Three-dimensional model to capture the fate and transport of combined sewer overflow discharges: A case study in the Chicago Area Waterway System

Ecotoxicological assessment of sanitary sewer overflows and rainfall dynamics offers insights into conditions for potential adverse ecological outcomes

Sewer overflows are an environmental concern due to their potential to introduce contaminants that can adversely affect downstream aquatic ecosystems. As these overflows can occur during rainfall events, the influence of rainwater ingress from inflow and infiltration on raw untreated wastewater (influent) within the sewer is a critical factor influencing the dilution and toxicity of the contaminants. The Vineyard sewer carrier in the greater city of Sydney, Australia, was selected for an ecotoxicological investigation of a sanitary (separate from stormwater) sewerage system and a wet-weather overflow (WWO). Three influent samples were collected representing dry-weather (DW), intermediate wet-weather (IWW) and wet-weather (WW). In addition, a receiving water sample was also collected downstream in Vineyard Creek (WW-DS) coinciding with a WWO. We employed direct toxicity assessment (DTA) and toxicity identification evaluation (TIE) approaches to gain comprehensive insights into the nature and magnitude of the impact on influent from rainwater ingress into the sewer. Three standard ecotoxicological model species, a microalga, Chlorella vulgaris, the water flea, Ceriodaphnia dubia and the midge larva, Chironomus tepperi were used for both acute and chronic tests. The study revealed variable toxicity responses, with the sample of influent collected in wet-weather displaying lower toxicity compared to the dry-weather sample of influent. Ammonia, and metals, were identified in dry weather as contributors to the observed toxicity, however, this risk was alleviated through rainwater ingress in wet-weather with further dilution within the receiving water. Based on toxicity data, dilutions of influent to minimise effects on C. vulgaris and C. dubia ranged from 1 in 12 in DW to 1 in 2.8 in WW, and further diminished in the receiving water to 1 in 1.8. The successful application of ecotoxicological approaches enabled the assessment of cumulative effects of contaminants in influent, offering valuable insights into the sanitary sewer system under rainwater ingress.

Hybrid deep learning based prediction for water quality of plain watershed

Establishing a highly reliable and accurate water quality prediction model is critical for effective water environment management. However, enhancing the performance of these predictive models continues to pose challenges, especially in the plain watershed with complex hydraulic conditions. This study aims to evaluate the efficacy of three traditional machine learning models versus three deep learning models in predicting the water quality of plain river networks and to develop a novel hybrid deep learning model to further improve prediction accuracy. The performance of the proposed model was assessed under various input feature sets and data temporal frequencies. The findings indicated that deep learning models outperformed traditional machine learning models in handling complex time series data. Long Short-Term Memory (LSTM) models improved the R2 by approximately 29% and lowered the Root Mean Square Error (RMSE) by about 48.6% on average. The hybrid Bayes-LSTM-GRU (Gated Recurrent Unit) model significantly enhanced prediction accuracy, reducing the average RMSE by 18.1% compared to the single LSTM model. Models trained on feature-selected datasets exhibited superior performance compared to those trained on original datasets. Higher temporal frequencies of input data generally provide more useful information. However, in datasets with numerous abrupt changes, increasing the temporal interval proves beneficial. Overall, the proposed hybrid deep learning model demonstrates an efficient and cost-effective method for improving water quality prediction performance, showing significant potential for application in managing water quality in plain watershed.

Addressing the challenges of combined sewer overflows

Europe's ageing wastewater system often combines domestic sewage with surface runoff and industrial wastewaters. To reduce the associated risk of overloading wastewater treatment works during storms, and to prevent wastewater backing-up into properties, Combined Sewer Overflows (CSOs) are designed into wastewater networks to release excess discharge into rivers or coastal waters without treatment. In view of growing regulatory scrutiny and increasing public concern about their excessive discharge frequencies and potential impacts on environments and people, there is a need to better understand these impacts to allow prioritisation of cost-effective solutions.We review: i) the chemical, physical and biological composition of CSOs discharges; ii) spatio-temporal variations in the quantity, quality and load of overflows spilling into receiving waters; iii) the potential impacts on people, ecosystems and economies. Despite investigations illustrating the discharge frequency of CSOs, data on spill composition and loading of pollutants are too few to reach representative conclusions, particularly for emerging contaminants. Studies appraising impacts are also scarce, especially in contexts where there are multiple stressors affecting receiving waters. Given the costs of addressing CSOs problems, but also the likely long-term gains (e.g. economic stimulation as well as improvements to biodiversity, ecosystem services, public health and wellbeing), we highlight here the need to bolster these evidence gaps. We also advocate no-regrets options to alleviate CSO problems taking into consideration economic costs, carbon neutrality, ecosystem benefit and community well-being. Besides pragmatic, risk-based investment by utilities and local authorities to modernise wastewater systems, these include i) more systemic thinking, linking policy makers, consumers, utilities and regulators, to shift from local CSO issues to integrated catchment solutions with the aim of reducing contributions to wastewater from surface drainage and water consumption; ii) broader societal responsibilities for CSOs, for example through improved regulation, behavioural changes in water consumption and disposal of waste into wastewater networks, and iii) greater cost-sharing of wastewater use.

Quantifying the land and population risk of sewage spills overland using a fine-scale, DEM-based GIS model

Accidental releases of untreated sewage into the environment, known as sewage spills, may cause adverse gastrointestinal stress to exposed populations, especially in young, elderly, or immune-compromised individuals. In addition to human pathogens, untreated sewage contains high levels of micropollutants, organic matter, nitrogen, and phosphorus, potentially resulting in aquatic ecosystem impacts such as algal blooms, depleted oxygen, and fish kills in spill-impacted waterways. Our Geographic Information System (GIS) model, Spill Footprint Exposure Risk (SFER) integrates fine-scale elevation data (1/3 arc-second) with flowpath tracing methods to estimate the expected overland pathways of sewage spills and the locations where they are likely to pool. The SFER model can be integrated with secondary measures tailored to the unique needs of decision-makers so they can assess spatially potential exposure risk. To illustrate avenues to assess risk, we developed risk measures for land and population health. The land risk of sewage spills is calculated for subwatershed regions by computing the proportion of the subwatershed's area that is affected by one modeled footprint. The population health risk is assessed by computing the estimated number of individuals who are within the modeled footprint using fine-scale (90 square meters) population estimates data from LandScan USA. In the results, with a focus on the Atlanta metropolitan region, potential strategies to combine these risk measures with the SFER model are outlined to identify specific areas for intervention.

Incorporating carbon sequestration into lake management: A potential perspective on climate change

Exploring the carbon sequestration capacity of water ecosystems would contribute to coping with climate change. This study conducted an integrated method framework to achieve an improved understanding of the relationship between carbon sequestration and lake ecosystem components, as well as provide a new perspective on climate change for policymakers. The vertically generalized production model revealed the carbon sequestration capacity of lakes. The hierarchical linear model identified the cross-scale factors affecting phytoplankton. Then a developed multi-agents-based model with scenario analysis provided adaptive management strategies for carbon sequestration. Furthermore, we applied the integrated framework in the 63 polluted lakes of Wuhan. The results showed that the average carbon sequestration per unit area was at 0.87 kgC·m-2·a-1, which was greater than that of the ocean and forest ecosystems, indicating that the lakes had a potential capacity for carbon sequestration. Total phosphorus had the strongest effect on the Chl-a (chlorophyll a) concentration (fixed effect (γ) =6.82, P < 0.1), followed by total nitrogen (γ = 6.38, P < 0.05), Rotifer biomass (γ = 1.95, P < 0.01) and water temperature (γ = 1.27, P < 0.05). These results indicated that the bottom-up effect of chemical factors on phytoplankton was greater than the top-down effect of zooplankton. The proportion of grassland at the whole-lakes level would have a negative synergistic impact on the Chl-a with changing the micro water temperature at the part-lakes level (γ = -46.64, P < 0.05). There was no significant interaction effect between land cover change and total nitrogen (phosphorus) on the Chl-a. Therefore, we could indirectly confirm that point source pollution emissions would synergistically affect the Chl-a and carbon sequestration along with the effects of physical-chemical conditions. The coordinated proportional control of nitrogen and phosphorus and the artificial controlling biomass of zooplankton-feeding fish were proposed to improve carbon sequestration and water quality for lake management.

Tracking contaminants of concern in wet-weather sanitary sewer overflows

Four representative sites in the greater city of Sydney, Australia, were selected for a study of the wet-weather overflow of sanitary (separate to stormwater) sewerage systems. Water samples were collected by autosamplers from up to eight wet weather overflow events over 16 months and from companion receiving water sites. The objective was to identify the risks posed by sewage contaminants to aquatic biota in the receiving waters, to aid in prioritising management actions. Twelve organic contaminants were identified in influents across the four sites under rainfall ingress diluted conditions, with measurements showing that the highest concentrations were restricted to the anti-inflammatory acetaminophen and the diabetes medication metformin. Lesser contaminants included theobromine, ibuprofen, sucralose, and three benzotriazoles (mainly 1-H benzotriazole). An assessment of the toxicity of the identified organic chemicals indicated that none appeared to pose concerns for ecosystem health before wet-weather ingress dilution, and this was even less likely after dilution in the receiving waters. Metal concentrations were low; however, ammonia concentrations in the influent did pose a risk to ecosystem health, although receiving water dilution diminished this risk at four of the five receiving water locations studied.

Deterministic and probabilistic modeling of microbiological quality using the QUAL-UFMG: a water resource management tool applied on the slope waters of the Grande River, Brazil

The present work presents a methodology for modeling the quality of surface water, aiming at the management of hydrographic basins and the best allocation of resources in the treatment of sanitary sewage, considering the predominant uses of water and microbiological quality. The QUAL-UFMG model was used, composed of Excel spreadsheets, where visual basic for applications (VBA) routines were implemented, enabling deterministic and probabilistic modeling through Monte Carlo simulations. The proposed methodology was applied to a Brazilian hydrographic basin, called the GD2 Planning Unit (Grande River Slopes), considering the discharges of sanitary sewage from 30 municipal seats and approximately 740,000 inhabitants. Four scenarios were studied: the current situation (C-01), the trend for the year 2033 (C-02), compliance with environmental legislation (C-03) and compliance with the main uses of the basin (C-04). The results showed that for C-01 and C-02, the water quality, in terms of thermotolerant coliforms, in most stretches does not meet the defined uses. Even complying with the provisions of environmental legislation (C-03), which do not provide for disinfection, only the largest watercourses would have adequate quality for use. Complete service would only be achieved in C-04, which provides for universal sewage treatment with disinfection for the vast majority of municipalities.

Investigating the impact of sewer overflow on the environment: A comprehensive literature review paper

Sewer networks play a pivotal role in our everyday lives by transporting the stormwater and urban sewage away from the urban areas. In this regard, Sewer Overflow (SO) has been considered as a detrimental threat to our environment and health, which results from the wastewater discharge into the environment. In order to grapple with such deleterious phenomenon, numerous studies have been conducted; however, there has not been any review paper that provides the researchers undertaking research in this area with the following inclusive picture: (1) detailed-scientometric analysis of the research undertaken hitherto, (2) the types of methodologies used in the previous studies, (3) the aspects of environment impacted by the SO occurrence, and (4) the gaps existing in the relative literature together with the potential future works to be undertaken. Based on the comprehensive review undertaken, it is observed that simulation and artificial intelligence-based methods have been the most popular approaches. In addition, it has come to the attention that the detrimental impacts associated with the SO are fourfold as follows: air, quality of water, soil, and business and structure. Among these, the majority of the studies' focus have been tilted towards the impact of SO on the quality of ground water. The outcomes of this state-of-the-art review provides the researchers and environmental engineers with inclusive hindsight in dealing with such serious issue, which in turn, this culminates in a significant improvement in our environment as well as humans' well-beings.

Impact of sewer overflow on public health: A comprehensive scientometric analysis and systematic review

Sewer overflow (SO), which has attracted global attention, poses serious threat to public health and ecosystem. SO impacts public health via consumption of contaminated drinking water, aerosolization of pathogens, food-chain transmission, and direct contact with fecally-polluted rivers and beach sediments during recreation. However, no study has attempted to map the linkage between SO and public health including Covid-19 using scientometric analysis and systematic review of literature. Results showed that only few countries were actively involved in SO research in relation to public health. Furthermore, there are renewed calls to scale up environmental surveillance to safeguard public health. To safeguard public health, it is important for public health authorities to optimize water and wastewater treatment plants and improve building ventilation and plumbing systems to minimize pathogen transmission within buildings and transportation systems. In addition, health authorities should formulate appropriate policies that can enhance environmental surveillance and facilitate real-time monitoring of sewer overflow. Increased public awareness on strict personal hygiene and point-of-use-water-treatment such as boiling drinking water will go a long way to safeguard public health. Ecotoxicological studies and health risk assessment of exposure to pathogens via different transmission routes is also required to appropriately inform the use of lockdowns, minimize their socio-economic impact and guide evidence-based welfare/social policy interventions. Soft infrastructures, optimized sewer maintenance and prescreening of sewer overflow are recommended to reduce stormwater burden on wastewater treatment plant, curtail pathogen transmission and marine plastic pollution. Comprehensive, integrated surveillance and global collaborative efforts are important to curtail on-going Covid-19 pandemic and improve resilience against future pandemics.

Catchment-wide validated assessment of combined sewer overflows (CSOs) in a mediterranean coastal area and possible disinfection methods to mitigate microbial contamination

The first phase of this study aimed to evaluate the environmental impact of combined sewer overflow (CSO) events originated from 35 spillways on the Rio Vallescura catchment (Central Italy) and to understand their contribution to the deterioration of the coastal bathing water quality. A specific analytical campaign was carried out in the sewer system and a dynamic rainfall-runoff simulation model was developed and integrated with a water quality model and further validated. The simulations led to identify the most critical spills in terms of flow rate and selected pollutant loads (i.e. suspended solids, biochemical oxygen demand, chemical oxygen demand, total Kjeldahl nitrogen, Escherichia coli). Specifically, the E. coli release in the water body due to CSO events represented almost 100% of the different pollutant sources considered. In the second phase, the applicability of various disinfection methods was investigated on the CSOs introduced into the catchment. On site physical (UV) and lab-scale chemical (peracetic acid (PAA), performic acid (PFA), ozone) disinfectant agents were tested on microbial indicators including E. coli and intestinal enterococci. PFA and ozone were more effective on the removal of both bacteria (above 3.5 log units) even at low concentration and with short contact time; whereas, PAA showed a moderate removal efficiency (around 2.5 log units) only for E. coli. The highest removal efficiency was achieved in the on-site UV unit and none of the indicator bacteria was detected in the final effluent after the sand filtration and UV treatment. Finally, potential scenarios were developed in comparison to the baseline scenario for the management and treatment of CSOs where a mitigation of E. coli loads from 28% to 73% was achieved on the receiving water body, and a comparative cost assessment of the disinfection methods was provided for in situ treatment of the most critical spillway.

Management of water quality targets based on river-lake water quality response relationships for lake basins - A case study of Dianchi Lake

In a lake basin, there is a mismatch between river and lake water quality targets and a method for setting specific water quality targets for these rivers is urgently needed. Using Dianchi Lake as an example, we proposed a lake basin water quality management system based on the river-lake water quality response relationship, coupled with a Soil and Water Assessment Tool (SWAT) basin hydrological model and Environmental Fluid Dynamics Code (EFDC) lake water quality hydrodynamic model. River water quality control requirements based on the river-lake water quality response were proposed, under the premise that the Dianchi Lake water quality reaches the required standard. Then, water quality control targets for rivers were determined, and corrected for influencing factors, such as current river water quality and composition of flow. Our systematic approach efficiently identified key lake basin pollution sources, and accurately located key points for water quality improvement and pollution control. Combined with a correction for clean water source and current water quality of each river, the proposed water quality targets were practical and operable. Meanwhile, the EFDC model was used to verify the entire process to ensure that river water quality targets could be set to achieve lake water quality targets. To ensure that Dianchi Lake water quality can reach Class IV standard, the Chemical oxygen demand (COD) concentration would need to be maintained under 30 mg/L,Waihai total nitrogen (TN) below 7 mg/L, total phosphorus (TP) below 0.2 mg/L, and ammonia nitrogen (NH₃-N) below 2 mg/L.

Applicability of water quality models around the world-a review

Water quality models are important tools used in the management of water resources. The models are usually developed for specific regions, with particular climates and physical characteristics. Thus, applying these models in regions other than those they were designed for can generate large simulation errors. With consideration to these discrepancies, the goal of this study is to identify the models employed in different countries and assist researchers in the selection of the most appropriate models for management purposes. Published studies from the last 21 years (1997-2017) that discuss the application of water quality models were selected from three engineering databases: SpringerLink, Web of Science, and Scopus. Seven models for water quality simulations have been widely applied around the world: AQUATOX, CE-QUAL-W2, EFDC, QUALs, SWAT, SPARROW, and WASP. The countries most frequently applying water quality models are the USA, followed by China, and South Korea. SWAT was the most used model, followed by the QUAL group and CE-QUAL-W2. This study provides the opportunity for researchers, who wish to study countries with fewer cases of applied water quality models, to easily identify the work from that region. Furthermore, this work collated central themes of interest and the most simulated parameters for the seven countries that most frequently employed the water quality models.

Spatial variations of pollutants from sewer interception system overflow

Sewer interception systems have been built along rivers in rapidly urbanizing areas to collect unregulated sewage discharges due to misconnections between storm sewers and sanitary sewers. During storm events, combined sewage might overflow from these systems into rivers through orifices and deteriorate water quality in rivers. Interception system overflows (ISOs) from different orifices in a sewer interception system might interact with each other, therefore pollutants from ISOs show a spatial variation. This paper aims to understand the spatial variation of pollutants from ISOs for informed decision making. In this study, an urbanized catchment in China is chosen as the study area, and the Storm Water Management Model (SWMM) is used to examine the spatial variation of pollutants from ISOs and to analyze the effect of sewer separation on ISOs. The results obtained from the case study indicate that: (1) Critical rainfall amounts which trigger overflows decrease downstream in an interception system while annual ISO volumes and pollutant loads from ISOs increase downstream; additionally, these variations are influenced by sizes and slopes of interceptors; (2) Runoff is the main source of COD from ISOs while sewage is the main source of NH₃-N, and ratios of pollutants from sewage to ISOs increase downstream; (3) Sewer separation can significantly reduce pollutant loads from sewage to ISOs, but it cannot significantly reduce pollutant loads from runoff. In order to mitigate ISO pollution, it is suggested to increase conveyance capacities of interceptors in the downstream, separate sewage from runoff, and promote source control for urban runoff in highly urbanized areas.

Temporal Variation and Reduction Strategy of Nutrient Loads from an Urban River Catchment into a Eutrophic Lake, China

Excessive nutrient input from urban areas increases the occurrence of eutrophication. Control of nutrient loads is perceived as the primary restoration method. Quantifying temporal variation of nutrient loads is essential to understand the dynamic relationships of nutrient source-impacts in the urban water system and investigate the operational efficiency of treatment facilities for eutrophication control. Here, a holistic approach was developed to estimate nutrient loads from different sources and evaluate nutrient impacts on the urban water environment. An integrated catchment model of nutrient loads was built and applied to calculate river nutrient loads from untreated rainfall runoff, untreated sewage, and treated recharge into the eutrophic Dianchi Lake from an urban river catchment with limited infrastructure. Nutrient impacts on the lake were evaluated and a load reduction strategy was given a hint to reduce nutrient impacts of urban rivers. During the study period 2014–2016, nutrient loads from the urban river generally decreased except during heavy winter rainfall events and high-intensity pollution events associated with rainfall runoff. The average contribution of annual nutrient loads to the lake capacity indicated the underestimation of nutrient impacts of urban rivers. This approach provides new insights into urban water management and underscores the importance of sewage infrastructure.

Distribution and fate modeling of 4-nonylphenol, 4-t-octylphenol, and bisphenol A in the Yong River of China

In this study, the concentrations of 4-nonylphenol (4-NP), 4-tert-octylphenol (4-t-OP), and bisphenol A (BPA) in the water column of the Yong River were investigated and found to be in the range of 140-3948, 6-828, and 15-1415 ng L^-1, respectively. A fate and transport model coupled with the Water Quality Analysis Simulation Program (WASP) was developed. After model calibration and validation, the distributions of 4-NP, 4-t-OP, and BPA in the Yong River were modeled for the duration of 2015. The total contaminant loads from the upstream boundary, four tributaries and two wastewater treatment plants were determined to be 2318 kg yr^-1 for 4-NP, 506 kg yr^-1 for 4-t-OP, and 970 kg yr^-1 for BPA. Both measured and modeled results reported higher concentrations of the selected contaminants near river confluences and at the outfalls of the wastewater treatment plants. Peak concentrations were found to always appear in months with relatively reduced precipitation. The influences of adsorption and degradation on the dissolved concentrations of the selected chemicals were also modeled. The combined effects of adsorption and degradation were found to reduce dissolved concentrations of 4-NP, 4-t-OP, and BPA by 17.9%, 30.7%, and 12.1%, respectively. Adsorption was shown to reduce 4-NP concentrations in the Yong River more than degradation. Conversely, adsorption and degradation caused almost equal reductions in the dissolved concentrations of 4-t-OP and degradation caused larger decreases than adsorption in the dissolved concentrations of BPA.

A Fusion Water Quality Soft-Sensing Method Based on WASP Model and Its Application in Water Eutrophication Evaluation

Water environment protection is of great significance for both economic development and improvement of people’s livelihood, where modeling of water environment evolution is indispensable in water quality analysis. However, many water quality indexes related to water quality model cannot be measured online, and some model parameters always vary among different water areas. Thus, this paper proposes a water quality soft-sensing method based on the water quality mechanism model to simulate evolution of water quality indexes online, where unscented Kalman filter is utilized to estimate model parameters. Furthermore, a modified fuzzy comprehensive evaluation method is presented to evaluate the level of water eutrophication condition. Finally, the water quality data collected from Taihu Lake and Beihai Lake are used to validate the effectiveness and generality of the proposed method. The results show that the proposed soft-sensing method is able to describe the variation of related water quality indexes, with better accuracy compared to nonlinear least squares based method and traditional trial-and-error based method. On this basis, the water eutrophication condition can be also accurately evaluated.

Sources of nitrogen and phosphorus emissions to Irish rivers and coastal waters: Estimates from a nutrient load apportionment framework

More than half of surface water bodies in Europe are at less than good ecological status according to Water Framework Directive assessments, and diffuse pollution from agriculture remains a major, but not the only, cause of this poor performance. Agri-environmental policy and land management practices have, in many areas, reduced nutrient emissions to water. However, additional measures may be required in Ireland to further decouple the relationship between agricultural productivity and emissions to water, which is of vital importance given on-going agricultural intensification. The Source Load Apportionment Model (SLAM) framework characterises sources of phosphorus (P) and nitrogen (N) emissions to water at a range of scales from sub-catchment to national. The SLAM synthesises land use and physical characteristics to predict emissions from point (wastewater, industry discharges and septic tank systems) and diffuse sources (agriculture, forestry, etc.). The predicted annual nutrient emissions were assessed against monitoring data for 16 major river catchments covering 50% of the area of Ireland. At national scale, results indicate that total average annual emissions to surface water in Ireland are over 2700tyr^-1 of P and 82,000tyr^-1 of N. The proportional contributions from individual sources show that the main sources of P are from municipal wastewater treatment plants and agriculture, with wide variations across the country related to local anthropogenic pressures and the hydrogeological setting. Agriculture is the main source of N emissions to water across all regions of Ireland. These policy-relevant results synthesised large amounts of information in order to identify the dominant sources of nutrients at regional and local scales, contributing to the national nutrient risk assessment of Irish water bodies.