimised it is shown that carbon fibres can be recovered with no loss in stiffness and strength. Most studies are still at laboratory- or pilot-scale, however, several companies are collaborating with researchers to investigate the potential of this reclamation method on a larger scale. Early analysis on the energy use of carbon fibre reclamation using superheated steam shows that energy savings of 25% could be made by recycling CFRP waste using superheated steam and using the recovered carbon fibres to displace virgin carbon fibres rather than landfilling and incinerating this waste. • Review of the developments pertaining to superheated steam use for carbon fibre reinforced polymer reclamation. • Superheated steam reclaimed carbon fibres retain tensile strengths of 65%–100% and tensile moduli of around 90%–100%. • Review of the life cycle assessment of superheated steam-based carbon fibre reinforced polymer reclamation. • Examples of superheated steam reclamation processes entering the pilot-plant/industrial phase. [ABSTRACT FROM AUTHOR]

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

Hot embossing is an efficient technology for the fabrication of glass micro- and nanostructures. However, the long cycle time, high energy consumption, and high nitrogen emissions in traditional hot embossing approach hinders sustainable production of glass micro-optics. Therefore, this paper proposes a novel two-stage gravity-assisted hot embossing process that enables the fabrication of high-quality glass micro-pillar arrays in a rapid, green manner. In this approach, the two-stage gravity loading unit provides accurate force on glass preform through a simple control system, and the tailor-made heating module based on Si 3 N 4 ceramic heaters requires an energy consumption of just 700 kJ per molding cycle. As a result, the proposed approach is featured by low energy consumption and high manufacturing efficiency. In this study, the effects of the embossing temperature, force, and time on the replication accuracy of a K9 glass micro-pillar array were investigated through a series of hot embossing experiments. Afterward, the form accuracy, uniformity of microstructures, and warpage of glass replicas under the optimal process parameters were evaluated separately. Finally, repeated hot embossing experiments were conducted to demonstrate the reproducibility of the hot embossing process. The experimental results show that embossing temperature had the most significant effect on the replication accuracy of glass micro-pillars. By optimizing the process parameters, the embossed glass micro-pillars could achieve transfer ratios of 99.00% and 95.14% in height and diameter, respectively. Moreover, the surface roughness of glass micro-pillars was less than 5 nm, and the warpage amplitude of glass replicas in a 3.9 × 3.9 mm area was smaller than 1 μm. The small discrepancy in geometric features of glass replica in the repeated trails reflects the satisfactory reproducibility of this hot embossing process on the micro and nano scales. The results indicate the strong industrialization potential of the proposed two-stage gravity-assisted hot embossing machine and hot embossing process for fabricating high-quality glass microstructures more cleanly and sustainably. • A novel gravity-assisted rapid high-temperature hot embossing apparatus is developed. • A novel hot embossing process is designed for fabricating high-quality glass micro-pillar arrays in a cleaner manner. • Effects of process parameters on the replication accuracy of glass micro-pillar arrays are evaluated. • Form deviation, uniformity of microstructures as well as warpage of glass replica are analyzed. • The reproducibility in replicating geometric features in the novel hot embossing process is demonstrated. [ABSTRACT FROM AUTHOR]

Energy intensive industries can be classified into those that process metal, glass, ceramics, paper, cement, and bulk chemicals. They are associated with significantly high proportions of carbon emissions, consume a lot of energy and raw materials, and cause energy wastage as a result of heat escaping from furnaces, reheating of products, and rejection of parts. In alignment with UN sustainable development goals of industry, innovation, infrastructure and responsible consumption and production, it is important to ensure that the energy consumption of EIIs are monitored and reduced such that their energy efficiency can be improved. Towards this aim, it is possible to employ the concepts of digitalisation and smart manufacturing to identify the critical areas of improvement and establish enablers that can help improve the energy efficiency. The aim of this research is to review the current state of digitalisation in energy-intensive industries and propose a framework to support the realisation of sustainable smart manufacturing in Energy Intensive Industries (EIIs). The key objectives of the work are (i) the investigation of process mining and simulation modelling to support sustainability, (ii) embedding intelligence in EIIs to improve energy and material efficiency and (iii) proposing a framework to enable the digital transformation of EIIs. The proposed five-layer framework employs data acquisition, process management, simulation & modelling, artificial intelligence, and data visualisation to identify and forecast energy consumption. A detailed description of the various phases of the framework and how they can be used to support sustainability and smart manufacturing is demonstrated using business process data obtained from a machining industry. In the demonstrated case study, the process management layer utilises Disco for process mining, the simulation layer utilises Matlab SimEvent for discrete-event simulation, the artificial intelligence layer utilises Matlab for energy prediction and the visualisation layer utilises grafana to dashboard the e-KPIs. The findings of the research indicate that the proposed digital life-cyle framework helps EIIs realise sustainable smart manufacturing through better understanding of the energy-intensive processes. The study also provided a better understanding of the integration of process mining and simulation & modelling within the context of EIIs. [Display omitted] • Framework to support the digital life cycle management of Energy Intensive Industries. • Investigate the interplay between process mining and simulation modelling to support sustainability. • Intelligence needs to be embedded to improve energy efficiency and material efficiency. [ABSTRACT FROM AUTHOR]

There is no one-size-fits-all solution for global energy sustainability. It is affected by a country's policies, resources, financing opportunities, the attention given to it, and the degree to which other pressing issues, such as poverty and access to power, are addressed in each country. This paper used 28 indicators to assess a country's energy sustainability. These indicators ranged from CO 2 per capita emissions to the share of electricity production from wind. The indicators were adjusted so that the lower values were more sustainable. 31 countries were selected. Kohonen's self-organizing maps were used to present this 28-dimensional model in a 2D map. This algorithm is a type of artificial neural network trained by unsupervised learning. Eight clusters of countries were found through the analysis using the four-light traffic panel, where green is the most sustainable, followed by blue, yellow, and red. The closeness on the map does not guarantee that two countries will be in the same cluster. Three color matches and closeness were the criteria for the creation of clusters. The energy transition from the map's lower to upper sides is plainly visible. Red clusters make up the lower side, while green clusters make up the top. One blue cluster and two yellow clusters are located between them. The algorithm converged in the 133rd iteration; the quantization error reached 0 and the topological error reached a value of 25. This method can be used to visualize how far or close a country is to the best achievers. It shows which parameters can or should be improved and what the world trend is. If there is a trend, cost-effective solutions are frequently present. [ABSTRACT FROM AUTHOR]

With the emergence of Internet of Things (IoT) and allied applications for smart cities, sustainability goals have seen a prominent emphasis. This paper focuses on the energy efficiency aspect of such sustainable smart city goals. Although energy efficiency has been studied at different levels of a smart city's Information and Communication Technology (ICT) infrastructure, this paper specially focuses on device level energy minimization strategy by means of modelling the energy consumption while accounting for the Clusterheads (CluH) and duty cycling and thereby using evolutionary algorithms. In this paper, a Genetic Algorithm (GA) and a hybrid Artificial Neural Network based Particle Swarm Optimization (PSO), namely Feed Forward Neural Network based PSO(FFNN-PSO) has been used to solve the energy minimization problem. Simulation experiments carried out for different scenarios with varying configuration demonstrate the efficacy of the hybrid neuro evolutionary scheme. [Display omitted] • IoT-based energy optimization model for smart city scenarios. • Genetic Algorithm (GA) and a hybrid Artificial Neural Network based Particle Swarm Optimization (PSO), namely Feed Forward Neural Network based PSO(FFNN-PSO). • Several output metrics, such as the number of alive nodes, load, residual energy, and cost function, were used to pick the best cluster head nodes in IoT network clusters. • The proposed method enacts an intelligent duty cycling by predicting sleep–wake cycles. [ABSTRACT FROM AUTHOR]

This paper discusses the application of distributed energy resources (DERs) at water resource recovery facilities (WRRF). The DERs considered include solar photovoltaic (PV) systems, biomass electricity generation, and energy storage systems (ESS). The financial and demand management implications of the deployment of various DER combinations are analyzed. The load profile of a single plant is studied in order to draw conclusions regarding the optimal size for energy storage solutions based on the goals of the WRRF. A case study of a Medium sized WRRF, located in a large metropolitan area, is used to compare different financial and technical implementation strategies. An ideal combination of DERs is determined based on analysis of various scenarios for nine distinct use cases. The overarching goal of this paper is to understand the potential of various combinations of DERs for managing peak demand and resilience at WRRFs. Elements in the financial models are compared to determine the combination that creates a financially viable project while providing tangible benefits in resilience and/or demand management to the WRRF. • Energy efficiency is key for urban regions to combat global warming. • Distributed energy resources (DERs) improve resiliency during power failures. • Energy efficiency is possible through deployment of DERs and better use of biogases • Distributed energy resources (DERs) improve resiliency during power failures. [ABSTRACT FROM AUTHOR]

In machining processes, there are contradictions between high efficiency and environmentally-friendly machining. This indicated that there is a major potential for sustainable machining to both increase efficiency and protect ecological balance. For this, the employment of effective methods has become imperative to reduce resource use. In this way, the use of analysis and optimization tools to select the tool material, cutting parameters, cooling/lubrication conditions, etc., will be a benefit for minimizing waste without sacrificing efficiency. In the literature, researchers have used various methods to reveal the requirements of sustainability. However, reaching the concept of sustainable machining by using one more than technique confuses the readers. Therefore, it was deemed necessary to present and discuss the current methods, models and analyzes in a comprehensive review paper. In this context, this paper reviewed the previously published works, especially focusing on sustainability and energy consumption modeling methods in machining operations. At the end of the study, it was seen that LCA provides a systematic and quantitative view of the system and thus can act as a decision support tool. Moreover, it can give an idea to the manufacturers about the improvement of the process and the areas of innovation. However, the method has several disadvantages such as relatively expensive and specific software, obtaining inventory data, impractical to use, time-consuming and requires large amounts of data. Various mathematical models and algorithms have been developed to deal with the complex situations and offer a more practical use compared to LCA. However, it is difficult to state that clear results have been achieved thanks to these models. It was seen that in complex machining processes, only approximate results can be found with models, which leads to questioning the reliability of the models. [ABSTRACT FROM AUTHOR]

[Display omitted] • Bimetallic catalyst of W-Ni on porous support yields high EG, up to 89% • Repeated use of catalyst causes metal leaching, oxidation, sintering and deposit. • The highest reusability of 34 runs was recorded for Ru/AC + H 2 WO 4 catalysts. • Impacts of impurities in biomass (i.e. lignin, sulfur, Al, Mg and Fe) are analyzed. • Pressure swing and extractive distillations reduce energy demand. Ethylene glycol (EG) is one of the most sought-after industrial compounds. High global demand necessitates for a production of up to 28 million metric tons EG a year. Reaction pathway for fossil fuel derived EG may be relatively simpler, but it remains a finite resource and is notorious for greenhouse gas emission. The increasing awareness for sustainable development and security of raw material has prompted researchers to explore novel ideas for production of EG from renewable feedstock. The abundance of lignocellulosic raw material naturally positions it as a desirable substitute to its petrochemical counterpart. This paper reviews recent progress in valorization of biomass via catalytic conversion through a broader lens, encompassing the vital aspects for commercialization of process technology. An in-depth analysis of three critical inter-related subjects for sustainable EG production, namely the catalytic system performance, effects of impurities in biomass and catalyst reusability in the harsh hydrothermal reaction is presented. Probing further into post-reaction process, purification strategies of close boiling points polyol mixture product through this bio-route are assessed. Finally, the challenges and prospects of scaling-up the technology are appraised. [ABSTRACT FROM AUTHOR]

Due to the energy shortage and environmental pollution, the development and utilization of biomass energy has aroused increasing attention all over the world. The crop straw cogeneration (CSC) of heat and power is an efficient renewable energy utilization technology in rural area, which is a practical solution to energy saving and pollution control. Circular economy, characterized by resource conservation, recycling and environment harmony, greatly enriches the connotation of energy projects, which is of guidance implications for the development of CSC. In this paper, the CSC project site selection is conducted under the multi-criteria decision-making (MCDM) framework from the perspective of circular economy. A complete criteria system considering the sustainability indicators is established to reflect the characteristics of CSC projects for the first time. Furthermore, due to the complexity and the lack of ready-made experience in the CSC site selection, the intuitionistic fuzzy sets (IFSs) are improved and applied by creating a novel IFSs distance formula to provide clear expression for the hesitation degrees of the experts. Finally, taking Changchun City, Jilin Province as an example, the improved TOmada de Decisao Interativa Multicriterio (TODIM) method is applied to obtain the optimal location. A 2 (Nongan) is the best choice among the four given alternatives, and comparative analysis shows that the improved TODIM method is better than the other methods. This study improves the application of intuitionistic fuzzy sets in site selection of energy projects and brings new insight for the decision-making from the perspective from circular economy. [Display omitted] • A criteria system is established from the circular economy perspective. • A new formula based on membership, non-membership and hesitation is defined. • A site selection framework is proposed based on the improved TODIM method. • Economic factors and social needs are dominant for CSC site selection. [ABSTRACT FROM AUTHOR]

Energy and environmental sustainability in urban rail transport have attracted substantial attention in the last decade. In the UK, about 29% of the current train fleets are run solely on diesel fuel, and the UK Government has pledged to remove all diesel-only trains by 2040. One option to achieve this ambitious goal is replacing diesel trains with hybrid trains. However, little has been done to evaluate the operational performance of replacing diesel trains with hybrid trains on the same track. This paper develops a novel Hybrid Train Simulator which can analyse the driving performance and energy flow among multiple energy sources (diesel, hydrogen and battery). Several practical case studies are presented based on typical mainline railways in the UK. Operation performance using diesel trains and hybrid trains is compared. This paper also proposes automatic smart switching control between multiple power sources according to the altitude of the route for hybrid trains. The case studies indicate that hybrid trains increase the journey time due to their low power capacity but improve energy efficiency significantly. Besides, implementing auto-switching on hybrid trains can reduce energy consumption by 6% compared with benchmark hybrid trains. [ABSTRACT FROM AUTHOR]

Reducing the cutting energy consumption in machining is important to improve the sustainability of cryogenic machining. Currently, the analysis of cutting energy for cryogenic machining mostly relies on equipment testing, while less research has been conducted on energy analysis based on material removal mechanisms. In this paper, the chip formation mechanism of cryogenic machining is studied on the basis of liquid nitrogen orthogonal milling experiments with Ti–6Al–4V alloy, and the corresponding specific cutting energy model is established. First, the effects of cooling conditions and process parameters on chip microscopic morphology were analyzed based on orthogonal milling experiments. Next, a specific cutting energy model was established according to the chip formation mechanism. Finally, the reliability of the model was verified by cutting forces. The results show that in cryogenic machining, when the cutting speed is less than 200 m/min, adiabatic shear dominates the formation of serrated chips, and the cutting energy consumption is higher than that of dry cutting. As the cutting speed exceeds 200 m/min, adiabatic shear and periodic fracture together dominate the formation of serrated chips, and the energy consumption of cutting is significantly reduced at this time. This research provides a reference and guidance for the sustainable development of cryogenic machining. • This research reveals the chip formation mechanism of cryogenic machining of TC4 alloy. • In this study, an energy consumption model for cryogenic machining was established. • Cryogenic machining is an energy saving and environmental protection method. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric and long-run effect of energy productivity on the quality of the environment in Finland. Finland, as one of the Nordic countries, is a major contributor to the global drive to achieve decarbonization by 2050. In effect, this study seeks to contribute to the strides by querying the extent to which shocks in energy productivity make or mar the sustainability of the Finland environment from 1990:Q1 to 2019:Q4. The other impacts of financial development, economic growth, and trade openness are considered in the model estimated by using the novel hidden panel cointegration and nonlinear autoregressive distributed lag (NARDL) methodology. The results reveal a significant asymmetric equilibrium cointegration relationship among the variables over long-run time horizons; energy productivity utilization enhances the quality of the environment in Finland over the long run while trade openness, financial development, and economic growth contribute to environmental degradation in Finland in the long term. In particular, a 1% positive and negative fluctuation in energy productivity lowers carbon emissions by 1.79442% and 0.84799% in the long term. Whereas 1% change in trade openness, financial development, and economic growth trigger CO 2 emissions (CO 2 E) by 1.15298%, 0.271365%, and 2.93402% in Finland's economies. The results of the frequency domain causality model corroborate the NARDL results. On the basis of these empirical findings, this study suggests that policymakers in Finland should consider the asymmetric behavior among these variables in setting their trade, environmental, growth, and energy policies. [Display omitted] • The effect of energy productivity on environmental degradation in Finland is examined. • Nonlinear ARDL, Fourier ADL cointegration and frequnecy domain causality tests are employed. • Energy productivity leads to lower environmental degradation in Finland. • Energy productivity causes environmental sustainability at different frequencies. [ABSTRACT FROM AUTHOR]

This paper aims to develop an optimal real-life energy-efficient design for a production plant within the concept of the circular economy. The problem is to install a Heat Recovery System (HRS) that utilizes the hot oil used by the compressors to heat the water for the central heating system. To achieve the desired level of energy efficiency this design problem must be formulated from both the optimization and sustainability points of view. Additionally, this design problem must also consider the investment cost. In line with this purpose, this paper formulates this design problem as an optimization problem employing a mathematical programming approach as a single objective, and as a multi-objective optimization problem through a goal programming approach. Besides, this paper uses the return on investment as a key performance indicator, since it deals with a real-life design problem with an investment cost. The related design problem is solved with the single objective and multi-objective versions of the developed mathematical programming model via a commercial solver to identify different design alternatives and hence giving the decision-maker to make a selection option. Finally, the capability of the developed mathematical programming model is tested on a set of randomly generated problems. The obtained results indicate that the developed mathematical programming model is a successful decision support system since its single and multi-objective versions are capable of identifying energy-efficient production designs within the context of the real-life problem on hand and the circular economy. • A real-life energy-efficient design problem for a production plant is undertaken. • A heat recovery system is proposed within the concept of a circular economy. • The problem is modelled from both the optimization and sustainability aspects. • The problem is formulated as multi-objective models using goal programming. • The models are solved to minimize investment costs and maximize energy efficiency. [ABSTRACT FROM AUTHOR]

Construction is nowadays considered an extremely energy intensive industry and one of the main sources of environmental pollution in the world. Therefore, the research and the development of novel energy-saving manufacturing processes and sustainable construction materials is more than ever urgent and challenging. This paper aims at identifying the industrial process for the production of novel geopolymers to be used as a greener substitute for cement, especially the Portland one, widely used for structural applications to significantly reduce the environmental impact of the construction industry. Here, the materials sustainability and the manufacturing process are improved by valorising and reusing wastes, deriving from the pulp-paper industry, as raw materials. This industry generates a great quantity of wastes that represent a real concern both for their environmental impact and cost of disposal. The new industrial process was evaluated after scaling up the laboratory procedure to an industrial dimension. Consequently, each small-scale process was deeply analysed (raw materials involved and processes) and transposed into a massive-production. The most relevant processes that show an elevated environmental impact were identified and the energy consumption of the whole process has been assessed resulting, for the analysed geopolymeric product, an embodied energy of 645 MJ/ton, being about one sixth of the OPC. Moreover, a preliminary economic analysis has been conducted in terms of raw materials involved in the proposed industrial process revealing a decreasing cost per ton increasing the waste recycling. All considered, the main conclusions are that the industrial scale up of the proposed geopolymeric product, assessed for the first time in literature along with the related proposed considerations, could be highly competitive to the Portland production involving greener processes with a much lower energy consumption and a greater financial saving by improving the wastes quantity. [ABSTRACT FROM AUTHOR]

It is important for Chinese cities to advance sustainable energy consumption and ensure that they achieve their carbon emission peak and carbon neutrality. This paper develops a comprehensive assessment of the spatial variability and influencing factors of the quantity of household energy consumption per capita in mega-cities. Based on microlevel household survey data from Guangzhou, Guangdong Province, China (N = 1082), we analyze the spatial effects and factors of urban residents' energy consumption. A spatial econometric model with four spatial weight matrices is employed, and the nested spatial weight matrix, which holds practical economic and geographical significance, is set. We find that (1) the quantity of energy consumption per capita of all households in Guangzhou is 189.57 kgce/year and shows a spatial difference, with 177.5 kgce/year in the central urban area and 203.47 kgce/year in the outskirts urban area. In particular, households in the outskirts of urban areas present a higher percentage of "high" and "medium-high" energy consumption per capita than those in central urban areas. (2) The quantity of household energy consumption per capita of urban residents is characterized by significant spatial correlation and agglomeration, with "high-high" and "low-low" agglomeration in central urban areas. (3) The household labor force, the housing area and household income are the core factors that drive the quantity of household energy consumption per capita, while the region and educational level are also main factors. We observe the diversity of the energy transition by comparing the patterns of the quantity of household energy consumption per capita within the city. A comprehensive picture of the diversity underlying the energy transition applied across cases can be distilled. [ABSTRACT FROM AUTHOR]

• Scandinavian countries are fostering a sustainable economy based on renewable energy. • The investments on renewable sources has positively affected the investments in this energy and GHG emissions. • A bidirectional causal relationship exists between renewable energy consumption and CO 2 emissions. • A causal relationship exists between renewable energy consumption and economic growth. Climate change presents the greatest challenge facing all countries of the world in the new millennium. Among others, objective 13 of the Sustainable Development Goals (SDGs) aims at adopting urgent measures to contrast climate change and its consequences. Part of the decline in the global growth of emissions has been the increase in using renewable energies. In this context, the relationship among GDP, CO 2 emissions, and renewable energy use has been investigated in this study, starting from a systematic review that has noticed the presence of three clusters focused on: CO2 emissions, GDP, and energy consumption. Despite the current level of interest in examining the relationship among these variables, there have been few empirical studies. To fill this knowledge gap, this paper has been focused on the Scandinavian countries, where the use of renewable energies has steadily increased, developing novel panel analysis estimates. Using a dataset of these five economies over a 1990–2018 time period, several panel data tests have been carried out, in order to robustly assess the causality issue among renewable energies, CO 2 emissions, and GDP. The results of the empirical analysis imply that renewable energy consumption is a useful policy instrument to reduce CO 2 emissions without adversely affecting GDP growth. The main implications have been that the decrease of CO 2 emissions, by increasing renewable energy use, can guarantee high levels of energy efficiency and economic growth. These empirical findings help design innovative energy policy roadmaps and accelerate the ecological transition through the promotion of renewable energy and the reduction of GHG emissions. [ABSTRACT FROM AUTHOR]

This paper proposes a novel integrated framework for nesting (i.e., part orientation selection and two-dimensional packing) and scheduling parts assigned to batches (or jobs) on additive manufacturing machines. For the first time, a tri-objective optimization model is designed that interprets profit, energy utilization of machines, and goodwill losses (i.e., tardiness, negotiation, and increasing due date) as three sustainability criteria. Besides, considered negotiation plans may reduce the prices of ordered parts for a possible increase in the initial due date set by customers. The model's scalability is supported by tailoring three algorithms: robust improved ɛ -constraint method, non-dominated sorting genetic algorithm (NSGA-II), and multi-objective grey wolf optimizer (MOGWO). Several insights are derived by analyzing the model's sensitivity to its key parameters and validating its applicability by a case study of Amazon's last-mile delivery process. The results confirm the conflicting objectives, suggested action plans, and proposed algorithms. [Display omitted] • Developing a flexible/faster nesting method in additive manufacturing (AM) systems. • Considering sustainability criteria for nesting and scheduling in AM systems. • Proposing a framework to set negotiation plans for scheduling and nesting decisions. • Developing a representation method for meta-heuristic algorithms. • Deriving insights for a last-mile delivery system in AM by a real-world case study. [ABSTRACT FROM AUTHOR]

Despite the substantial effort on almost all levels during the last decades, the buildings' renovation rate needs to be at least doubled from the current 1% to meet ambitious energy efficiency goals. In the same way, the energy-intensive material replacement did not reach yet the desired grade in terms of sustainability measures and outlined goals heading to a low-carbon economy. This paper summarizes principles of sustainable development together with the current methodological framework relevant to the civil engineering and construction industry. The main part is devoted to the identification and understanding of principal factors preventing faster adoption of energy efficiency measures. High initial financial costs, investment risk over a long-term period, poor acceptance of sustainable measures, lack of information, and limited methodological framework for a reliable evaluation of environmental projects with the intergeneration context or understanding of externalities of human activities are identified as the main barriers to the sustainable building retrofits. These barriers are closely related each other and can be merged into several groups according to the stakeholders or scientific disciplines to amplify their primary impact. Notwithstanding, solution strategies based on narrow boundary conditions and limited multidisciplinary approach prevent substantial advances towards the sustainable building sector. In this regard, the major obstacles preventing the achievement of energy efficiency goals can be remedied by interdisciplinary cooperation. • Lacking multidisciplinary approach hinders sustainable measures adoption. • Limited public acceptance prevents a stronger political commitment. • Methods of social measures need to be studied for decision support. • Sustainable building industry transition is not a technical issue only. [ABSTRACT FROM AUTHOR]

Responding to the increased interest in addressing organisational sustainability issues using behaviour change strategies, this paper aims to propose a methodology for doing so from a different perspective – namely, sociology and social practice theory. Firstly, the background of behaviour change approaches and practice theory are discussed. Then a methodology for conducting a pro-environmental organisational change project is proposed. The methodology involves five key elements: detailed analysis of context, outlining a theoretical framework, establishing project boundaries, acknowledging connectivity of practices and choosing data collection methods. We illustrate the application of methodology by using examples of everyday consumables, energy and waste in a hospital trust in the South East of England. This approach has been effective for analysing routine and inconspicuous consumption within an organisation, as it considers individual attitudes and motivations as well as the structural and habitual nature of communities of practices. It allows researchers and managers to understand workplace consumption issues from several perspectives and identify the best angle from which to approach potential resolutions. • A five-step methodology for an organisational change management project is proposed. • Practice theory helps analyse routine inconspicuous consumption in an organization. • Practice theory helps establish project boundaries and connectivity between practices. • Organisational context and structure can facilitate sustainable workplace consumption. • Energy and waste consumption practices in workplaces rely on habits and routines. [ABSTRACT FROM AUTHOR]

Battery demand is estimated to growth at a 25% annual rate, to reach a volume of 2600 GWh in 2030. Recovering critical raw materials from end-of-life batteries is now mandatory to limit the need of primary raw materials in the long-term. However, recycling of lithium-ion batteries (LIBs) is still in its early stage. Many technologies have been proposed, that consist of a combination of mechanical processing, often after thermal pre-treatment, ended up to hydrometallurgical or pyrometallurgical processing. All these methods have several pros and cons in terms of applicability, safety, environmental impact, eventual recovery efficiency of the components, and economic factors. In this frame, the evaluation of the sustainability of the proposed technologies plays a fundamental role in selecting the most suitable approaches able to support material supply for batteries, identifying the major solutions to optimize the end-of-life management strategies for LIBs, in the perspective of a circular economy context. However, LCA was developed to evaluate commercially mature technologies. This paper aims to propose and discuss, for the first time, the sustainability of 33 different technologies available in literature for LIBs recovery, even if developed only at laboratory level, by a screening approach, preliminary to LCA analysis. For this purpose, ESCAPE (standing for Evaluation of Sustainability of material substitution using CArbon footPrint by a simplified approach) tool based on the calculation of embodied energy and carbon footprint is used. Based on ESCAPE analysis results, this work shows and discusses the parameters that affect the technologies sustainability (thermal and mechanical treatments and chemicals and water use). The results, in accord with preliminary available LCA data, indicate that chemicals and ultrapure water consumption are the most energy-intensive processes drivers, showing that pyrometallurgy can limit carbon footprint and energy consumption in comparison to hydrometallurgy. Finally, by using the ESCAPE index, it is shown that some technologies may be improved for example by using industrial water instead of ultrapure water and/or by recycling the chemicals used for leaching steps. In summary it is shown that ESCAPE tool can be used in supporting eco-design strategies with the aim to facilitate the understanding of environmental implications of proposed LIBs recovery technologies and to focalize the research toward the more promising ones. [Display omitted] • Sustainability analysis of 33 technologies to recover spent LIBs is proposed. • The processes steps are evaluated in terms of embodied energy and carbon footprint. • LIBs recycling processes should aim for a better water management and leachants recovery. [ABSTRACT FROM AUTHOR]

• Purification processes can account for a large fraction of the total operating costs of biorefineries. • Intensified purification of biofuels considering novel technologies. • It is important to develop processes with low environmental impact. • Improvement in purification technologies can greatly reduce overall production costs. Biorefineries offer very interesting challenges and opportunities associated with the separation and purification of complex biomass components. Separation and purification processes can account for a large fraction of the total capital and operating costs. Significant improvement in separation and purification technologies can greatly reduce overall production costs and improve economic viability and environmental sustainability. Process intensification is a valuable strategy to enhance the performance of production processes. It may allow reductions in costs and environmental impact, and enhancements in terms of operability and safety. Although the PI philosophy and methodology have a relatively long history in the scientific field, the ideas of this philosophy fit well with the current trends of sustainability and circular economy; since both ideas, in short, seek the reduction of resource use, the reduction of waste, and the continuous and circular use of raw materials. To ensure the sustainability of the purification of biofuels, it is important to develop processes with low environmental impact, which can also be allowed through the development of intensified technologies. In this paper, advances on aided process design applied to the purification of liquid biofuels using Process Intensification are presented. Trends and challenges are discussed, together with the main opportunity areas. [Display omitted] [ABSTRACT FROM AUTHOR]

Biofuel manufacturing from renewable biomass through a smart manufacturing system is an important alternative to fossil fuels, which helps to decrease dependability on conventional fuel and decrease carbon emanations. By utilizing efficient labors, smart machines, and minimized energy utilization, the conventional biofuel manufacturing framework can be converted into a smart sustainable manufacturing framework. The existing conventional fuel demand can be replaced by biofuel. This study efforts to make pure biofuel with less amount of carbon emanations and energy utilization through a smart multi-type biofuel manufacturing framework, where the demand of the biofuel is selling price dependent. The different energy costs including air handling cost, lighting cost are calculated in this work-in-process inventory. The carbon emissions cost is included in every stage of this model. A variable demand has introduced for the maximization of profit. To reduce energy consumption and carbon emissions, a two-stage inspection cost with a variable manufacturing rate is taken to make the manufacturing process flexible such that the amount of impure biofuel is minimized. Although a random manufacturing rate is applied through a smart manufacturing system, still impure biofuel is manufactured. The impure biofuel is remanufactured again through refining just after the well-planned manufacturing ends. In this model, the multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to market places at predetermined intervals at the time of delivery frame. The classical optimization technique is used for continuous and differentiable variables and the mixed integer programming technique is utilized for discrete variables to maximize the total profit globally. To validate the model's usefulness, four numerical observations are studied. It is shown that by utilizing the said procedure, the percentage of impure biofuel can be decreased truly through the minimized energy consumption. The graphical representation and the sensitivity experiment show the impact of every parameter with the whole cost of the research paper. Numerical results assist to get the maximum profit and the optimum selling price of biofuel globally in a sustainable smart multi-type biofuel manufacturing system. [Display omitted] [ABSTRACT FROM AUTHOR]

• Assessing the Environmental Performance of china's Three Urban Agglomerations. • Using the dynamic DEA model based on the input–output perspective. • The total environmental efficiency exhibits a wave-like development trend. • PM2.5 is the best unexpected output after strict prevention from 2013 to 2017. • Industrial smoke and dust emissions need to strengthen management in the future. As a special form of a cluster city, urban agglomeration has become an important platform to support national economic growth and to participate in international competition and cooperation, but it faces severe environmental problems. This research thus selects panel data of 60 cities in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2013 to 2017. Based on the input–output perspective, labor and energy consumption per GDP are selected as input indicators, GDP, PM2.5, SO 2 , industrial smoke and dust emissions, and wastewater discharged as output indicators, and fixed assets as a carry-over variable in the dynamic DEA model to evaluate and analyze the environmental efficiencies of these three urban agglomerations. Findings show that their total environmental efficiency exhibits a wave-like development trend, and that the total efficiency score of BTH is better than that of PRD and YRD. From the viewpoint of a sub-efficiency index, PM2.5 is the lowest in unexpected output, where its average five-year efficiency score is 0.9847, while the average score of industrial smoke and dust emissions efficiency is the lowest at 0.6199. Finally, this paper offers suggestions for different problems facing the three urban agglomerations. [ABSTRACT FROM AUTHOR]

Lean manufacturing has already proven to be an effective management philosophy for eliminating waste in production processes, leading to operational gains. However, nowadays, it is not enough just to obtain economic results, with the environmental aspect being a concern that organizations have been incorporating into their production processes due to stakeholder's pressure in order to increase their sustainable performance. As such, a bibliometric and a structured analysis of the literature were carried out focusing on the connection between lean, green and sustainability concepts. The Web of Science platform was used to collect data, encompassing the period from 1900 to 2020. The carried analyses covered the identification of the most relevant papers, including their authors, as well as their temporal and geographical distribution. There was also focus on the draft of a map to observe an underlying intellectual structure through VOSviewer. The novelty of this research is that, through the gathering of relevant data related to the three concepts considered and their analysis, a conceptual model was proposed consisting of lean-green and sustainability (LGS) tools to achieve superior triple bottom line (TBL) performance. This study pinpointed that in most of the cases where LGS tools have been applied (TPM - Total Productive Maintenance - and 6R, e.g.), there was a positive impact mostly on the economic and environmental pillars of the targeted companies. Although there were also a small number of other cases where it was found that an improved efficiency induced an increased consumption of energy and water, namely by lean tools (SMED - Single Minute Exchange of Dies, e.g.), the results demonstrated the capability of lean and green, especially their combination, to enhance sustainability outcomes. Future research should focus on quantifying the effects that LGS tools, in a single way or combined, bring to all TBL pillars, especially the social one, e.g., by developing key performance indicators. The testing of the proposed conceptual model, including its completion, is also encouraged, namely through the evaluation of what is the best combination of LGS tools, considering specific sectors of activity. [ABSTRACT FROM AUTHOR]

Expanding the domestic bioeconomy can help diversify the use of national resources and reduce emissions. Evaluating the sustainability of a growing bioeconomy, however, is inherently complex since it spans several sectors and supply chains. It requires a comprehensive, integrated analysis framework to assess the developments across the traditional sustainability dimensions. Further, the assessment of bioeconomy developments requires a robust baseline of historic data and trends. In this paper, we analyze the evolution of the biofuel portion of the US bioeconomy, focusing on two fuels that had an exponential growth in the last two decades: corn ethanol and soybean biodiesel. For this purpose, we created a novel time series of harmonized environmentally-extended input-output (EEIO) tables based on a publicly available model from the US Environmental Protection Agency and expanded its disaggregation to reflect the main supply chains of the biofuels sectors. The EEIO time series provides the historical evolution of these biofuels relative to the rest of the economy as well as on an energy-unit basis. We find that, except for energy use, the broader US economy declined in both resource intensity and most environmental impacts when normalized per one million dollars of gross domestic product. Deviating from this trend are freshwater ecotoxicity and human toxicity, mainly attributable to the expansion of commodity crops and the increase of domestic oil and gas extraction respectively. We also find that the biofuel industry's total socioeconomic, resource use and environmental impacts grew with their production increases over time. However, the industry's maturation and scale-up, combined with higher feedstock yields, contributed to a reduction of most impacts on an energy-unit basis over time. [ABSTRACT FROM AUTHOR]

Advance cooling/lubrication (lubricooling) approaches are getting fame in industry and academia due to their excellent performance. A significant amount of work has been conducted to investigate the effect of various lubricooling approaches on the machinability of the hardened steel. However, sustainability-based performance evaluation of lubricooling assisted machining is missing. Thus, this paper presents 3E-based (Energy, Economics, Environment) analysis to compare the performance of various lubricooling approaches. Initially, preliminary experiments were performed to achieve optimal flow rates of various cutting fluids used in Minimum Quantity Lubrication (MQL), cryogenic cooling, and conventional emulsion (Flood) approaches. Later, optimal flow rates were used to achieve equal cutting-tool life under all machining environments. Results showed that with the same tool life method (STLM), Cryogenic-MQL(CryoMQL) could withstand aggressive cutting speeds and produce the highest productivity among all lubricooling approaches. In addition, it yielded 50% lower-priced specific production cost as compared to dry machining. However, 44.3% more specific-CO 2 emitted in CryoMQL as compared with dry machining. In summary, the hybrid CryoMQL assisted machining process is sustainable economically but not environmentally. The outcomes of the present study provide useful information, and it can help machinist to enhance the process performance. [Display omitted] • Holistic sustainability assessment of hard machining. • New holistic models for energy consumption, CO 2 emission, and cost. • Determining optimal flow rate of cooling/lubrication approaches. • Comparison of energy-conscious advanced lubricooling technologies. • Proposed CryoMQL yielded 50% lower price products. [ABSTRACT FROM AUTHOR]

Increasing energy demand and the rising levels of greenhouse gas emissions have increased the necessity of bioenergy and sustainable energy generation. The sustainable bioenergy supply chain is the key to produce sustainable biofuel. This paper points to render an optimization model for planning a versatile and dependable biomass-to-bioenergy sustainable supply chain network in which crop residuals from several agricultural sectors, multi-transportation disruption modes, multi-biorefineries, multi-biogas plants, and multi-market centers are investigated for two bioenergy sources, namely biofuel and biogas. For this reason, supply chain cost optimization, emissions of feedstock transport, processing, and distributing end biofuel to respective markets are utilized. The multi-setup-multi-delivery (MSMD) concept is incorporated and lead time crashing cost is applied to minimize the lead time in this model. The carbon emission costs at all steps and the variable production rate for the production of bioenergy are included within the model. Finally, one small-scale data and another large-scale data of six agricultural areas, four biorefineries, four biogas plants, and six markets are considered to validate the model's usefulness. The model's goal is to show bioenergy's effect to make a sustainable supply chain of biofuel and biogas. The numerical results reveal that the cost of bioenergy production contributed 54.12%, a major extent of the whole cost in biorefinery and biogas plants. The transportation segment is the preeminent initiator of carbon emissions with 83.33% in the entire carbon emission within the whole supply chain. Although, transportation cost contributed 33.09% of the total cost, the multi setup-delivery-multi-delivery policy minimized the whole supply chain cost. The results provide a systematic guideline for developing a sustainable biofuel supply-chain by minimizing cost, various aspects of transportation logistics, and multi-model alternatives under reduced energy effects. • Energy demand and two approaches of biofuel and biogas production are evaluated. • Reduction of the supply chain network's total cost. • Optimizing allocation of the appropriate quantity of residual biomass and biofuel. • Reducing energy consumption by using variable production rate. • An intelligent logistics system with multi-disruption is addressed. [ABSTRACT FROM AUTHOR]

The stamping industry is critical in the automotive and aerospace industries, and the environmental impacts and sustainability of stamping systems have attracted considerable attention. To analyze the environmental impact and sustainability of stamping systems quantitatively, this paper presents an emergy-based evaluation method considering all the associated environmental impact factors of a pressing workshop including material and energy consumption, waste flows, time and mass losses, and processing costs. On the basis of analyzing the stamping processes and sustainability, this method comprises data collection, emergy based sustainability evaluation model and the development of sustainable evaluation indexes and systems. Based on the proposed method, the environmental impact of an industrial vehicle stamping workshop was evaluated. The results show that the net emergy yield ratio of the stamping system was greater than 2, and the waste emergy output ratio was very low, indicating that the system had high productivity levels, high yields, and low pollution discharge rates. However, its sustainability index was less than one owing to its high energy and material consumption during the production processes. To reduce the environmental impact of this stamping system and improve its sustainability, we investigated the potential improvements that could be achieved in energy consumption, productivity, and environmental impact by implementing energy-saving scheduling in the stamping workshop. The results show that the corresponding net emergy yield ratio and sustainability index of the system were both improved. The proposed emergy-based method could be used to quantitatively evaluate the environmental impacts and sustainability of stamping systems and facilitate efforts to reduce the environmental impacts of pressing workshops while improving their productivity and economic profitability. [ABSTRACT FROM AUTHOR]