Search Results (444)

With the rapid development of the social economy, human activities have increasingly disrupted water environments, and the continuous input of pollutants poses significant challenges for water environment management. Taking the Xiaoxingkai Lake basin as the study area, this paper develops a social–economic–water environment model based on the system dynamics methodology, incorporating subsystems for population, agriculture, and water pollution. The model focuses on four key indicators of pollution severity, namely, total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), and ammonia nitrogen (NH₃-N), and simulates the changes in pollutant loads entering the river under five different scenarios from 2020 to 2030. The results show that agricultural non-point sources are the primary contributors to TN (79.5%) and TP (73.7%), while COD primarily originates from domestic sources (64.2%). NH₃-N is mainly influenced by urban domestic activities (44.7%) and agricultural cultivation (41.2%). Under the status quo development scenario, pollutant loads continue to rise, with more pronounced increases under the economic development scenario, thus posing significant sustainability risks. The pollution control enhancement scenario is most effective in controlling pollutants, but it does not promote socio-economic development and has high implementation costs, failing to achieve coordinated socio-economic and environmental development in the region. The dual-reinforcement scenario and moderate-reinforcement scenario achieve a balance between pollution control and economic development, with the moderate-reinforcement scenario being more suitable for long-term regional development. The findings can provide a scientific basis for water resource management and planning in the Xiaoxingkai Lake basin. Full article

To evaluate water pollution status and sustainable development potential in the Huai River Basin, this study focused on the spatiotemporal evolution and influencing factors of the grey water footprint (GWF) across 35 cities in the basin from 2005 to 2020. This study quantifies the GWF from agricultural, industrial, and domestic perspectives and analyzes its spatial disparities by incorporating spatial autocorrelation analysis. The Tapio decoupling model was applied to explore the relationship between pollution and economic growth, and geographic detectors along with the STIRPAT model were utilized to identify driving factors. The results revealed no significant global spatial clustering of GWF in the basin, but a pattern of “high in the east and west, low in the north and south” emerged, with high-value areas concentrated in southern Henan and northern Jiangsu. By 2020, 85.7% of cities achieved strong decoupling, indicating improved coordination between the environment and economy. Key driving factors included primary industry output, crop sown area, and grey water footprint intensity, with a notable interaction between agricultural output and grey water footprint intensity. The quantitative analysis based on the STIRPAT model demonstrated that seven factors, including grey water footprint intensity and total crop sown area, exhibited significant contributions to influencing variations. Ranked by importance, these factors were grey water footprint intensity > total crop sown area > urbanization rate > population size > secondary industry output > primary industry output > industrial wastewater discharge, collectively explaining 90.2% of the variability in GWF. The study provides a robust scientific basis for water pollution control and differentiated management in the river basin and holds significant importance for promoting sustainable development of the basin. Full article

Over the past 30 years, the City of Portland, Oregon, USA, has emerged as a national leader in green stormwater infrastructure (GSI). The initial impetus for implementing sustainable stormwater infrastructure in Portland stemmed from concerns about flooding and water quality in the city’s two major rivers, the Columbia and the Willamette. Heavy rainfall often led to combined sewer overflows, significantly polluting these waterways. A partial solution was the construction of “The Big Pipe” project, a large-scale stormwater containment system designed to filter and regulate overflow. However, Portland has taken a more comprehensive and long-term approach by integrating sustainable stormwater management into urban planning. Over the past three decades, the city has successfully implemented GSI to mitigate these challenges. Low-impact development strategies, such as bioswales, green streets, and permeable surfaces, have been widely adopted in streetscapes, pathways, and parking areas, enhancing both environmental resilience and urban livability. This perspective highlights the history of the implementation of Portland’s GSI programs, current design and performance standards, and challenges and lessons learned throughout Portland’s recent history. Innovative approaches to managing runoff have not only improved stormwater control but also enhanced green spaces and contributed to the city’s overall climate resilience while addressing economic well-being and social equity. Portland’s success is a result of strong policy support, effective integration of green and gray infrastructure, and active community involvement. As climate change intensifies, cities need holistic, adaptive, and community-centered approaches to urban stormwater management. Portland’s experience offers valuable insights for cities seeking to expand their GSI amid growing concerns about climate resilience, equity, and aging infrastructure. Full article

Background/Objectives: This study examines how seasonality, pollution, and sample type (water and sediment) influence the presence and distribution of antibiotic resistance genes (ARGs), with a focus on antibiotic resistance genes (ARGs) located on plasmids (the complete set of plasmid-derived sequences, including ARGs) in a tropical urban river. Methods: Samples were collected from three sites along a pollution gradient in the Virilla River, Costa Rica, during three seasonal campaigns (wet 2021, dry 2022, and wet 2022). ARGs in water and sediment were quantified by qPCR, and metagenomic sequencing was applied to analyze chromosomal and plasmid-associated resistance profiles in sediments. Tobit and linear regression models, along with multivariate ordination, were used to assess spatial and seasonal trends. Results: During the wet season of 2021, the abundance of antibiotic resistance genes (ARGs) such as sul-1, intI-1, and tetA in water samples decreased significantly, likely due to dilution, while intI-1 and tetQ increased in sediments, suggesting particle-bound accumulation. In the wet season 2022, intI-1 remained low in water, qnrS increased, and sediments showed significant increases in tetQ, tetA, and qnrS, along with decreases in sul-1 and sul-2. Metagenomic analysis revealed spatial differences in plasmid-associated ARGs, with the highest abundance at the most polluted site (Site 3). Bacterial taxa also showed spatial differences, with greater plasmidome diversity and a higher representation of potential pathogens in the most contaminated site. Conclusions: Seasonality and pollution gradients jointly shape ARG dynamics in this tropical river. Plasmid-mediated resistance responds rapidly to environmental change and is enriched at polluted sites, while sediments serve as long-term reservoirs. These findings support the use of plasmid-based monitoring for antimicrobial resistance surveillance in aquatic systems. Full article

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 prediction and management of water quality are critical to ensure sustainable water resources, particularly in regions like Malaysia, where rivers face increasing pollution from industrialisation, agriculture, and urban expansion. This review aims to provide a comprehensive analysis of machine learning (ML) models and statistical methods applied in forecasting and classification of water quality. A particular focus is given to hybrid models that integrate multiple approaches to improve predictive accuracy and robustness. This study also reviews water quality standards and highlights the environmental context that necessitates advanced predictive tools. Statistical techniques such as residual analysis, principal component analysis (PCA), and feature importance assessment are also explored to enhance model interpretability and reliability. Comparative tables of model performance, strengths, and limitations are presented alongside real-world applications. Despite recent advancements, challenges remain in data quality, model interpretability, and integration of spatio-temporal and fuzzy logic techniques. This review identifies key research gaps and proposes future directions for developing transparent, adaptive, and accurate models. The findings can also guide researchers and policymakers towards the development of smart water quality management systems that enhance decision-making and ecological sustainability. Full article

With the rapid progression of global industrialization and urbanization, emerging contaminants (ECs) have become pervasive in environmental media, posing considerable risks to ecosystems and human health. While multidisciplinary evidence continues to accumulate regarding their environmental persistence and bioaccumulative hazards, critical knowledge gaps persist in understanding their spatiotemporal distribution, cross-media migration mechanisms, and cascading ecotoxicological consequences. This review systematically investigates the global distribution patterns of ECs in aquatic environments over the past five years and evaluates their potential ecological risks. Furthermore, it examines the performance of various treatment technologies, focusing on economic cost, efficiency, and environmental sustainability. Methodologically aligned with PRISMA 2020 guidelines, this study implements dual independent screening protocols, stringent inclusion–exclusion criteria (n = 327 studies). Key findings reveal the following: (1) Occurrences of ECs show geographical clustering in highly industrialized river basins, particularly in Asia (37.05%), Europe (24.31%), and North America (14.01%), where agricultural pharmaceuticals and fluorinated compounds contribute disproportionately to environmental loading. (2) Complex transboundary pollutant transport through atmospheric deposition and oceanic currents, coupled with compound-specific partitioning behaviors across water–sediment–air interfaces. (3) Emerging hybrid treatment systems (e.g., catalytic membrane bioreactors, plasma-assisted advanced oxidation) achieve > 90% removal for recalcitrant ECs, though requiring 15–40% cost reductions for scalable implementation. This work provides actionable insights for developing adaptive regulatory frameworks and advancing green chemistry principles in environmental engineering practice. Full article

This study aimed to analyse the spatiotemporal evolution of phytoplankton community dynamics and its underlying mechanisms in the Liaoning section of the Liao River Basin in 2010, 2015, and 2020. Phytoplankton species diversity increased significantly, with an increase from three phyla and 31 species in 2010 to six phyla and 74 species in 2020. Concurrent increases in α-diversity indicated continuous improvements in habitat heterogeneity. The community structure shifted from a diatom-dominated assemblage to a green algae–diatom co-dominated configuration, contributing to an enhanced water purification capacity. The upstream agricultural zone (Tieling section) had elevated biomass and low diversity, indicating persistent non-point-source pollution stress. The midstream urban–industrial zone (Shenyang–Anshan section) emerged as a phytoplankton diversity hotspot, likely due to expanding niche availability in response to point-source pollution control. The downstream wetland zone (Panjin section) exhibited significant biomass decline and delayed diversity recovery, shaped by the dual pressures of resource competition and habitat filtering. The driving mechanism of community succession shifted from nutrient-dominated factors (NH₃-N, TN) to redox-sensitive factors (DO, pH). These findings support a ‘zoned–graded–staged’ ecological restoration strategy for the Liao River Basin and inform the use of phytoplankton as bioindicators in watershed monitoring networks. Full article

The integration of water resources, water environment, and water ecology (hereinafter “three-water”) is essential not only for addressing the current water crisis but also for achieving sustainable development. Chaohu Lake is an important water resource and ecological barrier in the middle and lower reaches of the Yangtze River, undertaking such functions as agricultural irrigation, urban water supply, and flood control and storage. Studying the performance of “three-water” in the Chaohu Lake Basin will help to understand the pollution mechanism and governance dilemma in the lake basin. It also provides practical experience and policy references for the ecological protection and high-quality development of the Yangtze River Basin. We used the DPSIR-TOPSIS model to analyze the performance of the river–lake system in the Chaohu Lake Basin and employed an obstacle model to identify factors influencing “three-water.” The results indicated that overall governance and performance of the “three-water” in the Chaohu Lake Basin exhibited an upward trend from 2011 to 2022. Specifically, the obstacle degree of driving force decreased by 19.6%, suggesting that economic development enhanced governance efforts. Conversely, the obstacle degree of pressure increased by 34.4%, indicating continued environmental stress. The obstacle degree of state fluctuated, showing a decrease of 13.2% followed by an increase of 3.8%, demonstrating variability in the effectiveness of water resource, environmental, and ecological management. Additionally, the obstacle degree of impact declined by 12.8%, implying the reduced efficacy of governmental measures in later stages. Response barriers decreased by 5.8%. Variations in the obstacle degree of response reflected differences in response capacities. Spatially, counties and districts at the origins of major rivers and their lake outlets showed lower performance levels in “three-water” management compared to other regions in the basin. Notably, Wuwei City and Feidong County exhibited better governance performance, while Feixi County and Chaohu City showed lower performance levels. Despite significant progress in water resource management, environmental improvement, and ecological restoration, further policy support and targeted countermeasures remain necessary. Counties and districts should pursue coordinated development, leverage the radiative influence of high-performing areas, deepen regional collaboration, and optimize, governance strategies to promote sustainable development. Full article

Urban river ecosystems are increasingly threatened by anthropogenic activities, with wastewater discharge being a significant contributor. The complex nature and diverse sources of wastewater pose challenges in assessing its impact on water quality and ecological health. This study investigated the distribution, toxicity, and ecological effects of organic pollutants in an urban river system during the dry season. A comprehensive analysis was conducted of 16 phthalate esters (PAEs), 16 polycyclic aromatic hydrocarbons (PAHs), and 8 antibiotics, with a focus on several key pollutants. The results revealed distinct pollutant profiles: Dibutyl phthalate (DBP), Dimethyl phthalate (DEHP), and Diisobutyl phthalate (DIBP) were the predominant PAEs, while Chrysene was the most abundant PAH. Among antibiotics, Oxytetracycline and Norfloxacin were the dominant compounds. Wastewater treatment plant (WWTP) effluents significantly altered the composition of organic pollutants in receiving waters. Although dilution reduced the concentrations of some pollutants, certain organic compounds were detected for the first time downstream of the WWTP, and some specific compounds exhibited increased concentrations. Toxicity prediction using the Concentration Addition (CA) model identified DBP as the primary contributor to overall toxicity, accounting for the highest toxic load among all detected pollutants. Furthermore, WWTP effluents induced significant shifts in microbial community structure downstream, with incomplete recovery to upstream conditions. Integrated analysis of 16S rRNA gene sequencing, water quality assessment, and toxicity prediction elucidated the multifaceted impacts of pollution sources on aquatic ecosystems. This study provides critical insights into the composition, spatial distribution, and toxicity characteristics of organic pollutants in urban rivers, as well as their effects on bacterial community structure. The findings offer a scientific foundation for urban river water quality management and ecological protection strategies. Full article

The Ghris watershed in southern Morocco is a significant ecological and agricultural area. However, due to the current impacts of climate change, farming activities, and pollution, data on its quality and biological importance need to be updated. Therefore, this study aimed to evaluate the physico-chemical and biological quality of surface water in the Ghris River. The Water Quality Index (WQI) and the Iberian Biological Monitoring Working Group (IBMWP) index were used to assess water quality along four sampling sites in 2024. The collected data were analyzed with descriptive and multivariate statistics. In total, 424 benthic macroinvertebrates belonging to seven orders were identified in the surface waters of the Ghris basin. These microfauna were significantly variable among the studied sites (p < 0.05). Station S4 is significantly rich in species, including seven orders and nine families of macroinvertebrates, followed by Station S2, with seven orders and eight families. Stations S3 and S1 showed less species diversity, with three orders and one family, respectively. The Insecta comprised 95.9% of the abundance, while the Crustacea constituted just 4.1%. The physico-chemical parameters significantly surpassed (p < 0.05) the specified norms of surface water in Morocco. This indicates a decline in the water quality of the studied sites. The findings of the principal component analysis (PCA) demonstrate that the top two axes explain 87% of the cumulative variation in the data. Stations 2 and 3 are closely associated with high concentrations of pollutants, notably Cl⁻, SO₄²⁻, NO₃⁻, and K⁺ ions. Dissolved oxygen (DO) showed a slight correlation with S2 and S3, while S4 was characterized by high COD and PO₄ concentrations, low levels of mineral components (except Cl⁻), and average temperature conditions. Bioindication scores for macroinvertebrate groups ranging from 1 to 10 enabled the assessment of pollution’s influence on aquatic biodiversity. The IBMWP biotic index indicated discrepancies in water quality across the sites. This study gives the first insight and updated data on the biological and chemical quality of surface water in the Ghris River and the entire aquatic ecosystem in southeast Morocco. These data are proposed as a reference for North African and Southern European rivers. However, more investigations are needed to evaluate the impacts of farming, mining, and urbanization on the surface and ground waters in the study zone. Similarly, it is vital to carry out additional research in arid and semi-arid zones since there is a paucity of understanding regarding taxonomic and functional diversity, as well as the physico-chemical factors impacting water quality. Full article

Heavy metal contamination in groundwater has emerged as a significant environmental issue, driven by rapid industrialization and intensified human activities, particularly in southern China. Heavy metal pollution in groundwater often presents complex spatial patterns and multiple sources; understanding the spatial heterogeneity and controlling factors of heavy metals is crucial for pollution prevention and water resource management in industrial regions. This study applied spatial autocorrelation analysis and self-organizing maps (SOM) coupled with K-means clustering to investigate the spatial distribution and key influencing factors of nine heavy metals (Cr, Fe, Mn, Ni, Cu, Zn, As, Ba, and Pb) in a typical industrial area in southern China. Heavy metals show significant spatial heterogeneity in concentrations. Cr, Mn, Fe, and Cu form local hotspots near urban and peripheral zones; Ni and As present downstream enrichment along the river pathway with longitudinal increase trends; Zn, Ba, and Pb exhibit a fluctuating pattern from west to east in the piedmont region. Local Moran’s I analysis further revealed spatial clustering in the northwest, riverine zones, and coastal outlet areas, providing insight into potential source regions. SOM clustering identified three types of groundwater: Cluster 1 (characterized by Cr, Mn, Fe, and Ni) is primarily influenced by industrial pollution and present spatially scattered distribution; Cluster 2 (dominated by As, NO₃⁻, Ca²⁺, and K⁺) is associated with domestic sewage and distributes following river flow; Cluster 3 (enriched in Zn, Ba, Pb, and NO₃⁻) is shaped by agricultural activities and natural mineral dissolution, with a lateral distribution along the piedmont zone. The findings of this study provide a scientific foundation for groundwater pollution prevention and environmental management in industrialized areas. Full article

In order to evaluate spatial pollution patterns of the Shaying River and assess human health risk, thirty-three sampling points were established in different reaches of the upper, middle, and lower reaches of the Shaying River. According to the difference in human activities and land use types, the sampling points were artificially divided into three areas: mountainous area, urban area, and agricultural area. Water samples and sediments were collected at each sampling site, and the physicochemical parameters of the water at each site were measured simultaneously. The nutrient content of water samples and the heavy metal content of sediments were measured in the laboratory. The water pollution status of the Shaying River, as well as the status of heavy metal pollution and its associated risk to human health, were assessed and analyzed using the Water Quality Index (WQI) method, principal component analysis (PCA) method, potential ecological risk index method, and health risk assessment method, respectively. The results of the Water Quality Index indicated that the water quality of the Shaying River was moderate, with the reaches in the urban area being more polluted, the agricultural area being the second most polluted, and the mountainous area being in better condition. The results of the principal component analysis showed that soluble ions, organic matter, and nutrients were the main factors contributing to water pollution in the Shaying River, and there was significant variability in the factors contributing to water pollution in different regions, with human activities being the main cause of this variation. The results of a potential ecological risk assessment of heavy metals in sediments showed that heavy metal pollution in the water bodies of the Shaying River was serious and had significant spatial variability. Mountain reaches were the most polluted, followed by agricultural reaches, and urban reaches were the least polluted. The results of the health risk assessment showed that non-carcinogenic risks of heavy metals in different reaches of the Shaying River were within acceptable limits, while carcinogenic risks in agricultural areas exceeded thresholds. Among them, agricultural areas had the highest health risk, with Cr being the most carcinogenic heavy metal and Pb and Cr being the most non-carcinogenic heavy metals. The assessment also found that children’s carcinogenic risk was 8.4 times higher than adult males and 7.3 times higher than adult females. This study involves the typical diverse areas where the Shaying River passes, in order to provide data support and a theoretical basis for environmental protection of the Shaying River Basin. Full article

The present study focuses on the dynamics of trace metals (TM) in two European rivers, the Mosel and the Meuse. A deterministic description of hydro-sedimentary processes has been performed. The model used to describe pollutant transport and dilution at the watershed scale has been enhanced with the implementation of the MicMod sub-model. The objective of this study is to characterise the dynamics of TM in the water column and bed sediment. A multi-class grain size representation has been developed in MicMod. The dissolved and particulate TM phases have been calculated with specific partitioning coefficients associated with each suspended sediment (SS) class. The processes involved in TM fate have been calibrated in MicMod, including settling velocity, TM releases from the watershed (point and diffuse loads), etc. Following the calibration of the parameters involved in TM transport within the river ecosystem, the main goal is to describe TM dynamics using a pressure–impact relationship model. It was demonstrated that the description of at least one class of fine particles is necessary to obtain an adequate representation of TM concentrations. The focus of this study is low flow periods, which are characterised by the presence of fine particles. The objective is to gain a deeper understanding of the processes that control the transport of TM. This paper establishes consistent pressure–impact relationships between TM loads (urban, industrial, soils) from watersheds and concentrations in rivers. Full article

Industrial and urban activity has inevitably changed the water environment and caused significant impacts on water resources’ quality and quantity. The identification of related impacts is particularly important in the context of increasing water shortages due to climate change. Overlapping industrial impacts and drought occurrence have resulted in the long-lasting deterioration of surface water status. Therefore, the mitigation of negative impacts is crucial for relevant and sustainable water management in river basins. One of the most impactful branches of industry is underground coal mining, which requires dewatering deposits and excavations. Mine waters discharged into rivers have induced significant increases of salinity, while urban wastewaters have increased biogenic contamination in surface waters. Sustainable development goals require water protection, energy transition, and circularity; therefore, coal will be repurposed in favor of alternative sources of energy. The phasing out of coal and cessation of dewatering of mines would rapidly reduce mine waters’ impact on the environment. However, in heavily industrialized urban basins, the share of natural waters in river flows is exceptionally low—due to significant and long-lasting transformations, industrial and urban wastewaters are the main constitutive components in certain river hydrological regimes. The case study of Bytomka in the Upper Silesian Coal Basin, Southern Poland is a vivid example of a river basin significantly impacted by urban and industrial activity over a long-term period. The Bytomka River’s water status and the development of its watershed area is an example of complex and overlapping impacts, wherein sustainable water management requires proper recognition of prevailing factors such as mine water discharges, climate change and drought periods, wastewater impacts, and urbanization of the water basin area. The presented study reveals key findings showing that future coal mine closures would result in significant water resource shortages due to a reduction of mine water discharges, significant biogenic (N and P) pollution increases, and hazards of harmful algal blooms. Therefore, there is an urgent need to increase the retention potential of the watershed, use nature-based solutions, and mitigate negative impacts of the coal mining transition. The increase in treatment capability of industrial wastewater and sewage discharge would help to cope with the natural water vulnerability induced by the impacts of climate change. Full article