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The paper industry is a traditional industry with extensive consumption of resources and energy and more pollutant discharge. This industry is closely related to production and life activities. Under the general requirement of "to step up conservation of the Yangtze River and stop its over development", the paper industry in the Yangtze River Economic Belt should urgently undergo green transformation and development. Based on the undesirable slack-based measure model, spatial gravity center, Kernel density function, Theil index, and panel model, this study examines the green development efficiency and its influencing factors of the paper industry in the Yangtze River Economic Belt from 2001 to 2016. Results showed the following: (1) from 2001 to 2016, the green development efficiency of the paper industry in the Yangtze River Economic Belt had been steadily improved, but the overall efficiency value is not high, which has a great potential for improvement. The green development efficiency of the paper industry in the Yangtze River Economic Belt presents the regional differentiation law of gradient increasing in the upper, middle, and lower reaches. (2) According to the gravity center trajectory, the efficiency center of the green development of the paper industry in the Yangtze River Economic Belt is located in the middle reaches of Hunan Province and Hubei Province and moves to the southwest. This case indicates that the green development efficiency of the paper industry in provinces and cities in the southwest has been improved. (3) The regional differences in the green development efficiency of the paper industry in the Yangtze River Economic Belt show the characteristics of narrowing fluctuations. The regional differences are the primary sources of the difference in the green development efficiency of the paper industry. (4) The enterprise scale, science and technology investment, and industrial structure have significant positive effects on the green development efficiency of the paper industry in the Yangtze River Economic Belt. On the contrary, environmental regulation and foreign investment intensity have significant negative effects. However, the above factors have different effects on the green development efficiency of the paper industry in the upper, middle, and lower reaches of the Yangtze River Economic Belt. [ABSTRACT FROM AUTHOR]

This document is a preface to a special issue of the journal "Mathematics" that focuses on mathematical modeling and optimization of service supply chains. The special issue includes 14 papers that cover a wide range of topics within this field. The papers provide valuable insights for researchers, students, and practitioners in supply chain management, operations research, industrial engineering, and business management. They address areas such as customer preferences, optimization of supply chain decisions, coordination mechanisms, and the effects of the external environment. The findings can assist in addressing current issues and challenges in service supply chains, ultimately enhancing performance and efficiency. [Extracted from the article]

In the field of risk assessment, the traditional econometric models are generally used to assess credit risk. And with the introduction of the "dual-carbon" goals to promote the development of a low-carbon economy, the scale of green credit in China has rapidly expanded. But with the advent of the big data era, due to the poor interpretability of a traditional single machine learning model, it is difficult to capture nonlinear relationships, and there are shortcomings in prediction accuracy and robustness. This paper selects the adjusted ensemble learning model based on the homogeneous and heterogeneous factors for user default prediction, which can efficiently process large quantities of high-dimensional data. This article adjusts each model to adapt to the task and innovatively compares various models. In this paper, the missing value filling method, feature selection, and ensemble model are studied and discussed, and the optimal ensemble model is obtained. When comparing the predictions of single models and ensemble models, the accuracy, sensitivity, specificity, F1-Score, Kappa, and MCC of Categorical Features Gradient Boosting (CatBoost) and Random undersampling Boosting (RUSBoost) all reach 100%. The experimental results prove that the algorithm based on adjusted homogeneous and heterogeneous ensemble learning can predict the user default efficiently and accurately. This paper also provides some references for establishing a risk assessment index system. [ABSTRACT FROM AUTHOR]

Under the double pressures of economic growth and ecological environment protection, sea green transformation and the sustainable development of mariculture are critical. This paper constructs an evolutionary game model with the government as the main body and mariculture farmers (enterprises) as the main body and puts forward the research hypothesis. Based on 2006–2019 longitudinal data of nine provinces along China's coast, using multi-period Difference-in-Difference (DID) and dual robust estimation, we empirically investigate the national oceanic ranch demonstration zones for the influence of the green sea aquaculture and their mechanism of action. The results showed that (1) the efficiency of green level of mariculture industry in China is not high, and the establishment of national marine pasture demonstration zone has not effectively promoted the improvement of green level of mariculture industry; (2) the institutional environment, unreasonable industrial structure, and lack of scientific and technological innovation have an effect on the national oceanic ranch demonstration area as the main causes of failure to effectively promote marine green farming; (3) the establishment of the national multi-period demonstration area in the north significantly hindered the growth of the green level of mariculture and fell into the "policy trap", while the establishment of the national multi-period demonstration area in the south significantly promoted the growth of the green level of mariculture. The conclusions of this paper provide an empirical basis and reference for the improvement of the national marine pasture demonstration zone policy and the green transformation of mariculture to a certain extent. [ABSTRACT FROM AUTHOR]

In the critical period of strengthening the construction of ecological civilization, the construction of forest cities has become an important measure to promote urban ecosystem restoration and achieve sustainable development. Based on the mechanism of forest city promoting green development, the construction of a national forest city is regarded as a "quasi-natural experiment". Using China's urban panel data from 2005 to 2019, the impact of national forest city construction on urban green total factor productivity was evaluated using Multistage asymptotic double difference. The results show that National Forest Cities with environmental regulation can significantly promote regional green total factor productivity, which is still valid after a series of Robustness tests. Mechanism analysis shows that forest city construction not only affects territorial spatial planning but also forms a linkage with green technology innovation, mutual promotion and mutual promotion to jointly promote the sustainable development goals. This paper argues that building a national forest city is an important measure to achieve China's sustainable development goals in the new era, but in the process of policy implementation, it is necessary to implement the national forest city selection system according to local conditions. [ABSTRACT FROM AUTHOR]

This document is a correction notice for a research paper titled "A Drone Based Transmission Line Components Inspection System with Deep Learning Technique." The authors have identified errors in the figures and main body paragraphs of the paper and have provided corrected versions of the figures. They have also made changes to the abstract and introduction sections. The paper discusses the use of a drone to detect and analyze transmission line components for defects, utilizing deep learning techniques and convolutional neural networks. The authors acknowledge the errors in the original paper and apologize for any confusion caused. The research is funded by the Korean Ministry of the Interior and Safety. The authors of the paper are Zahid Ali Siddiqui and Unsang Park. [Extracted from the article]

The architectural and construction professions are in a state of major transition. While wooden structures are known to have superior energy saving properties as compared with RC structures, this study establishes that hybrid refurbished structures in which RC beams and columns are retained, while floors and walls are replaced by new timber laminates, results in lighter, cheaper buildings, with energy performance superior to the replaced fully RC structures, yet only marginally less efficient than full wooden buildings. The fifth paper, "Automatically creating HVAC control strategies based on building information modeling (BIM)", Ref. [[6]] presents a method for optimizing building heating using BIM data. The imperative that the industry must embrace is "sustainability", and with that imperative is the requirement to develop applications that make buildings energy-efficient, eco-friendly, resilient, inclusive, and overall "greener". [Extracted from the article]

Urban waste heat recovery, in which low temperature heat from urban sources is recovered for use in a district heat network, has a great deal of potential in helping to achieve 2050 climate goals. For example, heat from data centres, metro systems, public sector buildings and waste water treatment plants could be used to supply 10% of Europe's heat demand. Despite this, at present, urban waste heat recovery is not widespread and is an immature technology. Based on interviews with urban waste heat stakeholders, investors interested in green investments, and experience from demonstrator projects, a number of recommendations are made. It is suggested that policy raising awareness of waste heat recovery, encouraging investment and creating a legal framework should be implemented. It is also recommended that pilot projects should be promoted to help demonstrate technical and economic feasibility. A pilot credit facility is suggested aimed at bridging the gap between potential investors and heat recovery projects. [ABSTRACT FROM AUTHOR]

Green practices are social practices that aim to harmonize the relations between people and the natural environment. They may involve minimizing the use of resources and the generation of waste and emissions. Detecting green practices in social media posts helps to understand which green practices are currently common and to develop recommendations on the scaling of green practices to reduce environmental problems. This paper describes GreenRu, a novel Russian social media dataset for detecting the mentions of green practices related to waste management. It has a sentence-level markup and consists of 1326 posts collected in Russian online communities. The total number of mentions of green waste practices is 3765. The paper assessed the effectiveness of the multi-label and one-versus-rest BERT-based models for detecting the mentions of green practices in social media posts and compared several data augmentation methods in terms of both classification metrics and human evaluation. To augment the dataset, a backtranslation method and generative language models, such as RuGPT, RuT5, and ChatGPT, were used in this study. The results enable researchers to monitor the green waste practices on social networks and develop environmental policies. Additionally, GreenRu can support machine learning models to analyze social media content, assess the prevalence and effectiveness of green waste practices, and identify ways to expand them. [ABSTRACT FROM AUTHOR]

The green transition in the sustainable production and processing of polymers poses multifaceted challenges that demand integral comprehensive solutions. Specific problems of presences of toxic trace elements are often missed and this prevents shifting towards eco-friendly alternatives. Therefore, substantial research and the development of novel approaches is needed to discover and implement innovative, sustainable production materials and methods. This paper is focused on the most vital problems of the green transition from the aspect of establishing universally accepted criteria for the characterization and classification of eco-friendly polymers, which is essential to ensuring transparency and trust among consumers. Additionally, the recycling infrastructure needs substantial improvement to manage the end-of-life stage of polymer products effectively. Moreover, the lack of standardized regulations and certifications for sustainable polymers adds to the complexity of this problem. In this paper we propose solutions from the aspect of standardization protocols for the characterization of polymers foreseen as materials that should be used in Zero Energy Innovations in Hydrogen Storage. The role model standards originate from eco-labeling procedures for materials that come into direct or prolonged contact with human skin, and that are monitored by different methods and testing procedures. In conclusion, the challenges of transitioning to green practices in polymer production and processing demands a concerted effort from experts in the field which need to emphasize the problems of the analysis of toxic ultra trace and trace impurities in samples that will be used in hydrogen storage, as trace impurities may cause terrific obstacles due to their decreasing the safety of materials. Overcoming these obstacles requires the development and application of current state-of-the-art methodologies for monitoring the quality of polymers during their recycling, processing, and using, as well as the development of other technological innovations, financial initiatives, and a collective commitment to fostering a sustainable and environmentally responsible future for the polymer industry and innovations in the field of zero energy applications. [ABSTRACT FROM AUTHOR]

This paper undertakes a comprehensive review to underscore the central role of sustainability in the evaluation and innovation of jet grouting technologies. It meticulously traces the evolution of evaluation methodologies, emphasizing the imperative of sustainable practices throughout history. Traditional evaluation paradigms are examined alongside contemporary trends, with a particular focus on sustainability metrics and visualization techniques. Through an examination of innovative jet grouting technologies, this paper illustrates how sustainability principles have driven advances aimed at improving the efficiency and environmental impact of jet grouting methods. Central to this review is an assessment of sustainability across multiple dimensions, including method applicability, installation and operational compatibility, and the performance of the resulting jet grouted piles. By emphasizing sustainability considerations, the paper highlights the intrinsic link between environmental integrity and technological innovation in the field of jet grouting. In addition, it discusses analytical evaluation methods designed to proactively address sustainability concerns prior to construction, thereby promoting a more environmentally responsible approach. Finally, this paper presents a pioneering evaluation framework that integrates real-time monitoring and visualization tools, allowing stakeholders to track sustainability milestones throughout the construction process. By emphasizing sustainability as a guiding principle, this review advocates for a paradigm shift toward more ecologically sound and resilient jet grouting practices. [ABSTRACT FROM AUTHOR]

The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China's urban industrial green TFPs as derived from the STE-SRM, employing Dagum's Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China's urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China's urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China's urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods. [ABSTRACT FROM AUTHOR]

Nowadays, one of the main challenges facing green innovation management is how to enhance the performance of innovation processes by utilizing asymmetric input and output data. Therefore, this paper develops an improved SBM model analysis framework for evaluating the green innovation efficiency of asymmetric input and output data. The framework is applied to assess the technical (TE), managerial (PTE), and scale (SE) efficiencies of new energy companies under three input variables (R&D personnel input, R&D capital input, and comprehensive energy consumption input), two desirable output variables (green technology output and economic output), and one undesirable output variable (greenhouse gas emissions). Then, environmental factors and random factors are eliminated from the obtained input slack variables based on the SFA model, placing decision-making units in a homogeneous environment. The results demonstrate that TE, PTE, and SE are improved after eliminating environmental factors and random factors. Subsequently, based on the entropy method, this paper classifies companies' green innovation patterns into four categories and provides targeted solutions. The purpose of this paper is to provide an evaluation method for new energy companies to understand green innovation efficiency and assist decision makers in identifying the most optimal resource allocation approach. The proposed improved SBM model contributes to the literature and to industry practice by (1) providing a reliable evaluation of green innovation efficiency under asymmetric input and output data; (2) determining effective improvement actions based on a slack analysis of environmental variables and random variables that lead to improved process performance; and (3) making fuzzy innovation performance efficient to facilitate understanding and managing innovation resource allocation quality. [ABSTRACT FROM AUTHOR]

Garbage classification is significant to alleviate the pressure of household waste management in rural areas and promote green development. Based on the micro survey data of 2228 households in rural areas of Jiangsu Province, this paper discusses the impact of internet use on the garbage classification's willingness and behavior based on the planned behavior theory. The results show that: (1) There is a deviation between willingness and behavior. Ninety percent of the surveyed farmers were willing to do garbage classification, but the garbage classification rate was only 53%. (2) Internet use has a positive effect on the willingness and behavior of farmers to classify garbage, and it can promote the willingness to change behavior and reduce the deviation between willingness and behavior. Specifically, internet use increased by 1 unit, the probability of farmers having neither willingness nor behavior, having both willingness and behavior, and only having willingness but not having the behavior decreased by 5.4%, increased by 13%, and decreased by 7.5%, respectively. (3) Further analysis according to different internet access methods shows that mobile internet access and mixed internet access can have a positive impact on farmers' willingness and behavior in relation to garbage classification, while computer internet access has no significant impact on farmers' willingness and behavior in relation to garbage classification. (4) Internet use can enhance farmers' willingness and behavior in relation to garbage classification by improving their knowledge, behavioral, and environmental cognition. Specifically, the mediating effects of knowledge, behavioral, and environmental cognition on willingness were 71.48%, 21.72%, and 40.49%, respectively, and the mediating effects on behavior were 89.47%, 8.89%, and 18.81%, respectively. Based on this, this paper puts forward the policy recommendations of strengthening the hardware and software construction of the internet, adopting diversified propaganda methods of garbage classification, and improving the social supervision and restraint mechanism. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to propose an improved hesitation fuzzy multi-attribute decision-making method to realize green supply chain member selection under green innovation vision. The method uses hesitation fuzzy sets to express decision information of decision makers, takes green innovation capability as the evaluation perspective, and selects green innovation input, synergy of subjects in green supply chain, green innovation output capability, institutional innovation capability of enterprises in green supply chain, and green innovation sustainability as the indexes to evaluate the green innovation capability of enterprises. The multi-attribute decision method proposed in this paper takes into account the shortcomings of the original hesitant fuzzy multi-attribute decision method considering attribute weight optimization in the determination of attribute weights and scheme ranking, then proposes a three-point estimation method for scheme ranking and optimizes the attribute weights by quantifying the balance coefficients of the original decision method. Finally, an example is used to verify the rationality and effectiveness of the proposed method, and a comparison with the original method is made to highlight the advantages of this paper's method. This paper provides a certain theoretical basis for the selection of members in green supply chains, which helps the selection of members in green supply chains and provides some insight for similar hesitant fuzzy multi-attribute decision-making problems in other fields. In future research, the method proposed in this paper can be considered to combine with probabilistic hesitant fuzzy sets and some other fuzzy sets for method extensions to solve multi-attribute decision-making problems. [ABSTRACT FROM AUTHOR]

Under the influence of the dual policies of sustainable economic development and the national dual-carbon target, the establishment of an environmental protection department for the treatment of heavily polluting industries is imminent, and the country has launched pollution control policies and regulations to restrict the emission rights of heavily polluting industries. Therefore, this paper focuses on whether the restriction of emission rights in key industries has reduced carbon emissions. To achieve this, this paper uses panel data of prefecture-level cities in China from 2006 to 2019 and adopts a two-way fixed-effects DID model to systematically analyze the impact of the key pollution industry governance policies launched by the Ministry of Environmental Protection on CO2 emissions in 2017. And further analyze the role of variables such as green technology innovation patents and energy efficiency using this model, while parallel trend tests and placebo tests, and related policies are used to ensure the robustness of the regression results. This paper reveals that: (1) The heavy pollution industry governance policy implemented in 2017 can effectively reduce CO2 emissions in the cities of the treated group, and the effect is more significant in the year of policy implementation; (2) Green utility patents and energy-use efficiency are the effective mediating mechanisms to reduce CO2 emissions; (3) Over time, the effect of heavy pollution industry governance policy on CO2 emissions gradually decreases; (4) The reliability of the baseline regression results of this paper is proved by the use of parallel trend tests, placebo tests, and tests excluding the influence factors such as relevant policies in the same period. Therefore, the key polluting industries treatment policy launched by China's Ministry of Environmental Protection in 2017 under the recent dual-carbon policy development goals formulated by China, can effectively reduce carbon emissions; however, in the future economic development process, the government should give more consideration to the continuity of the policy impact and its coherence on economic development when implementing the policy. [ABSTRACT FROM AUTHOR]

A major goal of the "14th Five-Year Plan" phase is to promote the green transformation of industrial enterprises to address the 'dual carbon' challenge. Utilizing the China Industrial Enterprises Database and the Polluting Enterprises Database, this paper calculates the carbon emissions of Chinese industrial enterprises from 2001 to 2010 at the micro level. It presents an analysis of the heterogeneity of carbon emission efficiency (TPI) in industrial enterprises, as well as the factors influencing corporate TPI. This study finds that enterprises within a subdivided industry exhibit heterogeneous levels of TPI, with carbon emissions largely affected by the structure of energy consumption. The researchers suggest accelerating the transition of industrial enterprises to green technology and argue that carbon emission policies should shift from controlling direct total targets to strengthening market-oriented policy tools. Carbon reduction targets should be more stringent for enterprises with lower TPI, considering the heterogeneity among enterprises. To meet the challenges of emission reduction, industrial enterprises are encouraged to actively reform their energy consumption structure. Government policies should aim to reduce clean energy costs and encourage the use of clean energy by industrial enterprises. [ABSTRACT FROM AUTHOR]

Nudging the adoption of agricultural green production technologies (AGPTs) by cotton farmers is a practical need to implement the national "green development" strategy. Based on the micro-survey data of 502 cotton farmers, this paper empirically analyzed the influence and driving mechanism of cotton farmers' participation in cooperatives on their adoption of green production technology from the perspective of their inner cognition and external regulation by using the propensity score matching (PSM) model and the intermediary effect model. The study found that (1) the importance of agricultural green production technology to cotton farmers was in the order of soil testing and formula fertilization technology, green prevention and control technology, deep tillage technology, water-saving irrigation technology, new variety technology, and straw-returning technology. (2) Participation in cooperatives can significantly improve the adoption of agricultural green production technologies by cotton farmers, with an increase of about 27.16%, and the improvement effect on technology-intensive production links is pronounced. (3) By improving the inner cognition and external regulation of cotton farmers, cooperatives can enhance the green endogenous power of cotton farmers, improve environmental external constraints, and become an intermediary path to guide cotton farmers to adopt agricultural green production technology. [ABSTRACT FROM AUTHOR]

The emergence of new transformational technology, known as the fourth industrial revolution, has crucially opened a new window to green economic growth. The transition to low carbon, green economy, and green sustainability has gained momentum simultaneously in developed and developing countries. The greening policy echoes the pending climate change and its entrenching disruptions. Financial technology, or FinTech seems to be a promising direction in unlocking the green dilemma; to be concrete, FinTech and the green economy are separately documented in the literature. Against this background, the current study investigates the intersection between green economic growth and FinTech by conducting a systematic-cum-bibliometric analysis of published papers in the Scopus database with the goal of first examining the role and opportunities of implementing green FinTech as a stimulus for transition towards green economic growth in African countries and, second, identifying knowledge gaps and future policy and research directions by developing an integrated framework to help African countries in the transition to green economic growth and green FinTech. The results illustrate an increasing trend in research attention towards the green FinTech concept and its relationship with green economic growth, climate change, and greening rules and standards. A deep inspection of the mined papers indicates that future research trajectories are oriented into five different mainstreams: technology and instruments in digital finance; regulation, policies, and green FinTech; climate risk mitigation through FinTech; FinTech and environmental quality; green finance and climate change mitigation. Based on these research directions, an integrated framework was conceptualised that aims to deliver green economic growth using FinTech as a vehicle of transition for African countries. [ABSTRACT FROM AUTHOR]

Supply chain green technology collaborative innovation is an important means for enterprises to improve the greenness of their products. This paper takes supply chain green technology innovation collaboration as the research object and constructs a stochastic differential game model, which not only provides reference for enterprises to choose the optimal type of technology innovation by combining with their own characteristics, but also provides a reference for their innovation decision-making in different market competition environments. The study shows the following: (1) in green product innovation, the formation of the cost-sharing contract is less affected by the intensity of competition in the green market when the market preference for greenness is relatively low. Therefore, government subsidies become an important tool to effectively guide the market mechanism to achieve the desired goal. As market competition intensifies, manufacturers' incentives to suppliers will shift from reducing costs to increasing demand. (2) In green process innovation, when the intensity of green competition is low and suppliers' process innovation efficiency is high, manufacturers should bear more costs; when the market preference for greenness is low, the market competition is intense, and the suppliers' process innovation efficiency is low, the suppliers should bear more costs to help the manufacturers gain more market shares. (3) When retailers' preference for greenness is relatively low, the government subsidy becomes an important tool to effectively guide the market mechanism to achieve the desired goal. (4) When the retailer's green promotion performance is higher than the manufacturer's, the manufacturer should bear more green promotion costs; conversely, the retailer should bear more green promotion costs. (5) Over time, the marginal increase in price over the marginal increase in greenness helps stabilise price volatility, considering consumer preferences. Conversely, it helps to increase the average value of prices. [ABSTRACT FROM AUTHOR]

Solid-state batteries (SSBs) have emerged as a promising alternative to conventional lithium-ion batteries, with notable advantages in safety, energy density, and longevity, yet the environmental implications of their life cycle, from manufacturing to disposal, remain a critical concern. This review examines the environmental impacts associated with the production, use, and end-of-life management of SSBs, starting with the extraction and processing of raw materials, and highlights significant natural resource consumption, energy use, and emissions. A comparative analysis with traditional battery manufacturing underscores the environmental hazards of novel materials specific to SSBs. The review also assesses the operational environmental impact of SSBs by evaluating their energy efficiency and carbon footprint in comparison to conventional batteries, followed by an exploration of end-of-life challenges, including disposal risks, regulatory frameworks, and the shortcomings of existing waste management practices. A significant focus is placed on recycling and reuse strategies, reviewing current methodologies like mechanical, pyrometallurgical, and hydrometallurgical processes, along with emerging technologies that aim to overcome recycling barriers, while also analyzing the economic and technological challenges of these processes. Additionally, real-world case studies are presented, serving as benchmarks for best practices and highlighting lessons learned in the field. In conclusion, the paper identifies research gaps and future directions for reducing the environmental footprint of SSBs, underscoring the need for interdisciplinary collaboration to advance sustainable SSB technologies and contribute to balancing technological advancements with environmental stewardship, thereby supporting the transition to a more sustainable energy future. [ABSTRACT FROM AUTHOR]

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

Nanotechnology has seen increased research and implementation in recent decades in numerous applications. Based on the information in the papers, we built a database that included algae species used, biomass pre-processing, main precursors, solvents, production approaches, final size, and possible uses. An analysis of this data revealed a great diversity of algae species investigated for this purpose (68 species of algae and 45 families). The analysis of the strategy plot shows that there are four clusters of themes that are different from each other. Still, some patterns are recognizable, e.g., the general cluster with general methodologies and concepts is in the intersection zone. The second cluster is related to the use of macroalgae, which has had a strong development in the past, but now seems to be less attractive, and the third cluster is on the use of nanoparticles to control bacteria, which seems to be a topic that, although not currently driving the field, could become a major driver if current trends continue. New technological developments should be expected in the near future as NPs synthesis from green renewable sources such as algae poses an alternative to the traditional means in the coming years. [ABSTRACT FROM AUTHOR]

In recent years, many industries have adopted technology and digital systems to automate, expedite and secure specific processes. Stakeholders in maritime transport continue to exchange physical documents in order to conduct business. The monitoring of supply chain goods, communication among employees, environmental sustainability and longevity control, along with time framing, all create challenges to many industries. Everyday onboard work, such as cargo operations, navigation and various types of inspections in shipping, still requires paper documents and logs that need to be signed (and stamped). The conversion of traditional paper contracts into smart contracts, which can be digitalized and read through automation, provides a new wave of collaboration between eco systems across the shipping industry. Various data collected and stored on board ships could be used for scientific purposes. Distributed ledger technology (DLT) could be used to collect all those data and improve shipping operations by process expediting. It could eliminate the need to fill in various documents and logs and make operations safer and more environmentally friendly. Information about various important procedures onboard ships could be shared among all interested stakeholders. This paper considers the possible application of distributed ledger technology as an aid for the control of overboard discharge of wastewater from commercial ships. The intended outcome is that it could help protect the environment by sending data to relevant stakeholders in real time, thus providing information regarding the best discharge areas. The use of a structured communal data transference would ensure a consistent and accurate way to transmit data to all interested parties, and would eliminate the need to fill in various paper forms and logs. Wastewater overboard discharges would be properly monitored, recorded and measured, as distributed ledger technology would prevent any possibility of illegal actions and falsification of documents, thus ensuring environmental sustainability. [ABSTRACT FROM AUTHOR]

Enhancing environmental regulation (ER) is an effective way to improve the green innovation efficiency (GIE) of the Yangtze River Economic Belt (YREB) and the key to achieving the target of carbon peaking and neutrality. Using the data of 103 cities in YREB in 2013–2019, this paper explores the effect of heterogeneous ER on GIE. The results of the study are as follows: first, we categorize environmental regulations into formal and informal environmental regulations and explore their impact on green innovation efficiency separately. The results show that both formal and informal environmental regulations can effectively promote GIE in the YREB urban agglomeration. Second, the Spatial Durbin Model (SDM) model is used to analyze the spatial effect. The results show that there are spatial effects between heterogeneous environmental regulations and GIE, and environmental regulation can significantly strengthen GIE through positive spatial effects. Third, this paper uses the threshold model to explore the non-linear relationship between environmental regulation and green innovation efficiency. The results show that as ER increases, the positive effect on GIE increases, and this interesting finding holds for both formal and informal environmental regulations. Fourth, the mediating effect model is used to examine whether green technological innovation and industrial structure upgrading exert mediation effects on how environmental regulations affect GIE. The research results can provide effective policy recommendations to promote the green development of the cities in YREB. [ABSTRACT FROM AUTHOR]

With the development of the manufacturing industry, environmental problems have become more and more serious. At present, green design is playing an increasingly important role in product design and manufacturing. How to combine traditional conceptual design methods with green designs to realize green conceptual design is of great practical significance. In order to realize the green concept design of a product and to allow the conceptual design scheme to meet the functional requirements and green performance requirements of the product at the same time, this study introduces the knowledge push process and the green filter process into product concept design. The knowledge of invention principles is retrieved by establishing the knowledge space of invention principles, by calculating the word segmentation based on the CRF (conditional random field), and calculating the word similarity using a thesaurus. This is performed in order to realize the transformation from product function requirements to invention principle knowledge. Then, by studying the relationship among the environmental efficiency factors, green design attributes, engineering technical parameters, and invention principles, the correlation mapping table for green design attributes and invention principles is established. Thus, the green filter is applied to the pushed knowledge according to the green performance requirements, so that the final push results after filtering can meet the functional and green performance requirements of the product. In the last section of this paper, a green concept design for cutting the fluid supply system in an enterprise is presented as an example to verify and analyse the proposed method. [ABSTRACT FROM AUTHOR]

The digital economy is a key driver of greener agriculture and sustainable development. This paper focuses on the impact of the digital economy on green agricultural development and the mediating role of green technology innovation. Using provincial panel data from China from 2011 to 2020, we test hypotheses using fixed effects models. The results indicate that: (a) the digital economy boosts agricultural total factor productivity (AGTFP); (b) green technology innovation positively moderates the relationship between the digital economy and AGTFP; and (c) the positive impact of the digital economy on green agriculture varies across regions, favoring eastern areas. [ABSTRACT FROM AUTHOR]

Environmental regulatory instruments are key to achieving synergy between high-quality economic development and ecological civilization construction. This paper measures the green overall factor productivity of the forestry in the Yangtze River Economic Belt by using the super-efficient nonexpected output SBM-ML index model. Additionally, it investigates the environmental regulation's impact on forestry's overall green factor productivity by using the conventional panel regression and panel smooth transformation model. The model was based on the relevant data obtained from eleven provinces along the Yangtze River Economic Belt in China from 2006 to 2021. This study concludes that command-and-control regulation of the environment and public engagement with environmental regulation can significantly promote the forestry green overall factor productivity in the Yangtze River Economic Belt, and the environmental regulation's effects on the forestry green overall efficiency in the economic region of the Yangtze River are regionally and temporally heterogeneous. The command-and-control environmental regulation also needs to exceed a certain level of regulatory coercion to promote the forestry green overall factor productivity positively. The effects of market-incentive environmental regulation were more pronounced with the increase in the regulatory intensity. When the regulation intensity surpasses the threshold, the public participation form of environmental regulation has a depressing impact on the forestry green overall factor output. To promote the development of the forestry industry in the Yangtze River Economic Zone, it is therefore necessary to strengthen the coordination of different environmental regulations, implement measures in each region, build a market-oriented green innovation system, and promote the structuralization and upgrading of the forestry industry. [ABSTRACT FROM AUTHOR]

This study aimed to systemize global scholarly publications on corporate social responsibility and renewable energy to detect their influence on green brand development within the SDGs. The initial data are retrieved from the Scopus database. To operate with the most relevant publications, several limitations were applied. The research sample consists of the 2000 most cited articles in the subject areas of (1) Social Sciences, (2) Business, Management, and Accounting, and (3) Economics, Econometrics, and Finance. This study is carried out in the following logical sequence. The first stage involves searching, collecting, and preprocessing articles representing the investigated topic. Then, several bibliometric techniques were employed to analyze and map the findings. The third stage integrated the obtained results and discussed future research directions. This paper offers some theoretical implications by analyzing and visualizing the investigated scientific output, particularly publication dynamics, the main trends in the investigated research field, the most productive scholars and their collaborations, and the contributions of the journals, affiliations, and countries analyzed. In addition, this study makes some practical contributions and could be used by scholars as detailed instructions for conducting bibliometric analyses in different contexts. Furthermore, researchers could exploit and expand their current study directions using the findings of this paper. However, the findings of this study are limited since they consider only articles from the Scopus database. Therefore, it is appropriate that further studies involve a broader data range. [ABSTRACT FROM AUTHOR]

With the development of a low-carbon economy, zero-energy structures will become prevalent and take center stage in the construction industry. This paper uses the CiteSpace software to create knowledge maps of authors, institutions and keywords, and then examined and commented on research publications regarding zero-energy buildings in order to understand the research state and development trends of zero-energy buildings. The findings demonstrate that: (1) Since its inception in 2000, research on zero-energy buildings has advanced significantly; (2) A subject analysis approach is used to identify development trends and research emphasis, and the four research areas with the most papers published are energy fuels, construction building technology, civil engineering and green sustainable science technology; (3) China, the United States and Italy are the countries with the most activity in zero-energy building research; (4) Out of the eight most prominent keywords for the study subjects, the design of zero-energy buildings, the estimation of the carbon emissions of zero-energy buildings, the technical challenges of zero-energy buildings and the follow-up energy-saving measures of zero-energy buildings are the four fundamental topics covered in the most cited papers; (5) There are three obstacles to the development of zero-carbon buildings: unclear standards, immature technology and insufficient development momentum. The following three problems should receive more attention in the future: how to develop a widely accepted zero-carbon building standard; how to coordinate national support to achieve technological breakthroughs; and the establishment of an effective incentive mechanism at the international and national levels to promote the development of zero-carbon buildings. [ABSTRACT FROM AUTHOR]

In this paper, we explore the integration of building information modeling (BIM) technology to assess carbon emissions, emphasizing the unique contributions to smart and sustainable approaches in prefabricated buildings and focusing on the application of digital construction strategies facilitated by BIM to evaluate carbon emissions in green prefabricated buildings, with a detailed case study on C-House at Southeast University, Nanjing, China. The research methodology involved creating a BIM model of C-House in Rhino and collecting data from the operationalization phase. This research work delves into analyzing the structural components, on-site assembling process, and evaluation of carbon emissions by using a BIM-based assessment, as well as the energy load and consumption of prefabricated components, including sustainable PV panels, to enhance building efficiency and sustainability. The findings uncover the life cycle of C-House, which spans seven stages, compared with the five stages of conventional builds. Currently in its third cycle, C-House exhibits significant reductions of 70.57% in carbon emissions during the second cycle and 43.53% in the first one. This highlights the pattern showing that the prolonged reuse of prefabricated buildings leads to decreasing emissions over time. Such results underscore the potential carbon emission reductions and environmental advantages of reusing green prefabricated buildings. Furthermore, this study provides insights into the entire life cycle of the building, from inception to occupation and post-phase performance evaluation. By employing BIM for modeling, simulation, and analysis, we offer practical insights into the application of smart technologies for sustainable construction practices, significantly contributing to the advancement of green and digital construction technologies. [ABSTRACT FROM AUTHOR]

The foundry industry is responsible for the production of several potentially polluting and hazardous compounds. One of the major sources of pollution is the use of organic binders for the manufacturing of sand cores and sand moulds. To address this problem, in recent years, the use of low-emission products, known as inorganic binders, has been proposed. Their use in ferrous foundries, otherwise, is limited due to some problematic features that complicate their introduction in the manufacturing process, as often happens when a breakthrough innovation is introduced. In light of this, the aim of this work is to provide a Green Innovation Practice (GIP) to manage the introduction of green breakthrough innovations, as previously described, within an existing productive context. This practice was applied to better manage the experimental phase of the Green Casting Life Project, which aims to evaluate the possibility of using inorganic binders for the production of ferrous castings. After describing the state of the art of GIPs and their application in manufacturing contexts, the paper described the proposed GIP and its application to a real case consisting of testing inorganic binders in a ferrous foundry. [ABSTRACT FROM AUTHOR]

Amid China's pursuit of a green and low-carbon transition, corporate social responsibility (CSR) is facing new challenges. Our research delves into the influencing factors and mechanisms for CSR reputation under green and low-carbon transition and provides practical enlightenment for enterprises to achieve sustainable development. This paper constructs a comprehensive index system of CSR from five dimensions (innovation, coordination, sustainability, openness, and sharing), and CSR reputation of China's A-share listed companies is comprehensively estimated by using an entropy method and data from 2013 to 2021. Then, from the perspective of external supervision and internal governance, we discuss the influence factors of CSR reputation, with an emphasis on the impact of public environmental concerns. Finally, the realization mechanism of CSR is further revealed. It is found that public environmental concern and the expansion of the enterprise scale boost the enhancement of CSR reputation. However, a higher proportion of female managers tends to hinder CSR reputation. Furthermore, public environmental concern plays a more prominent role in improving CSR reputation of non-state-owned and eastern enterprises. Additionally, public environmental concern significantly enhances CSR reputation through green technology innovation and executive environmental awareness. This research provides valuable insights for improving CSR reputation and optimizing regulatory compliance and governance practices. [ABSTRACT FROM AUTHOR]

Accurate urban green space (UGS) measurement has become crucial for landscape analysis. This paper reviews the recent technological breakthroughs in deep learning (DL)-based semantic segmentation, emphasizing efficient landscape analysis, and integrating greenness measurements. It explores quantitative greenness measures applied through semantic segmentation, categorized into the plan view- and the perspective view-based methods, like the Land Class Classification (LCC) with green objects and the Green View Index (GVI) based on street photographs. This review navigates from traditional to modern DL-based semantic segmentation models, illuminating the evolution of the urban greenness measures and segmentation tasks for advanced landscape analysis. It also presents the typical performance metrics and explores public datasets for constructing these measures. The results show that accurate (semantic) segmentation is inevitable not only for fine-grained greenness measures but also for the qualitative evaluation of landscape analyses for planning amidst the incomplete explainability of the DL model. Also, the unsupervised domain adaptation (UDA) in aerial images is addressed to overcome the scale changes and lack of labeled data for fine-grained greenness measures. This review contributes to helping researchers understand the recent breakthroughs in DL-based segmentation technology for challenging topics in UGS research. [ABSTRACT FROM AUTHOR]

The construction industry is in urgent need to transition away from its rough development and management practices. It is essential to embrace a sustainable development path to enhance core competitiveness, promote resource intensification, and prioritize environmental friendliness. The digital transformation uses information and data as the key elements to promote the transformation of traditional industries to become more intelligent and green. This ushers in new opportunities for transformation in the construction industry, marking a significant turning point for its evolution. This paper explores the impact of digital transformation on the green development of construction companies and its inner mechanism. Based on the panel data of the listed companies in China's construction industry from 2015 to 2021, the two-way fixed effect, mediating effect, moderating effect, and threshold effect models are used to test the relationship between them. The results indicate that digital transformation significantly promotes the green development of construction companies. Additionally, this result still holds after robustness and endogeneity tests. This effect is more significant in state-owned, larger companies situated in regions with weaker digital economy development. In addition, the intensity of regional environmental regulations strengthens the impact of digital transformation on green development. However, it has a threshold effect. In the test of mediating effect, it has been found that green innovation and corporate human capital structure can serve as mediators. In the general trend of digital change, the drive towards the sustainable development of construction companies offers micro-empirical evidence that the digital economy empowers green development in China. [ABSTRACT FROM AUTHOR]

With the progress of urbanization in China, the energy-saving renovation of a large number of existing buildings, especially old buildings, has become an important project for the green and low-carbon development of urban renewal. This paper takes the old brick school building in a university in Chengdu as an example. Through field research, the existing problems of the building are analyzed in detail in terms of building function, structure and appearance, and a detailed plan for functional upgrading, structural reinforcement and façade renovation is drawn up, taking into account the actual requirements and environmental status. In addition, solar photovoltaic technology is integrated into the renovation of the building's pitched roof. Through modelling and analysis, the amount of solar energy captured by the photovoltaic roof is quantitatively simulated and the dynamic energy-saving potential of the renovation project under changing actual meteorological conditions is pre-evaluated. The preliminary results indicate that such green renovations can contribute to about 164,066 kWh annual solar energy collection and the self-use electricity from the PV roof accounts for 42–76% of total energy consumption, leading to about 60% building energy consumption conservation. The payback period of such a renovation program is assessed to be about 1.9 years, which is quite economically feasible considering the local energy tariff policy. This paper explores the feasibility and design direction of green and low-carbon renovation and upgrading of old buildings, which can provide a reference for the application of green and low-carbon renovation of local old buildings. [ABSTRACT FROM AUTHOR]

To achieve high-quality corporate development, it is essential to undergo green transformation. Unlike previous literature, this paper explores relevant mechanisms affecting firms' green transformation from a novel perspective of green credit guidelines (GCG). Using A-share listed industrial enterprises in China from 2010 to 2020 as a sample, we combine the generalized moment estimation model (GMM) with the difference-in-difference model (DID) and demonstrate that (1) GCG significantly promotes enterprises' green transformation measured by the method of super-efficient Slacks-Based Measure and Data Envelopment Analysis (SBM-DEA). (2) GCG tends to improve green technology innovation, which further facilitates firms' green transformation, and corporate social responsibility (CSR) reinforces the positive relationship between GCG and firms' green transformation. Correspondingly, we provide policy recommendations for China and other developing countries. [ABSTRACT FROM AUTHOR]

Corporate greenwashing in response to carbon neutrality strategies has received substantial academic attention. Distinct from previous studies, this paper establishes a differential game model incorporating both green and brown enterprise types. The model compares greenness and total profits under two government scenarios: subsidies for green enterprises and the regulation of brown enterprises. It further analyzes the mechanism behind brown enterprise greenwashing formation. The results show that subsidies alone encourage brown enterprises to engage in greenwashing. However, government regulation inhibits such behaviors, with the inhibition effect positively correlated to regulatory intensity. Consumers' green perception of enterprises also significantly drives brown enterprise greenwashing degrees. Higher green enterprise perception coefficients reduce greenwashing, while higher brown enterprise perception coefficients increase it. Differential game and simulation analyses reveal that greenwashing governance should consider both direct policy effects on brown enterprises and indirect subsidy effects on green enterprises. [ABSTRACT FROM AUTHOR]

The spillover effects of climate change require the exploration and implementation of appropriate ways to reduce ecological issues while simultaneously maintaining economic and social well-being. The expansion of green energy allows for a reduction in the negative anthropogenic impact on the environment without restricting economic growth or social welfare. However, the expansion of green energy necessitates additional green investment. This paper aims to provide a comprehensive bibliometric analysis of studies on the interactions between green energy and green investment. The study is based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and employs Scopus Tools Analysis and VOSviewer version 1.6.20 software. The metadata for the investigation were compiled from scientific databases in Scopus. The findings allow for the identification of the most prolific countries and authors and their collaborative efforts, which contribute to the theoretical landscape of green energy and green investment. The study also illustrates the evolution of the investigation of the linkages between green energy and green investment. Furthermore, the results enable the identification of core scientific clusters in the analysis of green energy and green investment: the first cluster focuses on renewable energy and sustainable development; the second on government and green energy; and the third on green investment as the catalyst for green energy. The results of the meta-analysis facilitate the identification of new research areas related to the connection between green investment and green energy. [ABSTRACT FROM AUTHOR]

The integration of green design into building construction is a necessary process in today's world to address environmental issues and achieve sustainable development. However, when evaluating green building design schemes, various factors are intertwined with a high degree of complexity and uncertainty. To realise rational decision-making about green building design schemes, this paper first adopts the mixed techniques of triangular fuzzy numbers, quality function deployment, and Best–Worst Method. It aims to analyse the complex factor relationship between customer needs and green building design technical features and to solve the optimal green building design index weight allocation. Next, a hybrid fuzzy multi-criteria decision-making (MCDM) method integrating triangular fuzzy numbers, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, and Grey Correlation (GC) are proposed to evaluate green building design scheme performance. Finally, an example of a green design project for a hotel building is selected for application validation and analysis in comparison with the existing Complex Proportional Assessment, VlseKriterijuska Optimizacija I Komoromisno Resenje, and DEMATEL-ANP methods. These analyses demonstrate the stability and validity of the results, as well as the rationality and practicability of the proposed triangular fuzzy QFD–MCDM method. This research is a guide to the problem of evaluating green building design schemes. [ABSTRACT FROM AUTHOR]

Three-dimensional concrete printing (3DCP) is a sustainable and green approach for rapid construction with the ability to create complex shapes to preserve the intended aesthetic appearance for an affordable cost. Even after a decade of attempts, there are many limitations and challenges to applying this technology for constructions without borders. The lack of guidelines for mix designs, quality control procedures during extrusion, printing and building phases, compatibility of material with extruder, standard testing, and guidelines to verify suitability of mixture with respect to the application and exposure conditions and limited machine capacity are several areas to be addressed for applications without borders. The development of 3DCP applications as a sustainable and green technology is another challenging task due to high Portland cement consumption in 3DCP. However, reducing the high usage of ordinary Portland cement (OPC) with pozzolanic waste materials replacement and environmentally friendly cement indicates the direction of moving 3DCP into a sustainable pathway. The authors reviewed more than 200 refereed articles published on materials and techniques in 3DCP. Inconsistency in disseminating knowledge in research articles has hindered the creation of a monolithically connected chain of research efforts and findings in accelerating the development and adoption of this technology. This paper summarizes the common approach to developing 3DCP mix designs and identifies the key areas for the future development of materials and techniques and challenges to be addressed for the global adoption of 3DCP. The current progress and challenges in the context of Australia's construction industry and future trends for the acceptance of 3DCP are also reviewed. [ABSTRACT FROM AUTHOR]

The transformation of Chinese coal power firms is crucial for achieving carbon emission reduction (CER) goals, and promoting green technology innovation (GTI) is the key for the achievement. To examine the interactive mechanism of central and local government regulatory behavior and coal power firms' GTI behavior under China's dual-regulatory system, this paper introduces environmental impact coefficients and develops a tripartite evolutionary game model (EGM) from the perspective of CER. The influencing factors and interactive relationships among them are analyzed. Additionally, through numerical simulation, the impacts of changes in central and local government S&P (subsidies and penalties) on the evolution of the system are also obtained. The findings indicate the following: (1) Enhancing the initial willingness can accelerate the system's attainment of an optimal state. The local government exhibits a slower pace of evolution. Coal power firms are more sensitive to changes in the initial willingness of the central government. (2) The local government is more sensitive to changes in the central government's S&P intensity rather than changes in the central government's initial willingness. Low levels of central government S&P and high penalties are ineffective, while high subsidies can lead to a sudden decrease in the local government's willingness. (3) Local government penalties have a positive correlation with their effectiveness in promoting GTI, whereas high subsidies are ineffective. (4) The separate implementation of subsidies or penalties by either the central or the local government is detrimental to achieving the optimal state. Such an approach renders the fluctuant or negative behavior of the local government and coal power firms. [ABSTRACT FROM AUTHOR]

Guarantees of Origin (GOs) were introduced in order to enhance transparency about the origin of green electricity produced in Europe, and to deliberately empower end-consumers to participate in the sustainable energy transition. The separation of electricity and the GO trade has resulted in a prosperous GO market that, however, has been characterized by non-transparency and opportunistic behavior. Historic price development has been opaque and can therefore not be used to forecast future GO prices. This paper, firstly, provides a thorough overview of the European GO market and an analysis of the historic price development; secondly, it proposes a model, the first of its kind, for determining future price developments of European GOs for different renewable energy technologies in different countries up to 2040. For household consumers, GO price determination is based on willingness-to-pay estimates from the literature, whereas for non-household consumers, the model introduces a novel approach to determine the willingness to pay for green electricity. Four different scenarios are considered (Status Quo, Sustainable Development, Full Harmonization, and Ideal Development) and annual GO data are used. The findings indicate that GO prices can be expected to increase on average in the next years, with prices ranging from 1.77 to 3.36 EUR/MWh in 2040. Sensitivity analysis shows that 'WTP percentages' have the highest influence on GO prices. It can be concluded that future GO prices will remain challenging to predict, even with the support of sophisticated models, due to the expected supply and demand-driven market growth affecting the market equilibrium prices for different GOs in different countries. [ABSTRACT FROM AUTHOR]

Green hydrogen has been known in the UK since Robert Boyle described flammable air in 1671. This paper describes how green hydrogen has become a new priority for the UK in 2021, beginning to replace fossil hydrogen production exceeding 1 Mte in 2021 when the British Government started to inject significant funding into green hydrogen sources, though much less than the USA, Germany, Japan and China. Recent progress in the UK was initiated in 2008 when the first UK green hydrogen station opened in Birmingham University, refuelling 5 hydrogen fuel cell battery electric vehicles (HFCBEVs) for the 50 PhD chemical engineering students that arrived in 2009. Only 10 kg/day were required, in contrast to the first large, green ITM power station delivering almost 600 kg/day of green hydrogen that opened in the UK, in Tyseley, in July 2021. The first question asked in this paper is: 'What do you mean, Green?'. Then, the Clean Air Zone (CAZ) in Birmingham is described, with the key innovations defined. Progress in UK green hydrogen and fuel cell introduction is then recounted. The remarks of Elon Musk about this 'Fool Cell; Mind bogglingly stupid' technology are analysed to show that he is incorrect. The immediate deployment of green hydrogen stations around the UK has been planned. Another century may be needed to make green hydrogen dominant across the country, yet we will be on the correct path, once a profitable supply chain is established in 2022. [ABSTRACT FROM AUTHOR]

Featured Application: This paper presents a new, fifth industrial revolution (Industry 5.0)-inspired paradigm for educating and training Australian healthcare professionals and students in the field of digital health. By leveraging Industry 5.0-enabling technologies, such as artificial intelligence, machine learning, blockchain, big data analytics, etc., we can cultivate students to be job-ready for the future of work by providing them with hands-on experience in advanced healthcare technologies. Ultimately, this new training and education paradigm in digital health can help bridge the gap between training and the world of work and prepare students to deliver a more efficient, effective, and sustainable healthcare system. Digital transformation, characterised by advanced digitalisation, blockchain, the Internet of Things, artificial intelligence, machine learning technologies, and robotics, has played a key role in revolutionising various industries, especially the healthcare sector. The adoption of and transition (from traditional) to new technology will bring challenges, opportunities, and disruptions to existing healthcare systems. According to the European Union, we must pursue both digital and green transitions to achieve sustainable, human-centric, and resilient industries to achieve a world of prosperity for all. The study aims to present a novel approach to education and training in the digital health field that is inspired by the fifth industrial revolution paradigm. The paper highlights the role of training and education interventions that are required to support digital health in the future so that students can develop the capacity to recognise and exploit the potential of new technologies. This article will briefly discuss the challenges and opportunities related to healthcare systems in the era of digital transformation and beyond. Then, we look at the enabling technologies from an Industry 5.0 perspective that supports digital health. Finally, we present a new teaching and learning paradigm and strategies that embed Industry 5.0 technologies in academic curricula so that students can develop their capacities to embrace a digital future and minimise the disruption that will inevitably accompany it. By incorporating Industry 5.0 principles into digital health education, we believe students can gain a deeper understanding of the industry and develop skills that will enable them to deliver a more efficient, effective, and sustainable healthcare system. [ABSTRACT FROM AUTHOR]

Pereskia aculeata Miller, is an unconventional food plant native to South America. This study aimed to investigate the influence of different ultrasonic extraction times (10, 20, 30, and 40 min) on the phytochemical profile, antioxidant and antibacterial activities of ethanolic extracts obtained from lyophilized Pereskia aculeate Miller (ora-pro-nobis) leaves, an under-researched plant. Morphological structure and chemical group evaluations were also conducted for the lyophilized P. aculeate leaves. The different extraction times resulted in distinct phenolic content and Antioxidant Activity (ATT) values. Different extraction time conditions resulted in phenolic compound contents ranging from 2.07 to 2.60 mg EAG.g−1 of extract and different ATT values. The ATT evaluated by DPPH was significantly higher (from 61.20 to 70.20 μM of TE.g−1 of extract) in extraction times of 30 and 40 min, respectively. For ABTS, it varied between 6.38 and 10.24 μM of TE.g−1 of extract and 24.34 and 32.12 μM ferrous sulp.g−1 of extract. All of the obtained extracts inhibited the growth of Staphylococcus aureus, particularly the treatment employing 20 min of extraction at the highest dilution (1.56 mg.mL−1). Although liquid chromatography analyses showed that chlorogenic acid was the primary compound detected for all extracts, Paper Spray Mass Spectrometry (PS-MS) suggested the extracts contained 53 substances, such as organic, fatty, and phenolic acids, sugars, flavonoids, terpenes, phytosterols, and other components. The PS-MS proved to be a valuable technique to obtain the P. aculeate leaves extract chemical profile. It was observed that the freeze-drying process enhanced the conservation of morphological structures of P. aculeate leaves, as evidenced by scanning electron microscopy (SEM). Fourier transform infrared spectroscopy (FTIR) identified carboxyl functional groups and proteins between the 1000 and 1500 cm−1 bands in the P. aculeate leaves, thus favoring water interaction and contributing to gel formation. To the best of our knowledge, this is the first study to evaluate different times (10, 20, 30 and 40 min) for ultrasound extraction of P. aculeate leaves. The polyphenols improved extraction, and high antioxidant activity demonstrates the potential for applying P. aculeate leaves and their extract as functional ingredients or additives in the food and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

This paper proposes an AHP approach that utilizes the fuzzy extent model to prioritize five city parks based on their present quality and projected importance for Novi Sad City, the capital of Vojvodina Province, in Serbia. The study involved an expert evaluation of a set of eight criteria to identify the most relevant subset of criteria for a detailed park assessment. The park evaluation took into account uncertainties (fuzziness), the expert's risk tolerance, and different levels of optimism and pessimism. The obtained results could serve when defining upcoming city plans and management agendas related to green areas in the city. The proposed fuzzy-based methodology can be extended to group decision-making scenarios by involving more experts and stakeholder representatives. The park weights obtained through the fuzzy AHP methodology described in this paper can aid city planners and politicians in the strategic allocation of financial, organizational, and human resources for parks. [ABSTRACT FROM AUTHOR]

Exploring the spatial correlation network and its structural characteristics of China's industrial green technology innovation efficiency is significant for promoting the coordinated development of inter-regional industrial green transformation. Based on the innovation value chain, this paper divides China's industrial green technology innovation system into three interrelated sub-stages: technology research and development, achievement transformation, and commercialization. The NSBM model is used to measure the efficiency of industrial green technology innovation in 30 provinces and cities in mainland China from 2011 to 2020. The modified gravity model and social network analysis method are introduced to explore its spatial correlation network's structural characteristics and evolution rules. The results show that the spatial network correlation intensity of the three stages of green technology innovation efficiency in regional industry has gradually strengthened. There is no strict hierarchical structure, and the spatial network tends to be stable. The network shows an apparent "core–edge" distribution in all three stages, with the eastern coastal and central more developed regions at the network's core. Meanwhile, the northeastern and western remote areas are at the network's edge and less connected with other regions' provinces and cities. The distribution of network blocks in the three stages of green technology innovation efficiency is similar. The net benefit block mainly includes the eastern coastal and surrounding developed areas. The net spillover block mainly consists of the economically backward northwest region. The broker block is primarily distributed in the surrounding provinces and cities of the Bohai Rim. The bidirectional spillover block is mainly located in the southwest region. Finally, some suggestions are put forward to promote the coordinated improvement of regional industrial green technology innovation efficiency from the perspective of integrity, individuality, and agglomeration. [ABSTRACT FROM AUTHOR]

Rapid economic growth leads to such problems as resource scarcity and environmental degradation. Local governments successively take measures such as technological innovation to solve atmospheric environmental pollution; however, technological innovation fails to fundamentally alleviate atmospheric environmental pollution. Therefore, local governments come to realize the importance of green-technology innovation, which means an inevitable choice for various countries in the world to seek long-term development and win competitive advantage. Under such circumstances, this paper chooses the panel data of 30 provinces and regions in China from 2005 to 2018, takes environmental regulation as the threshold variable, and empirically analyzes the relationship between green-technology innovation and atmospheric environmental pollution by constructing a Spatial Measurement Model and Panel Regression Model. As evinced, green-technology innovation has a significant inhibitory effect and a spatial spillover effect on atmospheric environmental pollution. When environmental regulation reaches a level of intensity, green-technology innovation can effectively curb atmospheric environmental pollution. Accordingly, relevant parties should strengthen green-technology innovation, coordinate the development of the governance system of green-technology innovation, establish a joint prevention and control mechanism, increase the investment in green technology research and development, and augment the role of green-technology innovation. [ABSTRACT FROM AUTHOR]

In the Industry 5.0 era, companies are leveraging the potential of cutting-edge technologies such as artificial intelligence for more efficient and green human-centric production. In a similar approach, project management would benefit from artificial intelligence in order to achieve project goals by improving project performance, and consequently, reaching higher sustainable success. In this context, this paper examines the role of artificial intelligence in emerging project management through a systematic literature review; the applications of AI techniques in the project management performance domains are presented. The results show that the number of influential publications on artificial intelligence-enabled project management has increased significantly over the last decade. The findings indicate that artificial intelligence, predominantly machine learning, can be considerably useful in the management of construction and IT projects; it is notably encouraging for enhancing the planning, measurement, and uncertainty performance domains by providing promising forecasting and decision-making capabilities. [ABSTRACT FROM AUTHOR]