Sewer Overflows Research Articles

Sewer subsidies from overflows and pipe leaks dominate urban stream solute loads in all storm events

Stream channel burial drastically alters watershed flowpaths by routing surface waters underground and increasing the potential for interactions between stream water and urban infrastructure such as storm and sanitary sewers. While numerous studies have investigated storm event solute loads from urban watersheds, the influences of stream channel burial and sewer overflows are often overlooked. This study uses grab samples and natural abundance stable isotope tracers to quantify the event dynamics of solute concentration-discharge relationships as well as cumulative loads in a buried urban stream. Our results demonstrate that different solutes, as well as different sources of the same solute (atmospheric NO3− and sewer-derived NO3− differentiated by the Δ17O tracer), are delivered via separate watershed flowpaths and thus have different timings within the event and contrasting relationships to flow. This inter-event variability reveals dynamics that result from temporal and spatial heterogeneity in infiltration, exfiltration, and pipe overflows. These results can help guide system-wide infrastructure maintenance as cities seek to meet challenges in sustaining and improving water quality as infrastructural systems age.

Analysis of (Anti-)Oestrogenic and (Anti-)Androgenic Activities in Wastewater from the Lodz Sewer System

This article presents the results of a study on the oestrogenicity and androgenicity of urban wastewater in Lodz, and the possibility of their removal by the Group Wastewater Treatment Plant (GWWTP). Wastewater samples were taken at five points of the sewer system in the city and at the inlet and outlet of the GWWTP. The study was conducted using Yeast Oestrogen Screen (YES)/Yeast Androgen Screen (YAS) tests, which allow a general assessment of the content of compounds with (anti-)oestrogenic and (anti-)androgenic effects in wastewater, without identifying specific substances. Wastewater samples taken from the sewage network did not show (anti-)oestrogenic activity, while oestrogenic and antagonistic properties to androgens were detected in most of them. In the influent of the treatment plant, oestrogen agonistic activity was detected only in one sample (oestrogen equivalent—EEQ equal to 1.31 × 105 ng 17 β–oestradiol/L) and was 100% removed. The purification efficiencies in GWWTP for oestrogen and androgen antagonistic activity were 51.5–99.2% and 39.4–47.1%, respectively. Although no oestrogenic activity was detected in general wastewater in Lodz, observed high-antagonistic–androgenic activities may adversely affect the water body and cause, among others, the feminization of fish, especially in the case of discharge of untreated wastewater by combined sewer overflows.

Persistence of MRSA and ESBL-producing E. coli and K. oxytoca in river water

Due to climate change precipitation patterns are changing in terms of frequency and quantity in Germany. As a result, prolonged dry weather can lead to extremely low flow rates in river systems with large portions of treated wastewater. However, storm events and heavy rainfall events are increasing too, which may lead to higher frequencies of combined sewer overflows. Increased microbial pollution (e.g. coliform bacteria, clostridia, faecal streptococci) of waterbodies after heavy precipitation events was demonstrated in several studies. Pathogenic multi-resistant bacteria enter waterbodies via sewer systems. The persistence potential of such pathogens in aquatic environments is mainly still unknown. This study investigated the growth behaviour of Gram-negative extended spectrum beta-Lactamase-producing Klebsiella oxytoca and Escherichia coli and Gram-positive methicillin-resistant Staphylococcus aureus in river water. The concentrations of these antibiotic-resistant bacteria were monitored in batch experiments using river water differently impacted by wastewater. Staphylococcus aureus persisted for at least 3 days at incubation temperatures of 8 and 18 °C. The persistence of K. oxytoca and E. coli was shown for at least 37 days at both temperatures. In the river water at 8 °C, bacteria concentrations decreased slower, suggesting diminished persistence of ARB (antibiotic-resistant bacteria) with increasing temperatures. Initial concentrations of ARB and other pathogens in river water corresponded to the impact of wastewater. However, significant effects on the persistence itself by wastewater impact could not be shown for the bacteria species tested. Further studies should pursue our approaches concerning the persistence of pathogenic ARB in freshwater to assess the health risk for humans and animals.

Prototyping an integrated IoT-based real-time sewer monitoring system using low-power sensors

Improper monitoring of sewage networks may raise various issues such as overflows, pipe blockages, theft of manhole covers, leading to flooding and pollution, infrastructure damage, vehicles accidents, injury, and even death from falling into open manholes. The key objective of this research was to examine different elements and create a prototype architecture for a real-time sewer monitoring system. Implementation of the architecture involved constructing a data gathering station and experimenting with various wireless sensing devices to assess the precision of the sensors. In addition, the study sought to design a geographic information system that integrates algorithms capable of identifying sewer overflow, blocked pipes, and the presence of manhole covers. The performance of Sharp GP2Y0A41SK0F infrared, TF-Luna Benewake LiDar, TOF400 VL53L1X laser, JSN-SR04T ultrasonic distance sensors was tested in terms of their ability to monitor water level and manhole cover. Tests revealed the most favorable results in TOF400 VL53L1X at distances between 0.2 and 1.0 m (presumed distance to the manhole cover) with a standard deviation of 0.13–0.24, and in TF-Luna Benewake at distances between 1.0 and 5.0 m (presumed distance to the chamber bottom) with a standard deviation of 0.44–1.15. The deviation analysis has yielded equations that can be utilized to provide rough estimates of the accuracy levels of the aforementioned sensors, based on the measured distance. Additionally, the FC-28 analog and YL-63 infrared sensors were evaluated for detecting pipe blockages, with the YL-63 being more suitable. The outcomes of this study furnish valuable insights that can aid in achieving sustainable resolutions for issues related to sewer monitoring

Proximity to Combined Sewer Overflow-Impacted Waters in Philadelphia: A Geographic Information Systems Study to Explore Environmental Injustice

Background: Recreating in waterbodies impacted by combined sewer overflows (CSOs) can present health risks due to exposure to microbial pathogens. This study compares population characteristics of those living within walking distance to CSO-impacted versus nonimpacted waters in Philadelphia to determine whether these populations differ by race, ethnicity, and sociodemographic characteristics. Methods: Adults recreating at or near natural water bodies in Philadelphia completed a questionnaire that assessed the average walking distance to each site. Walking distance boundaries informed by questionnaire responses were created around each waterbody in Philadelphia, and population-level census data corresponding with block groups included within each buffer were used to characterize those living near a CSO-impacted and nonimpacted waterbodies in Philadelphia. Results: Compared with populations residing in census block groups within walking distance to a nonimpacted waterway, populations living within the same distance to a CSO-impacted waterway were more likely to comprise Hispanic residents (standardized adjusted prevalence ratio [APR] = 1.13) and those living in poverty (APR = 1.21) and less likely to comprise White residents (APR = 0.76). Conclusion: These findings suggest that communities of color and those experiencing poverty are disproportionally impacted by environmental hazards.

Evaluation of the adsorption characteristics of dissolved organic matter using granular activated carbon (GAC) and the regeneration efficiency of denitrification, Electro-Fenton, and Sono-Fenton oxidation

This research explored the use of a granular activated carbon (GAC) column to treat dissolved organics in Combined Sewer Overflows (CSOs), a major river pollutant. The regeneration efficiency of spent GAC was assessed utilizing three distinct methods: biological denitrification, electro-Fenton oxidation, and Sono-Fenton oxidation. Among the six organics tested, sucrose and raw sewage demonstrated the most comparable adsorption characteristics. GAC adsorption factors are multifaceted, involving pore size, surface functional groups, and competing solution substances, rather than just organic matter hydrophobicity. The biological denitrification enabled the utilization of the adsorbed organic matter on spent GAC, consequently reducing the initial NO3-N concentration from 99 mg/L to 8 mg/L over a period of 48 hours. Electro-Fenton treatment revealed marginal performance differences between SUS-SUS and Ti/Pt-Ti/Pt; however, the latter proved superior in terms of electrode stability over prolonged use. A combined strategy employing ultrasound and Fenton treatment at a frequency of 40 kHz yielded marginally higher GAC regeneration efficiency (68.5%) as compared to that at 750 kHz (67.8%). Among all regeneration techniques applied in this investigation, the Sono-Fenton method showed the highest efficiency.

Denitrification Potential of Surface Soils of Constructed Wetlands in Newtown Creek, an Urban Superfund Site.

Denitrification, the anaerobic microbial conversion of nitrate (NO3 - ), a common water pollutant, to nitrogen (N) gases, is often high in the soil of natural wetlands. In areas where natural wetlands have been degraded or destroyed, constructed and restored wetlands have been used to restore ecosystem services like denitrification. Thus, denitrification in restored and constructed wetlands could play an important role in treating anthropogenic N sources such as combined sewer overflow (CSO) discharges which can be high in NO3 - . In this study, we measured denitrification potential using an anaerobic slurry assay and made a suite of ancillary measurements (soil moisture content, microbial biomass carbon (C) and N content, potential net N mineralization and nitrification, soil inorganic N pools and soil respiration) in four constructed salt marsh wetlands, and a series of wetland habitat basins in Newtown Creek, NY, an urban superfund site. Samples were also taken from natural salt marshes located at Paerdegat Basin, Jamaica Bay, NY. Our results show that constructed Spartina alterniflora marshes in ultra-urban Newtown Creek support denitrification potential equivalent to rates of natural marshes in Jamaica Bay and reference marshes in other urban estuaries. There were significant positive correlations between microbial biomass C and N content and organic matter content and denitrification potential. Results suggest that constructed wetlandscan support wetland vegetation, soils, and microbial life and contribute to N removal under ultra-urban conditions. This article is protected by copyright. All rights reserved.

Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors.

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

On Optimizing the Conditional Value-at-Risk of a Maximum Cost for Risk-Averse Safety Analysis

The popularity of Conditional Value-at-Risk (CVaR), a risk functional from finance, has been growing in the control systems community due to its intuitive interpretation and axiomatic foundation. We consider a nonstandard optimal control problem in which the goal is to minimize the CVaR of a maximum random cost subject to a Borel-space Markov decision process. The objective represents the maximum departure from a desired operating region averaged over a given fraction of the worst cases. This problem provides a safety criterion for a stochastic system that is informed by both the <i>probability</i> and <i>severity</i> of the potential consequences of the system&#x0027;s behavior. In contrast, existing safety analysis frameworks apply stage-wise risk constraints or assess the probability of constraint violation without quantifying the potential severity of the violation. To the best of our knowledge, the problem of interest has not been solved. To solve the problem, we propose and study a family of stochastic dynamic programs on an augmented state space. We prove that the optimal CVaR of a maximum random cost enjoys an equivalent representation in terms of the solutions to these dynamic programs under appropriate assumptions. For each dynamic program, we show the existence of an optimal policy that depends on the dynamics of an augmented state under the assumptions. In a numerical example, we illustrate how our safety analysis framework is useful for assessing the severity of combined sewer overflows under precipitation uncertainty.

Deep learning's fitness for purpose: A transformation problem frame's perspective

AbstractCombined sewer overflows represent significant risks to human health as untreated water is discharged to the environment. Municipalities, such as the Metropolitan Sewer District of Greater Cincinnati (MSDGC), recently began collecting large amounts of water‐related data and considering the adoption of deep learning (DL) solutions like recurrent neural network (RNN) for predicting overflow events. Clearly, assessing the DL's fitness for the purpose requires a systematic understanding of the problem context. In this study, we propose a requirements engineering framework that uses the problem frames to identify and structure the stakeholder concerns, analyses the physical situations in which the high‐quality data assumptions may not hold, and derives the software testing criteria in the form of metamorphic relations that incorporate both input transformations and output comparisons. Applying our framework to MSDGC's overflow prediction problem enables a principled way to evaluate different RNN solutions in meeting the requirements.

A simplified approach for the hydrological simulation of urban drainage systems with SWMM

The management of an Urban Drainage System (UDS) is a complex task, as it requires extensive knowledge about precipitation regime, hydrological features of the catchment, hydraulic characteristics of the drainage network, and information about the water use by the served inhabitants. Complex semi-distributed hydrological and physically based hydraulic models are nowadays available to summarise such information and run simulations. However, in many cases, the uncertainty of the available hydrological information hampers the use of complex models. Hence, simple models with few parameters and small computational effort may be preferable, especially for UDS management problems requiring the execution of many simulations. This paper proposes a convenient approach to define effective lumped Simplified Models (SMs) of UDSs, the parameters of which can be estimated directly from cartographic information. For several case studies of UDS with different morphological and topological characteristics, SMs were built, capable of reproducing the hydrographs provided by available semi-distributed Detailed Models (DMs), assumed as benchmark in absence of measured hydrographs. To this aim, the SWMM simulation software was used, and the SM lumped parameters were calibrated by maximising the goodness of fit between the hydrograph of the DM and of the SM. The results show that SMs satisfactorily predict the hydrographs for all the case studies, and that robust relationships between the calibrated parameters and morphological and topological characteristics of the UDS can be established. This suggests that SMs can be used by decision makers for preliminary design, planning studies and management problems of UDSs, as their parameters can be soundly estimated from cartographic information. An example of application of SMs to Combined Sewer Overflow prediction is also presented.

The impact of stormwater management strategies on the flow regime of a peri-urban catchment facing urbanisation and climate change: a distributed modelling study in Lyon, France

ABSTRACT The relative impact of urbanisation (urban sprawl), climate change (rainfall and evapotranspiration) and stormwater disconnection strategies (implementation of green infrastructure (GI)) on a peri-urban stream in the western suburbs of Lyon, France, was investigated using a distributed, physically based model (J2000P). Results showed that ambitious catchment-scale implementation of GI has the potential to mitigate some hydrological effects of urbanisation, especially a drastic reduction of combined sewer overflows. However, GI did not have a large impact on the stream flow regime, especially in the context of climate change, as the stream is dominated by non-urban contributions. Spatially distributed models have the capacity to inform river managers about the extent of implementation of GI needed to achieve given management goals and highlight some limitations of disconnection strategies. Indeed, while GI improved the resilience of sewer networks to global change, it was not sufficient to compensate for the effects of climate change on streamflow.

Constructed wetlands for the treatment of combined sewer overflow upstream of centralized wastewater treatment plants

Combined sewer overflows (CSOs) constitute nowadays a major environmental concern, representing one of the main untreated sources of pollution for receiving water bodies. Additional, in recent years, the frequency and intensity of CSOs have increased due to the growing urbanisation and climate change. Although there is no single effective strategy, one of the most promising approaches for the control and treatment of CSOs can be found in nature-based solutions (NBS), such as constructed wetlands (CWs). Despite the demonstrated potential of CWs to treat CSOs, the only data reported in the literature refer to CSO-CW systems located along the sewerage network. This research represents, to the best of our knowledge, the first monitoring of a full-scale CSO-CW designed to treat the combined sewer overflow upstream of the WWTP located in Carimate, in the province of Como (Italy). The system is a multistage CW, composed by a 1st vertical subsurface flow (VF) stage (total area of 8500 m2) and a 2nd free water surface (FWS) stage (total area of 4500 m2). The observed removal rates during the 3 years monitoring campaign (mean values equal to 83.2%, 64.6%, 63.8% for COD, TP, and N-NH4+ respectively) confirmed the treatment efficiency of CW system for all the investigated parameters, consistent with literature data for CSO-CWs in line with the sewerage network, despite its large scale and different hydraulic characteristics. Furthermore, the system also provides additional ecosystem services such as flood mitigation (average CSO interception of 82%), enhancement of biodiversity and a low operational and maintenance cost.

Comparative study of deterministic and probabilistic assessments of microbial risk associated with combined sewer overflows upstream of drinking water intakes

Combined sewer overflows (CSOs) are a source of microbial contamination of drinking water intakes located downstream from their discharge. To safeguard the quality of the source water, it is essential to evaluate the risk levels associated with these municipal structures. This study compares two risk assessment approaches to test their applicability for assessing the risk of CSOs to drinking water intakes in a highly urbanized watershed. The first approach was based on a deterministic equation that combines the characteristics of an overflow structure allowing the risk to be rated as very low, low, medium, high, or very high. The second probabilistic risk assessment approach yielded findings that are probabilistically distributed across the five levels of risk. This approach was developed by constructing a novel Bayesian network to probabilistically link the different factors defining the exposure of water intakes to the hazards of CSOs. The comparison between the results of these two approaches highlighted the importance of simultaneously considering many scenarios for assessing the risk of contamination of source waters. It was possible to use the Bayesian network rather than the deterministic equation, which only supports one scenario at a time. It was also shown that the deterministic approach often overestimated risk levels for CSO outfalls close to the water intake. This occurred because the assessment process emphasized the distance factor between the discharge point and the water intake, while neglecting other crucial characteristics of the overflow, such as duration and frequency. In particular, the deterministic approach tended to underestimate risk for CSOs associated with low overflow frequencies as it did not support scenarios of overflow duration, unlike the probabilistic approach. The validation and sensitivity analysis of the Bayesian model revealed that the population residing in the CSO's drainage basin, along with the frequency and duration of the overflows, exerted the greatest influence on the resulting risk levels. These factors outweighed other variables utilized in the risk assessment, including vulnerability of the drinking water intake, the type of overflow recorder, pipe diameter, and variables defining the exposure of the water intake to the discharge. In the context of implementing action plans, the Bayesian network is estimated as a cost-effective technique as it prioritized overflow structures needing special attention in a highly urbanized watershed, where the same CSOs were deterministically rated as having the same risk level. The results also demonstrated the effectiveness of the Bayesian model in addressing data gaps faced by water managers and stakeholders. The Bayesian model proved capable of assessing risks with uncertainties for CSOs, even with limited input data available. These findings can assist managers in identifying problematic structures by considering various scenarios, unlike the deterministic approach, which left almost half (n = 42) of the study site's overflow structures unassessed due to data limitations.

Environmental DNA clarifies impacts of combined sewer overflows on the bacteriology of an urban river and resulting risks to public health

There is no reference of microbiological water quality in the European Union's Water Framework Directive, adapted into English law, and consequently microbial water quality is not routinely monitored in English rivers, except for two recently designated bathing water sites. To address this knowledge gap, we developed an innovative monitoring approach for quantitative assessment of combined sewer overflow (CSO) impacts on the bacteriology of receiving rivers. Our approach combines conventional and environmental DNA (eDNA) based methods to generate multiple lines of evidence for assessing risks to public health. We demonstrated this approach by investigating spatiotemporal variation in the bacteriology of the Ouseburn in northeast England for different weather conditions in the summer and early autumn of the year 2021 across eight sampling locations that comprised rural, urban, and recreational land use settings. We characterized pollution source attributes by collecting sewage from treatment works and CSO discharge at the peak of a storm event. CSO discharge was characterized by log10 values per 100 mL (average ± stdev) of 5.12 ± 0.03 and 4.90 ± 0.03 for faecal coliforms and faecal streptococci, and 6.00 ± 0.11 and 7.78 ± 0.04 for rodA and HF183 genetic markers, for E. coli and human host associated Bacteroides, respectively, indicating about 5 % sewage content. SourceTracker analysis of sequencing data attributed 72–77 % of bacteria in the downstream section of the river during a storm event to CSO discharge sources, versus only 4–6 % to rural upstream sources. Data from sixteen summer sampling events in a public park exceeded various guideline values for recreational water quality. Quantitative microbial risk assessment (QMRA) predicted a median and 95th percentile risk of 0.03 and 0.39, respectively, of contracting a bacterial gastrointestinal disease when wading and splashing around in the Ouseburn. We show clearly why microbial water quality should be monitored where rivers flow through public parks, irrespective of their bathing water designation.

Evaluating the sensory and health impacts of exposure to sewer overflows on urban population

Sewer overflow contains several hazardous contaminants causing adverse health effects and annoyance to the public. Despite this importance, few studies has hitherto been undertaken on examining the odor nuisance and risk of diseases due to contact with untreated overflow. However, quantitative investigation of odor emission from the sanitary sewage overflows has not been addressed. As such, this study aims to scrupulously investigate the deleterious impact of such phenomenon on public health in terms of the aforesaid matters. To this end, a multi-stage methodological approach was employed. Firstly, field data was collected from the vicinity of a wastewater treatment plant for three years, and then the concentrations of H2S in the aqueous phase and gaseous phase were estimated based on the environmental parameters. Afterward, the Gaussian aerial dispersion model and Quantitative Microbial Risk Assessment (QMRA) were employed. In parallel, the impact of the exposure to the malodorous H2S emitted from overflow cases was assessed. Furthermore, the results obtained from impact assessment were validated using the developed questionnaire survey. From the results obtained, the following major conclusions are drawn: (1) levels of H2S(g) near the overflow were high enough to be perceived by individuals, (2) concentrations of NH3(g) in the ambient air were estimated lower than the perception threshold, (3) the sulfide concentration in the overflow was the most influential parameter with positive linear correlation with the concentration of H2S(g), (4) the concentration of odor causes high annoyance, according to the questioning from the residents near the overflow events (5) exponential dose-response indicated 89–95% infection risk and (6) the good correlation between the estimated values of annoyance and the real annoyance level perceived by the residents proved accuracy of the methodology for estimation of H2S concentration and annoyance level. The unique findings obtained from this study guide the environmental decision-makers to take pre-emptive actions, preventing risk of infection and complaints from the residents.

Storm-event Dynamics of Nitrogen and Dissolved Oxygen in Urban River: The Upper Tame, Birmingham

Nitrogen (N) and dissolved oxygen (DO) are essential indicators of urban water pollution, with excess nitrogen causing eutrophication and low dissolved oxygen damaging the living environment of aquatic organisms and affecting biodiversity. Urban areas cover a high proportion of impervious areas. When heavy rainfall occurs, it rapidly generates surface runoff in urban areas and carries nitrogen into river systems. This study aims to assess the water quality of the river tame through the Birmingham metropolitan area over the last 15 years, investigate whether excess nitrogen input during storm events causes significant changes in dissolved oxygen, and find a linear relationship between nitrogen and dissolved oxygen. By comparing the water quality at the Sandwell Park sample point, which does not flow through urban Birmingham, with the water quality at the Minworth sample point, which is the final outlet of Birmingham, it was found that the nitrogen content of the river Tame increased from 4.17 mg/L to 13.09 mg/L, indicating a decline in water quality after the river Tame flowed through urban Birmingham. The correlation coefficient between nitrogen and dissolved oxygen increases from 0.65 to 0.8 between the rainfall event and the storm event, which is highly correlated, suggesting that combined sewer overflow (CSO) events coincided with peak nitrogen and strengthened the correlation between nitrogen and dissolved oxygen in the river Tame. A regular and continuous monitoring program should be established for the Tame catchment through urban Birmingham to prevent overflows as a priority and to enhance the treatment capacity of the sewage treatment plant.

Effect of microbial network complexity and stability on nitrogen and sulfur pollutant removal during sediment remediation in rivers affected by combined sewer overflows

Discovering the complexity and improving the stability of microbial networks in urban rivers affected by combined sewer overflows (CSOs) is essential for restoring the ecological functions of urban rivers, especially to improve their ability to resist CSO impacts. In this study, the effects of sediment remediation on the complexity and stability of microbial networks was investigated. The results revealed that the restored microbial community structure using different approaches in the river sediments differed significantly, and random matrix theory showed that sediment remediation significantly affected microbial networks and topological properties; the average path distance, average clustering coefficient, connectedness, and other network topological properties positively correlated with remediation time and weakened the small-world characteristics of the original microbial networks. Compared with other sediment remediation methods, regulating low dissolved oxygen (DO) shifts the microbial network module hubs from Actinobacteria and Bacteroidetes to Chloroflexi and Proteobacteria. This decreases the positive association of networks by 17%–18%, which intensifies the competitiveness among microorganisms, further weakening the influence and transmission of external pressure across the entire microbial network. Compared with that of the original sediment, the vulnerability of the restored network was reduced by more than 36%, while the compositional stability was improved by more than 12%, with reduced fluctuation in natural connectivity. This microbial network succession substantially increased the number of key enzyme-producing genes involved in nitrogen and sulfur metabolism, enhancing nitrification, denitrification, and assimilatory sulfate reduction, thereby increasing the removal rates of ammonia, nitrate, and acid volatile sulfide by 43.42%, 250.68% and 2.66%, respectively. This study comprehensively analyzed the succession patterns of microbial networks in urban rivers affected by CSOs before and after sediment remediation, which may provide a reference for reducing the impact of CSO pollution on urban rivers in the subsequent stages.

Precipitation and discharge changes drive increases in Escherichia coli concentrations in an urban stream

Determining the driving factors of E. coli dynamics and predicting future E. coli changes in urban aquatic systems are important for regulating water quality. In this study, data from 6985 measurements of E. coli from 1999 to 2019 in an urban waterway Pleasant Run in Indianapolis, Indiana (USA) were statistically analyzed by Mann-Kendall and multiple linear regression to assess the long-term trends in E. coli concentrations and to project E. coli concentrations under future climate change scenarios. E. coli concentrations monotonically increased over the last two decades, with the value increasing from 111 Most Probable Number (MPN)/100 mL in 1999 to 911 MPN/100 mL in 2019. E. coli concentrations have exceeded the Indiana standard of 235 MPN/100 mL since 1998. E. coli showed peak concentration in summer and higher concentration in sites with combined sewer overflows (CSOs) relative to those without. Precipitation had both direct and indirect impacts on E. coli concentrations meditated by stream discharge. Multiple linear regression results showed that annual precipitation and discharge accounted for 60 % of E. coli concentration variability. Based on the observed precipitation-discharge-E. coli concentration relationship, the projected results showed that, in the highest emission representative concentration pathways (RCP) 8.5 climate scenario, E. coli concentrations in the 2020s, 2050s, and 2080s will be 1350 ± 563 MPN/100 mL, 1386 ± 528 MPN/100 mL, and 1443 ± 479 MPN/100 mL, respectively. This study illustrates that climate change can impact E. coli concentrations by altering temperature, precipitation patterns, and stream flow in an urban stream and predicts an undesired future situation under a high CO2 emission scenario.

How reliable – and (net) beneficial – is the green in green infrastructure

AbstractThe idea of green infrastructure (GI) has generated great interest and creativity in addressing a range of challenging and expensive environmental problems, from coastal resilience to control of combined sewer overflows (CSOs). The appeal of GI stems from its cost savings compared to traditional “gray” infrastructure and the multiple benefits it provides, including biodiversity, aesthetics, and carbon sequestration. For example, a “green” approach to controlling CSOs in New York City saved $1.5 billion compared to a “gray” approach. Despite these advantages, GI still does not have detailed design and reliability specifications as compared to engineered gray infrastructure, potentially hindering its adoption. In this paper, we review some of the potential applications of GI in modern environmental science and discuss how reliability and associated (un)certainty in net benefits need to be addressed to realize the potential of this new approach.