Global Challenges Research Articles

Understanding the Relationship Between Attachment Orientation and Physical Activity Participation: An Exploratory Study.

Physical inactivity is recognized as a global health challenge. Attachment theory may provide insight into individual physical activity (PA) patterns, informing the development of PA interventions to promote the maintenance of behavior change. This study investigated the associations between attachment orientation and why and how individuals engage in PA. Given the association between attachment and sensory processing, this study also investigated the link between sensory processing and PA participation. Participants (N = 141) completed an online questionnaire that included the Modified Experiences of Close Relationships Scale and the Highly Sensitive Person Scale. The relationship between attachment orientation and sensory processing patterns, and preference for PA participation were analyzed using 2-sided independent t tests. Attachment avoidance, attachment anxiety, and sensory sensitivity were significantly related to participants' preference for PA participation in theoretically consistent ways. Avoidantly attached individuals were less likely to participate in PA as a form of social interaction (mean = 8.57, SD = 2.87, P = .005, d = 0.48). Anxiously attached individuals were more likely to participate in PA to support weight management (mean = 37.02, SD = 11.54, P = .01, d = -0.46) or if recommended by a health professional (mean = 43.55, SD = 12.45, P = .039, d = -0.88). Sensory sensitive individuals were more likely to participate in PA alone (mean = 124.11, SD = 19.23, P = .005, d = -0.510), and more likely to prefer light-intensity forms of PA (mean = 133.29, SD = 12.67, F3,123 = 5.49, P = .001). Findings highlight the potential value of considering an individual's attachment orientation and sensory processing patterns in the development of PA interventions. This may help to address the challenges of PA participation, by individually tailoring interventions to participants.

Functional inorganic nanoparticles in cancer: Biomarker detection, imaging, and therapy

Cancer poses a major global public health challenge. Developing more effective early diagnosis methods and efficient treatment techniques is crucial to enhance early detection sensitivity and treatment outcomes. Nanomaterials offer sensitive, accurate, rapid, and straightforward approaches for cancer detection, diagnosis, and treatment. Inorganic nanoparticles are widely used in medicine because of their high stability, large specific surface area, unique surface properties, and unique quantum size effects. Functional inorganic nanoparticles involve modifying inorganic nanoparticles to enhance their physical properties, enrichment capabilities, and drug-loading efficiency and to minimize toxicity. This Review provides an overview of various types of inorganic nanoparticles and their functionalization characteristics. We then discuss the progress of functional inorganic nanoparticles in cancer biomarker detection and imaging. Furthermore, we discuss the application of functional inorganic nanoparticles in radiotherapy, chemotherapy, gene therapy, immunotherapy, photothermal therapy, photodynamic therapy, sonodynamic therapy, and combination therapy, highlighting their characteristics and advantages. Finally, the toxicity and potential challenges of functional inorganic nanoparticles are analyzed. The purpose of this Review is to explore the application of functional inorganic nanoparticles in diagnosing and treating cancers, while also presenting a new avenue for cancer diagnosis and treatment.

Point-of-Care Testing for Cardiovascular Disease: A Narrative Review.

Cardiovascular disease is a major global public health challenge. Point-of-- care testing (POCT) technologies are crucial for the prevention, early diagnosis, and treatment of cardiovascular conditions. Numerous POCT technologies for cardiovascular disease are currently available, which include but are not limited to conventional methods, paper-based microfluidic technology, microfluidic chip technology, electrochemical detection technology, ultrasonic detection technology, and smartphone-based detection technology. Each method has a broad range of applications and performs differently across various detection scenarios. This article offers a comprehensive analysis of current POCT technologies for cardiovascular disease, assessing their effectiveness, limitations, and future development directions. The aim is to provide insights and theoretical references for innovative research and clinical applications in POCT methods for cardiovascular disease.

Enhancing Renewable Energy Evaluation: Utilizing Complex Picture Fuzzy Frank Aggregation Operators in Multi-Attribute Group Decision-Making

Renewable energy resources are pivotal in addressing global energy challenges and achieving sustainable development goals. In this context, the complex picture fuzzy sets (CPFS) theory provides a robust framework for handling complex and uncertain information. This article presents innovative strategies based on Frank aggregation tools to evaluate and prioritize renewable energy resources. By incorporating the concepts of abstinence value, membership value, and non-membership values in the CPFS framework, the characteristics and capabilities of the CPFS are extended to represent a broader range of information. Specifically, we introduce novel operators such as the CPF Frank weighed average (CPFFWA) and CPF Frank weighed geometric (CPFFWG) operators, effectively handling insufficient and unpredictable information during the aggregation process. Moreover, we explore specialized variants of these operators, such as the CPF Frank order weighed average (CPFFOWA) and CPF Frank order weighed geometric (CPFFOWG) operators, which possess distinct characteristics suitable for specific decision-making scenarios. The proposed methodologies are applied within the framework of multi-attribute group decision-making (MAGDM) to evaluate and identify optimal renewable energy options from a group of alternatives. Through comparative analyses and validation against existing approaches, the advantages and consistency of our developed operators are demonstrated. The findings highlight the effectiveness of the CPF-based Frank aggregation operators in evaluating renewable energy resources, providing decision-makers with a comprehensive and reliable framework for renewable energy planning and decision-making.

Advances in the Elimination of Viral Hepatitis in Mexico: A Local Perspective on the Global Initiative

Viral hepatitis (A–E) presents a major global health challenge. In 2015, the World Health Organization (WHO) launched an initiative to eliminate viral hepatitis, with the aim of reducing new infections by 90% and deaths by 65% by 2030. Mexico is one of 38 focus countries identified by the WHO, collectively accounting for 80% of global infections and deaths. While hepatitis B and C are commonly diagnosed in Mexico, routine diagnosis for hepatitis D and E is lacking, with no specific epidemiological data available. In 2020, Mexico implemented the National Hepatitis C Elimination Program, focusing on preventing new infections, reducing complications like cirrhosis and hepatocellular carcinoma, ensuring access to treatment, and improving patient care. However, this program has not been extended to hepatitis B and E. Addressing the challenges of viral hepatitis control in Mexico requires increased resource allocation, expanded diagnosis, vaccination for hepatitis A and B, and treatment coverage for hepatitis B and C, along with multisectoral engagement. This work provides an overview of Mexico’s response to the global initiative, highlighting its progress, challenges, and areas of opportunity.

Gradient of acid mine drainage regulates microbial community assembly and the diversity of species associated with native plants

Acid mine drainage (AMD) is considered as one of the most important global environmental challenges. Therefore, understanding the impact of AMD on the diversity of microbial communities associated with native plants is important for phytoremediation. In this study, the community assembly and microbial diversity associated with native plants growing along an AMD impact gradient was investigated using metabarcoding and high throughput iChip technique. The study revealed that across both domains of bacteria and fungi, richness and species diversity decreased according to AMD impact. Bacterial species diversity was more stratified according to the pH gradient than fungi, and the AMD impact on the plant-associated microbial diversity decreased towards the plant roots. The microbial community composition of the undisturbed site was significantly different from the AMD impacted sites, and the communities in the AMD impacted sites were further stratified according to the degree of impact. The overall microbial diversity was mediated by the AMD impact, niche differences and plant species differences. Dispersal limitation was the most important community assembly process in the undisturbed site, while the homogenous selection of Burkholderia, Actinospica, Puia and Bradyrhizobium increased along the AMD impact gradient. Differential abundance analysis further revealed that Umbelopsis, Burkholderia and Sphingomonas were among the biomarkers of the AMD impacted sites. Several strains of some of these responsive genera were subsequently isolated using the iChip. Overall, this study presents novel insight into the ecology of plant-associated microbial communities that are relevant for environmental monitoring and for enhancing the revegetation of AMD impacted sites.

Change in the Global burden of depression from 1990-2019 and its prediction for 2030

ObjectiveDepression is a global health challenge, but only a few studies have fully assessed and predicted the disease burden. This study described the trend of global depression burden from 1990 to 2019 through age-standardized incidence rate (ASIR), age-standardized disability-adjusted life rate (ASDR), and predicted the number of cases of depression during 2020-2030. Methods: Linear regression analysis was used to calculate the estimated annual percentage change (EAPC) in the age-standardized rates. The trends of global depression burden from 1990 to 2019 were analyzed by age, sex, and socio-demographic index (SDI) across various regions. Finally, we used the Bayesian age-period-cohort (BAPC) model to predict the disease burden in the coming 10 years. Results:Globally, the ASIR of depression decreased from 3,681.24 per 100,000 population in 1990 to 3,588.25 per 100,000 population in 2019 and the EAPC was -0.29%. ASDR also decreased, following a similar trend as the ASIR. The highest ASDR was observed in adults aged 60-64 years. The burden of depressive illness was higher in women, with the greatest increase in incidence in low SDI areas. BAPC predicted that the worldwide ASIR and ASDR of depression would stabilize from 2020 to 2030, with an increasing number of cases. By 2030, the ASIR was estimated to be 2,519.88 per 100,000 men and 3,835.11 per 100,000 women. Conclusion: From 1990 to 2019, the global burden of depression remained significant, especially among women. It is important to address depression in older people, and it is therefore necessary to develop measures for prevention.

A life cycle-based comparison study of sludge recycling technology incorporating subjective and objective evaluations

Inadequate land capacity and low sludge recycling rates have become a major global environmental challenge. Low organic sludge content and inadequate waste management policy mean that there is an urgent need to improve sludge solutions in China, which has the world’s largest WWT capacity. Decision-makers face difficulties in selecting sustainable sludge-to-resource technologies given the existence of multiple social, environmental and economic objectives, and also in optimizing the allocation of sludge between different available technologies. In this paper we used a combined analytic hierarchic process (AHP) and entropy weight (EW) method to evaluate four recycling technologies: aerobic composting (AC), dry-incineration (DI), hydrothermal carbonization (HTC) and pyrolysis (PY), in terms of five economic, environmental and land resource indicators. The results showed that human toxicity was viewed as the most important indicator, while economic value of sludge product was the least important. HTC had the best overall performance of the evaluated technologies while PY was the least attractive. However, all four sludge recycling technologies showed greater potential for reducing carbon emissions and human toxicity than landfilling when sludge dewatering was included. Sensitivity analysis showed that adjustments to AHP weights only had a limited impact on the technical ranking. Finally, the result was further verified by a particle swarm optimization algorithm. Considering capacity constraints, the optimal proportion of the four technologies was found to be 44.9%, 42.7%, 0 and 12.4% for HTC, DI, PY and AC respectively. The paper demonstrates the effectiveness of combining subjective and objective methods to evaluate multiple indicators, providing decision-makers with a practical analysis framework for waste technology selection.

Application of Nanocomposites and Nanoparticles in Treating Neurodegenerative Disorders.

Neurodegenerative diseases represent a formidable global health challenge, affecting millions and imposing substantial burdens on healthcare systems worldwide. Conditions, like Alzheimer's, Parkinson's, and Huntington's diseases, among others, share common characteristics, such as neuronal loss, misfolded protein aggregation, and nervous system dysfunction. One of the major obstacles in treating these diseases is the presence of the blood-brain barrier, limiting the delivery of therapeutic agents to the central nervous system. Nanotechnology offers promising solutions to overcome these challenges. In Alzheimer's disease, NPs loaded with various compounds have shown remarkable promise in preventing amyloid-beta (Aβ) aggregation and reducing neurotoxicity. Parkinson's disease benefits from improved dopamine delivery and neuroprotection. Huntington's disease poses its own set of challenges, but nanotechnology continues to offer innovative solutions. The promising developments in nanoparticle-based interventions for neurodegenerative diseases, like amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS), have offered new avenues for effective treatment. Nanotechnology represents a promising frontier in biomedical research, offering tailored solutions to the complex challenges posed by neurodegenerative diseases. While much progress has been made, ongoing research is essential to optimize nanomaterial designs, improve targeting, and ensure biocompatibility and safety. Nanomaterials possess unique properties that make them excellent candidates for targeted drug delivery and neuroprotection. They can effectively bypass the blood-brain barrier, opening doors to precise drug delivery strategies. This review explores the extensive research on nanoparticles (NPs) and nanocomposites in diagnosing and treating neurodegenerative disorders. These nanomaterials exhibit exceptional abilities to target neurodegenerative processes and halt disease progression.

Photocatalytic Nanocomposite Based on Titanate Nanotubes Decorated with Plasmonic Nanoparticles for Enhanced Broad-Spectrum Antibacterial Activity.

Infections resulting from microorganisms pose an ongoing global public health challenge, necessitating the constant development of novel antimicrobial approaches. Utilizing photocatalytic materials to generate reactive oxygen species (ROS) presents an appealing strategy for combating microbial threats. In alignment with this perspective, sodium titanate nanotubes were prepared by scalable hydrothermal method using TiO2 and NaOH. Ag, Au, and Ag/Au-modified titanate nanotubes (TNTs) were prepared by a cost-effective and simple ion-exchange method. All samples were characterized by XRD, FT-IR, HRTEM, and DLS techniques. HRTEM images indicated that the tubular structure was preserved in all TNTs even after the replacement of Na+ with Ag+ and/or Au3+ ions. The antibacterial activity in dark and sunlight conditions was evaluated using different bacterial strains, Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. The results showed that while a low bacterial count (∼log 5 cells per well) was used for inoculation, the TNTs exhibited no antibacterial activity against the three bacterial strains, regardless of whether they were tested under light or dark conditions. However, the plasmonic nanoparticle-decorated TNTs showed remarkable activity in the dark. Additionally, Ag/Au-TNTs demonstrated significantly higher activity in the dark compared with either Ag-TNTs or Au-TNTs alone. Notably, under dark conditions, the Au/Ag-TNTs achieved log reductions of up to 4.5 for P. aeruginosa, 5 for S. aureus, and 3.7 for E. coli. However, when exposed to sunlight, Au/Ag-TNTs resulted in a complete reduction (log reduction ∼9) for P. aeruginosa and E. coli. The combination of two plasmonic nanoparticles (Ag/Au) decorated on the surface of TNTs showed synergetic bactericidal activity under both dark and light conditions. Ag/Au-TNTs could be explored to design surfaces that are responsive to visible light and exhibit antimicrobial properties.

Macrophages and T cells in metabolic disorder-associated cancers.

Cancer and metabolic disorders have emerged as major global health challenges, reaching epidemic levels in recent decades. Often viewed as separate issues, metabolic disorders are shown by mounting evidence to heighten cancer risk and incidence. The intricacies underlying this connection are still being unraveled and encompass a complex interplay between metabolites, cancer cells and immune cells within the tumour microenvironment (TME). Here, we outline the interplay between metabolic and immune cell dysfunction in the context of three highly prevalent metabolic disorders, namely obesity; two associated liver diseases, metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH); and type 2 diabetes. We focus primarily on macrophages and T cells, the critical roles of whichin dictating inflammatory response and immune surveillance in metabolic disorder-associated cancers are widely reported. Moreover, considering the ever-increasing number of patients prescribed with metabolism disorder-altering drugs and dietsin recent years, we discuss how these therapies modulate systemic and local immune phenotypes, consequently impacting cancer malignancy. Collectively, unraveling the determinants of metabolic disorder-associated immune landscape and their role in fuelling cancer malignancy will provide a framework essential to therapeutically address these highly prevalent diseases.

Chinese herbal medicine for the treatment of intestinal cancer: preclinical studies and potential clinical applications

AbstractIntestinal cancer (IC) poses a significant global health challenge that drives continuous efforts to explore effective treatment modalities. Conventional treatments for IC are effective, but are associated with several limitations and drawbacks. Chinese herbal medicine (CHM) plays an important role in the overall cancer prevention and therapeutic strategies. Recent years have seen a growing body of research focus on the potential of CHM in IC treatment, showing promising results in managing IC and mitigating the adverse effects of radiotherapy and chemotherapy. This review provides updated information from preclinical research and clinical observation on CHM’s role in treatment of IC, offering insights into its comprehensive management and guiding future prevention strategies and clinical practice.

Identifying food safety risks with a novel digitally-driven food safety early warning tool – a retrospective study on the pesticide ethylene oxide

Foodborne diseases present a major global health challenge, with 600 million annual cases and 420,000 deaths worldwide in 2023 reported by the World Health Organization, underscoring the critical need for early risk detection and swift measures. Novel solutions for early risk detection in food are emerging due to artificial intelligence-based data models. By applying diverse algorithms and ontologies in data processing, the continually expanding amount of available data can be harnessed in a precise manner. To assess the efficacy of such technologies in early risk detection, we evaluated whether the risk to exceed a legal limit for ethylene oxide – specifically in sesame seeds – could have been identified sooner with the assistance of a commercially available Artificial Intelligence (AI)-based platform. The non-compliance of sesame seeds led to various product recalls in the year 2020. The result of this retrospective case study shows that the first indirect indications of the issue started to emerge from the year 2018 with initial Rapid Alert System for Food and Feed (RASFF) notification of ethylene oxide limit value exceedances in black pepper powder. Based on these promising findings, the subsequent challenge is to develop a methodology for systematically categorizing and evaluating similar risks in the light of the exponentially growing volume of accessible data.

Boundary spanning increases knowledge and action on invasive species in a changing climate

Abstract Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary‐spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary‐spanning activities could support proactive, research‐informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary‐spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non‐members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non‐members and short‐term members more frequently identifying range‐shifting neonative species and their impacts on native communities as higher priorities compared to long‐term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range‐shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication: Although real‐world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary‐spanning efforts to address other global change challenges to conservation.

Evaluation of Renewable Energy Sources for a Sustainable Future: A Multi-Criteria Decision-Making Approach

The urgent global challenges of climate change, energy security, and environmental degradation highlight the need for sustainable energy solutions. Renewable energy sources (RES) present a viable pathway towards sustainability by mitigating greenhouse gas emissions, reducing reliance on fossil fuels, and fostering economic resilience. Purpose: The purpose of this paper is to propose an advanced Multi-Criteria Decision-Making (MCDM) approach to evaluate various RES by integrating environmental, economic, technological, social acceptance, and resource availability criteria, to identify the most suitable RES for sustainable energy solutions. Methodology: The study employs a hybrid method combining Type-2 Neutrosophic Numbers (T2NN) with LOPCOW (Logarithmic Percentage Change Operator Weighting) and MAIRCA (Multi-Attributive Ideal-Real Comparative Assessment) to rank the suitability of different RES, including solar, wind, hydropower, and geothermal energy. Findings: The case study results reveal wind energy as the top-ranked alternative, supported by consistent findings across comparative methods such as COPRAS, MABAC, EDAS, and TOPSIS. Sensitivity analysis further confirms the stability of the proposed model under various scenarios. Originality: The originality of this study lies in the integration of T2NN, LOPCOW, and MAIRCA to address the limitations of traditional MCDM approaches in handling uncertainty and imprecision in data. The study demonstrates the efficacy of the proposed framework in providing a robust evaluation of RES, and its value lies in its potential to inform decision-making in the field of sustainable energy solutions.

Engineering hierarchical TiO2/ZnIn2S4 hybrid heterostructure with synergistic interfaces: A dual-functional S-scheme photocatalyst for efficient CO2 reduction and norfloxacin degradation

The development of multifunctional photocatalysts that can harness solar energy for both environmental remediation and energy generation is a considerable challenge in achieving sustainable development. This study introduces a dual-functional S-scheme hybrid catalyst comprising hierarchical 3D flower-like ZnIn2S4 (ZIS) microspheres embedded with TiO2 (TO) nanoparticles, synthesized via a facile in situ hydrothermal process. The unique structural and compositional synergy between ZIS and TO leverages their complementary photocatalytic properties, facilitating efficient solar energy utilization, increasing specific surface area, and enhancing CO2 adsorption capabilities. The S-scheme mechanism, confirmed by in situ-irradiated X-ray photoelectron spectroscopy and electron spin resonance spectroscopy, underlying this system promotes effective separation of photoexcited charge carriers while preserving the intrinsic strong reducibility of ZIS and high oxidizability of TO. These beneficial properties of the TO/ZIS hybrid provide a robust platform for CH4 production (75.6 μmol h−1 g−1) through selective (99.6%) CO2 reduction over competing water reduction and achieve exceptional degradation and mineralization of the persistent antibiotic norfloxacin in water, addressing both energy and environmental challenges. Furthermore, the hybrid catalyst exhibits significant stability and recyclability, maintaining high catalytic performance across multiple cycles, thereby underscoring its practical viability. This work offers a promising blueprint for developing multifunctional photocatalysts capable of addressing critical global challenges, demonstrating the potential of hierarchical nanostructures and S-scheme charge transfer mechanisms.

Unveiling mid-century conservation priorities: Co-occurrence of biodiversity, climate change exposure, and carbon storage in the Middle and Lower Yangtze River Basin, China

The global challenges of biodiversity loss and climate change necessitate the implementation of integrated conservation strategies. A forward-looking framework is necessary to reconcile climate change adaptation and mitigation efforts with biodiversity goals, supporting effective long-term planning and management of protected areas (PAs) network. This study develops a comprehensive approach to identify priority areas for biodiversity conservation until 2050, integrating assessments of species distributions, climate change exposure and carbon storage under distinct shared socioeconomic pathways. The Middle and Lower Yangtze River Basin (MLYRB) in China serves as a case study. Using an ensemble species distribution modeling (ESDM) method, we predicted the distributions of 435 threatened terrestrial vertebrate species and plants. We then mapped their richness in the MLYRB. Distance-based climate velocity analysis was performed to identify climate change coldspots and hotspots. The patch-generating land use simulation (PLUS) model and InVEST model were coupled to simulate carbon storage changes. Systematic conservation planning tool, Zonation, was used to prioritize species conservation hotspots. By examining the co-occurrence of these hotspots with climate change coldspots/hotspots and areas of high carbon storage, conservation priorities for the MLYRB were revealed. Our findings indicate that 18.27–24.94% of the MLYRB risks over 20% species richness declines by 2050 under various scenarios, while increases over 10% are projected for only 0.81–1.75% of the area. Co-occurrence analysis highlights significant associations, such as a 32.26% overlap between species conservation hotspots and climate change hotspots in SSP1-2.6. Particularly noteworthy is the substantial co-occurrence (57.93–59.50% across scenarios) between areas maximizing species conservation and carbon storage. The identified conservation priority areas, covering 41.95% of the MLYRB (441554km2), hold potential for long-term species conservation, climate resilience, and nature-based climate solutions by 2050. However, only 6.08% of these priorities currently benefit from protection. These results offer valuable guidance for region-specific landscape management and conservation policy aligned with international goals. The presented methodology provides a broader application, serving as a valuable resource for prioritizing conservation efforts in other regions integrating biodiversity, climate change adaptation, and mitigation goals.

Facile fabrication of Cu/kaolin nanocomposite as highly efficient heterogeneous catalyst for 4-nitrophenol reduction in aqueous solution

Hazardous organic pollutants in industrial wastewaters are becoming a major global challenge that threatens life on earth and particularly poses a serious health risk to human beings. 4-Nitrophenol (4-NP) is a highly hazardous organic contaminant that has been extensively utilized across multiple industries, and their wastewater disposal into water streams leads to a higher accumulation of 4-NP. It is therefore important for both academia and industry to make catalysts that are cheap, very effective, good for the environment, easy to recover, and can be used more than once for reducing 4-NP in normal conditions. This paper reports the synthesis, characterization, and application of Cu/kaolin nanocomposite as an efficient heterogeneous catalyst for decomposing 4-NP, a model organic molecule. The catalyst was synthesized by incorporating a copper precursor into layered kaolin clay and directly reducing the metal precursor using sodium borohydride (NaBH4). The morphology, structure, surface property, and interaction of the resulting Cu/kaolin nanocomposite (NC) were characterized by ultraviolet–visible spectroscopy, Fourier transform infrared spectroscopy, scanning electron spectroscopy/energy-dispersive X-ray spectroscopy, selected area electron diffraction, X-ray diffraction, and N2 adsorption/desorption, and the results clearly demonstrated the growth of copper nanoparticles on the kaolin surface. It was discovered that the Cu nanoparticles (NPs) on the kaolin surface had a crystallite size of about 23.6 nm. The significance of Cu NPs and the high catalytic activity of the synthesized Cu/kaolin NC toward 4-NP reduction by NaBH4 were evaluated by the catalytic reduction experiments. Among the different nanocomposites synthesized, 30-Cu/kaolin showed the highest catalytic activity for 4-NP reduction, with a reduction efficiency of over 99 % within 4 min with a pseudo-first-order rate constant, kapp, of 1.23 min−1. Furthermore, the reusability test indicated that Cu/kaolin NC can be reused for up to six runs efficiently without significant decrease in its catalytic performance, indicating the nanocomposite has excellent stability and great potential applications in industrial and agricultural wastewater treatment.

Ozone Plasma Nanobubble (OPN) Reactor Combined with Coagulation-Flocculation Process: A Promising Technology for Leachate Treatment

According to World Bank data, approximately 2.01 billion tons of urban waste is produced annually, with approximately 33% of waste being improperly managed, leading to concentrated and toxic leachate. This poses a global challenge due to its varied characteristics influenced by climate, landfill age, and waste composition, resulting in groundwater and surface water pollution with severe impacts on human health, ecosystems, and biodiversity, necessitating stringent treatment measures. To address this, a study integrated coagulation-flocculation and advanced oxidation processes (AOPs) using a dielectric barrier discharge (DBD) ozone plasma nanobubble (OPN) reactor to degrade leachate. Gas flow rate, plasma voltage, and gas sources are variated. This research uses O2 or air as a gas source that produces plasma. The leachate is fed into the DBD reactor, so the bubble will burst and produce further ROS. Optimal results were observed after 60 min, with oxygen gas feed reducing total suspended solids (TSS), chemical oxygen demand (COD), and biological oxygen demand (BOD) by 100, 93.93, and 74.12%, respectively, alongside a decrease in pH. This study indicates the promising potential of this technology for leachate treatment and demonstrates the potential for nitrate production using both types of gas feed.

Trends in Water Quality Research: A Bibliometric Study of Factors and Parameters in Drinking Water

ABSTRACT This study examines trends in water quality research through a bibliometric approach with the aim of mapping dominant factors and parameters and identifying research gaps in this area. The introduction of this research highlights the importance of water quality as a global issue that affects public health and environmental sustainability. The main objective of the study was to analyze water quality-related publications published between 2017 and 2024 using the Publish or Perish application to identify trends, distribution, and research focus. The method used involved collecting data from the 50 highest-ranked journals on Google Scholar, then classifying them by year of publication, publication type, number of citations, and author country. The data obtained was analyzed with the VOSviewer application to generate network visualizations, overlays, and densities to reveal the linkages between research topics. The analysis showed that research on water quality is highly diversified with the main focus on factors affecting water quality and the development of assessment methods. The publications reviewed highlighted global challenges in water quality management and the need for cross-disciplinary collaboration. The conclusions of this study emphasize several research gaps, such as the need for the development of more sensitive water quality indices, the application of new technologies, and further research in local and regional contexts. This research provides valuable insights into current research trends and encourages further exploration to improve water quality management effectively and sustainably. Keywords: Water Quality, Bibliometrics, Assessment Methods, Emerging Technologies, Research Gaps.