Search Results (590)

Japan has largely achieved the “first half” of SDG 6—universal access to safe drinking water and sanitation—through decades of intensive investment in water supply and sewerage systems, implementation of the Total Pollutant Load Control System, and stringent regulation of industrial effluents. National indicators show that coverage of safely managed drinking water and sanitation services is nearly 99%, and domestic statistics report high compliance rates for BOD/COD-based environmental standards in rivers, lakes, and coastal waters. Conversely, the “second half” of SDG 6 reveals persistent gaps: ambient water quality (6.3.2) remains at 57% (2023 data), while water stress (6.4.2) is at approximately 21.6%. Furthermore, SDG 6.6.1 shows that 3% of water basins are experiencing rapid changes in surface water area (2020 data), with ecosystems increasingly threatened by hypoxia in enclosed bays and climate-induced vulnerabilities. Drawing on global comparisons, this review synthesizes Japan’s progress toward SDG 6, elucidates the structural drivers for remaining gaps, and proposes policy pathways for a nature-positive water future. Using national statistics (1970–2023) and the DPSIR framework, our analysis confirms that improvements in BOD/COD compliance plateaued around 2002, reinforcing concerns that point-source measures alone are insufficient to address diffuse pollution, groundwater nitrate contamination, and emerging contaminants like PFAS. We propose six strategic directions: (1) climate-resilient water systems leveraging groundwater; (2) smart infrastructure renewal; (3) advanced treatment for emerging contaminants; (4) basin-scale IWRM enhancing transboundary cooperation; (5) data transparency and citizen engagement; and (6) scaled nature-based solutions (NbS) integrated with green–gray infrastructure. The paper concludes by outlining priorities to close the gaps in SDG 6.3 and 6.6, advancing Japan toward a sustainable, nature-positive water cycle. Full article

The Citarum River Basin (DAS Citarum) in Indonesia faces significant challenges in waste management, necessitating a circular economy-based approach to reduce land-based pollution, which is critical for achieving the sustainability goals of the blue economy in the basin. This study addresses the complexity and inherent uncertainty in decision-making processes related to this challenge by developing a novel hybrid model, namely the Weighted Fuzzy N-Soft Set combined with the COmbinative Distance-based Assessment (CODAS) method. The model synergistically integrates the weighted 10R strategies in the circular economy, obtained via the Analytical Hierarchy Process (AHP), the capability of Fuzzy N-Soft Sets to represent uncertainty granularly, and the robust ranking mechanism of CODAS. Applied to a case study covering 16 types of waste in the Citarum River Basin, the model effectively processes expert assessments that are ambiguous regarding the 10R criteria. The results indicate that single-use plastics, particularly plastic bags (HDPE), styrofoam, transparent plastic sheets (PP), and plastic cups (PP), are the top priorities for intervention, in line with the high AHP weights for upstream strategies such as Refuse (0.2664) and Rethink (0.2361). Comparative analysis with alternative models, namely Fuzzy N-Soft Set-CODAS, Weighted Fuzzy N-Soft Set with row-column sum ranking, and Weighted Fuzzy N-Soft Set-TOPSIS, confirms the superiority of the proposed hybrid model in producing ecologically rational priorities, free from purely economic value biases. Further sensitivity analysis shows that the model remains highly robust across various weighting scenarios. This study concludes that the WFN-SS-CODAS framework provides a rigorous, data-driven, and reliable decision support tool for translating circular economy principles into actionable waste management priorities, directly supporting the restoration and sustainability goals of the blue economy in river basins. The findings suggest that targeting the high-priority waste types identified by the model addresses the dominant fraction of riverine pollution, indicating the potential for significant waste volume reduction. This research was conducted to directly contribute to achieving multiple targets under SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 14 (Life Below Water). Full article

Foodborne diseases remain a major global challenge because pathogenic microorganisms persist in food systems, often protected by biofilms and increasing resistance to conventional chemical preservatives and sanitizers. Control strategies that were effective in the past are becoming less reliable in complex processing environments, creating a need for more precise and adaptable food-safety approaches. This review examines emerging technologies that shift food safety from broad, reactive control toward targeted, data-driven intervention. Biological tools, including bacteriophages, phage-derived enzymes, bacteriocins, quorum-sensing inhibitors, and gene-guided antimicrobial systems, are discussed for their capacity to selectively control specific pathogens while limiting unintended effects on beneficial microbiota. The review also addresses nano-enabled strategies that improve antimicrobial stability, delivery, and performance, along with plant-derived and microbial bioactive compounds that support clean-label and sustainable preservation. In parallel, advances in anti-biofilm surface engineering, such as nano-textured, contact-active, and responsive materials, are examined as preventive measures to reduce microbial attachment and persistence on food-contact surfaces. Beyond individual interventions, this review emphasizes integration within coordinated multi-hurdle systems supported by real-time monitoring and predictive analytics. Emerging digital frameworks, including digital twins of food-processing lines, are highlighted as tools to link detection, risk prediction, and targeted control. Finally, remaining knowledge gaps, regulatory challenges, and research priorities are identified, highlighting the need for realistic testing, long-term safety evaluation, standardized validation, and collaborative efforts to translate precision food-safety technologies into dependable real-world applications. Full article

Inadequate hygiene knowledge and poor sanitation practices remain key challenges to safe learning environments in South Africa, with 462 million learners attending schools without basic handwashing facilities and many schools failing to meet sanitation standards. Although national policies and infrastructure investments have improved water, sanitation, and hygiene (WASH) services in some schools, access and behaviours remain uneven across socio-economic contexts. This study evaluated knowledge, attitudes, and practices (KAP) related to WASH among 1200 learners from 40 high schools in Durban using a cross-sectional design and interviewer-administered questionnaires. Data were analysed using descriptive statistics, Pearson correlations, ANOVA, and multiple regression. The study addressed the research question: To what extent do learners’ knowledge and attitudes predict hygiene practices across socio-economic contexts? It was hypothesised that higher knowledge and more positive attitudes would significantly predict improved hygiene practices. Results showed that while 74.6% reported handwashing after toilet use, only 39.3% consistently used soap. Knowledge of disease transmission through unsafe water was 35.4%, although overall attitudes were positive. Learners from higher-quintile schools had significantly better KAP scores than those from lower quintiles (p < 0.001). Both knowledge (β = 0.232, p < 0.001) and attitudes (β = 0.266, p < 0.001) were significant predictors of learners’ hygiene practices. Significant group differences were also observed by gender (t = 18.032, p = 0.001) and district (t = −3.895, p = 0.001). These findings highlight persistent WASH gaps and inequities across schools, underscoring the need for integrated interventions that strengthen both hygiene education and school infrastructure to achieve Sustainable Development Goal 6. Full article

Although much research in environmental and sustainability education has focused on knowledge and awareness, fewer studies have examined how school-based projects can foster young learners’ capacity for action. This study investigates how emancipatory, school-based environmental projects can foster young learners’ foundational capacities for contributing to a more sustainable and caring future. Grounded in the Bildung perspective and the action competence framework, a 16-week intervention was implemented with Grade 8 students who collaboratively identified and addressed authentic environmental issues—such as waste mismanagement, sanitation concerns, and safety risks—within their school community. Using a concurrent mixed-methods design, quantitative data from the Student Action Competence Questionnaire were integrated with qualitative evidence from worksheets and reflective journals. Results show consistent improvement across all dimensions of action competence, particularly in democratic collaboration and students’ willingness to take shared responsibility for environmental well-being. Qualitative findings reveal the development of critical reflection, co-creation with school stakeholders, and a growing sense of social responsibility, as students engaged in activities ranging from redesigning waste systems to proposing improvements through official communication channels. Rather than focusing on large-scale environmental outcomes, the projects cultivated everyday practices of care, participation, and ethical awareness—key dispositions for inspiring long-term change toward a greener and more sustainable future. The study highlights how context-based, dialogic learning can empower students as emerging environmental citizens within their immediate communities. Full article

Our world is rapidly urbanizing, while 2.5 billion people are projected to shift from rural to urban areas by 2050, with close to 90% occurring in Asia and Africa. In Southeast Asia, particularly, the Phnom Penh capital city of Cambodia is experiencing this rapid urbanization, facing significant challenges in improving the quality of urban life and achieving social sustainability. Hence, this research aims to assess this capital on social sustainability dimensions to find out the strong and weak points of its 14 districts in order to reveal the improvement potential. The research developed and applied an urban social sustainability index based on national development priorities, SDG11, the New Urban Agenda, and other SDGs that related to human wellbeing and social inclusiveness. The AHP was used to prioritize indicators to develop a priority index, while the standard score was used to apply the index to assess the 14 districts of Phnom Penh. The data for this index application were sourced from Phnom Penh’s commune database. The results showed that the highest-scoring district for urban social sustainability was Chamkarmon, followed by Boeng Keng Kang and Doun Penh. The findings revealed that Prek Pnov was weak in income generation and welfare, while Kamboul was weak in gender inclusion compared to other districts. Prampir Makara was strong, and Sen Sok was weak in resilience to vulnerability. Boeng Keng Kang was strong in welfare and sanitation, while Kamboul was weak in sanitation. Doun Penh was strong, and Mean Chey was weak in water supply. Full article

An improved understanding of the sanitation enabling environment and status of market development (“sanitation economy”) is crucial not only for advancing national and global sanitation goals, but also for attracting the financing necessary to drive meaningful progress in low- and middle-income countries (LMICs). This need is particularly pressing as the sanitation sector faces a significant funding gap that must be bridged to meet the growing demands for sanitation services, infrastructure, and innovation. This paper reviews frameworks that assess the sanitation economy in LMICs with the aim of informing the development of more impactful future frameworks and the wider application of existing frameworks. Frameworks were identified through internet search and interviews with representatives of international sanitation sector organisations and universities. Thirty-nine frameworks were identified that have been or are currently being used in sanitation. Frameworks are diverse in the structure they adopt, their focus areas, the number of indicators, the number of countries covered, the frequency with which they have been applied, their reliance on primary versus secondary data sources, and their uptake and impact. Overall, use of the frameworks has been piecemeal and sporadic in LMICs. Only few frameworks have been picked up and applied by another organisation, although the results of some frameworks are widely used and cited. To ensure future efforts to measure and monitor the sanitation economy are evidence-based and make the best use of limited resources, frameworks currently in use should be independently evaluated and there should be greater collaboration and adoption of common frameworks. Full article

Mercury (Hg²⁺) contamination in water systems poses a severe environmental and health hazard due to its high toxicity and bioaccumulation potential. In this study, a novel adsorbent was developed by sequentially modifying kaolin via acid–base treatment, titanium dioxide (TiO₂) incorporation, and 3-aminopropyltriethoxysilane (APTES) grafting. Batch adsorption experiments revealed that the fully modified kaolin (TiO₂-loaded and APTES grafted) exhibited the highest adsorption capacity (25.6 mg/g) compared to the acid–base-treated (5.8 mg/g) and TiO₂-loaded (17.7 mg/g) kaolin. Under optimal conditions (75 mg adsorbent dosage; 70 mg/L Hg²⁺; pH 5), the fully modified kaolin maintained its performance even in the presence of varying ionic strengths, natural organic matter, and competing metal ions. Adsorption kinetics followed a pseudo-second-order model, and the equilibrium data were well fitted by the Langmuir isotherm. Antibacterial activity assay revealed that the TiO₂-loaded kaolin effectively inhibited S. aureus (minimum inhibitory concentration = 2.5 mg/mL) and showed moderate activity against E. coli (BL21) (minimum inhibitory concentration = 5 mg/mL). However, antibacterial activity decreased after amine functionalization, indicating a compromise between enhancing adsorption capacity and preserving antibacterial functionality. This study presents a promising cost-efficient approach for the simultaneous removal of Hg²⁺ ions from water matrices and inhibiting bacterial growth, aligning with SDG 6 (Clean Water and Sanitation). Full article

Background: Access to water, sanitation, and hygiene (WASH) services is internationally recognized as a fundamental human right and an essential determinant of health. Yet, many healthcare facilities in sub-Saharan Africa face persistent WASH deficits, undermining safe and effective care delivery. Aim: To explore how water (in)accessibility influences patient healthcare experiences and patient–provider relationships in Yendi Hospital, a major referral facility in northern Ghana. Methods: Using a qualitative design, we gathered data from patients (n = 21), caregivers (n = 11), and nurses (n = 11) through in-depth interviews, participant observation, and a focus group to document their lived experiences and perceptions. We transcribed and inductively coded the data for thematic analysis. Results: Our key findings reveal that water inaccessibility is not solely an infrastructural issue but also a pervasive challenge with profound implications for care delivery. Patients and caregivers often leave the hospital to bathe at home, resulting in missed ward rounds, delayed reviews, and/or refusal of admission. Nurses described how water inaccessibility disrupted clinical routines and strained relationships with patients and caregivers. These dynamics eroded trust, rapport, and professional morale, while exacerbating inequities in healthcare access and outcomes. Conclusions: This study underscores that addressing water challenges in the hospital is imperative not only for infection control but also for fostering equity, patient rights, and institutional resilience. We argue that policy interventions to strengthen WASH systems are urgently required to advance progress toward Sustainable Development Goal 6. Full article

Background: Sustainable sanitation underpins Sustainable Development Goal (SDG) 6.2, which mandates safe, equitable services and the elimination of open defecation by 2030. Rural South African communities continue to face significant Water, Sanitation and Hygiene (WASH) challenges driven by economic, environmental and governance constraints. Methods: An explanatory sequential mixed-methods design was conducted in King Sabata Dalindyebo Local Municipality, Eastern Cape. Quantitative data comprised household surveys (n = 246) and structured observations of VIP latrines (n = 50). Qualitative data were gathered from 20 semi-structured interviews with community representatives and four focus groups (n = 32). Results: While 63% of households owned VIP latrines, only 22% of the inspected facilities were in good working condition and 20% were abandoned; 58% required major maintenance. Major barriers to sustainable sanitation included limited financial capacity, structural damage related to a high-water table, gendered safety risks, and low community engagement in sanitation planning and maintenance. Conclusions: Achieving SDG 6.2 in rural South Africa requires co-productive governance that integrates infrastructure maintenance with community leadership. Recommended actions include delegated WASH committees, targeted subsidies for vulnerable households, routine gender and safety audits, and enforcement of environmental protection measures to secure long-term sanitation sustainability. Full article

Background: Diarrheal disease (DD) remains a major public health challenge and is the leading cause of malnutrition and the second leading cause of death among children under five globally. Although DD can be caused by a wide range of pathogens, its primary drivers are often linked to unimproved sanitation, limited access to clean drinking water, and poor hygiene practices. Low- and middle-income countries, particularly those in South Asia, experience the highest burden. These regions are also increasingly vulnerable to climate change and land use/cover changes, which may further exacerbate DD risk. However, the relative influence of environmental and social drivers at localized scales is not well understood. This gap presents a critical opportunity to identify scalable, data-informed interventions that address environmental determinants of health in the context of a changing climate. Methods: To investigate these dynamics, we analyzed 21,779 records from the Demographic and Health Surveys (DHS) for Bangladesh, integrating them with remotely sensed data on forest cover change, temperature, and rainfall. Using Random Forest machine learning models, we assessed the relative importance of both environmental and socio-demographic variables at household and regional (village) levels. Results: The results show that DD risk varies across scales: household-level outcomes are primarily associated with socio-demographic characteristics, while regional-level outcomes are more strongly influenced by environmental and geographic features, including precipitation, elevation, and proximity to water bodies. Conclusions: These findings underscore the importance of scale-sensitive approaches when assessing environmental health risks and developing climate-adaptive public health strategies. Full article

Time-series water-quality forecasting plays a crucial role in sustainable environmental monitoring, early-warning surveillance, and data-driven water-resource governance. Degradation of river ecosystems poses significant risks to public health, biodiversity, and long-term socio-economic resilience, particularly in rapidly developing regions. In this study, a multi-scale diffusion forecaster (MDF) is introduced to enhance predictive accuracy and uncertainty quantification for river water-quality dynamics in Thailand. The proposed framework integrates seasonal-trend decomposition with a hierarchical denoising diffusion process to model stochastic environmental fluctuations across multiple temporal resolutions. Experiments conducted using real water-quality datasets from the Mae Klong, Khwae Noi, and Khwae Yai Rivers, and the Port Authority of Thailand, demonstrate that MDF achieves superior probabilistic calibration under noise and data incompleteness compared to conventional deterministic baselines. The forecasting capability supports proactive pollution control, sustainable resource allocation, and climate-resilient water-policy design, directly contributing to Sustainable Development Goals (SDG 6: Clean Water and Sanitation; SDG 13: Climate Action; and SDG 14: Life Below Water). The findings highlight the potential of diffusion-based learning as an enabling technology for sustainable aquatic ecosystem governance and long-term environmental planning. Full article

Background and Aims: In recent decades, lifestyle patterns have undergone significant transformations, particularly in low- and middle-income countries (LMICs). These changes have contributed to a dual nutritional crisis characterized by the coexistence of undernutrition and overweight/obesity, commonly referred to as the Double Burden of Malnutrition (DBM). Compounding this issue is the persistent prevalence of parasitic infections, due to poor personal hygiene and sanitation practices which further exacerbate nutritional imbalances, creating what is now recognized as the Triple Burden of Malnutrition (TBM). This review aims to explore the evolving lifestyle factors that have contributed to the emergence of the DBM and to examine its intersection with parasitic infections. The focus is particularly on South Asian low- and middle-income countries, where these overlapping burdens present a significant public health challenge. By highlighting the interconnectedness of malnutrition, obesity, and parasitic diseases, this study seeks to provide a comprehensive understanding of the current nutritional landscape in South Asian LMICs and to inform future health interventions and policies. Methods: This study was conducted using published and unpublished secondary data that are available on websites and other printed materials. One of the main requirements is date, with 2013 being regarded as the initiative’s landmark. Another crucial factor is the availability of the entire article. For this study, only research publications published in English were taken into consideration. Zotero was used for compilation. The majority of the analysis was performed using percentages and ratios. A thorough evaluation of all the studies’ methodology, design, execution, and reporting was performed in order to spot any systematic flaws in this study. Results: Only 45 of the 105 full-text papers that were screened met the requirements for inclusion. Of these studies, 15 satisfied the inclusion and exclusion requirements. The results show that China, with a comparatively higher income level status, has more prevalence of overweight and obesity among children (11.5%) and women (34.6%) than India (2.1% of OWOB among children and 20.6% among women). Nepal stands behind China and India with 1.2% of OWOB among children and between them with 22.2% OWOB among women. Interestingly, among the three South Asian nations, India has the highest stunting, wasting, and underweight among children (38.4%, 21%, and 35.7%, respectively) followed by Nepal (35.8%, 9.7%, and 27%) and China (8.1%, 2%, and 2.5%). This study finds no significant difference in the prevalence of intestinal parasitic infections among OWOB and underweight populations. This review finds that the DBM along with parasitic infections has resulted in a Triple Burden of Malnutrition, which is currently a major public health issue in low- and middle-income countries in South Asia. Discussion: The various types of malnutrition were once thought of and treated as distinct public health problems, but the new understanding is that undernutrition and overnutrition are linked, and that in order for policy solutions to be successful, double-duty measures that simultaneously address multiple dimensions must be put in place. When the DBM is combined with parasite illnesses, it becomes the Triple Burden of Malnutrition, which is the primary cause of the financial burden in LMICs. China has the worst obesity problem, yet it also has more obesity-related laws and intervention programs than India and Nepal combined. All three nations, however, have failed to stop or deal with the dramatic increase in OWOB over the last 20 years. For effective implementation and results, genetic and psychological factors must also be taken into account when developing policies and programs to tackle the obesity epidemic, undernutrition, and parasite diseases. Conclusions: The prevalence of the DBM has been rising globally, with South Asia seeing a faster rate of increase. A growing DBM is favorably correlated with national economic development. In South Asian LMICs, the DBM combined with parasite diseases has resulted in a Triple Burden of Malnutrition, a debilitating illness. Full article

Background: Soil-transmitted helminth (STH) infections, including ascariasis, trichuriasis, and hookworm disease, are among the most common neglected tropical diseases (NTDs) globally. This study evaluates the disease burden of STH in China from 1990 to 2021 and projects trends to 2035. Methods: Data from the Global Burden of Disease 2021 database were utilized to analyze the prevalence and disability-adjusted life years (DALYs) of STH infections in China from 1990 to 2021. The estimated annual percentage change (EAPC) was calculated to assess trends over time, and a Bayesian age-period-cohort model was used to project the disease burden up to 2035. Results: From 1990 to 2021, the prevalence and DALYs of STH infections decreased significantly by 85.08% and 98.01% in China, respectively. The age-standardized prevalence rate (ASPR) of STH infections dropped from 34,073.24/10⁵ to 4981.01/10⁵ with an EAPC of −6.62% [95% confidence interval (CI): −7.40%, −5.83%], and the age-standardized DALY rate (ASDR) decreased from 1.77/10⁵ to 0.18/10⁵, with an EAPC of −14.05% (95% CI: −15.04%, −13.06%). Trichuriasis contributed to 78.85% of the total ASPR for STH, whereas hookworm disease accounted for 51.14% of STH’s ASDR. The highest disease burden due to STH peaked in the 5–9 years age group, with prevalence of 8030.05/10⁵ [95% uncertainty interval (UI): 5356.86/10⁵–11,662.62/10⁵] and DALYs rate of 2.99/10⁵ (95% UI: 1.56/10⁵−4.87/10⁵). The projected ASDR and ASPR of trichuriasis rose to 0.55/10⁵ and 5362.50/10⁵ by 2035. Conclusions: China has achieved remarkable reductions in the burden of STH infections over the past three decades. However, the predominance between the species has changed. The projected rebound in trichuriasis underscores the importance of sustained control efforts. To achieve the 2030 elimination target outlined in the WHO NTDs roadmap, it is crucial to integrate precision epidemiology with ongoing water, sanitation, and hygiene initiatives, targeted chemotherapy and health education. Full article

The classification of encrypted traffic is critical for network security, yet it faces a significant “few-shot” challenge as novel applications with scarce labeled data continuously emerge. This complexity arises from the high-dimensional, noisy nature of traffic data, making it difficult for models to generalize from few examples. Existing paradigms, such as meta-learning from scratch or standard pre-train/fine-tune methods, often fail in this scenario. To address this gap, we propose Contrastive Learning Meta-Flow (CL-MetaFlow), a novel two-stage learning framework that uniquely synergizes the strengths of contrastive representation learning and meta-learning adaptation. In the first stage, a robust feature encoder is pre-trained using supervised contrastive learning on known traffic classes, shaping a highly discriminative and metric-friendly embedding space. In the second stage, this pre-trained encoder initializes a Prototypical Network, enabling rapid and effective adaptation to new, unseen classes from only a few samples. Extensive experiments on a benchmark dataset (ISCX-VPN-2016 & ISCX-Tor-2017) demonstrate the superiority of our approach. Notably, in a five-way five-shot setting, CL-MetaFlow achieves a Macro F1-Score of 0.620, significantly outperforming from-scratch ProtoNet (0.384), a standard fine-tuning baseline (0.160), and strong pre-training counterparts like SimCLR+ProtoNet (0.545) and a re-implemented T-Sanitation (0.591). Our work validates that a high-quality, domain-adapted feature prior is the key to unlocking high-performance few-shot learning in complex network environments, providing a practical and powerful solution for real-world traffic analysis. Full article