Search Results (306)

Plastic pollution is a growing environmental and social concern, particularly in Southeast Asia, where urban rivers serve as key pathways for transporting waste to marine environments. This scoping review examines 110 peer-reviewed studies to understand how plastic pollution in waterways is being researched, addressed, and reconceptualized. Drawing from the literature across environmental science, technology, and social studies, we identify four interconnected areas of focus: urban pollution pathways, innovations in monitoring and methods, community-based interventions, and interdisciplinary perspectives. Our analysis combines qualitative synthesis with visual mapping techniques, including keyword co-occurrence networks, to explore how real-time tools, such as IoT sensors, multi-sensor systems, and geospatial technologies, are transforming the ways plastic waste is tracked and analyzed. The review also considers the growing use of novel theoretical frameworks, such as post-phenomenology and ecological materialism, to better understand the role of plastics as both pollutants and ecological agents. Despite progress, the literature reveals persistent gaps in longitudinal studies, regional representation, and policy translation, particularly across the Global South. We emphasize the value of participatory models and community-led research in bridging these gaps and advancing more inclusive and responsive solutions. These insights inform the development of plastic tracker technologies currently being piloted in Vietnam and contribute to broader sustainability goals, including SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 14 (Life Below Water). Full article

The escalating global demand for fresh water, driven by urbanization and industrial growth, underscores the need for sustainable water management, particularly in the water-intensive construction sector. Although prior studies have primarily concentrated on treated wastewater, the practical viability of utilizing untreated wastewater has not been thoroughly investigated—especially in developing nations where treatment expenses frequently impede actual implementation, even for non-structural uses. While prior research has focused on treated wastewater, the potential of untreated or partially treated wastewater from diverse industrial sources remains underexplored. This study investigates the feasibility of incorporating wastewater from textile, sugar mill, service station, sewage, and fertilizer industries into concrete paver block production. The novelty lies in a dual approach, combining experimental analysis with XGBoost-based machine learning (ML) models to predict the impact of key physicochemical parameters—such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Hardness—on mechanical properties like compressive strength (CS), water absorption (WA), ultrasonic pulse velocity (UPV), and dynamic modulus of elasticity (DME). The ML models showed high predictive accuracy for CS (R² = 0.92) and UPV (R² = 0.97 direct, 0.99 indirect), aligning closely with experimental data. Notably, concrete pavers produced with textile (CP-TXW) and sugar mill wastewater (CP-SUW) attained 28-day compressive strengths of 47.95 MPa and exceeding 48 MPa, respectively, conforming to ASTM C936 standards and demonstrating the potential to substitute fresh water for non-structural applications. These findings demonstrate the viability of using untreated wastewater in concrete production with minimal treatment, offering a cost-effective, sustainable solution that reduces fresh water dependency while supporting environmentally responsible construction practices aligned with SDG 6 (Clean Water and Sanitation) and SDG 12 (Responsible Consumption and Production). Additionally, the model serves as a practical screening tool for identifying and prioritizing viable wastewater sources in concrete production, complementing mandatory laboratory testing in industrial applications. Full article

The Sustainable Development Goals seek to achieve universal, adequate, and equitable access to drinking water and sanitation by the year 2030. Yet, significant and persistent disparities in water and sanitation access exist, with rural and low-income households in Sub-Saharan Africa exhibiting some of the lowest levels. This paper uses household surveys from rural villages in Zambia’s Western Province to identify, highlight, and examine spatial barriers to improved water and sanitation. Most households included in the study area drink unimproved water, including surface water, and either use unimproved sanitation facilities or practice open defecation. Access to improved water sources and improved sanitation in the study area lags behind the rest of rural Zambia. Beyond the distance to urban areas that makes piped water and sanitation expensive, the location of these villages in the Barotse Floodplain necessitates seasonal migration, which creates barriers to universal access to improved water and sanitation. Full article

In high-density and land-scarce urban environments such as Taipei—a typical example of compact development in East Asia—informal green spaces (IGSs)—defined as unmanaged or unplanned vegetated urban areas such as vacant lots, street verges, and railway margins—play a growing role in urban environmental and social dynamics. This study explores residents’ perceptions of IGSs and examines how these spaces contribute to urban sustainability and land governance. Using a mixed-methods approach that combines the literature review, field observations, and a structured public opinion survey in Taipei’s Wenshan District, the study identifies key perceived benefits and drawbacks of IGSs. Findings show that residents highly value IGSs for enhancing urban greenery, offering recreational opportunities, and promoting physical and mental health. However, concerns persist regarding safety, sanitation, and maintenance—particularly fears of waste accumulation, mosquito breeding, and risks to children. The results highlight the dual nature of IGSs as both vital ecological assets and potential sources of urban disorder. These insights underscore the need for inclusive, community-based governance models that can transform IGSs into legitimate components of green infrastructure. The study contributes to emerging discussions on adaptive urban land governance by proposing that informal spaces be strategically integrated into urban planning frameworks to enhance environmental equity, resilience, and citizen well-being. Full article

Sewer pipelines are essential urban infrastructure that play a key role in sanitation and disaster prevention. Regular condition assessments are necessary to detect defects early and determine optimal maintenance timing. However, traditional visual inspection using closed-circuit television (CCTV) footage is time-consuming, labor-intensive, and dependent on subjective human judgment. To address these limitations, this study develops a convolutional neural network (CNN)-based sewer defect classification model and analyzes how data quality—such as mislabeled or redundant images—affects model accuracy. A large-scale public dataset of approximately 470,000 sewer images was used for training. The model was designed to classify non-defect and three major defect categories. Based on the ResNet50 architecture, the model incorporated dropout and L2 regularization to prevent overfitting. Experimental results showed the highest accuracy of 92.75% at a dropout rate of 0.2 and a regularization coefficient of 0.01. Further analysis revealed that mislabeled, redundant, or obscured images within the dataset negatively impacted model performance. Additional experiments quantified the impact of data quality on accuracy, emphasizing the importance of proper dataset curation. This study provides practical insights into optimizing data-driven approaches for automated sewer defect detection and high-performance model development. Full article

The Roma population is one of Europe’s largest ethnic minorities, often living in inadequate living conditions, worse than those of the majority population. They frequently lack access to essential services, even in high-income countries. This lack of basic services—particularly in combination with proximity to (stray) animals and human and solid waste—significantly increases environmental health risks, and leads to a higher rate of endoparasitic infections. Our study sheds light on the living conditions and health situation in Roma communities in Slovakia, focusing on the prevalence of intestinal endoparasitic infections across various settlement localisations. It highlights disparities and challenges in access to safe drinking water, sanitation, and hygiene (WASH) and other potentially disease-exposing factors among these marginalised populations. This study combines a comprehensive review of living conditions as per national data provided through the Atlas of Roma communities with an analysis of empirical data on parasitological infection rates in humans, animals, and the environment in settlements, applying descriptive statistical methods. It is the first study in Europe to provide detailed insights into how living conditions vary and cause health risks across Roma settlements, ranging from those integrated within villages (inside, urban), to those isolated on the outskirts (edge, sub-urban) or outside villages (natural/rural). Our study shows clear disparities in access to services, and in health outcomes, based on where people live. Our findings underscore the fact that (i) place—geographical centrality in particular—in an already challenged population group plays a major role in health inequalities and disease exposure, as well as (ii) the urgent need for more current and comprehensive data. Our study highlights persistent disparities in living conditions within high-income countries and stresses the need for greater attention and more sensitive targeted health-promoting approaches with marginalised communities in Europe that take into consideration any and all of the humans, ecology, and animals affected (=One Health). Full article

The unprecedented development of coastal cities in West Africa is marked by anarchic urbanization accompanied by ineffective environmental management, leading to water pollution. This study is conducted in the southern districts of Lomé, Togo, an area built on sandbars where inappropriate attitudes, behaviors, and inadequate hygiene and sanitation practices prevail. The objective of this study is to characterize the quality of groundwater in the study area. Bacteriological and physicochemical analyses were carried out on 11 wells in 10 districts in the southern districts during the four seasons of the year. The analysis shows that the groundwater is polluted in all seasons. Nitrate concentrations exceed 50 mg/L in 65% of the samples, while chloride levels surpassed 250 mg/L in 18% of the cases. Regardless of the season, the dominant facies is sodium chloride and potassium chloride. In all districts, the analysis of microbiological parameters including total germs (30 °C, 100/mL), total coliforms (30 °C, 0/mL), Escherichia coli (44 °C, 2/250 mL), fecal streptococci (0/100 mL), and anaerobic sulfite reducers (44 °C, 2/20 mL) reveals values exceeding the European Union standards (2007). Groundwater contamination is facilitated by the sandy nature of the soil, which increases its vulnerability to various pollutants. Togo continues to experience cholera outbreaks, aggravated by poor sanitation infrastructure and limited vaccination coverage. Public health efforts are directed toward improving sanitation and raising awareness about waterborne and non-communicable diseases. Full article

Currently, the management, availability, and equitable access to water are some of the most critical environmental challenges in many countries, including Mexico. The Household Water Insecurity Experience Scale (HWISE) offers a more comprehensive and accurate assessment of water insecurity (WI) as well as its relationship to poverty, at the local, state, and national levels, than traditional usage indicators do. Therefore, this study aims to estimate the association between water insecurity and household wellbeing in Mexico, as well as the role of geographic factors. Methods: We analyzed data from 11,512 households that had previously participated in a representative survey at the national, regional, and urban/rural levels. We conducted descriptive and bivariate analyses on the variables of interest according to household WI status. Multivariate logistic regression models were used to determine the association between WI and the geographic, household, and household head variables of interest. Results: The factors associated with a greater odds ratio of household WI were low wellbeing conditions (OR = 1.74, p < 0.01), no running water in the home (OR = 2.71, p < 0.01), a monthly household income less than 6000 Mexican pesos (less than 352 dollars) (OR = 2.31, p = 0.006), living in an urban area (OR = 1.93, p = 0.001), and living in the Mexico State (OR = 3.92, p < 0.01), Mexico City (OR = 3.19, p < 0.01), or Central Pacific (OR = 3.27, p < 0.01) regions. Conclusions: Currently, multiple factors threaten household water security. These findings can inform decision-makers about the driving factors behind gaps in water access, availability, and use in Mexican households, thereby ensuring the “availability and sustainable management of water and sanitation for all”. Full article

Morocco’s Témara Plain relies heavily on its aquifer system as a critical resource for drinking water, irrigation, and industrial activities. However, this essential groundwater reserve is increasingly threatened by over-extraction, seawater intrusion, and complex hydrogeochemical processes driven by the region’s geological characteristics and anthropogenic pressures. This study aims to assess groundwater quality and its vulnerability to pollution risks and map the spatial distribution of key hydrochemical processes through an integrated approach combining Geographic Information System (GIS) techniques and multivariate statistical analysis, as well as applying the DRASTIC model to evaluate water vulnerability. A total of fifty-eight groundwater samples were collected across the plain and analyzed for major ions to identify dominant hydrochemical facies. Spatial interpolation using Inverse Distance Weighting (IDW) within GIS revealed distinct patterns of sodium chloride (Na-Cl) facies near the coastal areas with chloride concentrations exceeding the World Health Organization (WHO) drinking water guideline of 250 mg/L—indicative of seawater intrusion. In addition to marine intrusion, agricultural pollution constitutes a major diffuse pressure across the aquifer. Shallow groundwater zones in agricultural areas show heightened vulnerability to salinization and nitrate contamination, with nitrate concentrations reaching up to 152.3 mg/L, far surpassing the WHO limit of 45 mg/L. Furthermore, other anthropogenic pollution sources—such as wastewater discharges from septic tanks in peri-urban zones lacking proper sanitation infrastructure and potential leachate infiltration from informal waste disposal sites—intensify stress on the aquifer. Principal Component Analysis (PCA) identified three key factors influencing groundwater quality: natural mineralization due to carbonate rock dissolution, agricultural inputs, and salinization driven by seawater intrusion. Additionally, The DRASTIC model was used within the GIS environment to create a vulnerability map based on seven key parameters. The map revealed that low-lying coastal areas are most vulnerable to contamination. Full article

Rapid urbanization in China has led to an increase in the volume of daily road garbage, posing challenges to municipal sanitation. Automatic garbage collection is thus essential for sustainable management. This paper proposes an improved RT-DETR-based (Real-Time Detection Transformer) detection model, RGD-DETR, to improve road garbage detection performance. Firstly, an improved feature pyramid module that leverages multi-scale feature fusion techniques to enhance feature extraction effectiveness is designed. Secondly, a state space model is introduced to accurately capture long-range dependencies between image pixels with its spatial modeling capability, thus obtaining high-quality feature representation. Thirdly, a Dynamic Sorting-aware Decoder is adopted to embed a dynamic scoring module and a query-sorting module in adjacent decoder layers, enabling the model to focus on high-confidence predictions. Finally, the classification- and localization-oriented loss and matching cost are introduced to improve target localization accuracy. The experimental results on the road garbage dataset show that the RGD-DETR model improves detection accuracy (mAP) by 1.8% compared with the original RT-DETR, performing well for small targets and in occlusion scenarios. Full article

Analyzing the population’s access to ecosystem services offered by urban greening constitutes a measure of environmental justice, as it directly affects the quality of life and health of the population living in cities. This article is committed to proposing a geoenvironmental model in a geographic information system (GIS), envisaged to estimate the share of urban forests and green spaces in territorial planning units (TPUs), corresponding to neighborhoods of a pilot city, using high-spatial-resolution images of the China–Brazil Earth Resources Satellite (CBERS-4A) and the normalized difference vegetation index (NDVI). These data were combined by means of a Boolean analysis with social vulnerability indicators assessed from census data related to income, education, housing, and sanitation. This model ultimately aims to identify priority areas for urban afforestation in the context of environmental justice and is thus targeted to improve the inhabitants’ quality of life. The municipality of Goiânia, the capital of Goiás state, located in the Brazilian Central–West Region, was chosen as the study area for this experiment. Goiânia presents 19.5% of its urban territory (82.36 km²) covered by vegetation. The analyses indicate an inequity in the distribution of urban forest patches and green areas in this town, where 7.8% of the total TPUs have low priority, 28.2% have moderate to low priority, 42.2% have moderate to high priority, and 21.8% have high priority for urban afforestation. This urban greening imbalance is particularly observed in its most urbanized central nuclei, associated with a peripheralization of social vulnerability. These findings are meant to support initiatives towards sound territorial planning processes designed to promote more sustainable and equal development to ensure environmental justice and combat climate change. Full article

Rodents represent the most diverse order of mammals, comprising over 2200 species and nearly 42% of global mammalian biodiversity. They are major reservoirs of zoonotic pathogens, including viruses, bacteria, protozoa, and fungi, and are particularly effective at transmitting diseases, especially synanthropic species that live in close proximity to humans. As of April 2025, approximately 15,205 rodent-associated viruses have been identified across 32 viral families. Among these, key zoonotic agents belong to the Arenaviridae, Hantaviridae, Picornaviridae, Coronaviridae, and Poxviridae families. Due to their adaptability to both urban and rural environments, rodents serve as efficient vectors across diverse ecological landscapes. Environmental and anthropogenic factors, such as climate change, urbanization, deforestation, and emerging pathogens, are increasingly linked to rising outbreaks of rodent-borne diseases. This review synthesizes current knowledge on rodent-borne viral zoonoses, focusing on their taxonomy, biology, host associations, transmission dynamics, clinical impact, and public health significance. It underscores the critical need for early detection, effective surveillance, and integrated control strategies. A multidisciplinary approach, including enhanced vector control, improved environmental sanitation, and targeted public education, is essential for mitigating the growing threat of rodent-borne zoonoses to global health. Full article

Water scarcity and energy consumption are two pressing global challenges, especially in arid regions, that require sustainable solutions in line with circular economic principles. This study investigates the feasibility of greywater recycling systems for a 10-floor residential building housing 425 occupants by optimizing non-potable water demand and energy consumption. The grey-box modeling approach and energy balance optimization analysis are used to identify effective practices for implementing greywater recycling through the evaluation of environmental and economic effects on the performance of residential buildings. The findings are that there are 18% and 40% savings in water and energy, respectively, with greywater recycling systems. The research concludes that maximum treatment and recovery efficiencies significantly enhance the performance of the systems. Thus, there are 2.25 million kWh of annual energy savings that can repay itself in 4.42 years, as well as savings in the long-term consequences. These findings contribute further to achieving the UN-SDGs on Clean Water and Sanitation (SDG 6) and Affordable and Clean Energy (SDG 7). This study contributes to a better understanding of optimizing greywater recycling systems that are practical and scalable for residential use and promote sustainable urban development with minimal environmental impacts. Full article

Water quality in urban streams is closely linked to socioeconomic conditions, particularly in densely populated and poorly sanitized areas. This study evaluates the physicochemical and microbiological quality of water in the Billings-Tamanduateí sub-basin and investigates its correlation with social indicators such as population density, informal settlements, and lack of sewage treatment. Water samples were collected from 14 sub-basins, analyzing parameters, including dissolved organic and inorganic carbon, total dissolved nitrogen, pH, dissolved oxygen, oxidation-reduction potential, conductivity, and the presence of enterobacteria (Escherichia coli, Enterococcus, and Pseudomonas aeruginosa). Statistical analyses revealed strong associations between water quality degradation and increased population density, lack of sanitation, and lower per capita income. The findings reinforce that socially vulnerable areas are the most affected, with higher levels of organic and microbiological contamination. Despite improvements in sewage collection over time, gaps in wastewater management persist, even in major metropolitan areas such as São Paulo. Future studies could expand the analysis to include less vulnerable regions for comparison and explore the impacts of climate change on urban stream water quality. The results highlight the urgent need for improved sanitation infrastructure and policies to mitigate contamination and protect public health. Full article

(1) Background: The Guarapiranga reservoir, located in the metropolitan region of São Paulo (RMSP), plays an important role in supplying water to the population. However, the growing urbanization in the region, which has occurred in a disorderly manner and lacks basic sanitation infrastructure, has had a detrimental impact on the reservoir’s conditions. The aim of this study was to evaluate the physicochemical parameters and detect coliforms to determine the water quality of the Guarapiranga reservoir, as well as to characterize the microbial diversity and antimicrobial-resistance genes (ARGs) present in the reservoir water. (2) Methods: Four sampling campaigns of the Guarapiranga reservoir were carried out between October 2020 and July 2022. Physicochemical analyses, and selective microbiological culture for coliforms, as well as the extraction of bacterial DNA for subsequent sequencing and search for ARGs were carried out. (3) Results: Analysis of the physicochemical results showed a progressive reduction in the quality of the reservoir’s water, and the microbiological tests consistently showed the presence of Escherichia coli, Salmonella spp., Shigella spp. and Klebisiella spp. in the water samples collected from the reservoir. Analyses of the sequencing data showed the predominant presence of the phyla Proteobacteria, Cyanobacteria, Bacteroidetes, Verrucomicrobia, Planctomycetes, and 12 ARGs were detected in the reservoir. (4) Conclusions: The increase in sewage discharge, mainly due to the growth of irregular housing, has affected the quality of the water, as indicated by the physicochemical analysis and detection of coliforms and ARGs. Full article