Search Results (26,178)

Textile industry wastewater poses a significant environmental challenge due to the presence of persistent dyes. Cationic dyes are characterized by resistance to the conventional coagulation method. The appropriate properties and combination of chemicals guarantee an effective removal process. This study explains the effect of modification of methylene blue solution by the addition of a natural biopolymer—hydrolyzed tannic acid (TA). The study assumed that a combination of tannic acid, methylene blue and polyaluminum chloride would provide a synergistic effect and significantly improve the coagulation and sediment filtration process. Coagulation tests were carried out for a range of methylene blue concentrations. The optimal arrangement of solution components and coagulant doses was selected and tested. Over 95% dye removal efficiency was achieved. The maximum dye removal efficiency was determined to be 5 mg/mg Al at pH = 5.0. Based on the analysis of UV-VIS spectroscopy, FTIR and electrokinetic potential, changes in the solutions of tannin-modified dyes and their effect on the precipitation of flocs and the nature of sorption were determined. The main phenomena affecting the removal mechanism are discussed. The results indicate that tannic acid can serve as a sustainable coagulant aid, supporting the development of technologies for treating cationic-dye-laden wastewater. Full article

Biodiesel is a sustainable and promising alternative energy source produced from renewable raw materials using various methods. One effective approach is simultaneous esterification and transesterification, which relies on suitable catalysts that can be either homogeneous or heterogeneous. Homogeneous catalysts (acid or base) offer high activity but are corrosive and difficult to recover, necessitating energy-intensive processes such as aqueous quenching and neutralization, which can lead to soap formation and stable emulsions. By comparison, heterogeneous catalytic systems overcome many of these challenges due to their ease of recovery, reusability, and simplified product separation, which collectively enhance economic viability and environmental sustainability. This review highlights recent progress in the application of zeolite-based solid catalysts for biodiesel synthesis, with particular emphasis on their use in converting waste cooking oil and other low-cost feedstocks, including non-edible oils, non-food biomass sources, algal resources, and genetically engineered microorganisms. Key factors such as catalytic activity, selectivity, catalyst loading, and reusability are discussed, highlighting the advantages of zeolites due to their unique crystal structure, high thermal stability, and ease of product recovery. Overall, this review underscores the challenges and opportunities in zeolite-based catalysis to provide a comprehensive understanding of its potential to enhance the efficiency and scalability of biodiesel production. Full article

Arsenic contamination in groundwater is a severe and widespread environmental and public health challenge. Recent years have witnessed rapid advances in catalytic remediation technologies, particularly those integrating advanced oxidation processes (AOPs), bifunctional materials, and field-scale applications. This comprehensive review synthesizes recent developments, emphasizing the synergy between catalytic oxidation and adsorption, the design of innovative and recyclable materials, and the practical translation of laboratory findings to real-world remediation scenarios. Key breakthroughs include dual-function catalysts for combined contaminant removal, scalable systems compatible with renewable energy, and hybrid strategies integrating conventional and catalytic routes. Case studies from arsenic hotspots worldwide demonstrate not only technological feasibility but also highlight knowledge gaps and sustainability challenges. By evaluating catalytic mechanisms, operational performance, and environmental impact, this review identifies promising directions for the next generation of arsenic remediation and offers a critical roadmap to guide future research and practice. Full article

The synergistic effects of soil acidification and heavy metal pollution present major challenges for global agroecosystems. To systematically trace the evolution of research and identify key topics in this field, this study employed CiteSpace to visualize and analyze 691 records from the China National Knowledge Infrastructure (CNKI) and 6747 highly relevant articles or reviews from the Web of Science (WOS) Core Collection database from 2005 to 2025. The results indicate a steady to rapid rise in global publications, with China contributing the largest share, at 2468 publications. This has produced a research cluster centered around the Chinese Academy of Sciences (CAS); however, the centrality of its international cooperation remains limited. Studies in the CNKI database are driven by agricultural needs, focusing on national food security, rice yield stability, improvement of arable land, and heavy metal passivation and remediation, with a concentration on basic agricultural science. By contrast, research in the WOS database emphasizes fundamental mechanisms and interdisciplinary integration, addressing aluminum toxicity, microbial communities, the nitrogen cycle, and global climate change, intersecting fields such as environmental science, soil science, ecology, and microbiology. The evolution of research hotspots shows a clear trajectory: from acidity regulation and chemical speciation analysis of heavy metals (2005–2013), to heavy metal passivation, remediation, and phytoremediation (2014–2018), and then to biochar materials, microbiome analysis, and the synergistic role of carbon sequestration (2019–2025). This study argues that future research should move beyond single remediation measures and adopt integrated strategic management to jointly improve bioremediation efficiency, promote soil carbon sequestration and soil health, and enhance microbial adaptation to global climate change. Full article

Sulfur-mediated autotrophic denitrification (SAD) is an innovative and sustainable water treatment technology, which operates without an external carbon source and achieves lower sludge production. Firstly, this review provides a detailed examination of sulfur-based fillers, encompassing their respective types, preparation methods, advantages and drawbacks. Subsequently, it reviews the mainstream functional microbial communities across various process stages, such as Thiobacillus, Sulfurimonas, and Ignavibacterium. Moreover, the process characteristics of mainstream SAD reactor types, such as fluidized bed, fixed bed, and moving bed biofilm reactors, are reviewed, and the effects of key process parameters like pH, temperature, and dissolved oxygen on treatment efficiencies are further analyzed. Additionally, the applications cases of SAD in advanced wastewater treatment, river remediation, wetland restoration, and groundwater purification are summarized, demonstrating its broad and diverse application potential in environmental engineering. Finally, key challenges of SAD are identified, including the complexity of microbial metabolic interactions, the accumulation of intermediate products, and the need for improved fillers and reactor configurations. Future research priorities are discussed in three areas: microbial community regulation, control and utilization of intermediate products, and development of advanced fillers and reactor configurations. Overall, this review integrates key technical parameters and operational experience of SAD, providing a consolidated reference for researchers and practitioners interested in the development and application of this technology. Full article

As a representative form of extreme weather, typhoons inflict widespread and systemic damage, posing a severe threat to the livestock industry. The stress they induce, typhoon stress (TS), is an unavoidable and complex environmental challenge that severely disrupts the ovarian function of Wenchang chickens. In this preliminary study, we employed a two-group comparison design (n = 6 per group) integrating behavioral observations, serum biochemical assays, histopathological examinations, and molecular analyses (qPCR, 16S rDNA sequencing, and transcriptome sequencing) to explore the role of the microbiota–gut–brain–ovarian axis (MGBOA) in this process. The findings revealed that TS markedly reduced water intake and locomotor activity, while it elevated serum corticosterone (CORT) and oxidative stress markers. It also induced shifts in gut microbiota composition, including a decrease in Bacteroides and an increase in Escherichia–Shigella. Furthermore, TS compromises duodenal intestinal barrier integrity, as evidenced by downregulation of the tight junction proteins TJP1 and CLDN1, structural damage to intestinal villi, and a reduced villus-to-crypt ratio. In the hypothalamus, VIP mRNA expression was upregulated, while GHSR expression was downregulated; the expression of the tight junction protein CLDN5 was also reduced. In the ovary, reproductive potential was suppressed, manifested by a reduction in follicle number and downregulation of STAR expression. Ovarian transcriptome analysis highlighted enrichments in pathways associated with inflammation (e.g., Toll-like receptor signaling) and lipid metabolism (e.g., PPAR signaling). These results support the hypothesis that TS impairs egg production via the MGBOA, providing preliminary mechanistic insights into how environmental stressors might disrupt animal productivity through MGBOA-mediated pathways. Full article

Odour recognition with low-cost gas sensors is challenging in open-air settings due to the non-specificity of the sensors and environmental variability. This can be mitigated by incorporating additional information into the classification process. This paper investigates odour-image multimodality in two case-studies of increasing complexity: banana ripening in open-air environment and strawberry ripening in a glasshouse environment. Data were collected using custom acquisition platforms equipped with cameras and MOX gas sensors operated with temperature modulation. For the visual modality, image classification (MobileNetV3) and object detection (YoloV5) models are trained. For the odour modality, established classical machine learning methods (Random Forest, XGBoost, SVM and Logistic Regression) and neural networks (1D-CNN, LSTM, MLP, and ELM) are employed. Each modality is analysed independently and together to critically assess scenarios in which combining modalities provides a clear advantage over using either modality alone. Results show that models trained on odour data achieve high accuracy in controlled environments but underperform in more dynamic open-air settings. Image-based models are sensitive to the image quality in all environments; however, they are more robust when deployed in different environments. Lastly, it is demonstrated that decision fusion consistently increases the accuracy, by as much as +12.36% in the banana ripening and +3.63% in the strawberry ripening scenario. Where decision fusion does not improve classification accuracy significantly, it is shown that the multimodal approach can still be leveraged to identify high-confidence predictions by selecting samples where both modalities agree on the label. Full article

Postsecondary institutions are seeing an increased prevalence of student mental health concerns and disabilities, highlighting the need for campus-based approaches that support student well-being. While college campuses provide many services to support students, occupational therapists are largely absent from these support systems, despite growing interest in this emerging field of practice. This program description and implementation case study examines preliminary indicators of feasibility for the WILL Thrive program, which delivered occupational therapy (OT) services on a college campus through a Level II fieldwork placement. Feasibility was examined across domains of acceptability, demand and implementation using an integrated approach combining a needs assessment, service development and process evaluation. Data sources included environmental observations, surveys, stakeholder interviews and process evaluation measures, including service delivery tracking, referral patterns, and resource utilization. Referrals and service utilization in this case were most frequently observed among students reporting neurodevelopmental and mental health-related functional challenges, providing preliminary indicators of potential service users, though a small, heterogeneous sample size limits generalizability. Referral patterns and engagement from the wellness center and accessibility staff highlight preliminary strengths of the program, including early indicators of acceptability and demand. In contrast, implementation barriers were also identified, including limited campus-wide understanding of the OT scope and role and constraints in on-campus OT supervision. Findings offer early, exploratory signals of feasibility for integrating OT services through an OT fieldwork II model and suggest that OT may complement existing campus supports by addressing participation-focused, functionally orientated needs. Results should be viewed as preliminary and inform future implementation studies that include systematic outcome measures, comparative analysis with existing services, and broader assessment across diverse higher education contexts. Full article

Heart rate variability (HRV) has emerged as a key biomarker for assessing autonomic nervous system activity, stress, fatigue, and emotional states. With the rapid development of wearable sensor technologies, HRV analysis has expanded from clinical environments to real-world, continuous monitoring. This review summarizes current applications of HRV metrics in wearable devices, including fitness tracking, mental stress assessment, sleep quality evaluation, and early detection of physiological or psychological disorders. Recent advances in photoplethysmography (PPG)-based HRV estimation have enabled noninvasive and user-friendly measurement, though challenges remain in accuracy under motion and variable environmental conditions. We also discuss methodological considerations, such as artifact correction, data segmentation, and the integration of HRV with other biosignals for multimodal analysis. Emerging research suggests that combining HRV with metrics such as respiration rate, skin conductance, and accelerometry can enhance robustness and interpretability in dynamic settings. Finally, future directions are proposed toward personalized health analytics, emotion-aware computing, and real-time adaptive feedback systems. This review highlights the growing potential of wearable HRV analysis as a foundation for preventive healthcare and human–machine symbiosis. Full article

Semi-coking wastewater generated during coal pyrolysis contains extremely high concentrations of refractory organic pollutants, resulting in elevated chemical oxygen demand (COD) and posing significant environmental risks, making efficient COD removal a critical challenge for sustainable wastewater treatment in the coal chemical industry. In this study, a porous carbon-based resin (XDA-1G) was investigated as an adsorbent for COD removal from semi-coking wastewater. The adsorption performance and underlying mechanisms were systematically evaluated through adsorption isotherm, kinetic, and thermodynamic analyses, combined with structural characterization using FTIR, XPS, BET, XRD, and SEM–EDS. The resin exhibited a high COD removal efficiency of up to 91% with a maximum adsorption capacity of 2182 mg g⁻¹. Kinetic analysis followed the pseudo-second-order model, while the Freundlich isotherm best described the equilibrium behavior, indicating heterogeneous adsorption. Thermodynamic parameters confirmed that the adsorption process is spontaneous and endothermic. Spectroscopic and structural analyses revealed that COD removal is mainly governed by synergistic mechanisms including π–π interactions between aromatic pollutants and the carbon framework, hydrogen bonding with oxygen-containing functional groups, and pore filling within the hierarchical porous structure. These findings demonstrate the strong potential of porous carbon-based resins as efficient adsorbents for treating high-strength industrial wastewater. Full article

Trajectory planning in dynamic multi-vehicle interaction environments faces three critical challenges, including the difficulty of quantifying spatial risk distributions, the complexity of characterizing behavioral uncertainty arising from the multimodal maneuvers of surrounding vehicles, and the challenge of simultaneously optimizing multiple competing objectives such as safety, efficiency, comfort, and energy consumption. To address these challenges, this paper proposes an Improved Driving Risk Field-based Multi-objective Trajectory Optimization (IDRF-MTO) method. First, a joint spatiotemporal social attention mechanism achieves unified modeling of spatial interactions, temporal dependencies, and spatiotemporal coupling, combined with a lateral–longitudinal intent strategy for multimodal trajectory prediction. Second, an improved dynamic risk field model is constructed comprising three components: a vehicle risk field that incorporates spatial orientation and motion direction factors for anisotropic risk representation, along with a collision tendency factor that converts objective risk into effective risk; a predicted trajectory risk field that achieves anticipatory quantification of future risk from surrounding vehicles through confidence-weighted fusion; and a driving environment risk field that encapsulates road geometry, static obstacles, and environmental conditions. Finally, a multi-objective cost function embedding risk field gradients is formulated, and multi-objective coordinated optimization is realized through a three-dimensional spatiotemporal situation graph with adaptive safety sampling. Simulation results demonstrate that the proposed method enhances safety while simultaneously improving comfort and efficiency and reducing energy consumption, exhibiting excellent planning performance in complex dynamic environments. Full article

Tailings management presents a critical challenge for the mining industry, particularly in mountainous regions with high seismicity and steep slopes. This article presents the development and design criteria for dry stacking of filtered tailings as a sustainable and safe alternative to conventional slurry tailings storage facilities (TSFs). The study focuses on the extreme conditions of a mountainous location characterized by complex topography with 10% slopes, space constraints, and significant seismic activity defined by a peak ground acceleration (PGA) of 0.3 g. The design methodology, which incorporates layered compaction of the filtered tailings to achieve a geotechnically stable structure, is detailed for a filtered TSF consisting of 7 terraces, each 10 m high, reaching a total height of 70 m. This approach minimizes the risk of liquefaction and prepares the filtered tailings surface for progressive closure, with unit operating costs (OPEX) of 2.5 USD/t. The results of the physical stability analysis confirm the viability of this solution: pseudo-static stability analysis yielded a safety factor of 1.22, demonstrating a significant reduction in water consumption and potential environmental impact. It is concluded that the dry disposal of filtered tailings is a technically robust option for tailings management in extreme mountainous environments, offering greater long-term safety guarantees and facilitating landscape integration, thus setting a precedent for mining projects in similar geographies. Full article

The circular economy necessitates the identification of waste management methods that minimise the use of environmental resources and do not generate secondary waste streams, whose management poses further challenges. The aim of this analysis was to evaluate the environmental and energy performance of slaughterhouse waste treatment using anaerobic digestion and incineration. The quantity of greenhouse gases emitted during slaughterhouse waste processing was adopted as the evaluation criterion. Although the incineration of slaughterhouse waste delivered a higher net energy yield compared with anaerobic digestion, it was characterised by substantially higher carbon dioxide emissions per unit of energy. Anaerobic digestion of poultry slaughterhouse waste demonstrated superior environmental performance, provided that the resulting digestate is utilised as a source of plant nutrients. The modification of the anaerobic digestion technology did not lead to a reduction in greenhouse gas emissions per unit of energy produced. The most effective method for the treatment of poultry slaughterhouse waste was anaerobic digestion without co-digestion, combined with the use of digestate as a feedstock for fertiliser production. For small slaughterhouses generating less than 3 tonnes of waste per day, incineration was the more rational solution. The efficient utilisation of slaughterhouse waste critically depends on its processing at the place of generation. Full article

Air–ground collaborative systems leverage the complementary strengths of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) and hold significant potential for logistics in complex, unstructured environments. However, trajectory planning in infrastructure-free mountainous regions remains challenging owing to the need for continuous tight coupling, obstacle avoidance, and reliable communication-link maintenance. To address these challenges, this study proposes a cooperative trajectory planning framework that enforces strict inter-vehicle distance constraints to maintain communication connectivity. By formulating the coordination problem in terms of relative configurations between air and ground vehicles, the proposed framework exhibits translational invariance, reflecting an underlying symmetry with respect to global position shifts. This symmetry-aware formulation reduces reliance on absolute coordinates and promotes consistent cooperative behavior under environmental variability. The trajectory planning problem is mathematically formulated as a constrained multi-objective nonlinear programming (MONLP) model that balances energy consumption and trajectory smoothness. An adaptive inertia weight particle swarm optimization (AIWPSO) algorithm is developed to efficiently solve the resulting optimization problem. Simulation results demonstrate that the proposed approach generates smooth, collision-free trajectories while maintaining stable air–ground coordination, demonstrating improved feasibility and robustness over conventional planning methods in unstructured mountainous environments. Full article

The development of effective water disinfection treatment processes will be crucial to help food producers save water and cope with the inevitable challenges resulting from increases in human population and climate change, while promoting sustainable agriculture. The inactivation efficiency of UV-C light emitting diodes (LEDs) that emit light at 280 nm was tested as a disinfection method. Water samples from a horticulture industry were collected and characterized in terms of total microorganisms, total coliforms, Escherichia coli and enterococci as well as parameters that influence photolysis such as the percent transmittance of the irrigation water (that, due to the nutrients added for plant growth, was extremely low and varied between 40 and 55%). Nevertheless, laboratory scale results showed that three single small UV LEDs that emit light at 280 nm were extremely efficient for the inactivation of microorganisms present at occurrence levels in the irrigation water samples, as well as Phytophthora capsici and Escherichia coli spiked in sterile distilled water and filtered irrigation water samples. Overall, the findings demonstrate that UV-C LEDs operating at 280 nm represent a promising sustainable disinfection strategy for modern food production systems facing tightening environmental and public-health pressures. Full article