Environmental Management Research Articles

Optimizing Eri Silkworm Productivity: Evaluating the Performance of Ecoraces of Samia ricini (Donovan) in the East Coastal Condition of Tamil Nadu, India

This study investigated raising Eri silkworms, Samia ricini (Donovan) a multi-voltine, domestic moth, traditionally bred indoors and known for its spun silk, in the eastern coast of Tamil Nadu, India. Eri silkworms typically thrive in the northeast regions, but the growing demand for Eri silk has led to exploring new locations for their production. The eight ecoraces of Eri silkworm i.e. C2, Borduar, Khanapara, Mendipathar, Dhanubanga, Nongpoh, Borduar and Titabar were selected for this study reared on castor plants under varied climatic conditions in Tamil Nadu. The economic and grainage characters such as larval duration, matured larval weight, survival rate, cocoon weight, shell weight, shell ratio, effective rearing rate, rate of pupation, rate of moth emergence, fecundity and hatchability were analyzed. This study revals that C2 ecorace consistently outperformed the other ecoraces, exhibiting superior growth parametrics, cocoon quality, and silk production potential.Findings indicate that optimal temperature and humidity conditions are crucial for enchancing performace, particularly for sensitive ecoraces like Barpathar and Nongpoh, highlighting the importance of ecorace selection and environmental management for sustainable eri silk production.

Integrating material flow analysis into hydrological model for water environment management of large-scale urban-rural mixed catchment

Simultaneous simulation of urban and rural hydrological processes is important for water environment management of mixed land-uses catchments. However, the discharge paths of pollution in the urban drainage system are not described in traditional catchment hydrological models. In this study, an urban-rural water environment (URWE) model is developed through incorporating the material flow analysis (MFA) and the soil and water assessment tool (SWAT) into a general framework. The URWE model is an advancement with respect to traditional hydrological models in terms of simultaneously simulating the urban organized and rural decentralized discharges of pollution. Due to the low data requirement and high computational efficiency of MFA, URWE model is applicable to large-scale catchment with wide urban area. The URWE model is applied to a typical urban-rural mixed catchment, the Dianchi Catchment (China), where the pollution characteristics are analyzed and the pollution control measures are investigated. Results indicate that the URWE model outperforms the conventional SWAT model for both water quantity and quality simulations, with an 8.5 % improvement in average coefficient of determination (R2) and a 67.4 % improvement in average Nash coefficient (NSE). Rural best management practice, rainwater-sewage separation, and storage capacity expansion are identified as the most cost-effective measures for COD, TN, and TP reduction, respectively. Contributions of this study are to improve the accuracy of water environment simulation in urban-rural mixed catchment, as well as to help decision-makers develop synergistic urban-rural water environment management measures.

Anthropogenic Lead (Pb) deposition history of the western Indian Ocean from coral-based Pb/Ca ratio and Pb isotope records

Despite the rapid industrial growth and urban expansion along the coastline of the Western Indian Ocean, knowledge of both historical and current levels of anthropogenic lead (Pb) contamination, as well as its impact on the biosphere, remains limited compared to other industrialized regions. We present a twenty-four year long coralline record (1989–2013) of Pb/Ca ratio and Pb isotopes from the Lakshadweep coral reef in the Western Indian Ocean. This new record provides critical insight into source(s), possible transport pathways, and temporal trends in Pb deposition during the studied interval. The long-term trend in the surface seawater Pb concentration ([Pb]SW), reconstructed from the coralline Pb/Ca record, reveals almost doubling in [Pb]SW from ~50 pmol/kg in the year 1990 to ~107 pmol/kg in the year 2013. Bayesian mixing model calculations reveal that among the potential Pb polluting sources to this region, anthropogenic aerosol from the hinterland of the continents was the dominant contributor of Pb (23–89 %). A compilation of available Pb records from the Indian Ocean reveals that Pb isotope distribution patterns in the western and central equatorial Indian Oceans are distinctly different from those observed in the eastern Indian Ocean. The western Indian Ocean records exhibit lower Pb isotope ratios (206Pb/207Pb and 208Pb/207Pb) compared to the East Indian Ocean, suggesting a greater influence of anthropogenic Pb on seawater concentration. These findings highlight the spatio-temporally spread of anthropogenic Pb pollution and its potential impact on the biosphere in the Indian Ocean and therefore emphasize the urgent need for region-specific environmental management strategies. Plain language summaryThis study reconstructs the history of lead (Pb) pollution in the Western Indian Ocean. We analyzed a specimen of coral, collected from Lakshadweep, to create a 24-year-long (years 1989 to 2013) for Pb concentration and isotopic composition of seawater in the Western Indian Ocean. Using the coralline Pb/Ca ratio and Pb isotope data, we have reconstructed surface ocean Pb concentration ([PbSW]) and isotopic composition to understand the sources, transport pathways, and temporal depositional trends over the western Indian Ocean during the past two decades. This reconstruction of [PbSW] reveals a doubling from ~50 pmol/kg in the year 1990 to ~107 pmol/kg in the year 2013. Our investigations to fingerprint the Pb source(s) to our study area reveal that majority of the anthropogenic Pb has been contributed by aerosol deposition sourced from the hinterland of the surrounding continents. Our investigation also revealed that the western Indian Ocean is more contaminated by anthropogenic Pb compared to the eastern Indian Ocean. These findings highlight the need for region-specific monitoring efforts in the Indian Ocean as well as the formulation of environmental strategies to mitigate the impact of Pb pollution.

Technological development and eco-efficiency: Drivers of total factor productivity in OECD countries

This study delves into the total factor productivity growth in OECD countries, focusing on the crucial role of technological advancement and environmental management. By utilizing the Malmquist-Luenberger index, the paper encompasses both positive and negative outputs, such as pollution, providing a comprehensive productivity analysis by breaking it down into efficiency and technical change. Data from 36 OECD countries from 2000 to 2021 were examined to uncover trends and patterns in productivity growth and its unintended environmental consequences. The results emphasize the dominant influence of technological progress, particularly after 2006, as the primary driver of productivity growth, surpassing improvements in technical efficiency. A significant increase in technical change (1.56 in 2021) compared to technical efficiency (1.05) underscores the importance of sustained investment in research and development (R&D), which correlates positively with patent generation and technological advancement. The study also illustrates that OECD countries have effectively integrated eco-efficient practices, aligning with global trends in environmentally conscious productivity analyses. By integrating environmental outputs such as PM2.5 pollution, the analysis demonstrates that countries mitigating these adverse effects achieve higher productivity growth. These findings challenge conventional productivity models, where productivity diminishes when environmental aspects are considered. The analysis emphasizes the necessity for tailored policy approaches to address disparities in R&D investments, technological adoption, and eco-efficiency among countries. Countries with more significant R&D investments consistently demonstrate superior technological advancement in patents (0.745). Policymakers are urged to prioritize long-term strategies that foster technological innovation and environmental sustainability to ensure sustained productivity growth and economic resilience.

Policy, innovation, market or behavior driven effects: energy green transition and environmental management in Chinese heterogeneous cities

Energy green transition (EGT) is currently one of the main measures for countries around the world to address the contradiction between economic growth and increasingly deteriorating environmental and climate issues. Cities are the center of energy consumption. The key to EGT lies in urban energy green transition. Therefore, the focus of this study is on the driving mechanism of urban EGT. Firstly, the spatial-temporal characteristic of EGT in Chinese heterogeneous cities is analyzed by using methods such as gravity model. Secondly, the possible paths includes policy driven, innovation driven, market driven, and behavior driven for urban EGT are discussed through theoretical analysis. Finally, combined with panel data of 236 Chinese cities in 2007-2022, this study empirically analyzes the complex driving mechanism of urban EGT. Results show that: (1) The EGT in Chinese cities is continuing. From the perspective of urban heterogeneous, EGT in 1-tier and 2-tier cities is significantly faster than that in 3-, 4-, and 5-tier cities. The EGT speed in eastern cities is the fastest, while that in northeastern cities is the slowest. The difficulty of EGT in energy resource-based cities is actually the greatest. From the perspective of spatial features, the spatial center of EGT in Chinese cities generally shows a changing trend from northwest to southeast. (2) Policy driven, innovation driven, market driven, and behavior driven constitute the complex driving mechanism of urban EGT, and policy driven is the primary driving force for this round of EGT. (3) Positive effect of economic development level and education level improvement on EGT in Chinese cities is significant while resource endowment and population agglomeration level exhibit significant inhibitory effects. (4) There are significant differences in the core driving force for EGT in heterogeneous cities. Both policy driven effect and market driven effect have the highest impact in 1- and 2-tier cities. Innovation driven effect, market driven effect, and behavior driven effect are only significant in eastern and central cities. In energy resource-based cities, innovation driven effect of green innovation is not significant. This study can assist government departments better in formulating relevant policies to support energy transition, promote technological innovation, design market mechanisms, and guide energy consumption behavior.

Continuous Inertial Alignment and Isolation of Spherical Microparticles and Nonspherical Flagellate Microalgae

Flagellate microalgae play an increasingly significant role in environmental management and biotechnology for valuable bioproducts, excellent photosynthetic capability, and autonomic movement. However, multiple flagellate microalgae practically live together in the ocean and lake areas, and they are susceptible to contamination as a result of improper operations. Enthused by these aspects, we develop a reliable inertial microfluidic method to overcome the influence of flagella movement and non-spherical shape on the alignment and isolation of target flagellate microalgae. Firstly, a computational model incorporating fluid-structure interaction was established to investigate influence of releasing position and shape parameters on the displacement and rotation of non-spherical microalgal cells and numerically studied the processes of shape- and size-based particle separation. Secondly, the movement of different-size particles under diverse flow rates in the channel was explored, and the capability of this method was validated by aligning and separating 10 μm and 20 μm polystyrene particles. Thirdly, this method was applied to align H. pluvialis and isolate Dunaliella salina from the mixed microalgal samples to explore the influence of flow rate on the alignment and isolation of flagellate microalgae. Fourthly, this method was engineered to select 20 μm polystyrene particles from three types of particles and isolate H. pluvialis from the mixture of multiple microalgae species. Finally, we leveraged this approach to realize separation of H. pluvialis and Synedra ulna to explore the performance of this method in shape-based cell separation, and we isolated Euglena from microalgal cell wastes, including dead cells, bacteria, and particles. This method has promising prospects to be a reliable tool to isolate target flagellate microalgae to address problematic issues in environmental monitoring, pharmaceutical synthesis, and chronic wound treatment for the advantage of good adaptability and reliability.

Synergistic influence of gyrotactic microorganisms and bimolecular reaction on bidirectional tangent hyperbolic fluid with Nield boundary conditions: A biomathematical model

In biomedical engineering, the behaviour of gyrotactic microorganisms with non-Newtonian fluids such as tangent hyperbolic fluids improve the design of targeted drug delivery systems. In this system control over microorganism movement is essential. The present study deals with the synergistic influence of gyrotactic microorganisms and bimolecular reactions on the bidirectional flow of tangent hyperbolic fluids under Nield boundary conditions. Further, the flow characteristic of the non-Newtonian fluid is enhanced by incorporating the impact of thermal radiation, heat sources, Brownian motion, and thermophoresis. The presentation of these phenomena is vital for an extensive range of applications, including industrial processes, biomedical engineering, and environmental management. The analysis employs advanced mathematical modelling which needs suitable transformation rules to get the non-dimensional form and further numerical simulation is presented with the assistance of the “shooting-based fourth-order Runge-Kutta technique”. The results are depicted for the several contributing factors via the built-in in-house function bvp4c in “MATLAB”. The authentication of the study with the prior research is a benchmark to precede further research in this direction. However, the outstanding results are; the fluid velocity is controlled by increasing non-Newtonian Weissenberg number whereas the velocity slip shows dual characteristics on the axial velocity distribution. Further, the motile microorganism profile is controlled by the enhanced bioconvection Lewis number.

Deciphering the driving factors and probabilistic health risks of potentially toxic elements in arid surface water: Insights from the Tarim River Basin

Potentially toxic elements (PTEs) in surface water in arid areas pose a serious threat to environmental safety and human health within a basin. It is important to determine the factors controlling PTEs and to assess the likelihood that they will pose a risk to human health in order to support the development of environmental protection and risk management strategies. In this study, a structural equation model and Bayesian method were combined to discuss the distribution and probabilistic health risks of PTEs in surface water in arid area, and the Tarim River Basin was taken as a case study. The results show that the average concentrations of As, Co, Cu, and Ni in the surface water in the Tarim River Basin ranged from 0.04 to 2.92 μg/L, which do not exceed the international standard values. However, the maximum value of As (19.20 μg/L) exceeded both the recommended drinking water standards and the Chinese irrigation water standards. Spatially, the high As concentrations were distributed in the upper reaches of the Kashgar River, and the high Co, Cu and Ni concentrations were distributed in reservoirs and lakes on the main stream of the Tarim River. The concentrations of the PTEs in the surface water in the basin were not only affected by random anthropogenic factors such as traffic discharge, agricultural activities and mining industry, but were also directly and indirectly influenced by climatic factors. The results of the probabilistic health risk assessment showed that the 95th percentile the total hazard index for infants exceeded the allowable value of 1, and the total carcinogenic risk of PTEs exposure in four age groups was at the notable level. In this study, we conducted a comprehensive analysis of the controlling factors and health risks associated with PTEs in surface water in the Tarim River Basin, and the findings are expected to provide a scientific basis for regional water environment management and safety control.

Ethnoecology: The Community Adaptation Patterns of Forest Management in Grobogan Central Java

The aims of this research are to describe community adaptation patterns and determine community perceptions regarding forest environmental management. This qualitative research was studied using an ethnoecological approach with the research focus being the people of the Perhutani area of ​​Grobogan Regency. This research carried out the data collection through interviews, observation and documentation, with the main informant being Pesanggem as a forest land manager. This research produced the first findings in the form of community adaptation patterns in managing the environment covering three aspects, namely ecological adaptation, economic adaptation and social adaptation in the Pesanggem community in Gedangan Village, Wirosari District under the auspices of BKPH Sambirejo. 1) Ecological adaptation in Pesanggem showed the availability of well water which previously only relied on rainwater, then adjustments to various types of plants, as well as an understanding of prohibitions and sanctions for illegal activities in forest areas; 2) economic adaptation showed an increase in income for Pesanggem from forest land management; 3) social adaptation showed the existence of cooperation between members and other farmer groups within the LMDH forum. The second finding is that the public's perception in interpreting environmental management is that there are 5 values, namely the values ​​of wisdom, independence, religion, creativity and healthy living. Based on the research results, the author recommends that forest area communities be involved in managing and guarding forests for generational sustainability, and Perum Perhutani should invite partners from surrounding school institutions as a means of educating generations in joint forest management.

Preparation of Superhydrophobic and Multifunctional Sponges for Oil/Water Separation and Oil Absorption.

For settling the recycling problem of waste polyurethane sponges (PU) and environment pollution of oil spills simultaneously, this work exploited the multifunctional superhydrophobic PU materials via the dip-coating method, which were prepared by anchoring modified Fe3O4 and expandable graphite (EG) on PU sponges under the adhesion effect of polydimethylsiloxane (PDMS). The water contact angle and sliding angle of as-prepared PU sponges reached 154.1 ± 1.6 and 8°, respectively. Most importantly, the superhydrophobic PU sponges were endowed with the multipath oil treatment ability, which consisted of magnetically driven, gravity-driven, peristaltic pump-driven, and photothermally driven modes. Besides, the light oil absorption capacity, separation flux, and efficiency for superhydrophobic PU sponges reached 23.9 g/g, 27779 L m-2 h-1, and 99.5%, respectively. Owing to the photothermal conversion ability of Fe3O4 and EG, the temperature of superhydrophobic PU sponges was raised to 71.5 °C within 233 s under 1.2 solar irradiation (1200 W/m2), demonstrating its absorption potential for high-viscosity crude oils. In addition, the prepared sponges exhibited good chemical/mechanical stability, self-cleaning, and flame retardancy. In a nutshell, this article has evolved an environmentally benign and practical method for fabricating the multifunctional materials in oil spill treatment, which will efficiently accomplish the targets of low carbon and environmental management.

Quantifying Streamflow Prediction Uncertainty Through Process‐Aware Data‐Driven Models

ABSTRACTThe hydrological model simulation accompanied with uncertainty quantification helps enhance their overall reliability. Since uncertainty quantification including all the sources (input, model structure and parameter) is challenging, it is often limited to only addressing model parametric uncertainty, neglecting other uncertainty sources. This paper focuses on exploiting the potential of state‐of‐the‐art data‐driven models (or DDMs) in quantifying the prediction uncertainty of process‐based hydrological models. This is achieved by integrating the robust predictive ability of the DDMs with the process understanding ability of the hydrological models. The Bayesian‐based data assimilation (DA) technique is used to quantify uncertainty in process‐based hydrological models. This is accomplished by choosing two DDMs, random forest algorithm (RF) and support vector machine (SVM), which are distinctly integrated with two process‐based hydrological models: HBV and HyMOD. Particle filter algorithm (PF) is chosen for uncertainty quantification. All these combinations led to four different process‐aware DDMs: HBV‐PF‐RF, HBV‐PF‐SVM, HyMOD‐PF‐RF and HyMOD‐PF‐SVM. The assessment of these models on the Baitarani, Beas and Sunkoshi river basins exemplified an improvement in the accuracy of the daily streamflow simulations with a reduction in the prediction uncertainty across all the models for all the basins. For example, the nash‐sutcliffe efficiency improved by 54.69% and 10.61% in calibration and validation of the Baitarani river basin, respectively. Equivalently, average bandwidth improved by 79.37% and 71.59%, respectively. This signified the (a) potential of the DDMs in quantifying and reducing the prediction uncertainty of the hydrological model simulations, (b) transferability of the model with an appreciable performance irrespective of the choice of basins having varying topography and climatology and (c) ability to perform significantly irrespective of different process‐based and DDMs being involved, thereby ensuring generalizability. Thus, the framework is expected to assist in effective decision‐making, including various environmental management and disaster preparedness.

Understanding Polycyclic Aromatic Hydrocarbon Accumulation in Road Dust of a Tropical Megacity in Southern Vietnam: Implications on Environmental Management

This study investigated the characteristics of 23 PAHs in road dust from various areas in Ho Chi Minh City (HCMC), focusing on spatial distribution, pollution levels, human health risks, and source apportionment. PAH levels in urban samples (residential and industrial sites) ranged from 208 to 7665 (μg/kg), significantly higher than background levels (135±42.2μg/kg). A west>east gradient in PAH distribution, particularly in crowded traffic intersections, suggested traffic activities as a major source. Pollution load indices indicated moderate to very high pollution in most urban sites. Incremental lifetime cancer risk assessments showed moderate to high risks, especially for children. Statistical analyses and diagnostic ratios identified vehicular emissions as the primary PAH sources, with Positive Matrix Factorization analysis attributing 46.6% to gasoline vehicles, 21.9% to diesel vehicles and petroleum evaporation, 18.3% to tar oil, and 10.2% to coal burning. This study fills a significant information gap on PAHs in road dust, which has not been previously reported in southern Vietnam, specifically in HCMC-a dynamic and rapidly developing city in Southeast Asia. The findings highlight the need for synchronized management and technical solutions to mitigate PAH risks in road dust, contributing valuable knowledge on PAH accumulation in a major southern city of Vietnam.

Target detection and simultaneous degradation of furazolidone by molecularly imprinted CoWO4/g-C3N4

In this study, a "Two birds with one stone" strategy was employed to concurrently address the challenges of electrochemical detection and photocatalytic degradation of the environmentally hazardous furazolidone (FRZ). An innovative molecularly imprinted CoWO4/g-C3N4 (i.e. MIP-CoWO4/g-C3N4) nanomaterials was constructed through a combination of hydrothermal and electrochemical polymerization techniques. The resulting MIP-CoWO4/g-C3N4 nanocomposites can be served as an exceptional sensing platform for FRZ detection, demonstrating low detection limit (2.61×10−13 mol L−1), considerable sensitivity (2.03 μA. nM−1. mm−2), excellent selectivity and decent stability. Meanwhile, the MIP-CoWO4/g-C3N4 nanocomposites exhibited remarkable photocatalytic efficiency for FRZ degradation (79.87 %). In addition, the systematic investigation into the impact of operational reaction parameters on both the electrocatalytic and photocatalytic reactions was conducted, elucidating the plausible mechanisms for both detecting and degrading FRZ. This research provides firm foundation for the development of multifunctional nanomaterials, further advancing the "integration of diagnosis and treatment" in environmental management and control.

Role of supply chain digitalization and global supply chain in decarbonization of natural resources sector supply chain

Environmental management and decarbonization are becoming increasingly critical as industries seek sustainable development paths that align with global climate targets. As businesses aim to reduce their carbon footprint, integrating effective environmental strategies with technological advancements is essential. This necessitates a clear understanding of digital technologies and environmental policies to drive decarbonization efforts. In this context, this study explores the role of digitalization in reducing carbon emissions in the natural resources sector supply chain. Furthermore, it examines the role of supply chain mapping as a mediator in the relationship between supply chain digitalization and supply chain decarbonization efforts, providing a novel perspective on how technology can intersect to foster environmental sustainability. This research targets the metal sector supply chain, a significant contributor to global carbon emissions. The data for the study was gathered through a questionnaire administered to 246 employees from various levels of the metal industry in China. We employed Covariance-based Structural Equation Modelling (CB-SEM) using AMOs for analysis. Our results show that level digitalization of supply chain processes in the metal sector has a profound and direct impact on its supply chain decarbonization. Digital technologies facilitate more efficient resource use, improved energy efficiency, and the adoption of cleaner production methods. Importantly, the study identifies supply chain mapping as a crucial mechanism through which digitalization exerts its positive influence on decarbonization. Through detailed mapping, organizations can gain visibility over their entire supply chain, identifying carbon hotspots and opportunities for improvement that digital solutions can address. The novelty of this study lies in its systematic exploration of how supply chain mapping serves not just as a tool for transparency and efficiency but as a strategic facilitator of the beneficial impacts of digitalization on decarbonization.

The Evolution Of Organizational Energy Management: Developed Methodologies And The ISO 50001 Standard

This article presents the evolution of practices and procedures developed and applied in energy management in organizational environments. The global evolution of energy management and the evolution of guidelines applied in organizational energy management are discussed, which were consolidated in norms and standards, whose peak was reached with the international standard ISO 50001. This article reviews the published works that bring with them some contribution related to the methods developed and applied in conducting the process of implementing an energy management system, where the implementation of the ISO 50001 standard stood out, mainly in industrial environments. In all the works reviewed, it is clear that the success in implementing energy management through the ISO 50001 standard was achieved due to the continuous support of the organization's top management and the involvement and commitment of all members of the organization

Multi-crosslinked Ta4C3TX MXene composites with “interlocked structure” for efficient gamma-ray shielding, behavioural detection and thermal management in nuclear environments

Multi-crosslinked Ta4C3TX MXene composites with “interlocked structure” for efficient gamma-ray shielding, behavioural detection and thermal management in nuclear environments

Embryonic and Pre-Larval Developmental Patterns in Cryptocentroides arabicus (Teleostei, Gobiidae).

The Arabian goby, Cryptocentroides arabicus (Gobiidae: Gobiinae), is a significant species in marine and brackish water ecosystems. However, limited information is available about the reproductive biology and the early life history of this species. This study aimed to understand the embryonic and pre-larval development of C. arabicus under controlled laboratory conditions using light microscopy. Ten fish pairs were placed in five 70-L glass aquaria, and environmental parameters were carefully monitored. After 4 months, spawning began, with each event yielding between 700 and 1500 eggs, totaling 10 spawning events. The elliptical-shaped eggs, measuring 3.9 ± 0.1 mm in length and 1.6 mm in maximum width, hatched after 7 days and 4 h at a water temperature of 28°C. This process resulted in the identification of eight distinct larval developmental stages. Parental care by both the male and female was observed during the incubation period. Documenting the morphological changes during incubation contributes to a better understanding of the reproductive behaviour and early life history of C. arabicus. This is essential for the conservation management of marine and brackish water environments.

How does the use of cryptocurrency affect circular economy practices in manufacturing companies?

In nations facing international pressures, such as sanctions, leaders should attempt to utilize advanced technologies more effectively, while fostering the skills and intelligence of the human resources, and enhancing public confidence in the use of emerging technologies in Industry 5.0. In this article our goal is to investigate the effect of acceptance and use of cryptocurrencies on the circular economy. The theoretical contribution of this research is to enrich the literature related to the factors affecting the adoption of digital currencies and its impact on the circular economy. Also, due to the importance of technology awareness in Industry 5, its effect on the adoption of digital currencies was evaluated. For several decades, Iran has been exposed to political and economic sanctions by the United Nations Security Council, the US, and the European Union (EU). Given the importance of natural resources in Iran's economy, and the presence of barriers regarding financial transactions, all manufacturing companies working in Iran were selected as the statistical population of the current study. The findings showed that variables like the realized ease of use, the realized efficiency, trust, technological intelligence and social influence have been effective on the acceptance and use of cryptocurrencies. Also, use of cryptocurrencies in manufacturing companies has had effect on the circular economy activities. The other research results revealed that the factor of economic sanction in the studied society might have effect on the use of cryptocurrencies and consequently companies’ circular economy. The policy-makers active in the field of the environment, and also managers of manufacturing companies by creating an infrastructure for financial exchange based on digital currency can provide the needed ground for production in line with the environment and sustainable resource management.

Advanced machine learning schemes for prediction CO2 flux based experimental approach in underground coal fire areas

IntroductionUnderground coal fires pose significant environmental and health risks due to releasing CO2 emissions. Predicting surface CO2 flux accurately in underground coal fire areas is crucial for understanding the distribution of spontaneous combustion zones and developing effective mitigation strategies. In recent years, advanced machine learning techniques have shown promise in various carbon-related studies. This research uses an experimental approach to explore the power of advanced machine learning schemes for predicting CO2 flux in underground coal fire areas. ObjectivesBy leveraging the power of advanced machine learning schemes and experimental approaches, this research aims to provide valuable insights into CO2 flux prediction in coal fire areas and inform environmental monitoring and management strategies. MethodsThe study involves the collection of an experimental dataset specific to underground coal fire areas, encompassing various parameters related to CO2 flux and underground coal fire characteristics. Innovative feature engineering techniques are applied to capture the unique characteristics of underground coal fire areas and their impact on CO2 flux. Different machine learning algorithms, including Natural gradient boosting regression (NGRB), Extreme gradient boosting (XGboost), Light gradient boosting (LGRB), and random forest (RF), are evaluated and compared for their predictive capabilities. The models are trained, optimized, and assessed using appropriate performance metrics. ResultsThe NGRB model yields the best predictive performances with R2 of 0.967 and MAE of 0.234. The novel contributions of this study include the development of accurate prediction models tailored to underground coal fire areas, shedding light on the underlying factors driving CO2 flux. The findings have practical implications for delineating the spontaneous combustion zone and mitigating CO2 emissions from underground coal fires, contributing to global efforts in combating climate change.

Associations of menopausal symptoms with job-related stress and social support in Japanese school teachers

ObjectivesBeing a school teacher is highly stressful. This study aimed to clarify the prevalence of menopausal symptoms and explore the association between these symptoms and job-related stress among Japanese school teachers. Study designA cross-sectional study was conducted among randomly selected elementary and junior high school teachers in Japan. Data from 284 teachers aged 45–60 years were analyzed. Main outcome measuresMenopausal symptoms were measured using the Greene Climacteric Scale, and the Brief Job Stress Questionnaire was used to assess job stressors, social support, and job/family satisfaction. Associations between scores on the Greene Climacteric Scale and on the Brief Job Stress Questionnaire, and demographic information were analyzed. ResultsThe most common menopausal symptom was “feeling tired or lacking in energy” (reported by 94.4 % of menopausal respondents). The total intensity of menopausal, psychological, and somatic symptoms was significantly correlated with the total level of job stress. Moderate correlations were found between depressive symptoms and job stress regarding suitable jobs, job control, and rewarding jobs, while weak correlations were evident between depressive symptoms and job stress regarding quantitative job overload, interpersonal conflict, and poor physical environment. Higher levels of perceived support from supervisors or co-workers and job satisfaction were associated with less severe psychological and somatic symptoms. ConclusionsMost middle-aged school teachers felt tired or lacking in energy. Higher job-related stress and lower levels of support from supervisors or co-workers were correlated with more severe menopausal symptoms. A supportive work environment and stress management are essential for such teachers.