A review of sustainable cementation strategies for precious metal recovery: Efficiency, environmental impact and future prospects

Retraction notice to “Integrated Development of Industrial and Regional Economy using Big Data Technology” [Computers and Electrical Engineering 109 (2023) 108764

Towards upgrading the lowland bamboo (Oxytenanthera abyssinica (A.Rich.) Munro) value chains in Ethiopia: Available resources versus economic development perspectives

• A data-driven probabilistic simulation model of vessel operations is proposed. • The model integrates stochastic environmental and operational parameters. • Probabilistic characterizations of key vessel operational metrics are produced. • The model is applied to five strategic regions in the U.S. Blue Economy. • Applications to offshore energy O&M and electrification planning are examined. Vessel operations are central to several Blue Economy industries, from offshore and marine energy to fisheries and aquaculture, ensuring efficient and safe transport of crew, equipment, and materials between ocean-based assets and land-based ports. Careful logistical planning of these vessels relies on accurate, data-driven simulation models of vessel operations which can rigorously account for the stochastic environmental parameters (i.e., met-ocean conditions) and operational parameters (e.g., route, activities, vessel speed and propulsion system). Along this line, we propose a data-driven simulation framework which integrates environmental and operational information to produce probabilistic characterizations of key vessel operational metrics, including serviceability, fuel consumption, emissions, and costs. Five case studies, focused on strategic regions in the United States (U.S.) Blue Economy, demonstrate the framework’s effectiveness in modeling vessel operations across diverse environments and operational conditions. While broadly applicable, we demonstrate the simulation framework’s value in two specific contexts: serviceability assessment to inform operations and maintenance (O&M) for offshore energy assets, and fleet electrification planning.

For much of the past century, carbon dioxide (CO2) has received little attention scientifically outside of its role as a byproduct in the industrialization of the global economy. This trend has recently been upended where, due to mounting environmental concerns, CO2 has been brought squarely into the public consciousness. This surge in activity has contributed to a once unimaginable idea now pervading the scientific community: could CO2, a highly stable byproduct of hydrocarbon combustion, be recycled and converted back into useful chemicals and fuels? Owing to its ubiquitous nature and availability at truly massive quantities, it is thought that CO2-based products could offer a meaningful pathway toward lowering the environmental impact of many of the top industrial products while also enhancing supply chain diversification and resilience. In this manuscript we provide a holistic review of the pathways for CO2 conversion, the underlying chemistry and challenges involved in the transformation to products, and considerations for commercialization.

This study examines strategies to enhance the economic viability and environmental sustainability of lithium-ion battery (LiB) remanufacturing in electric vehicles (EVs). It evaluates centralised and decentralised closed-loop supply chain (CLSC) models, integrating blockchain technology and dynamic optimisation to improve transparency, coordination, and cost efficiency. Using Tesla’s battery collection and remanufacturing operations in China as a case study, the research employs expert interviews, legal framework analysis, and industry reports. Optimisation techniques, including Python’s PuLP and Monte Carlo simulations, identify cost-effective network configurations. Findings reveal that economies of scale and blockchain integration significantly reduce costs by over 86% for moderate volumes and 81% for large volumes. The study challenges the perception of LiB remanufacturing as unprofitable, demonstrating its commercial feasibility at scale. Strategic measures, including regional remanufacturing centres and optimised logistics, are recommended to support the circular economy and long-term sustainability in the EV industry.

The purpose of this research is to recover and recycle graphite from spent lithium-ion batteries through the application of flotation and acid leaching. This is to promote the circular economy in the battery manufacturing industry and reduce environmental pollution by waste lithium-ion batteries. This study investigated the effects of collector dosage, pH, and roasting time on the separation of graphite and lithium metal oxides through flotation from black mass of spent lithium-ion batteries. The work also involved the purification of recovered graphite through leaching with HCl. The best flotation conditions were found to be a roasting time of 1 h, collector dosage of 200 g/ton, and pH of 7, resulting in a froth product containing 67.3% fixed carbon (FC). The product was leached with 3 M HCl at 80 °C for 4 h. The final product contained Co, Al, and Cl at concentrations of 6.1%, 0.9%, and 0.7%, while other elements were present at concentrations less than 0.5%. X-ray Diffraction (XRD) showed existence of carbon in multiple phases, with a dominant peak at 2θ = 26.65 ° for raw froth product and 26.48 ° for leached product. Scanning Electron Microscope- Dispersive X-ray Spectroscopy (SEM-EDS) revealed that leaching resulted in a smoother material surface. Raman spectroscopy indicated that crystallinity of the recovered graphite was reduced after leaching, with D-band intensity divided by G-band intensity (ID/IG) ratio increasing to 0.51 for the leached product from 0.24 for raw froth product. The leached product had FC, ash, volatile matter, and moisture contents of 92.5%, 3.6%, 3.9% and 0.2%, respectively. • Graphite can be recovered and purified from spent LIBs through flotation. • Leached froth product contains Co and Al as major impurities. • Leaching results in graphite losing its crystallinity. • The leached froth product has a fixed carbon content of 92.45%. • The recycled graphite has carbon as 5 crystalline phases.

The integration of circular economy (CE) practices with Industry 4.0 (I4.0) technologies in industrial sectors remains limited, primarily due to a lack of practical knowledge about key drivers, barriers, and mitigation strategies. Despite their strong potential to enhance sustainable performance (SP), the adoption of CE–I4.0 faces several challenges across organizational levels. This study aims to empirically investigate the key drivers, barriers, and mitigation strategies for effective CE–I4.0 adoption, focusing on micro, meso, and macro-organizational contexts. Data were collected through an open-ended survey of 287 professionals, including sustainability leaders, managers, executives, and consultants, with 128 responses from micro level organizations, 87 from meso level organizations, and 71 from macro level organizations. The findings reveal level-specific drivers: “Technological innovation” at the micro level, “Regulatory pressure and sustainability standards” at the meso level, and “Regulatory and policy support” at the macro level. Across all levels, financial constraints emerged as the most critical barrier: “High initial investment costs” at the micro level, “High capital investment requirements” at the meso level, and “High upfront and ongoing costs” at the macro level. Mitigation strategies varied accordingly, including financial, skill, and change management at the micro level; education, collaboration, and technology adoption at the meso level; and awareness, stakeholder engagement, and infrastructure development at the macro level. These results underscore the need to tailor interventions to organizational scale while coordinating system-wide actions for enhanced sustainability. The study introduces a CE–I4.0 integration framework that consolidates these insights into an evidence-based roadmap linking drivers, barriers, and strategies across levels, providing actionable guidance for managers and policymakers. By offering a multi-level empirical analysis of CE–I4.0 integration, the study advances theory and practice, supporting coordinated adoption that enhances efficiency, sustainability, and organizational resilience. • First multi-level empirical study of CE–I4.0 integration across micro, meso, macro levels. • Identifies level-specific drivers, barriers, and mitigation strategies for CE–I4.0 adoption. • Introduces an evidence-based framework linking drivers, barriers, and strategies across levels. • Provides actionable insights for managers and policymakers to enhance sustainability outcomes. • Supports coordinated adoption to improve operational efficiency, resilience, and system-wide SP.

This article provides a comprehensive analysis of the efficiency and effectiveness of labor costs in Kazakhstan’s industrial sector. The main indicators of labor productivity, such as the volume of output, labor input per unit of time, and labor costs per unit of production, are examined. The study is conducted at three levels – enterprise, industry, and national economy – in order to identify the structure of labor costs and their impact on overall production efficiency. Special attention is given to the role of digital transformation, including automation, IIoT, ERP systems, artificial intelligence applications, and workforce retraining programs, in optimizing labor costs and enhancing productivity. The article presents real examples of Kazakhstani enterprises, such as “Asia Auto,” the Karaganda Foundry and Engineering Plant, and Eurasian Resources Group (ERG). These cases illustrate how digital technologies reduce nonproductive costs, increase per-worker output, and improve the cost-efficiency of production. At the macroeconomic level, the study examines state programs (“Digital Kazakhstan”, Industrial and Innovation Development Program) as well as international indices (WIPO Global Innovation Index, OECD digital framework assessments, IMF data) to evaluate Kazakhstan’s position in the global digital economy. Empirical findings, based on correlation and regression analysis, demonstrate that digitalization is the key driver of labor productivity growth in Kazakhstan. The results highlight that while the number of employees and working time have a positive but limited effect, the introduction of digital technologies significantly boosts efficiency and competitiveness. Thus, fostering digital transformation alongside workforce reskilling and innovation ecosystem development is essential for sustainable industrial growth and strengthening Kazakhstan’s global economic position.

Abstract Steel is a pillar industry of the national economy, in which scrap, as an important secondary raw material for steel production, is of great significance for its rapid identification in order to realize accurate classification for recycling and reuse. In this paper, Laser-Induced Breakdown Spectroscopy (LIBS) combined with the Restricted Boltzmann machine-Backpropagation algorithm (RBM-BP) is used for the rapid identification of 13 steel samples. Based on the collected spectral data, spectral preprocessing was performed using the discrete wavelet transform (DWT) to eliminate redundant information such as spectral interference and background noise. In particular, the number of DWT decomposition layers was 10, the wavelet function was selected as db2, and the calibration RMSEC was 0.99%. The preprocessed data were subjected to downscaling and feature extraction using Restricted Boltzmann machine (RBM) and Principal Component Analysis (PCA), respectively, and then the back propagation algorithm (BP) was used to classify and model the steel samples and compare the performance of the two models, RBM-BP and PCA-BP. The results show that the classification accuracy of the RBM-BP model is up to 99.88%, and the dimensionality reduction time is 16.74 s, which is much lower than the 78.73 s of the PCA-BP model. The measured results show that LIBS combined with the RBM-BP algorithm can realize the fast and accurate classification of steel, and this technology has great potential in the accurate classification of scrap steel for recycling and reuse, which can provide important support for the sustainable development of the steel industry and the construction of a resource-saving and environment-friendly society.

To address the mounting environmental burden caused by solid waste from the food supply chain-specifically agricultural residues and plastic packaging-this study systematically investigated the synergistic mechanisms and product regulation pathways in the co-pyrolysis of four representative food processing by-products-rice husk, pine wood, corn stover, and chestnut shell-with polypropylene, a common food packaging material. A comprehensive methodology integrating thermogravimetric analysis, kinetic modeling, and product characterization was employed. The results demonstrate that incorporating polypropylene into co-pyrolysis systems, such as those involving waste oil, significantly reduces the average activation energy, indicating a catalytic effect that enhances reaction kinetics. Notably, the co-catalytic interaction between corn stover and PP led to a substantial 54.90% reduction in oxygen content, underscoring PP's role as an effective hydrogen donor that promotes deoxygenation and free radical reactions, thereby increasing hydrocarbon production. At an optimal pyrolysis temperature of 600 °C, product distribution was effectively regulated: the hydrocarbon yield in the CP (corn stover/PP) system increased from 39.8% to a maximum of 65.6%, reflecting a targeted conversion of oxygenated compounds into high-value hydrocarbons. Furthermore, greenhouse gas (GHG) emission calculation and techno-economic analyses indicate that a natural gas-assisted co-pyrolysis process (Scenario C) can generate a net daily profit of 1835 RMB while reducing annual CO2 emissions by 6515 tons, demonstrating both economic feasibility and environmental benefits. This study provides a theoretical foundation for the circular economy in the food industry, offering a viable technical pathway for the simultaneous treatment of organic food waste and packaging plastics, thereby supporting the sustainable development of the agri-food sector.

The evolution of consumer behavior plays a critical role in advancing sustainability within the fashion sector, particularly in emerging economies. This study investigates changes in Brazilian fashion consumption patterns between 2012 and 2022, focusing on sustainability awareness, purchasing behaviors, and disposal practices. Using two national datasets and applying descriptive statistics, cluster analysis, and forecasting models, we identified a significant increase in “Fast Fashion Followers,” characterized by frequent purchasing and unsustainable disposal habits. Concurrently, willingness to pay for sustainable fashion markedly declined despite modest growth in the “Conscious Consumers” segment. Forecasts indicate that fast fashion-oriented consumers will likely dominate the Brazilian market by 2033, unless effective interventions are implemented. Our findings underscore the importance of comprehensive consumer education, economic incentives, and effective regulatory frameworks in promoting circular fashion practices. This study contributes to the literature by offering empirical evidence on consumer behavior dynamics in a primary emerging market and providing actionable insights to support the transition toward a circular economy in the fashion industry.

Material passport constitutes a digital repository for tracking and recording the circularity characteristic of materials to support end-of-life recovery, recycling, refurbishment, and reuse. As essential enablers of the circular economy, this paper presents a state-of-the-art review of the scientific literature on material passports in the construction industry. Drawing on a sample of 64 peer-reviewed articles, this study synthesized the lifecycle considerations, digital technologies, circular materials, and circularity characteristics prominent in material passports. The results revealed a significant rise in material passport research since 2016. However, the scientific material passport research has been dominated by evidence from Europe. Only 17% of the reviewed studies developed actual material passports for real-world projects, while the rest mainly developed conceptual frameworks and simulations. It is discovered that 40 digital technologies have been explored to develop material passports, with building information modelling dominating. Over 60 potential circular materials have been studied in the literature, where wood, concrete, aggregates, and steel received the highest attention. The key research gaps include fragmented lifecycle coverage of MPs, static BIM centric implementations and inconsistent definitions and measurement protocols for circularity characteristics. Therefore, this paper mapped the boundaries of the literature on material passports for circular economy in construction industry.

This review utilizes bibliometric analysis to examine global research trends and the chronological development of studies on the incorporation of mine wastes and tailings in concrete. A total of 345 publications were extracted from the Web of Science (WOS) database, and their analysis revealed a clear upward trajectory in scientific output since 2000. Respectively, China, India, Canada, and the USA were identified as the countries contributing the most to this research area. Among the 1139 author keywords extracted from the collected papers, 103 keywords with a minimum of three occurrences were analyzed using the VOSviewer software. VOSviewer further supports identifying research gaps and emerging trends by visualizing relationships among authors, publications, and keywords, facilitating a deeper understanding of the dynamics within the field. The analysis of keyword occurrences shows convergence towards research that focuses on the development of sustainable and high-performance materials that equate environmental responsibility with industrial economy demands. The current review also uses Biblioshiny, a web-based tool that explores topic timelines. It reflects that, in recent years, research focuses have shifted toward more sustainability, advanced materials, and performance optimization in the use of mine tailings in concrete.

Assessing the investment attractiveness of companies is essential for effective capital allocation under conditions of uncertainty and heterogeneous risk–return profiles. Investors typically face multiple financing alternatives, making comparative evaluation impossible without robust and specialized assessment methodologies. This study proposes a refined conceptual model for assessing the investment attractiveness of production companies, with a specific focus on the manufacturing sector of Kazakhstan. The research is based on a modeling-oriented methodological framework that integrates a modified discounted cash flow (DCF) approach with elements of environmental controlling. The proposed model incorporates sector-specific characteristics, including resource utilization patterns, regulatory requirements and the potential “green” premium observed in capital markets. To capture investment-related uncertainty and risk, the study employs material flow cost accounting, scenario-based modeling and probabilistic decision tree analysis. Particular attention is given to improving the determination of the discount rate, recognizing its critical influence on present value-based investment assessments. The model accounts for macroeconomic and sectoral factors specific to Kazakhstan’s production industry and offers alternative discount rate estimation scenarios under different initial conditions. The study contributes to the literature on investment attractiveness assessment by integrating financial, environmental and risk dimensions into a unified framework. The proposed model enhances transparency in investment decision-making and provides new insights into investment evaluation practices in emerging industrial economies.

ABSTRACT Artificial intelligence (AI) is increasingly embedded in the industrial economy, reshaping work practices and the demands for skilled labor. These transformations have promoted vocational education to integrate AI into teaching and training systems, for which teachers’ AI literacy constitutes a critical prerequisite. However, research on AI literacy of vocational education teachers remains limited, particularly from a typological perspective. This study developed and validated an AI literacy scale specifically designed for teachers in Chinese higher vocational colleges. The instrument comprised five dimensions: AI application concepts, AI foundational knowledge and skill, AI application practices, AI ethics and responsibility, and AI-supported professional development. Drawing on survey data from 1,637 teachers and applying Latent Profile Analysis (LPA), four distinct AI literacy profiles were identified: exploratory, conceptual, balanced, and innovative. Chi-square analyses further indicated that both individual characteristics (e.g. gender, teaching experience, professional title) and contextual factors (e.g. region, major, school category) were significantly associated with profile membership. These findings illuminated the structural features and profile differences of AI literacy among teachers in Chinese higher vocational college, providing empirical evidence and practical insights for developing targeted and profile-based professional development strategies to enhance teachers’ AI literacy.

Rubber trees are crucial to the global industrial economy, but they are facing the threat of powdery mildew caused by Erysiphe quercicola. Effective management of this disease depends on early detection. However, traditional monitoring methods are labor-intensive and often inaccurate. This limitation underscores the need for more precise and efficient techniques. This study developed and validated an integrated molecular detection platform that combines quantitative PCR (qPCR), droplet digital PCR (ddPCR), and propidium monoazide (PMA) treatments. The platform demonstrated a robust detection range, accurately quantifying E. quercicola at concentrations as low as 10 spores/mL spore DNA and 10-5 ng/μL mycelial DNA. Additionally, the system distinguished viable from non-viable spores and detected E. quercicola mycelia in both asymptomatic leaves and aged lesions, significantly enhancing early-stage detection and disease monitoring. This technology also helps assess the efficacy of fungicides against powdery mildew, potentially reducing the use of chemicals and their environmental impact. By improving early diagnosis and disease management, this approach promises to reduce dependence on fungicides and mitigate economic and environmental impacts, highlighting the enormous potential of advanced molecular technologies in sustainable agricultural practices in rubber plantations.

ABSTRACT Establishing low-carbon cities is a crucial strategy for reducing emissions, essential to tackling global climate change, reducing emissions, and achieving green development. This paper evaluates the impact of low-carbon city pilot (LCCP) policy on carbon emissions employing the difference-in-differences method. Our findings show that LCCP policy can significantly reduce carbon emissions. LCCP policy reduces carbon emissions by strengthening government environmental governance, promoting green innovation in enterprises, and raising public low-carbon awareness, with green innovation being the main channel. The carbon reduction effect of LCCP policy is more pronounced in southern regions, cities with high manufacturing concentration, green invention patents, and patents related to digital economy industries. Phased implementation of LCCP policy reduces carbon emissions, demonstrating its promotional effect. Our findings underscore that LCCP policy has long-lasting benefits for emission reduction, offering the important policy guidance for reaching carbon neutrality and fostering the green economy transformation.

The relevance of the work. In the 21st century, humanity has faced global challenges, among which the issues of environmental degradation, depletion of natural resources and climate change have become particularly acute. Against this background, the traditional linear economic model, which involves excessive use of resources and the generation of a large amount of waste, has exhausted its potential. This is especially critical in the construction industry ‒ one of the most resource-intensive sectors of the world economy. In response to the challenges of modernity, more and more attention is paid to the concept of a circular economy, which allows creating closed production cycles, reducing the burden on the environment. In the context of restoring Ukraine's infrastructure after the war, the relevance of the transition to a circular construction model is growing exponentially. Purpose. The purpose of the article is to comprehensively analyze the possibilities and limitations of implementing a circular economy in the construction industry as a tool for implementing the principles of sustainable development. The research is aimed at studying theoretical foundations, practical experience, international cases, innovative materials and technologies that can transform approaches to the design, construction and operation of facilities. Methodology. The article uses an interdisciplinary approach that combines the concepts of ecological economics, urbanism, architecture, and systems analysis. A comparative analysis of linear and circular economic models is conducted, and examples of successful implementation of circular practices in construction in different countries, including Germany, Great Britain, the Scandinavian countries, and Japan, are studied. Statistical data on material consumption, energy costs, and waste generation in the construction sector are used. Special attention is paid to the analysis of regulatory, institutional, and behavioral barriers to circularity in Ukraine. The results. The author proves that the circular economy is not only an environmentally sound, but also an economically profitable strategy for construction. The use of secondary materials, organic insulation, energy-efficient technologies, and local raw materials allows for a reduction in carbon footprint, reduced waste disposal costs, and improved quality of the living environment. Key barriers to the implementation of a circular approach in Ukraine are identified – from the lack of a regulatory framework to the low level of environmental culture. At the same time, the country’s potential in implementing relevant solutions is highlighted, especially in the context of post-war reconstruction. The article calls for a revision of the paradigm of construction as a technical process and its transformation into a worldview model based on long-term responsibility to society, nature and future generations.

Purpose Digital tools are a critical enabler of the circular economy (CE) and sustainability practices in construction. While technological evolution has continued, there is a dearth of studies on the specific competencies required to drive digital technology (DT) integration in the CE transition in developing countries. The purpose of this study is to assess specific competencies required by the construction professionals to enable a digitalisation-led circular economy transition for sustainable development in the Nigerian construction industry (NCI). Design/methodology/approach Twenty-nine competencies were obtained from a literature review and categorised into four groups, which informed the structured questionnaire used to collect 187 relevant responses from construction professionals in Nigeria. The gathered data yielded a reliability index of 0.829. They were analysed using mean analysis, coefficient of variation (CV), Kruskal–Wallis (K–W) test, Fuzzy Set Theory (FST) and Spearman correlation analysis. Findings The descriptive analysis revealed that possessing the assessed competencies is significant for promoting digital technologies-driven CE transition in construction. The K–W test revealed no statistically significant difference in the perception of construction experts regarding the competencies. FST revealed that Digital Literacy and Technical Proficiency (index = 3.98), Management and Stakeholders Engagement Competencies (Index = 3.97), Data and Decision-Making Competencies (index = 3.94) and Understanding of CE Principles and Practices (Index = 3.90) were critical competencies clusters, and the correlation analysis showed that these competencies are significant in promoting a technology-led CE transition in construction. Originality/value Studies on competencies for digitalisation and CE transition have remained fragmented in developing countries like Nigeria and are an underexplored domain in the literature. The study presents the outcomes of specific competencies for catalysing a digitalisation-led CE transition to drive a sustainable built environment in Nigeria.