Search Results (9,224)

Exposure to per- and polyfluoroalkyl substances (PFASs) can cause detrimental health effects. The consumption of contaminated food is viewed as a major exposure pathway for humans, but the relationship between agriculture and PFASs has not been investigated thoroughly, and it is becoming a pressing issue since health advisories are continuously being reassessed. This semi-systematic literature review connects the release, environmental fate, and agriculture uptake of PFASs to enhance comprehension and identify knowledge gaps which limit accurate risk assessment. It focuses on the heavily agricultural state of Minnesota, USA, which is representative of the large Midwestern US Corn Belt in terms of agricultural activities, because PFASs have been monitored in Minnesota since the beginning of the 21st century. PFAS contamination is a complex issue due to the over 14,000 individual PFAS compounds which have unique chemical properties that interact differently with air, water, soil, and biological systems. Moreover, the lack of field studies and monitoring of agricultural sites makes accurate risk assessments challenging. Researchers, policymakers, and farmers must work closely together to reduce the risk of PFAS exposure as the understanding of their potential health effects increases and legacy PFASs are displaced with shorter fluorinated replacements. Full article

This paper presents a comprehensive review of dealuminated metakaolin (DK), a hazardous industrial by-product generated by the aluminium sulphate (alum) industry and evaluates its potential as a component in cementitious systems for the partial or full replacement of Portland cement (PC). Positioned within the context of waste valorisation in concrete, the review aims to establish a critical understanding of DK formation, properties, and reactivity, particularly its pozzolanic potential, to assess its suitability for use as a supplementary cementitious material (SCM), or as a precursor in alkali-activated cement (AAC) systems for concrete. A systematic methodology is used to extract and synthesise relevant data from existing literature concerning DK and its potential applications in cement and concrete. The collected information is organised into thematic sections exploring key aspects of DK, beginning with its formation from kaolinite ores, followed by studies on its pozzolanic reactivity. Applications of DK are then reviewed, focusing on its integration into SCMs and alkali-activated cement (AAC) systems. The review consolidates existing knowledge related to DK, identifying scientific gaps and practical challenges that limit its broader adoption for cement and concrete applications, and outlines future research directions to provide a solid foundation for future studies. Overall, this review highlights the potential of DK as a low-carbon, circular-economy material and promotes its integration into efforts to enhance the sustainability of construction practices. The findings aim to support researchers’ and industry stakeholders’ strategies to reduce cement clinker content and mitigate the environmental footprint of concrete in a circular-economy context. Full article

The Santurbán paramo is a sensitive high-mountain ecosystem exposed to pressures from extractive and agricultural activities, as well as increasing tourism. In response, this study presents a context-aware recommendation system designed to support sustainable tourism through the integration of deep neural networks and ontology-based semantic modeling. The proposed system delivers personalized recommendations—such as activities, accommodations, and ecological routes—by processing user preferences, geolocation data, and contextual features, including cost and popularity. The architecture combines a trained TensorFlow Lite model with a domain ontology enriched with GeoSPARQL for geospatial reasoning. All inference operations are conducted locally on Android devices, supported by SQLite for offline data storage, which ensures functionality in connectivity-restricted environments and preserves user privacy. Additionally, the system employs geofencing to trigger real-time environmental notifications when users approach ecologically sensitive zones, promoting responsible behavior and biodiversity awareness. By incorporating structured semantic knowledge with adaptive machine learning, the system enables low-latency, personalized, and conservation-oriented recommendations. This approach contributes to the sustainable management of natural reserves by aligning individual tourism experiences with ecological protection objectives, particularly in remote areas like the Santurbán paramo. Full article

Outdoor access, often referred to as pop holes, is widely used to improve the production and welfare of hens. Such cage-free environments present an opportunity for precision flock management via best environmental control practices. However, outdoor access disrupts the integrity of the indoor environment, including properly planned ventilation. Moreover, complaints exist that hens do not use the holes to access the outdoor environment due to the strong incoming airflow through the outdoor access, as they behave as uncontrolled air inlets in a negative pressure ventilation system. As the egg industry transitions to cage-free systems, there is an urgent need for validated computational fluid dynamics (CFD) models to optimize ventilation strategies that balance animal welfare, environmental control, and production efficiency. We developed and validated CFD models of a cage-free hen house with outdoor access by specifying real-world conditions, including two exhaust fans, sidewall ventilation inlets, wire-meshed pens, outdoor access, and plenum inlets. The simulations of four ventilation scenarios predict the measured air flow velocity with an error of less than 50% for three of the scenarios, and the simulations predict temperature with an error of less than 6% for all scenarios. Plenum-based systems outperformed sidewall systems by up to 136.3 air changes per hour, while positive pressure ventilation effectively mitigated disruptions to outdoor access. We expect that knowledge of improved ventilation strategy will help the egg industry improve the welfare of hens cost-effectively. Full article

The genus Sonchus (Asteraceae) comprises 98 species, including 17 predominantly herbaceous taxa native to the Mediterranean region. These plants have long been utilized as traditional wild food sources due to their high nutritional value, as they are rich in vitamins A, C, and K, essential minerals, and bioactive compounds with antioxidant and anti-inflammatory properties. This review aims to provide a comprehensive synthesis of the taxonomy, geographic distribution, phytochemical composition, traditional uses, historical significance, and pharmacological properties of Sonchus species. A systematic literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies from 1980 to 2024. Inclusion and exclusion criteria were applied, and methodological quality was assessed using standardized tools. A bibliometric analysis of 440 publications (from 1856 to 2025) reveals evolving research trends, with S. oleraceus, S. arvensis, and S. asper being the most extensively studied species. The review provides detailed taxonomic insights into 17 species and 14 subspecies, emphasizing their ecological adaptations and biogeographical patterns. Additionally, it highlights the cultural and medicinal relevance of Sonchus since antiquity while underscoring the threats posed by environmental degradation and changing dietary habits. Sonchus oleraceus and S. tenerrimus dominate the culinary applications of the genus, likely due to favorable taste, wide accessibility, and longstanding cultural importance. The comprehensive nutritional profile of Sonchus species positions these plants as valuable contributors to dietary diversity and food security. Finally, the study identifies current knowledge gaps and proposes future research directions to support the conservation and sustainable utilization of Sonchus species. Full article

Root phenology significantly influences ecosystem processes yet remains poorly characterized across biomes. This study synthesized data from 59 studies spanning Arctic to tropical ecosystems to identify woody plants root phenological patterns and their environmental drivers. The analysis revealed distinct climate-specific patterns. Arctic regions had a short growing season with remarkably low temperature threshold for initiation of root growth (0.5–1 °C). Temperate forests displayed pronounced spring-summer growth patterns with root growth initiation occurring at 1–9 °C. Mediterranean ecosystems showed bimodal patterns optimized around moisture availability, and tropical regions demonstrate seasonality primarily driven by precipitation. Root-shoot coordination varies predictably across biomes, with humid continental ecosystems showing the highest synchronous above- and belowground activity (57%), temperate regions exhibiting leaf-before-root emergence (55%), and Mediterranean regions consistently showing root-before-leaf patterns (100%). Winter root growth is more widespread than previously recognized (35% of studies), primarily in tropical and Mediterranean regions. Temperature thresholds for phenological transitions vary with climate region, suggesting adaptations to environmental conditions. These findings provide a critical, region-specific framework for improving models of terrestrial ecosystem responses to climate change. While our synthesis clarifies distinct phenological strategies, its conclusions are drawn from data focused primarily on Northern Hemisphere woody plants, highlighting significant geographic gaps in our current understanding. Bridging these knowledge gaps is essential for accurately forecasting how belowground dynamics will influence global carbon sequestration, nutrient cycling, and ecosystem resilience under changing climatic regimes. Full article

The demand for high-performance computing (HPC) continues to grow, driven by its critical role in advancing innovations in the rapidly evolving field of artificial intelligence. HPC has now entered the era of exascale supercomputers, introducing significant challenges related to sustainability. Balancing HPC performance with environmental sustainability presents a complex, multi-objective optimization problem. To the best of the author’s knowledge, no recent comprehensive investigation has explored the interplay between supercomputer performance and sustainability over a five-year period. This paper addresses this gap by examining the balance between these two aspects over a five-year period. This study collects and analyzes multi-year data on supercomputer performance and energy efficiency. The findings indicate that supercomputers pursuing higher performance often face challenges in maintaining top sustainability, while those focusing on sustainability tend to face challenges in achieving top performance. The analysis reveals that both the performance and power consumption of supercomputers have been rapidly increasing over the last five years. The findings also reveal that the performance of the most computationally powerful supercomputers is directly proportional to power consumption. The energy efficiency gains achieved by some top-performing supercomputers become challenging to maintain in the pursuit of higher performance. The findings of this study highlight the ongoing race toward zettascale supercomputers. This study can provide policymakers, researchers, and technologists with foundational evidence for rethinking supercomputing in the era of artificial intelligence. Full article

The ongoing degradation of global forests has severely weakened ecosystem service functions, and traditional judicial remedies have struggled to quantify intangible ecological losses. China has become an important testing ground for restorative justice through the establishment of specialized environmental courts and the practice of environmental public interest litigation. Since 2015, China has actively explored and institutionalized the application of the concept of restorative justice in its environmental justice reform. This concept emphasizes compensating environmental damages through actual ecological restoration acts rather than relying solely on financial compensation. This shift reflects a deep understanding of the limitations of traditional environmental justice and an institutional response to China’s ecological civilization construction, providing critical support for forest ecosystem restoration and enabling ecological restoration activities, such as replanting and re-greening, habitat reconstruction, etc., to be enforced through judicial decisions. This study conducts a qualitative analysis of judicial rulings in forest restoration cases to systematically evaluate the effectiveness of restorative justice in compensating for losses in forest ecosystem service functions. The findings reveal the following: (1) restoration measures in judicial practice are disconnected from the types of ecosystem services available; (2) non-market values and long-term cumulative damages are systematically underestimated, with monitoring mechanisms exhibiting fragmented implementation and insufficient effectiveness; (3) management cycles are set in violation of ecological restoration principles, and acceptance standards lack function-oriented indicators; (4) participation of key stakeholders is severely lacking, and local knowledge and professional expertise have not been integrated. In response, this study proposes a restorative judicial framework oriented toward forest ecosystem services, utilizing four mechanisms: independent recognition of legal interests, function-matched restoration, application of scientific assessment tools, and multi-stakeholder collaboration. This framework aims to drive a paradigm shift from formal restoration to substantive functional recovery, providing theoretical support and practical pathways for environmental judicial reform and global forest governance. Full article

Air pollution is linked to childhood mortality and morbidity in low- and middle-income countries globally. There is growing evidence linking air pollution to asthma and other respiratory diseases in children. Studies have shown that children are likely to experience asthma due to their narrow airways and their heightened sensitivity to environmental irritants. This study aims to investigate the relationship between ambient air pollution and respiratory diseases in children under the age of 5. The study will be conducted in the informal township of Alexandra, north of Johannesburg, South Africa. A quantitative approach will be used in this cross-sectional analytical study. Data will be collected using different tools that include a questionnaire to determine the prevalence of asthma and respiratory disease and potential risk factors. While environmental air pollution will be measured using Radiello passive samplers and Gillian pumps. Data will be analyzed using the latest version of the STATANow/MP 19.5 software. Furthermore, health risk assessment will be conducted for lifetime non-carcinogenic and carcinogenic risk estimation following the USEPA framework. The study will identify environmental triggers that exacerbate asthma and other respiratory conditions in other similar community settings and will contribute to the body of knowledge in public health. Ethical approval was obtained from the Research Ethics Committee, Faculty of Health Sciences at the University of Johannesburg. Full article

This paper presents a critical and comprehensive review of the application of mining waste, specifically waste rock and tailings, in asphalt pavements, with the aim of synthesizing performance outcomes and identifying key research gaps. A systematic literature search yielded a final dataset of 41 peer-reviewed articles for detailed analysis. Bibliometric analysis indicates a notable upward trend in annual publications, reflecting growing academic and practical interest in this field. Performance-based evaluations demonstrate that mining wastes, particularly iron and copper tailings, have the potential to enhance the high-temperature performance (i.e., rutting resistance) of asphalt binders and mixtures when utilized as fillers or aggregates. However, their effects on fatigue life, low-temperature cracking, and moisture susceptibility are inconsistent, largely influenced by the physicochemical properties and dosage of the specific waste material. Despite promising results, critical knowledge gaps remain, particularly in relation to long-term durability, comprehensive environmental and economic Life-Cycle Assessments (LCA), and the inherent variability of waste materials. This review underscores the substantial potential of mining wastes as sustainable alternatives to conventional pavement materials, while emphasizing the need for further multidisciplinary research to support their broader implementation. Full article

This study investigates the foundational causes of unsustainability that obstruct efforts to address global challenges such as climate change, environmental degradation, water crises, and public health deterioration. Using qualitative research with in-depth expert interviews from education, environmental studies, and business, it finds that these global challenges, while visible on the surface, are deeply rooted in worldviews that shape human behavior, societal structures, and policies. Building on this insight, the thematic analysis manifests three interrelated systemic paradigms as the fundamental drivers of unsustainability: a crisis of wholeness, reflected in fragmented identities and collective disorientation; a disconnection from nature, shaped by human-centered perspectives; and the influence of dominant political-economic systems which prioritize growth logics over ecological and social concerns. These paradigms underlie both structural and cognitive barriers to systemic transformation, which influence the design and implementation of education for sustainability. By clarifying a body of knowledge and systemic paradigms regarding unsustainability, this paper calls for transformative education that promotes a holistic, value-based approach, eco-empathy, and critical thinking, aiming to equip future generations with the tools to challenge and transform unsustainable systems. Full article

Fungi, from saprophytes to pathogens, face predictable daily fluctuations in light, temperature, humidity, and nutrient availability. To cope, they have evolved an internal circadian clock that confers a major adaptive advantage. This review critically synthesizes current knowledge on the molecular architecture and physiological relevance of fungal circadian systems, moving beyond the canonical Neurospora crassa model to explore the broader phylogenetic diversity of timekeeping mechanisms. We examine the core transcription-translation feedback loop (TTFL) centered on the FREQUENCY/WHITE COLLAR (FRQ/WCC) system and contrast it with divergent and non-canonical oscillators, including the metabolic rhythms of yeasts and the universally conserved peroxiredoxin (PRX) oxidation cycles. A central theme is the clock’s role in gating cellular defenses against oxidative, osmotic, and nutritional stress, enabling fungi to anticipate and withstand environmental insults through proactive regulation. We provide a detailed analysis of chrono-pathogenesis, where the circadian control of virulence factors aligns fungal attacks with windows of host vulnerability, with a focus on experimental evidence from pathogens like Botrytis cinerea, Fusarium oxysporum, and Magnaporthe oryzae. The review explores the downstream pathways—including transcriptional cascades, post-translational modifications, and epigenetic regulation—that translate temporal signals into physiological outputs such as developmental rhythms in conidiation and hyphal branching. Finally, we highlight critical knowledge gaps, particularly in understudied phyla like Basidiomycota, and discuss future research directions. This includes the exploration of novel clock architectures and the emerging, though speculative, hypothesis of “chrono-therapeutics”—interventions designed to disrupt fungal clocks—as a forward-looking concept for managing fungal infections. Full article

Objectives: This study assessed the effectiveness of a cognitive behavioral therapy (CBT)-based fine dust education program, grounded in the Health Belief Model (HBM), on elementary students’ fine dust knowledge, related behaviors, and mental health (depression, anxiety, stress, sleep quality). Methods: From September to November 2024, 95 students (grades 4–6) living near a coal-fired power plant in midwestern South Korea were assigned to either an intervention group (n = 44) or a control group (n = 51). The intervention group completed a three-session CBT-based education program; the control group received stress management education. Assessments were conducted at weeks 1, 2, 4, and 8 using standardized mental health and behavior scales (PHQ: Patient Health Questionnaire, GAD: Generalized Anxiety Disorder Assessment, PSS: Perceived Stress Scale, ISI: Insomnia Severity Index). Results: A chi-square test was conducted to compare pre- and post-test changes in knowledge and behavior related to PM2.5. The intervention group showed significant improvements in seven fine dust-related knowledge and behavior items (e.g., PM2.5 awareness rose from 33.3% to 75.0%; p < 0.05). The control group showed limited gains. Regarding mental health, based on a mixed-design ANCOVA, anxiety scores significantly declined over time in the intervention group, with group and interaction effects also significant (p < 0.05). Depression scores showed time effects, but group and interaction effects were not significant. No significant changes were observed for stress, sleep, or group × PM2.5 interactions. Conclusions: The CBT-based education program effectively enhanced fine dust knowledge, health behaviors, and reduced anxiety among students. It presents a promising, evidence-based strategy to promote environmental and mental health in school-aged children. Full article

Global marine coastal aquaculture increased by 6.7 million tons in 2024, with whiteleg shrimp (Penaeus vannamei) dominating crustacean production. However, reliance on a single species raises sustainability concerns, particularly in the face of climate change. Diversifying shrimp farming by cultivating native species, such as the European brown shrimp (Crangon crangon), presents an opportunity to develop a sustainable blue bioeconomy in Europe. C. crangon holds significant commercial value, yet overexploitation has led to population declines. Integrated Multi-Trophic Aquaculture (IMTA) offers a viable solution by utilizing fish farm wastewater as a nutrient source, reducing both costs and environmental impact. Research efforts in Germany and other European nations are exploring IMTA’s potential by co-culturing shrimp with species like sea bream, sea bass, and salmon. The physiological adaptability and omnivorous diet of C. crangon further support its viability in aquaculture. However, critical knowledge gaps remain regarding its lipid metabolism, early ontogeny, and reproductive biology—factors essential for optimizing captive breeding. Future interdisciplinary research should refine larval culture techniques and develop sustainable co-culture models. Expanding C. crangon aquaculture aligns with the UN’s Sustainable Development Goals by enhancing food security, ecosystem resilience, and economic stability while reducing Europe’s reliance on seafood imports. Full article

Environmental, social, and governance (ESG) evaluation has become increasingly critical for company sustainability assessments, especially for enterprises in the construction industry with a high environmental burden. However, existing methods face limitations in subjective evaluation, inconsistent ratings across agencies, and a lack of industry-specificity. To address these limitations, this study proposes a large language model (LLM)-based intelligent ESG evaluation model specifically designed for the construction enterprises in China. The model integrates three modules: (1) an ESG report information extraction module utilizing natural language processing and Chinese pre-trained language models to identify and classify ESG-relevant statements; (2) an ESG rating prediction module employing XGBoost regression with SHAP analysis to predict company ratings and quantify individual statement contributions; and (3) an ESG intelligent evaluation module combining knowledge graph construction with fine-tuned Qwen2.5 language models using Chain-of-Thought (CoT). Empirical validation demonstrates that the model achieves 93.33% accuracy in the ESG rating classification and an R² score of 0.5312. SHAP analysis reveals that environmental factors contribute most significantly to rating predictions (38.7%), followed by governance (32.0%) and social dimensions (29.3%). The fine-tuned LLM integrated with knowledge graph shows improved evaluation consistency, achieving 65% accuracy compared to 53.33% for standalone LLM approaches, constituting a relative improvement of 21.88%. This study contributes to the ESG evaluation methodology by providing an objective, industry-specific, and interpretable framework that enhances rating consistency and provides actionable insights for enterprise sustainability improvement. This research provides guidance for automated and intelligent ESG evaluations for construction enterprises while addressing critical gaps in current ESG practices. Full article