Combined sewer overflows (CSOs) are of major environmental concern for impacted surface waterbodies. In the last decades, major storm events have become increasingly regular in some areas, and ...meteorological scenarios predict a further rise in their frequency. Consequently, control and treatment of CSOs with respect to best practice examples, innovative treatment solutions, and management of sewer systems are an inevitable necessity. As a result, the number of publications concerning quality, quantity, and type of treatments has recently increased. This review therefore aims to provide a critical overview on the effects, control, and treatment of CSOs in terms of impact on the environment and public health, strict measures addressed by regulations, and the various treatment alternatives including natural and compact treatments. Drawing together the previous studies, an innovative treatment and control guideline are also proposed for the better management practices.
The sewer system is a critical component of urban infrastructure, responsible for transporting wastewater and stormwater away from populated areas. Proper design and management of sewer systems are ...essential to prevent flooding, reduce environmental pollution, and ensure public health and safety. One crucial parameter in sewer system design and management is the particle Froude number (Frn). The goal of this study is to develop a predictive algorithm that takes into account the relevant input parameters, such as volumetric sediment concentration (Cv), dimensionless grain size of particles (Dgr), the ratio of sediment median size to the hydraulic radius (d/R), pipe friction factor (λ) to accurately predict the Frn using an ablation study for the condition of non-deposition with clean bed data. The proposed approach is based on hyper-parameter optimization techniques, i.e., Babysitting method (BSM), GridSearchCV (GS), random search (RS), Bayesian optimization with Gaussian process (BO-GP), Bayesian optimization with tree-structures Parzen estimator (BO-TPE), and particle swarm optimization (PSO), which are applied to the four machine learning algorithms such as random forest (RF), gradient boosting (GB), K-nearest neighbor (KNN), and support vector regression (SVR). The proposed algorithms are compared with the existing algorithms in terms of coefficient of determination (R2), root mean square error-observations standard deviation ratio (RSR), and normalized mean absolute error (NMAE) to assess the performance of the proposed algorithms. The results show that the proposed algorithms yield superior outcomes across all performance metrics. Among the proposed algorithms, GB+PSO predicted Frn with significant accuracy and has the highest prediction accuracy (R2 = 0.996, RSR = 0.068, and NMAE = 0.009, respectively), followed by RF+BO-GP, SVR+RS, and KNN+PSO. We have provided a comparison with the existing state-of-the-art methods and beat them. We evaluate these proposed algorithms against several widely recognized empirical equations found in the existing literature.
•The study introduces a novel approach for predicting particle Frn and compares four ML algorithms (RF, GB, KNN, SVR).•The study implements HPOTs (BSM, GS, RS, BO-GP, BO-TPE, PSO) to enhance ML algorithms’ performance.•The study examines feature selection’s effect on algorithm performance using an ablation study.•The findings offer insights into selecting ML algorithms and settings for accurate Frn prediction.
•A new sewerage design concept to medical wastewater discharge is proposed.•Residual chlorine inhibits the biodegradation of organic matter in sewer systems.•Pathways related to stress response such ...as TCS were significantly enriched.•Carbon metabolism shifted from EMP to PPP pathway to reduce oxidative stress.•The decay and transformation of residual chlorine in sewers were explored.
The severely low influent chemical oxygen demand (COD) concentration at wastewater treatment plants (WWTPs) has become a critical issue. A key factor is the excessive biodegradation of organic matter by microbial communities within sewer systems. Intense disinfection commonly adopted for medical wastewater leads to abundant residual chlorine entering sewers, likely causing significant changes in microbial communities and sewage quality in sewers, yet our understanding is limited. Through long-term sewer simulation batch tests, this study revealed the response mechanism of microbial communities to residual chlorine and its impact on organic matter concentration in sewage. Under residual chlorine stress, microbial community structure rapidly changed, and more complex microbial interactions were observed. Besides, pathways related to stress response such as two-component system were significantly enriched; pathways related to energy metabolism (such as carbon fixation in prokaryotes and citrate cycle) in microbial communities were inhibited, and carbon metabolism shifted from the Embden-Meyerhof pathway to the pentose phosphate pathway to enhance cellular reducing power, reduce oxidative stress, and consequently decrease organic matter degradation. Therefore, compared to sewers with normal disinfection, concentrations of COD and dissolved organic carbon in sewage under chlorine stress increased by 12.6 % and 7.4 %, respectively. Besides, the decay and transformation of residual chlorine in sewers were explored. These findings suggest a new approach to medical wastewater discharge management: placing the medical wastewater outlet at the upstream in sewer systems, which ensures that residual chlorine consumption reaches maximum during long-distance transportation, mitigating its harmful effects on WWTPs, and increases the influent organic matter concentration, thereby reducing the need for additional carbon sources.
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•A comprehensive study on the transportation characteristics of PPCPs in sewers.•Mass balance analysis reveals degradation pathway of PPCPs in sewers.•Six transformation products were ...identified by used UHPLC-Q Exactive MS.•The environmental risk of PPCPs in sewers were evaluated for the first time.
The release of pharmaceuticals and personal care products (PPCPs) is one of the most concern issues which affect the stability of environment. In this study, the transformation, typical metabolites and risk evaluation of five dominating PPCPs (acetaminophen, triclosan, caffeine, N,N-diethyl-m-toluamide and sulfamethoxazole) were investigated in a pilot sewer. Firstly, the mass balance analysis indicated, although the PPCPs have the peculiarity of degradation-resistant, the biodegradation of PPCPs still plays a more important role in sewers, and then, liquid chromatography coupled to mass spectrometry (UHPLC-Q Exactive MS) methods were utilized to reveal their fate during pipeline transportation. In total, six transformation products (TPs) were detected and identified. The transformation occurring in sewers involved rearrangement of the aminobenzene moiety, ether bond breaking, hydrolysis of hydroxy compounds and dealkylation. Finally, risk(s) were estimated by calculating risk quotients (RQs). TCS is “high risk” (RQ > 200), SMX is “minimal risk” (RQ < 0.3), and the other compounds examined are “low or medium risk” and vary widely (RQ ≈ 3.75–98.19). Thus, based on this investigation, insights into PPCPs bioconversions in sewers were revealed, which could improve the understanding of subsequent treatment process of the wastewater treatment plant (WWTP) and reduced environmental risks caused by micropollutants.
Morphometric properties of channel networks are useful tools to classify catchments and calculate their hydrological response. Scaling laws have been established for Optimal Channel Networks (OCNs), ...which are defined based on a generative geomorphological mechanism of minimizing the total energy dissipation. However, sewer networks obey engineering efficiency rules and are conceived based on local optimizations, both in time and space, for minimal costs. Not all the scaling laws have been verified for artificial sewer networks found in urban areas. This raises questions regarding the applicability of OCN scaling laws to sewer networks and their potential impact on the shape of the Geomorphological Instantaneous Unit Hydrograph (GIUH). Hence, this work aims to study the morphometric properties of the Greater Paris combined sewer system through a case study on twelve nested subcatchments. A two‐step methodology is used. First, the morphometric properties are analysed using the reference Horton‐Strahler, Rodríguez‐Iturbe and Moussa‐Bocquillon scaling laws. The results show that Horton‐Strahler's laws of bifurcation are verified while the length and area laws are not always verified. Rodriguez‐Iturbe and Moussa‐Bocquillon laws are verified with slightly different values of the descriptors in comparison to OCNs. Second, these morphometric properties are used to calculate four GIUHs: the reference Width Function (GWF), the Nash unit hydrograph (GN) using Horton‐Strahler ratios, the Nash Unit Hydrograph equivalent (GNe) using Moussa‐Bocquillon descriptors, and the Hayami function (GH) solution of the diffusive wave equation. We identified four catchments for which the scaling laws are verified and therefore all GIUHs are similar while for four other catchments the scaling laws are not verified and strongly impact the GIUHs. These morphometric descriptors and the GIUHs can be considered as ‘hydrological signatures’ of Combined Sewer Systems (CSSs) and are useful for the comparison and classification of hydrological responses.
This work aims to study the morphometric properties of a non‐Optimal Channel Network, the Greater Paris Combined Sewer System (CSS), through a case study on twelve nested subcatchments. The morphometric properties are analysed using the Horton‐Strahler, Rodriguez‐Iturbe and Moussa Bocquillon laws. These morphometric properties are then used to calculate four GIUHs. The morphometric descriptors and the GIUHs can be considered as ‘hydrological signatures’ of CSSs and are useful for the comparison and classification of hydrological responses.
Climate change and urbanization are key factors affecting the future of water quality in urbanized catchments. The work reported in this paper is an evaluation of the combined and relative impact of ...climate change and urbanization on the water quality of receiving water bodies in the context of a highly urbanized watershed served by a combined sewer system (CSS) in northern Italy. The impact is determined by an integrated modelling study involving two years of field campaigns. The results obtained from the case study show that impervious urban surfaces and rainfall intensity are significant predictors of combined sewer overflows (CSOs) and consequently of the water quality of the receiving water body. Scenarios for the year 2100 demonstrate that climate change combined with increasing urbanization is likely to lead to severe worsening of river water quality due to a doubling of the total phosphorus load from CSOs compared to the current load. Reduction in imperviousness was found to be a suitable strategy to adapt to these scenarios by limiting the construction of new impervious areas and decreasing the existing areas by only 15%. This information can be further utilized to develop future designs, which in turn should make these systems more resilient to future changes in climate and urbanization.
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•Impervious surfaces and rainfall intensity are significant predictors of CSOs.•Urbanization and climate change impacts on surface water quality are addressed.•The coupled scenarios show a TP load from CSOs double than the current one.•Reduction of imperviousness is a suitable adaptation strategies for these scenarios.
Risk‐informed asset management is key to maintaining optimal performance and efficiency of urban sewer systems. Although sewer system failures are spatiotemporal in nature, previous studies analyzed ...failure risk from a unidimensional aspect (either spatial or temporal), not accounting for bidimensional spatiotemporal complexities. This is owing to the insufficiency of good‐quality data, which ultimately leads to under‐/overestimation of failure risk. Here, we propose a generalized methodology/framework to facilitate a robust spatiotemporal analysis of urban sewer system failure risk, overcoming the intrinsic challenges of data imperfections—e.g., missing data, outliers, and imbalanced information. The framework includes a two‐stage data‐driven modeling technique that efficiently models the highly right‐skewed sewer system failure data to predict the failure risk, leveraging a bidimensional space‐time approach. We implemented our analysis for Bogotá, the capital city of Colombia. We train, test, and validate a battery of machine learning algorithms—logistic regression, decision trees, random forests, and XGBoost—and select the best model in terms of goodness‐of‐fit and predictive accuracy. Finally, we illustrate the applicability of the framework in planning/scheduling sewer system maintenance operations using state‐of‐the‐art optimization techniques. Our proposed framework can help stakeholders to analyze the failure‐risk models' performance under different discrimination thresholds, and provide managerial insights on the model's adequate spatial resolution and appropriateness of decentralized management for sewer system maintenance.
Combined sewer overflows (CSOs) occur when untreated raw sewage mixed with rainwater, runoff, or snowmelt is released during or after a storm in any community with a combined sewer system (CSS). ...Climate change makes CSOs worse in many locales; as the frequency and severity of wet weather events increases, so do the frequency and volume of CSO events. CSOs pose risks to humans and the environment, and as such, CSS communities are under regulatory pressure to reduce CSOs. Yet, CSS communities lack the tools needed, such as performance indicators, to assess CSS performance. Using the city of Cumberland, Maryland as a case study, we use public data on CSOs and precipitation over a span of 16 years to identify a new critical rainfall intensity threshold that triggers likely CSO incidence, and a multiple linear regression model to predict CSO volume using rainfall event characteristics. Together, this indicator and modeling approach can help CSS communities assess the performance of their CSS over time, especially to evaluate the effectiveness of efforts to reduce CSOs.
Water quality impaired by excess nutrients has been linked to negative effects on human health, the environment, and the economy. Residential septic systems (i.e., onsite sewage treatment) contribute ...to these excess nutrients. Conversion from a septic system to a sewer system (hereafter referred to as S2S) is one way to mitigate pollution from excess nutrients. There are voluntary and mandatory S2S conversion programs throughout and beyond Florida. While there are multiple benefits of making such a change, S2S conversion is a complex and costly process. This document was developed to aid environmental management professionals, policymakers, and communication and education professionals (e.g., Extension agents) in understanding residents’ perceptions pertaining to S2S conversion. More details on the study presented in this document are available at: https://doi.org/10.1016/j.jenvman.2022.115651.
•Stormwater management practices help to adapt to extreme rainfall events.•Green roofs, rain gardens and porous pavement are helpful to cope with heavy rains.•Creation of living space can be combined ...with water resilient planning.•Compaction by additional storeys with green roofs preferable over extra buildings.•Reduction of climate change impact of heavy rainfall with nature-based solutions.
The demand for living space is rising in growing cities. To restrict urban expansion in the outskirts, a common strategy is to densify existing neighbourhoods. Densification implies the increase of water impervious area which increases the vulnerability to flooding during extreme precipitation events. Sustainable urban drainage systems are considered as a strategy to handle stormwater runoff locally and thus relieve the sewage system. This study investigates the combined quantitative hydrological impact of densification and sustainable stormwater management measures in a residential neighbourhood in Munich, Germany. The living-lab approach pursues the application of nature-based solutions in a real planning case to achieve positive climate effects while densifying the neighbourhood. The study is based on single event simulations of three return periods with the physically based software PCSWMM. The events are implemented for both current and climate change precipitation intensities of the RCP 8.5 projection for 2040–2069. Three scenarios are implemented: a status quo, a business as usual scenario (additional buildings without compensation measures) and a best-case scenario (one additional floor with green roofs disconnected from the sewers in combination with rain gardens and porous pavements on the land parcels). The comparison between the different scenarios focuses on three main aspects of the water balance, namely, infiltration, runoff and storage. The results show that measures for sustainable stormwater management are crucial elements to cope with an increasing number of heavy precipitation events due to climate change. The best-case scenario significantly outperforms the other two concerning water infiltration, surface runoff and storage. Most notably is the impact of climate change projection rainfall intensities for 2040–2069. The outcomes for these intensities clearly show the positive impact of sustainable water-sensitive design. The results demonstrate that it is in fact possible to enhance the water balance and gain new living space simultaneously if a sustainable urban planning strategy is implemented that includes future-oriented stormwater management.
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