Real-time prediction of rain-impacted sewage flow for on-line control of chemical dosing in sewers

A data-driven method for estimating sewer inflow and infiltration based on temperature and conductivity monitoring

Quantitation of sewer inflow and infiltration (I/I) is important for maintaining efficient wastewater transport and treatment. I/I flows can be quantified based on flow rate and water quality measurements. Flow rate-based methods require continuous monitoring of flow rates using flow meters that are costly and prone to fouling. In comparison, conductivity and temperature, as simple water quality parameters, are more easily measurable with more cost-effective and reliable sensors. In this study, a data-driven methodology is developed for estimating I/I flows based on online conductivity and temperature measurements. A Prophet-model-based analytic algorithm is first developed to reconstruct the temperature and conductivity profiles of the base wastewater flow (BWF) from the measured temperature and conductivity time series. The algorithm is shown to be able to reconstruct the BWF temperature and conductivity profiles in two monitored catchments. The reconstructed BWF data are then incorporated into mass/energy balance equations for estimating I/I flows from the measured temperature and conductivity data. The overall I/I quantification method is finally demonstrated using simulation studies of a real-life sewer network and validated against the known I/I flows. This work provides a reliable method for I/I quantification based on simple measurements.

Sulfur-containing substances in sewers: Transformation, transportation, and remediation

Sulfur-containing substances in sewers frequently incur unpleasant odors, corrosion-related economic loss, and potential human health concerns. These observations are principally attributed to microbial reactions, particularly the involvement of sulfate-reducing bacteria (SRB) in sulfur reduction process. As a multivalent element, sulfur engages in complex bioreactions in both aerobic and anaerobic environments. Organic sulfides are also present in sewage, and these compounds possess the potential to undergo transformation and volatilization. In this paper, a comprehensive review was conducted on the present status regarding sulfur transformation, transportation, and remediation in sewers, including both inorganic and organic sulfur components. The review extensively addressed reactions occurring in the liquid and gas phase, as well as examined detection methods for various types of sulfur compounds and factors affecting sulfur transformation. Current remediation measures based on corresponding mechanisms were presented. Additionally, the impacts of measures implemented in sewers on the subsequent wastewater treatment plants were also discussed, aiming to attain better management of the entire wastewater system. Finally, challenges and prospects related to the issue of sulfur-containing substances in sewers were proposed to facilitate improved management and development of the urban water system.

Establishing boundary conditions in sewer pipe/soil heat transfer modelling using physics-informed learning

Modelling heat transfer in sewers and the surrounding soil is important for effective sewer maintenance, and for heat recovery from wastewater. The boundary conditions, including both the thickness of the soil layer to be modelled and the temperature distribution around the boundary of the soil layer, directly determine both the efficiency and accuracy of the models. Yet there is no systematic method to establish these conditions. This study presents a novel and generic approach to establishing efficient boundary conditions for sewer heat transfer modelling. Fourier transform is applied to identify the dominant frequencies of the temperatures of the heat sources/sinks, namely the atmosphere, sewer air and wastewater. A simple data-driven model for determining the thickness of the soil-layer to be included, and three physics-informed models for predicting the temperatures at the soil-layer boundary are then learnt from mechanistic models for sewer heat transfer, taking into consideration the frequency spectra. The methodology achieved high fidelity to the mechanistic models in predicting the soil-layer boundary temperatures and sewer wall temperatures for real-life sewers. This approach offers an easy yet reliable way to obtain efficient boundary conditions that significantly improve both the accuracy and speed of sewer heat transfer modelling.

A critical review of chemical uses in urban sewer systems

Chemical dosing is the most used strategy for sulfide and methane abatement in urban sewer systems. Although conventional physicochemical methods, such as sulfide oxidation (e.g., oxygen/nitrate), precipitation (e.g., iron salts), and pH elevation (e.g., magnesium hydroxide/sodium hydroxide) have been used since the last century, the high chemical cost, large environmental footprint, and side-effects on downstream treatment processes demand a sustainable and cost-effective alternative to these approaches. In this paper, we aimed to review the currently used chemicals and significant progress made in sustainable sulfide and methane abatement technology, including 1) the use of bio-inhibitors, 2) in situ chemical production, and 3) an effective dosing strategy. To enhance the cost-effectiveness of chemical applications in urban sewer systems, two research directions have emerged: 1) online control and optimization of chemical dosing strategies and 2) integrated use of chemicals in urban sewer and wastewater treatment systems. The integration of these approaches offers considerable system-wide benefits; however, further development and comprehensive studies are required.

Hydrogen sulfide control in sewer systems: A critical review of recent progress

In sewer systems where anaerobic conditions are present, sulfate-reducing bacteria reduce sulfate to hydrogen sulfide (H₂S), leading to sewer corrosion and odor emission. Various sulfide/corrosion control strategies have been proposed, demonstrated, and optimized in the past decades. These included (1) chemical addition to sewage to reduce sulfide formation, to remove dissolved sulfide after its formation, or to reduce H₂S emission from sewage to sewer air, (2) ventilation to reduce the H₂S and humidity levels in sewer air, and (3) amendments of pipe materials/surfaces to retard corrosion. This work aims to comprehensively review both the commonly used sulfide control measures and the emerging technologies, and to shed light on their underlying mechanisms. The optimal use of the above-stated strategies is also analyzed and discussed in depth. The key knowledge gaps and major challenges associated with these control strategies are identified and strategies dealing with these gaps and challenges are recommended. Finally, we emphasize a holistic approach to sulfide control by managing sewer networks as an integral part of an urban water system.

The role of the sewer system in estimating urban emissions of chemicals of emerging concern

The use of chemicals by society has resulted in calls for more effective control of their emissions. Many of these chemicals are poorly characterized because of lacking data on their use, environmental fate and toxicity, as well as lacking detection techniques. These compounds are sometimes referred to as contaminants of emerging concern (CECs). Urban areas are an important source of CECs, where these are typically first collected in sewer systems and then discharged into the environment after being treated in a wastewater treatment plant. A combination of emission estimation techniques and environmental fate models can support the early identification and management of CEC-related environmental problems. However, scientific insight in the processes driving the fate of CECs in sewer systems is limited and scattered. Biotransformation, sorption and ion-trapping can decrease CEC loads, whereas enzymatic deconjugation of conjugated metabolites can increase CEC loads as metabolites are back-transformed into their parent respective compounds. These fate processes need to be considered when estimating CEC emissions. This literature review collates the fragmented knowledge and data on in-sewer fate of CECs to develop practical guidelines for water managers on how to deal with in-sewer fate of CECs and highlights future research needs. It was assessed to what extent empirical data is in-line with text-book knowledge and integrated sewer modelling approaches. Experimental half-lives (n = 277) of 96 organic CECs were collected from literature. The findings of this literature review can be used to support environmental modelling efforts and to optimize monitoring campaigns, including field studies in the context of wastewater-based epidemiology.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11157-022-09638-9.

A learning-based approach towards the data-driven predictive control of combined wastewater networks - An experimental study

Smart control in water systems aims to reduce the cost of infrastructure expansion by better utilizing the available capacity through real-time control. The recent availability of sensors and advanced data processing is expected to transform the view of water system operators, increasing the need for deploying a new generation of data-driven control solutions. To that end, this paper proposes a data-driven control framework for combined wastewater and stormwater networks. We propose to learn the effect of wet- and dry-weather flows through the variation of water levels by deploying a number of level sensors in the network. To tackle the challenges associated with combining hydraulic and hydrologic modelling, we adopt a Gaussian process-based predictive control tool to capture the dynamic effect of rain and wastewater inflows, while applying domain knowledge to preserve the balance of water volumes. To show the practical feasibility of the approach, we test the control performance on a laboratory setup, inspired by the topology of a real-world wastewater network. We compare our method to a rule-based controller currently used by the water utility operating the proposed network. Overall, the controller learns the wastewater load and the temporal dynamics of the network, and therefore significantly outperforms the baseline controller, especially during high-intensity rain periods. Finally, we discuss the benefits and drawbacks of the approach for practical real-time control implementations.

A full-view management method based on artificial neural networks for energy and material-savings in wastewater treatment plants

Carbon neutrality has been received extensive attention in the field of wastewater treatment. The optimal management of wastewater treatment plants (WWTPs) has great significance and urgency since the serious energy and materials waste. In this study, a full-view management method based on artificial neural networks (ANNs) for energy and material savings in WWTPs was established. More than 5 years of historical operating data from two typical plants (size 40,000 t/d and 10,000 t/d) located in Chongqing, China, were obtained, and public data in the service area of each plant were systematically collected from open channels. These abundant historical and public data were used to train two ANNs (GRA-CNN-LSTM model and PCA-BPNN model) to predict the inlets/outlets wastewater quality and quantity. The overall average prediction accuracy of inlets/outlets wastewater indicators are greater than 92.60% and 93.76%, respectively. By combining the two models, more appropriate process operation strategies can be obtained 2 weeks in advance, with more than 11.20% and 16.91% reduction of energy and material costs, respectively. This proposed method can provide full-view decision support for the optimal management of WWTPs and is also expected to support carbon emission control and carbon neutrality in the field of wastewater treatment.

Swift hydraulic models for real-time control applications in sewer networks

Real-time control (RTC) is an important tool for safe and cost-effective operations of sewer systems by, for example, reducing sewer overflow or enhancing sulfide mitigation. Due to the long transport time of sewage and the inherent dynamics in sewage flow rates, model-predictive control is often needed, which requires the prediction of sewage hydraulic characteristics across the network. The full hydraulic models are often unsuitable for such purposes due to their high computational demands, which are not affordable as the models need to be called for numerous times in each optimisation step. In this study, two swift, data-driven hydraulic models are developed to predict sewage flow rates in gravity sewers receiving feeds from rising main(s) and gravity main(s), respectively. The models are shown to be able to predict both the sewage flow rate and the cross-sectional flow area in high fidelities with solutions of Saint-Venant Equations, but reduce the computational time by up to four orders of magnitude. The swift hydraulic models were then integrated into an RTC strategy for NaOH dosing in a simulated real-life sewer network, and achieved cost-effective control of sulfide. These models could potentially be used for other sewer RTC applications.

Effect of rainfall characteristics on the sewer sediment, hydrograph, and pollutant discharge of combined sewer overflow

Significant management needs raised in urban sewer system to facilitate urban resilience to rainstorm. The work investigated the effects of temporal evolution of rainfall on hydrograph and pollutant discharge of CSO over an intensive observation period of 12 months, with special attention to differences in temporal scale for supporting management decision making. The characteristics of rainfall in different temporal scales helped overflow-risk identification and assessment. Prolonged dry seasons over 112 days in the CSO monitored year 2018 increased the sediment buildup in the pipes. The built sediment was mostly flushed out to overflow (and the treatment facility) by initial rainfall during 47 h. Following CSO hydraulics and pollutant discharge follows initial peak patterns which responded to rainfall patterns. Results of Redundancy analysis and network analysis showed that the combined effects of rainfall, urbanization, and sediments as "CSO troika" are the driving forces for CSO pollutants in the long-term. The improved characterization of CSO events and the associated pollutants has refined our understanding of how overflow hydrograph and pollutant discharge responds to rainfall temporally, which methodology supported decision making in the combining source/process control with terminal management for facilizing urban resilience.

Variations of Concentration Characteristics of Rainfall Runoff Pollutants in Typical Urban Living Areas

Based on a typical residential area, this paper studies the characteristics of pollutant concentration changes in two rainfall runoffs and the first flush effect of rainfall. In rainfall runoff, the concentrations of seven pollutants (COD_Mn, TN, DTN, NH₃-N, TP, DTP, and PO₄^3-) increased during the initial rainfall period and decreased in the later period. Rainfall causes the erosion of pollutants on the underlying surface so that water pollution begins when rainfall runoff occurs, and the pollution level drops over time. The seven pollutants all experience this first flush effect, of which, rainfall has the strongest scouring effect on NH₃-N produced by domestic sewage. The significant excess of pollutants in rainfall runoff should be considered by management departments. In addition, the existence of the first flush effect makes it possible in theory to partially intercept rainfall runoff to control water pollution, thereby reducing the cost of pollution control.

Implementation of a MEIoT Weather Station with Exogenous Disturbance Input

Due to the emergence of the coronavirus disease (COVID 19), education systems in most countries have adapted and quickly changed their teaching strategy to online teaching. This paper presents the design and implementation of a novel Internet of Things (IoT) device, called MEIoT weather station, which incorporates an exogenous disturbance input, within the National Digital Observatory of Smart Environments (OBNiSE) architecture. The exogenous disturbance input involves a wind blower based on a DC brushless motor. It can be controlled, via Node-RED platform, manually through a sliding bar, or automatically via different predefined profile functions, modifying the wind speed and the wind vane sensor variables. An application to Engineering Education is presented with a case study that includes the instructional design for the least-squares regression topic for linear, quadratic, and cubic approximations within the Educational Mechatronics Conceptual Framework (EMCF) to show the relevance of this proposal. This work's main contribution to the state-of-the-art is to turn a weather monitoring system into a hybrid hands-on learning approach thanks to the integrated exogenous disturbance input.

Experimental and modelling evaluations of sulfide formation in a mega-sized deep tunnel sewer system and implications for sewer management

Mega-sized deep tunnel sewer systems are indispensable infrastructures to convey the sewage and/or stormwater to the centralized sewage treatment works in large cities with dense populations and limited land. The rapid urbanization in China and other countries is boosting the construction of the deep tunnel sewer systems. However, the formation of sulfide, which induces serious odor nuisance and sewer corrosion, has not been investigated in such sewer systems. Taking a real Sewage Conveyance System (SCS) with 23.3 km-long and 70-160 m-deep interconnected tunnels in Hong Kong as a representative example, this study conducted experimental and modelling investigations to evaluate the sulfide formation in the mega-sized deep tunnel sewer systems. The field investigation revealed that the daily sulfide production rate in the SCS was up to 1410 kg S/d, suggesting the substantial sulfide production during the long-distance and long-time sewage conveyance. Using a validated Biofilm-Initiated Sewer Process Model (BISM), the sulfide formation in the SCS under the influences of various factors, which are relevant to the situations in China and other countries, were simulated. The simulation results showed that 89% of the total sulfide production in the SCS was generated in the two tunnels with long hydraulic retention times (HRT) and large flowrates. The specific sulfide formation rates exhibited a linear relationship with HRT (R² = 0.61), but the linear relationship with the sewer diameter was weak. The sulfide production rate increased with increasing temperature (12 °C-32 °C) by 3.5 times, and it only decreased by 50% when the sulfate concentration decreased from 309 to 17 mg S/L, indicating that serious sulfide pollution could still happen in the sewers with a low concertation of sulfate in sewage. Increasing the organic levels in sewage would also promote the sulfide production in sewers. The flowrate would not influence the sulfide production rate significantly, but a storm event could remarkably reduce the sulfide production in rainy days. The findings unveil the potential serious sulfide problems in the mega-sized deep tunnel sewer systems, which are being increasingly constructed in China and other countries. To mitigate the odor and corrosion problems in the deep tunnel sewer systems, the sulfide control strategies should be considered during the sewer design and management.

Sweating the assets - The role of instrumentation, control and automation in urban water systems

Instrumentation, control and automation (ICA) are currently applied throughout the urban water system at water treatment plants, in water distribution networks, in sewer networks, and at wastewater treatment plants. However, researchers and practitioners specialising in respective urban water sub-systems do not frequently interact, and in most cases to date the application of ICA has been achieved in silo. Here, we review start-of-the-art ICA throughout these sub-systems, and discuss the benefits achieved in terms of performance improvement, cost reduction, and more importantly, the enhanced capacity of the existing infrastructure to cope with increased service demand caused by population growth and continued urbanisation. We emphasise the importance of integrated control within each of the sub-systems, and also across the entire urban water system. System-wide ICA will have increasing importance with the growing complexity of the urban water environment in cities of the future.

Case study of sulfide generation and emission in sanitary sewer with drop structures and pump station

Field work was carried out to identify sewer odor hotspots and corresponding causes in a sanitary sewer trunk with drop structures and pump station in Steinhauer area, Edmonton, Canada. Relatively high concentrations of H₂S were detected at the beginning and the end of the trunk with odor complaints. At the beginning of the trunk, sulfide emission was mainly caused by the increased stripping effect of the drop structures. The pump operation at the end of the trunk causes the long retention time of the sewage and the subsequent sulfide generation. The sulfide generation was modeled and calibrated using field measurements. The model was applied to assess mitigation strategies, and optimized pump operation was found to be able to reduce sulfide generation in the study trunk sewer.