Search Results (138)

Wastewater containing high pollutant loads is discharged into the municipal sewerage system by industrial facilities operating within the industrial zones of Konya, Türkiye. Although regulations mandate that wastewater be treated to comply with specified discharge standards, some facilities lack pretreatment systems due to high capital and operational costs, while existing systems experience operational deficiencies. As a consequence, operational disruptions and increased environmental risks occur within the municipal sewerage system. Periodic sampling and inspection activities conducted by municipal authorities are becoming increasingly challenging for effective monitoring and evaluation as the number of facilities increases. In this study, a Geographic Information System (GIS)-based approach was developed to enhance monitoring effectiveness, and industrial wastewater quality data were analyzed using ArcGIS Pro 2.9 software (Esri, Redlands, CA, USA) to generate spatial pollution distribution maps. Samples were collected from five industrial facilities and four sewer junction points located in the Hacıyusufmescit, Emirgazi, and Fetih neighborhoods, where odor problems are frequently reported, during the 2022–2023 period. It was determined that COD (24,960 mg/L), BOD (2970 mg/L), and oil and grease (254 mg/L) concentrations significantly exceeded the regulatory discharge limits, particularly during the summer season. The results demonstrate that GIS-based monitoring systems constitute an effective tool for the early detection of pollution and odor-related problems at the urban scale, for the systematic management of control processes, and for the facilitation of evidence-based decision-making. Full article

Pharmaceuticals and personal care products (PPCPs) are widely recognized as persistent contaminants in urban aquatic systems, yet their behavior is typically interpreted under steady-state assumptions driven by continuous discharge of treated wastewater. This paradigm overlooks the dominant role of episodic pollution pulses associated with combined sewer overflow (CSO) events. This review advances a new conceptual framework in which PPCP contamination is understood as a manifestation of complex phenomenon, arising from the interaction of intense precipitation, hydraulic exceedance of sewer systems, and mobilization of accumulated contaminants. We critically synthesize current knowledge on the occurrence, transport, transformation, and removal of PPCPs across wastewater effluents and CSO discharges, integrating insights from degradation kinetics, environmental monitoring, and treatment technologies. Comparative analysis reveals strong matrix-dependent variability in PPCP attenuation, with enhanced degradation in estuarine and marine systems driven by complex photochemical and biogeochemical interactions. However, under CSO-driven pulse conditions, these processes become transient and non-linear, challenging conventional assumptions of steady-state degradation and risk assessment. The findings highlight that CSO events can generate short-duration but high-intensity contamination peaks, often exceeding baseline concentrations and potentially amplifying ecological risks and antimicrobial resistance selection. We propose a matrix-reactivity and pulse-driven framework to better capture the dynamic fate of PPCPs under real-world conditions. Future research should prioritize event-based monitoring, real-time sensing, and time-resolved risk assessment models to address the limitations of current approaches. This work redefines PPCP pollution as a dynamic, episodic, extreme-event-driven process, with important implications for urban water management under increasing climatic variability. Full article

Urban drainage systems (UDSs) are critical built assets increasingly challenged by short-duration extreme rainfall, aging infrastructure, and rising surcharge risk. Physics-based hydrodynamic models are widely used for system assessment, but their high computational cost limits real-time operational prediction. Existing data-driven prediction approaches improve computational efficiency, but often rely mainly on sensor inputs and provide limited asset-level interpretation. This study develops an explainable digital twin for real-time prediction of storm-driven water level response in a separate sewer network in the Yangtze River Delta, China. The framework integrates 5 min monitoring and SCADA data, including water level, flow, pump status, and rainfall, with GIS and as-built asset information, including pipe geometry, hydraulic capacity, catchment characteristics, and network connectivity. A hybrid TCN-LSTM model was developed to predict water level and surcharge risk probability at 15–60 min lead times. A surrogate-based SHAP module was used to explain model predictions at the node and subcatchment scales. Multi-source fusion reduced the RMSE by approximately 18% compared with sensor-only baselines. The SHAP results showed that the pipe capacity-related variables and upstream contributing area were the main drivers of surcharge onset. The framework provides interpretable, operationally relevant predictions to support the resilience-oriented management of urban drainage systems. Full article

The accurate quantification of microplastics (MPs) in aquatic environments remains challenging due to the heterogeneous distribution of MPs in different environments, making representative sampling difficult, as well as methodological variabilities in sampling, sample processing, and detection. This study examined measurement fluctuations for MP analysis across four distinct water matrices: wastewater treatment plant (WWTP) effluent, tap water (TW), combined sewer overflow (CSO), and surface water (SW). Two sampling strategies were compared: grab sampling (0.5 L, n = 5) and large-volume filtration using a particle sampling unit (PSU; 100 L, 10 µm mesh, subsampled). Samples were processed through oxidative digestion, stained with fluorescent dye, and analyzed via fluorescence microscopy with automated particle counting. Recovery experiments using polyamide (PA) reference particles (357 ± 60 µm) were conducted to assess method accuracy. PSU sampling demonstrated higher precision (mean R.S.D. 41 ± 17%) compared to grab sampling (mean R.S.D. 64 ± 19%), despite additional variability introduced by subsampling. Recovery rates reached 93 ± 7% for grab samples and 88 ± 23% for PSU samples with complete filter analysis. Statistical modeling revealed that achieving a ±25% margin of error (95% CI) required 21 PSU samples versus 51 grab samples. The quadratic relationship between the margin of error and required sample size underscores the importance of methodological optimization for cost-effective monitoring. These findings provide practical guidance for designing MP monitoring campaigns and demonstrate that fluorescent labeling combined with large-volume sampling offers a reliable approach for MP quantification in diverse aquatic environments. Full article

Historic cities face a dual challenge of managing waterlogging risks while adhering to strict preservation constraints. Traditional drainage upgrades often require extensive excavation, threatening cultural heritage. This study establishes a quantitative assessment framework for the historic urban district of City B using a 1D-2D-coupled hydrodynamic model (InfoWorks ICM). The model was calibrated using continuous monitoring data, achieving a Nash–Sutcliffe Efficiency (NSE) of 0.91. Its spatial accuracy was subsequently validated against historical waterlogging records, showing a strong consistency between simulated flood-prone areas and observed flood locations. We simulated waterlogging distribution under rainfall events with return periods of 0.5 to 5 years. Results reveal two key deficiencies in the current drainage system under a 0.5-year return period storm event. Firstly, 75.3% of the pipe segments are hydraulically overloaded, failing to meet the design standard. Secondly, this widespread network overload contributes to surface waterlogging, with 9.58 ha (1.80% of the total area) being waterlogged. We evaluated three strategies: Low Impact Development (LID), underground storage tanks, and intercepting sewers. A hybrid grey-green infrastructure (HGGI) system was proposed, integrating source reduction and terminal storage. The HGGI system reduced waterlogged areas by 83.58% (0.5-year event) and 64.87% (5-year event), outperforming single measures. Crucially, this hybrid system achieves minimal intervention in historic street patterns through trenchless construction for intercepting sewers, decentralized LID layout and underground storage tanks, avoiding large-scale road excavation while enhancing flood resilience. This study demonstrates that hybrid strategies can effectively balance flood resilience with environmental and cultural preservation in high-density historic districts. Full article

Despite the importance of wastewater environmental monitoring in disease prevention and response strategies, its use remains poorly documented in Senegal. In addition, there is more onsite sanitation than sewer networks in Dakar, and open drains channel for rainwater are also used as clandestine wastewater discharge into the sea. This study aimed to assess the presence of specific pathogens in wastewater, faecal sludge, and bathing water (the sea). Samples were taken at treatment plants, an open drain, and in the receiving environment (the sea) from June to December 2023. Total nucleic acid was subjected to multiplex qualitative qPCR using SeeGene Allplex™ kits targeting 34 gastrointestinal pathogens. Descriptive statistics, multiple correspondence analysis (MCA) and logistic regression were performed. Considering all matrices, across 51 analysed samples, the results revealed strong bacterial (96.08%, n = 49), parasitic (84.31%, n = 43), and viral (68.63%, n = 35) presence. These results showed high levels of Aeromonas spp. (96.08%), Blastocystis hominis (80.39%), Enterocytozoon (58.82%), and Norovirus GII (74.51%) among bacteria, protozoa, helminths, and viruses, respectively. Moreover, faecal sludge and pumping station samples show more identified pathogen than wastewater treatment plant and seawater samples. The MCA revealed that the dry season is spatially associated with a greater number of pathogens than the rainy season, but the latter showed a greater species diversity. Logistic regression showed that certain physicochemical parameters, including BOD5, turbidity, pH, and suspended solids, influence pathogen detection. However, qualitative detection and sampling period may constitute limitations. These results reveal that wastewater and bathing water can serve as sources of information on the circulation of pathogens of interest with epidemic potential. Therefore, this valuable epidemiological tool could serve as an adjunct to clinical surveillance in order to prevent future epidemics. Full article

Combined sewer overflow (CSO) pollution has consequently become a critical challenge, yet its formation depends on tightly coupled dry- and wet-weather processes. This study aims to integrate high-resolution field monitoring with statistical analysis to characterize the full “accumulation–transport–discharge” cycle of CSO pollution in a representative combined sewer catchment located in the Yangtze River basin, China. A dynamic analytical framework was established, combining multiple pollution media and linking dry-weather accumulation with rainfall-driven transport, enabling quantitative source apportionment of pollutant contributions. Results indicated that during dry periods, domestic sewage exhibited strong enrichment, with concentrations of total inorganic nitrogen (TIN), chemical oxygen demand (COD), and total phosphorus (TP) being 2.1-, 2.3-, and 1.9-fold higher, respectively, than the Chinese secondary discharge standards (GB 18918-2002). Surface sediment showed pronounced spatial heterogeneity, with greater loads in residential than transportation areas and substantial fine-particle accumulation on roofs (particle size < 150 μm, accounting for 73% by mass). Sewer sediments, dominated by coarse inorganic particles (over 77% by mass), represented the main pollutant reservoir. Rainfall produced distinct hydrodynamic and water quality responses. Light rain following long antecedent dry periods generated a high-concentration but low-load regime with a strong first flush, whereas moderate rain yielded lower concentrations but higher loads. Overflow occurred when rainfall exceeded ~14 mm, with pollutant peaks lagging rainfall by 20–45 min in the studied area. TIN and TP peaked sharply at rainfall event onset, and first-flush intensities followed TIN > TP > COD > suspended solids (SS). Source apportionment identified sewer sediments as the dominant CSO source, followed by surface runoff and domestic sewage. These findings clarify the mechanisms linking dry-weather accumulation to wet-weather transport and support targeted CSO pollution control and urban water quality management. Full article

This dataset compiles continuous hydraulic and water quality observations from the combined sewer overflow structure at the outlet of the Graz-West R05 catchment in Austria, covering the period from 2008 to 2011. It integrates high-resolution in-sewer measurements of flow rate, water level, flow velocity and water quality parametres (COD, TSS, temperature), complemented by laboratory analyses of discrete grab samples. Water quality parametres were monitored using an in situ UV/VIS spectrometer installed on a floating pontoon. Additional locally calibrated COD values derived from laboratory measurements are included. The in-sewer data were acquired at 1 or 3 min intervals depending on flow conditions. Flow rates, water levels and overflow discharges were monitored using radar and ultrasonic sensors. Three nearby tipping-bucket rain gauges provided time-stamped precipitation increments, enabling the detailed reconstruction of wet-weather dynamics. A hydrodynamic SWMM model of the catchment, including geospatial information and dry-weather calibration, is included to support modelling applications. This combination of long-term measurements and a calibrated hydrodynamic model supports the development, testing and validation of process-based, statistical or data-driven approaches for simulating combined sewer system behaviour and pollutant dynamics. Full article

Wastewater-Based Epidemiology (WBE) has emerged as a critical tool for monitoring SARS-CoV-2 circulation at the community level. This study assessed spatiotemporal viral dynamics in Las Heras, Mendoza, Argentina, by comparing wastewater samples from six sewer maintenance holes and three wastewater treatment plants (WWTPs) between January and June 2021, and by conducting long-term surveillance at Campo Espejo WWTP during epidemic (2020–2021) and endemic (2024–2025) phases of COVID-19. Viral particles from sewer manholes and WWTPs samples were concentrated by polyethylene glycol precipitation or aluminum polychloride adsorption–precipitation methods, and then SARS-CoV-2 RNA was quantified by reverse transcription quantitative polymerase chain reaction targeting N1 and N2 nucleocapsid viral markers. Results showed consistent detection of viral RNA across all sites, with peaks in wastewater preceding diagnosed COVID-19 cases increases, confirming WBE as an early-warning system. Localized sewer sampling identified urban hotspots, while WWTPs monitoring captured broader epidemiological trends. Recently, COVID-19 surveillance showed lower and intermittent viral loads, decoupled from diagnosed cases, compared to epidemic phase, indicating a transition to endemic circulation. Overall, combining upstream and downstream WBE enhanced spatial and temporal resolution, demonstrating its utility for public health monitoring during both epidemic and endemic phases. Full article

Predictive pest management in urban sewer networks represents a sustainable alternative to reactive, biocide-based methods. Using data collected through an IoT architecture and validated with manual inspections across eight manholes over 113 days, we implemented a rigorous comparative framework evaluating eleven data mining algorithms, including classical methods (KNN, SVM, decision trees) and advanced ensemble techniques (XGBoost, LightGBM, CatBoost) optimized for unbalanced datasets. Gradient boosting models with explicit handling of class imbalance—where the absence of pests exceeds 77% of observations—showed exceptional performance, achieving a Macro-F1 score above 0.92 and high precision in identifying the minority high-risk class. Explainability analysis using SHAP consistently revealed that elevated CO₂ concentrations are the primary predictor of infestation, enabling early identification of critical zones. This study demonstrates that carbon dioxide (CO₂) acts as the most robust bioindicator for predicting severe infestations of Periplaneta americana, significantly outperforming conventional environmental variables such as temperature and humidity. The implementation of the model in a real-time monitoring platform generates interpretable heat maps that support proactive and localized interventions, optimizing resource use and reducing dependence on biocides. This study presents a scalable, operationally viable predictive system designed for direct integration into municipal asset management workflows, offering a concrete, industry-ready solution to transform pest control from a reactive, labor-intensive process into a data-driven, proactive operational paradigm. This approach not only transforms pest management from reactive to predictive but also aligns with the Sustainable Development Goals, offering a scalable, interpretable, and operationally viable system for smart cities. Full article

Antimicrobial resistance (AMR) in hospital wastewater is a recognized public health concern, yet the dynamics of its emergence remain poorly understood. This study aimed to characterize the quantitative and qualitative changes in the microbial community of a newly built internal medicine intensive care hospital wing following the start of patient treatment. Wastewater samples were collected regularly from eight relevant sites, including seven patient-associated locations within the intensive care ward and the central sanitary sewer where all effluent converged. Culture-based analyses targeted the “ESCAPE-SO” bacterial and fungal groups (“Enterococci”, “Staphylococci”, “Candida”, “Acinetobacter”, “Pseudomonas”, “Enterobacteriaceae”, “Stenotrophomonas”, “Others”). Comparisons were made between a 12-month pre-operation period (only flushing every 72 h to prevent contamination of the drinking water system) and the first 12 months of patient treatment. The results showed a significant increase in mean bacterial concentrations from 53 [0–349] CFU/mL before patient treatment to 8423 [3054–79,490] CFU/mL during patient treatment (p = 0.0224) with a particular focus on Pseudomonas spp. as the dominant genus. Resistance against all four main antibiotic classes of the WHO AWaRe essential “watch” list (carbapenems, third-generation cephalosporins, broad-spectrum penicillin and ciprofloxacin) emerged within the first twelve months and depended on the amount of prescribed antibiotics and the number of patients treated. These findings indicate that hospital activity drives rapid development of antimicrobial resistance in wastewater microbial communities, highlighting the critical role of clinical antibiotic use in shaping environmental resistomes. This study provides quantitative evidence that resistance can emerge within months of hospital operation, emphasizing the need for early monitoring and targeted interventions to mitigate the spread of AMR from hospital effluents into broader environmental systems. Full article

Sewer corrosion driven by sulfur metabolism threatens infrastructure durability. Current study examined the effect of conductive lining materials on microbial communities and sulfide control under simulated sewer conditions. Three lab-scale reactors (3.5 L total volume, 2.1 L working volume) were prepared with amorphous carbon (SAN-EARTH) and magnetite-black (MTB) linings, while a Portland cement reactor with no coating served as the control. Each reactor was operated for 120 days at room temperature and fed with artificial wastewater. The working volume consisted of 1.4 L of synthetic wastewater mixed with 0.7 L of sewage sludge used as the inoculum source. Sulfate, sulfide, hydrogen sulfide, nitrogen species, pH, and organic carbon were monitored, and microbial dynamics were analyzed via 16S rRNA sequencing and functional annotation. SAN-EARTH and MTB reactors completely suppressed sulfide and hydrogen sulfide, while Portland cement showed the highest accumulation. Both conductive linings maintained alkaline conditions (pH 9.0–10.5), favoring sulfide oxidation. Microbial analysis revealed enrichment of sulfur-oxidizing bacteria (Thiobacillus sp.) and electroactive taxa (Geobacter sp.), alongside syntrophic interactions involving Aminobacterium and Jeotgalibaca. These findings indicate that conductive lining materials reshape microbial communities and sulfur metabolism, offering a promising strategy to mitigate sulfide-driven sewer corrosion. Full article

The long-distance transport of wastewater in sewers inevitably leads to the formation of biofilms on the inner wall of sewers. Numerous studies have focused on analyzing the hydrogen sulfide, methane production, and emission patterns associated with sewer biofilms in sewer systems. This study employed bibliometric methods to analyze the research progress in the field of sewer biofilms from 1995 to 2025, and revealed the associated development trend, international cooperation network, and research hotspots. The results demonstrate a substantial increase in the number of annual publications over the past decade, with China and Australia as the primary contributors. The journal Water Research has been found to exert a significant influence. The research hotspots concentrate on the generation and control of hydrogen sulfide and methane, sewer corrosion mechanisms, and microbial community dynamics, with chemical dosing, sulfate-reducing bacteria, and biofilm metabolism as the key directions. The evolution of keywords demonstrates that early research focused on organic matter transformation, and in recent years, there has been a shift towards microbial ecology and wastewater epidemiology, along with other emerging areas. Recent years have seen China as well as China’s institution and authors emerge as the primary contributors in the sewer biofilm field, a development attributable to the country’s policy support, which has precipitated the development of green technologies and smart monitoring systems. This study demonstrates the necessity of international cooperation and provides theoretical references and technological directions for future sewer biofilms research. Full article

Rural tropical regions face escalating threats from zoonotic AIV and dengue virus but lack sewered infrastructure for conventional wastewater surveillance. We implemented surface water-based surveillance (SWBS) in peri-urban Dhaka (Bangladesh) and Ruili (China) from July to November 2023 and coupled it with machine learning-enhanced digital epidemiology. Reverse transcription quantitative PCR (RT-qPCR) was employed to detect the M gene of AIV and to subtype H1, H5, H7, H9, and H10 in surface water. Wild bird feces (n = 40) were collected within 3 km of positive sites to source-track AIV. For the dengue virus, a serogroup-specific RT-qPCR assay targeting the CprM gene was used. Genomic sequencing of AIV and dengue virus was performed to elucidate phylogenetic relationships with local clinical strains. Clinical data related to dengue fever were also collected for correlation analysis. Meanwhile, 13 dengue-related keyword search volumes were harvested daily from Google, Bing and Baidu for four cities to reveal the relationship between dengue epidemics and the web search index. AIV H5 was detected in Dhaka city from week 38, peaking at week 39, while dengue virus was persistently detected from week 29 to week 45, aligning with clinical trends. Time-series cross-correlation analysis revealed that variations in surface water viral load led clinical case reports by approximately two weeks (max CCF = 0.572 at lag −2). In Ruili city, dengue virus was detected from week 32 to week 44. To sharpen sensitivity, 383 weekly web search series for 13 dengue keywords from four countries were screened; random-forest and XGBoost models retained five symptom queries that generated a composite index explaining 79% of variance in dengue RNA levels in an independent Ruili test set (n = 24) and reduced superfluous sampling by 35%. Phylogenetic analysis verified identity between water-derived and patient-derived DENV-2, confirming local transmission. The study demonstrates that AIV SWBS is optimally integrated with wild bird sampling for source attribution, whereas dengue SWBS achieves maximal efficiency when combined with real-time web search monitoring, providing tailored, low-cost early-warning modules for resource-constrained tropical settings. Full article

Escherichia coli is an important indicator microorganism of fecal contamination in water. However, routine government monitoring often fails to capture the actual state of pollution, because E. coli concentrations in urban rivers are highly variable. This study presents a case study on factors influencing E. coli concentrations in an urban river draining a fully sewered area. An approximately 70-fold higher concentration compared with the average dry-weather concentration (1.9 CFU/mL) was observed under wet-weather conditions, probably due to the effects of combined sewer overflows. A very short survival of E. coli (less than one day) was expected in the unfiltered overlying water, due to the contributions of bacteriophages, protozoan predation, and bacterial competition, whereas a longer survival was expected in the sediment. Such a short survival may be a characteristic of the target watershed, where treated wastewater accounted for approximately 75% of the total flow. The highly variable antimicrobial resistance among E. coli populations under dry-weather conditions was possibly caused by the regrowth of a limited number of E. coli individuals in the sediment. Rising temperatures due to global warming are expected to decrease the concentration of E. coli in the target watershed, where E. coli populations are strongly suppressed by predation and competition. Full article