Search Results (547)

Background: The growing complexity of production processes in the metal–mechanical industry demands ever more effective strategies for managing machine and equipment maintenance, as unexpected failures can incur high operational costs and compromise productivity by interrupting workflows and delaying deliveries. However, few studies have combined end-to-end data analytics and data mining methods to proactively predict and mitigate such failures. This study aims to develop and validate a comprehensive framework combining data analytics and data mining to prevent machine failures and support decision-making in a metal–mechanical manufacturing environment. Methods: First, exploratory data analytics were performed on the sensor and logistics data to identify significant relationships and trends between variables. Next, a preprocessing pipeline including data cleaning, data transformation, feature selection, and resampling was applied. Finally, a decision tree model was trained to identify conditions prone to failures, enabling not only predictions but also the explicit representation of knowledge in the form of decision rules. Results: The outstanding performance of the decision tree (82.1% accuracy and a Kappa index of 78.5%), which was modeled from preprocessed data and the insights produced by data analytics, demonstrates its ability to generate reliable rules for predicting failures to support decision-making. The implementation of the proposed framework enables the optimization of predictive maintenance strategies, effectively reducing unplanned downtimes and enhancing the reliability of production processes in the metal–mechanical industry. Full article

Coal serves as the primary energy source for China, with production anticipated to reach 4.76 billion tons in 2024. However, the mining process generates a significant amount of gangue, with approximately 800 million tons produced in 2023 alone. Currently, China faces substantial gangue stockpiles, characterized by a low comprehensive utilization rate that fails to meet the country’s ecological and environmental protection requirements. The environmental challenges posed by the treatment and disposal of gangue are becoming increasingly severe. This review employs bibliometric analysis and theoretical perspectives to examine the latest advancements in gangue utilization, specifically focusing on the application of computational chemistry to elucidate the structural features and interaction mechanisms of coal gangue, and to collate how these insights have been leveraged in the literature to inform its potential utilization routes. The aim is to promote the effective resource utilization of this material, and key topics discussed include evaluating the risks of spontaneous combustion associated with gangue, understanding the mechanisms governing heavy metal migration, and modifying coal byproducts to enhance both economic viability and environmental sustainability. The case studies presented in this article offer valuable insights into the gangue conversion process, contributing to the development of more efficient and eco-friendly methods. By proposing a theoretical framework, this review will support ongoing initiatives aimed at the sustainable management and utilization of coal gangue, emphasizing the critical need for continued research and development in this vital area. This review uniquely combines bibliometric analysis with computational chemistry to identify new trends and gaps in coal waste utilization, providing a roadmap for future research. Full article

Concern over the presence of pharmaceutical waste in the environment has prompted research into the management of emerging organic micropollutants (EOMs). In response, sustainable technologies have been applied as alternatives to reduce the effects of these contaminants. This study investigated the capacity of filamentous fungi isolated from iron mine soil in the Amazon region to biodegrade the drug chloroquine diphosphate. An initial screening assessed the growth of four fungal strains on solid media containing chloroquine diphosphate: Trichoderma pseudoasperelloides CBMAI 2752, Penicillium rolfsii CBMAI 2753, Talaromyces verruculosus CBMAI 2754, and Penicillium sp. cf. guaibinense CBMAI 2758. Among them, Penicillium sp. cf. guaibinense CBMAI 2758 was selected for further testing in liquid media. A Box–Behnken factorial design was applied with three variables, pH (5, 7, and 9), incubation time (5, 10, and 15 days), and chloroquine diphosphate concentration (50, 75, and 100 mg·L⁻¹), totaling 15 experiments. The samples were analyzed by gas chromatography–mass spectrometry (GC-MS). The most effective conditions for chloroquine biodegradation were pH 7, 100 mg·L⁻¹ concentration, and 10 days of incubation. Four metabolites were identified: one resulting from N-deethylation M1 (N4-(7-chloroquinolin-4-yl)-N1-ethylpentane-1,4-diamine), two from carbon–carbon bond cleavage M2 (7-chloro-N-ethylquinolin-4-amine) and M3 (N1,N1-diethylpentane-1,4-diamine), and one from aromatic deamination M4 (N1-ethylbutane-1,4-diamine) by enzymatic reactions. The toxicity analysis showed that the products obtained from the biodegradation of chloroquine were less toxic than the commercial formulation of this compound. These findings highlight the biotechnological potential of Amazonian fungi for drug biodegradation and decontamination. Full article

Acid mine drainage (AMD) remains a critical environmental challenge in South Africa due to its severe impact on water quality, ecosystems and public health. Numerous studies on AMD management, treatment and resource recovery have been conducted over the past 20 years. This study presents a comprehensive review of research activities on AMD in South Africa from 1998 to 2025, highlighting key trends, emerging challenges and future directions. The study reveals a significant focus on passive and active treatment methods, environmental remediation and the recovery of valuable resources, such as iron, rare earth elements (REEs) and gypsum. A bibliometric analysis was conducted to identify the most influential studies and thematic research areas over the years. Bibliometric tools (Biblioshiny and VOSviewer) were used to analyse the data that was extracted from the PubMed database. The findings indicate that research production has increased significantly over time, with substantial contributions from top academics and institutions. Advanced treatment technologies, the use of artificial intelligence and circular economy strategies for resource recovery are among the new research prospects identified in this study. Despite substantial progress, persistent challenges, such as scalability, economic viability and policy implementation, remain. Furthermore, few technologies have moved beyond pilot-scale implementation, underscoring the need for greater investment in field-scale research and technology transfer. This study recommends stronger industry–academic collaboration, the development of standardised treatment protocols and enhanced government policy support to facilitate sustainable AMD management. The study emphasises the necessity of data-driven approaches, sustainable technology and interdisciplinary cooperation to address AMD’s socioeconomic and environmental effects in the ensuing decades. Full article

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and grid scales. Therefore, this study selects Zhejiang Province—a representative rapidly transforming region in China—to establish a “type-process-ecological effect” analytical framework. Utilizing four-period (2005–2020) 30 m resolution land use data alongside natural and socio-economic factors, four spatial scales (city, county, township, and 5 km grid) were selected to systematically evaluate multi-scale impacts of land use transition on EEQ and their driving mechanisms. The research reveals that the spatial distribution, changing trends, and driving factors of EEQ all exhibit significant scale dependence. The county scale demonstrates the strongest spatial agglomeration and heterogeneity, making it the most appropriate core unit for EEQ management and planning. City and county scales generally show degradation trends, while township and grid scales reveal heterogeneous patterns of local improvement, reflecting micro-scale changes obscured at coarse resolutions. Expansive land transition including conversions of forest ecological land (FEL), water ecological land (WEL), and agricultural production land (APL) to industrial and mining land (IML) primarily drove EEQ degradation, whereas restorative ecological transition such as transformation of WEL and IML to grassland ecological land (GEL) significantly enhanced EEQ. Regarding driving mechanisms, natural factors (particularly NDVI and precipitation) dominate across all scales with significant interactive effects, while socio-economic factors primarily operate at macro scales. This study elucidates the scale complexity of land use transition impacts on ecological environments, providing theoretical and empirical support for developing scale-specific, typology-differentiated ecological governance and spatial planning policies. Full article

Background: Gold mining is a critical part of the industry of Central Asia, contributing significantly to regional economic growth. However, gold production management faces numerous challenges, including adopting innovative technologies such as AI, using improved logistical equipment, resolving supply chain inefficiencies and disruptions, and incorporating modernized waste management and advancements in gold bar processing technologies. This study explores how advanced technologies and improved logistical processes can enhance efficiency and sustainability. Method: This paper examines gold production processes in Kyrgyzstan, a gold-producing country in Central Asia. The case study approach combines qualitative interviews with industry stakeholders and a system dynamics (SD) simulation model to compare current operations with a technology-based scenario. Results: The simulation model shows improved outcomes when innovative technologies are applied to ore processing, waste refinement, and gold bar production. The results also indicate an approximate twenty-five percent reduction in transport time, a thirty percent decrease in equipment downtime, a thirty percent reduction in emissions, and a fifteen percent increase in gold extraction when using artificial intelligence, smart logistics, and regional smelting. Conclusions: The study concludes with recommendations to modernize equipment, localize processing, and invest in digital logistics to support sustainable mining and improve operational performance in Kyrgyzstan’s gold sector. Full article

Coal gangue, a major by-product of coal mining, poses significant environmental challenges due to its large-scale accumulation, land occupation, and potential for air and water pollution. This manuscript presents a comprehensive overview of continuous chamber gangue storage technology as a sustainable mining solution for coal mines. The principles of this approach emphasize minimizing disturbance to overlying strata, enabling uninterrupted mining operations, and reducing both production costs and environmental risks. By storing the surface or underground gangue in continuous chambers, the proposed method ensures the roof stability, maximizes the waste storage, and prevents the interaction between mining and waste management processes. Detailed storage sequences and excavation methods are discussed, including continuous and jump-back excavation strategies tailored to varying roof conditions. The process flows for both underground and ground-based chamber storage are described, highlighting the integration of gangue crushing, paste preparation, and pipeline transport for efficient underground storage. In a case study with annual storage of 500,000 t gangue, the annual economic benefit reached CNY 1,111,425,000. This technology not only addresses the urgent need for sustainable coal gangue management, but also aligns with the goals of resource conservation, ecological protection, and the advancement of green mining practices in the coal industry. Full article

This study suggests a method for analyzing the risk of methane explosions using the N-K model and Social Network Analysis (SNA) to understand how different risk factors related to coal-mine methane explosions are connected and change over time, aiming to prevent these accidents effectively. We identified 41 secondary risk factors and four fundamental risk factors—human, equipment, environment, and management—based on the 4M accident causation theory. The SNA model was utilized to determine the main risk factors and their evolutionary routes, while the N-K model was utilized to quantify the degree of risk coupling. The findings show that the number of risk variables engaged in the methane-explosion risk system closely correlates with the number of accidents that occur and the maximum coupling level among the four elements. The primary control factors in the methane-explosion risk system are poor equipment management, broken safety monitoring and control systems, inadequate safety education and training, safety regulation violations, and poor safety production responsibility system implementation. We utilized the primary evolution paths and key elements to propose risk control approaches. A reference for ensuring safety in coal-mine operations can be found in the research findings. Full article

Life Cycle Impact Assessments (LCIAs) examine the environmental impacts of products using life cycle inventories (LCIs) of quantified inputs and outputs of a product through its life cycle. Currently, estimated impacts from mining are dominated by long-term metal release from tailings due to inaccurate assumptions regarding metal release and transport within and from mine materials. A conceptual model approach is proposed to support the development of a new database of LCI data, applying mechanistic processes required for the release and transport of metals through tailings and categorizing model inputs into ‘bins’. The binning approach argues for accuracy over precision, noting that precise metal release rates are likely impossible with the often-limited data available. Three case studies show the range of forecasted metal release rates, where even after decades of monitoring within the tailings and underlying aquifer, metal release rates span several orders of magnitude (<100 mg/L to >100,000 mg/L sulfate at the Faro Mine). The proposed tool may be useful for the development of a new database of LCI data, as well as to analyze mine’s regional considerations during designs for risk evaluation, management and control prior to development, when data is also scarce. Full article

Background/Objective: Frontline healthcare staff who contend diseases and mitigate their transmission were repeatedly exposed to high-risk conditions during the COVID-19 pandemic. They were at risk of mental health issues, in particular, psychological stress, depression, anxiety, financial stress, and/or burnout. This study aimed to investigate and evaluate the occupational stress of medical doctors, nurses, pharmacists, physiotherapists, and other hospital support crew during the COVID-19 pandemic in Saudi Arabia. Methods: We collected both qualitative and quantitative data from a survey given to public and private hospitals using methods like correspondence analysis, cluster analysis, and structural equation models to investigate the work-related stress (WRS) and anxiety of the staff. Since health-related factors are unclear and uncertain, a fuzzy association rule mining (FARM) method was created to address these problems and find out the levels of work-related stress (WRS) and anxiety. The statistical results and K-means clustering method were used to find the best number of fuzzy rules and the level of fuzziness in clusters to create the FARM approach and to predict the work-related stress and anxiety of healthcare staff. This innovative approach allows for a more nuanced appraisal of the factors contributing to work-related stress and anxiety, ultimately enabling healthcare organizations to implement targeted interventions. By leveraging these insights, management can foster a healthier work environment that supports staff well-being and enhances overall productivity. This study also aimed to identify the relevant health factors that are the root causes of work-related stress and anxiety to facilitate better preparation and motivation of the staff for reorganizing resources and equipment. Results: The results and findings show that when the financial burden (FIN) of healthcare staff increased, WRS and anxiety increased. Similarly, a rise in psychological stress caused an increase in WRS and anxiety. The psychological impact (PCG) ratio and financial impact (FIN) were the most influential factors for the staff’s anxiety. The FARM results and findings revealed that improving the financial situation of healthcare staff alone was not sufficient during the COVID-19 pandemic. Conclusions: This study found that while the impact of PCG was significant, its combined effect with FIN was more influential on staff’s work-related stress and anxiety. This difference was due to the mutual effects of PCG and FIN on the staff’s motivation. The findings will help healthcare managers make decisions to reduce or eliminate the WRS and anxiety experienced by healthcare staff in the future. Full article

This study presents a methodology developed in collaboration with the Colombian National Mining Agency, aimed at enhancing the economic and productive activity of small-scale miners in Colombia through the promotion of associativity. Despite persistent challenges in the formalization and sustainable development of the artisanal mining sector, fostering associative models offers a pathway towards a more sustainable mining industry, aligned with current national policies. The proposed roadmap, designed to achieve this objective, is divided into three sequential phases. The first, the Baseline Survey, focuses on comprehensively understanding the initial socio-economic and operational conditions of mining communities. This is followed by Participatory Strategic Planning, which involves projecting the long-term role and development of mining associative figures. Finally, the Annual Operational Planning and Execution phase concentrates on the concrete implementation of activities designed to achieve sustainable organizational goals. During the design and initial implementation of this roadmap, we found that continuous support and tailored training programs are essential for mining communities. These programs are critical for fostering the development of collective skills and strengthening community ties within mining organizations. The findings highlight that by strengthening collective capabilities and community ties, mining organizations can enhance their self-management capacities and significantly contribute to the economic development of their regions. This approach addresses key challenges in the sector by promoting a more organized and resilient operational framework. The implementation of a participatory methodology, coupled with specific organizational strengthening programs, coordinated execution, and continuous monitoring, provides a viable route towards a more sustainable and formalized small-scale mining sector in Colombia. This roadmap offers a practical framework for fostering self-managed and economically contributing mining organizations. Full article

Sulfate as a potential pollution source in the water environment of the basin, identifying sulfate sources and migration mechanisms is essential for protecting the water environment and ensuring sustainable water management. Liuyang River is a primary tributary of the Xiangjiang River. It has experienced progressively intensifying anthropogenic influences in recent decades, manifested by sustained sulfate concentration increases. However, the sulfate sources and their contributions were not clear. This study used hydrochemistry and multi-isotopes methods combined with Simmr model to study the hydrochemical characteristics, sulfate sources, and migration–transformation processes of surface water and groundwater. The results showed that the hydrochemical types of surface water were HCO₃-Ca and HCO₃·SO₄-Ca·Mg, and groundwater were HCO₃-Ca, HCO₃-Ca·Mg, and HCO₃·SO₄-Ca. Ions in the water primarily originated from carbonate and silicate rocks dissolution and sulfide oxidation, augmented by mining operations, sewage discharge, and chemical production. The analyses of hydrochemistry, isotopes, and Simmr model revealed that surface water sulfate originated from soil sulfate (35.70%), sulfide oxidation (26.56%), sewage (16.58%), and atmospheric precipitation (12.45%). Groundwater sulfate was derived predominantly from sewage (34.96%), followed by soil sulfate (28.09%), atmospheric precipitation (17.35%), and sulfide oxidation (12.25%). Sulfate migration and transformation were controlled by the natural environment and anthropogenic impacts. When unaffected by human activities, sulfate mainly originated from soil and atmospheric precipitation, relating to topography, geological conditions, agricultural activities, and precipitation intensity. However, in regions with intense human activities, contributions from sewage and sulfide oxidation significantly increased due to the influences of mining and industrial activities. Full article

Increasing water scarcity in arid regions has prompted the mining industry to develop strategies to maximize water recovery and reuse, especially in tailings treatment processes. In this context, the present investigation evaluated the effects of sodium polyacrylate (NaPA) on the compressibility and viscoelasticity of clayey tailings in the presence of hard water containing calcium and magnesium. To this end, clayey slurries were analyzed using rheological tests (rheograms and oscillatory viscoelasticity), zeta potential measurements, and compressibility tests using batch centrifugation. The yield stress was determined using the Herschel–Bulkley model, while the compressive yield stress (Py(Φ)) was calculated as a key indicator to characterize the degree of sediment consolidation. The results showed that NaPA, due to its anionic nature and high degree of ionization at pH 8, induces effective particle dispersion by increasing electrostatic repulsion and decreasing the interaction force between particles, which reduces both rheological parameters and compressive yield stress. For the 70/30 quartz/kaolin mixture, the yield stress decreased from 70.54 to 61.64 Pa in CaCl₂ and from 57.51 to 52.95 Pa in MgCl₂ in the presence of NaPA. It was also observed that suspensions in the presence of magnesium ions presented greater compressibility than those with calcium, attributable to the greater hydration radius of magnesium (10.8 Å), which favors less dense and more easily deformable network structures. Furthermore, a higher proportion of kaolin in the mixture resulted in higher yield stresses, a product of the clay’s laminar structure, colloidal size, and high surface area, both in the absence and presence of NaPA. Overall, the results show that incorporating NaPA significantly improves the compressibility and rheology of clayey tailings in hard water, offering a promising alternative for optimizing water recovery and improving tailings management efficiency in the context of water restrictions. Full article

Exploiting clay for brick production results in soil damage. There are no field evaluations for its recovery with organic amendments comprising biochar. We conducted a small-scale experiment to assess the recovery effects of soil using biochar, both alone and in combination with compost. On a remnant of soil from clay mining, we applied the following to plots of 2.25 m² in a randomized complete block design: (1) biochar + efficient microorganisms (EMs), (2) compost + EMs, (3) compost + biochar + EMs, and (4) a control group without amendments. Composite soil samples from each plot were collected at the beginning of the experiment and at 30, 120, and 210 days. We analyzed some physicochemical properties of the soil and recorded the number and morphotypes of seedlings. We found that biochar + EMs and biochar + compost + EMs had positive effects in the short term, particularly in reducing bulk density. No synergistic effect was observed between biochar and compost, contrary to what was expected, which may be due to the short term of the experiment and prevailing low temperatures. The compost + EM treatment resulted in greater seedling diversity. In conclusion, bulk density can be used as an early indicator of soil improvement when biochar alone or combined with compost is used. Biochar may be a striking solution for promoting sustainable soil management after clay mining in high-elevation conditions. Full article

Mobile phone waste management is a growing environmental challenge, with improper disposal contributing to resource depletion, pollution and missed opportunities for material recovery. This study presents the findings of a dual-purpose survey (11,163 respondents) conducted in a wide academic context in Italy, aimed at both assessing mobile phones disposal behaviors and knowledge and raising awareness through structured educational prompts about sustainable e-waste management. The results reveal significant behavioral patterns and knowledge gaps across demographic groups. While most respondents (90.6%) own one phone, males tend to have more than females. Phones are replaced every 3–5 years by 48.8% of users and every 1–3 years by 36.7%, with students tending to replace them earlier. Only 20.2% replace their phone when irreparable while 46% replace them due to high repair costs. A large majority (92.3%) store old devices at home, forming an estimated urban mine of 29,799 unused phones. The awareness of hazardous components is higher than that of critical raw materials, with males more informed than females and students in scientific fields displaying greater awareness than those in humanities and health disciplines. The awareness of official take-back programs is particularly low, especially among younger generations. Notably, 90% reported increased awareness from the educational survey and 93.1% expressed willingness to use an on-campus e-waste collection system. These results highlight the role of universities as catalysts for sustainable behavior, supporting the design of targeted educational strategies and policy actions in line with circular economy principles and Sustainable Development Goal 12 “Responsible consumption and production”. Full article