Looking through the FOG: microbiome characterization and lipolytic bacteria isolation from a fatberg site

Sewer systems are complex physical, chemical and microbial ecosystems where fats, oils and grease (FOG) present a major problem for sewer management. Their accumulation can lead to blockages (‘Fatbergs’), sewer overflows and disruption of downstream wastewater treatment. Further advancements of biological FOG treatments need to be tailored to degrade the FOG, and operate successfully within the sewer environment. In this study we developed a pipeline for isolation of lipolytic strains directly from two FOG blockage sites in the UK, and isolated a range of highly lipolytic bacteria. We selected the five most lipolytic strains using Rhodamine B agar plates and pNP-Fatty acid substrates, with two Serratia spp., two Klebsiella spp. and an environmental Acinetobacter strain that all have the capacity to grow on FOG-based carbon sources. Their genome sequences identified the genetic capacity for fatty acid harvesting (lipases), catabolism and utilization (Fad genes). Furthermore, we performed a preliminary molecular characterization of the microbial community at these sites, showing a diverse community of environmental bacteria at each site, but which did include evidence of sequences related to our isolates. This study provides proof of concept to isolation strategies targeting Fatberg sites to yield candidate strains with bioremediation potential for FOG in the wastewater network. Our work sets the foundation for development of novel bioadditions tailored to the environment with non-pathogenic Acinetobacter identified as a candidate for this purpose.

Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems

Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control (MPC) systems offer a new approach to mitigate the impact of CSOs by generating optimal temporally and spatially varied dynamic control strategies of sewer system actuators. This paper presents a novel MPC based on neural networks for predicting flows, a stormwater management model (SWMM) for flow conveyance, and a genetic algorithm for optimizing the operation of sewer systems and defining the best control strategies. The proposed model was tested on the sewer system of the city of Casablanca in Morocco. The results have shown the efficiency of the developed MPC to reduce CSOs while considering short optimization time thanks to parallel computing.

Barriers to the digital transformation of infrastructure sectors

Digital technologies can be important to policy-makers and public servants, as these technologies can increase infrastructure performance and reduce environmental impacts. For example, utilizing data from sensors in sewer systems can improve their management, which in turn may result in better surface water quality. Whether such big data from sensors is utilized is, however, not only a technical issue, but also depends on different types of social and institutional conditions. Our article identifies individual, organizational, and institutional barriers at the level of sub-states that hinder the evaluation of data from sewer systems. We employ fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare 23 Swiss sub-states and find that two barriers at different levels can each hinder data evaluation on their own. More specifically, either a lack of vision at the individual level or a lack of resources at the organizational level hinder the evaluation of data. Findings suggest that taking into account different levels is crucial for understanding digital transformation in public organizations.

Analysis of the Inflow Characteristics of Separate Sewer Systems for Rainfall Using an XP-SWMM Model and the SSOAP Toolbox

Even after the sewer system rehabilitation project, sewer system-related problems caused by inflow still persist. However, analysis of the characteristics of the inflow has been limited to specific rainfall events and monitoring points. This study analyzed inflow characteristics according to rainfall events using an XP-SWMM model and the Sanitary Sewer Overflow Analysis and Planning (SSOAP) Toolbox. In this study, the XP-SWMM model was built for sewers and collecting pipes in urban areas where classification projects were completed. The R, T, and K parameters were calculated using the SSOAP tool based on the sewer volume data of the study area. The calculated parameters were inputted into the XP-SWMM model and used to analyze R, T, and K of unmeasured sampling intervals. The amount of rainfall-derived inflow and infiltration (RDII) increased according to the amount of rainfall, and the correlation coefficient between the amount of rainfall and the amount of RDII was 0.9352, indicating a high correlation. The results of this study can support efficient facility planning that reflects the rainfall characteristics of specific areas, including areas where actual survey of sewage data is not possible.

Model-Driven Strategies for Sulfide Control in a Regional Wastewater System Receiving Tannery Effluents in Portugal

Ageing infrastructure are a concern for many wastewater utilities. This is accentuated with the presence of hydrogen sulfide within the sewer headspace, known to induce concrete corrosion, toxicity and odours. Some industrial effluents contain significant sulfide concentrations, however most field studies in the literature refer to domestic networks, or lab/pilot scale sulfide abatement strategies for varied effluents. Hence, the objectives of this work are: (1) To obtain data regarding the evolution of sulfides in a full-scale industrial sewer system in Portugal, receiving wastewater from a number of tanneries; (2) model their fate within the system and (3) experimentally evaluate sulfide precipitation with iron salts. Field work evidenced heavily sulfide loaded effluents, exceeding by far literature values for sewer systems. Modelling was carried out based on the AeroSept+ model, specifically calibrated to this type of effluent. Results showed the model was capable of reproducing the overall levels of sulfide in wastewater and H2S in the sewer headspace, while allowing insights into industrial discharges, originating a set of proposed interventions for sulfide abatement. This may be carried out by iron salts addition, in a ratio of 2.75:1, at existing monitoring stations. This approach was fundamental for an affordable performance assessment, under considerable uncertainty.

Large-Volume Samplers for Efficient Composite Sampling and Particle Characterization in Sewer Systems

The assessment of pollution from sewer discharges requires flexible and reliable sampling methods. The characteristics of the sampling system must be known to allow comparison with other studies. Large volume samplers (LVS) are increasingly used for monitoring in sewer systems and surface waters. This article provides a comprehensive description of this widely applicable sampling system, gives insight into its comparability to standard methods, and provides recommendations for researchers and practitioners involved in water quality monitoring and urban water management. Two methods for subsampling from LVS are presented, i.e., collection of homogenized or sedimented samples. Results from a sampling campaign at combined sewer overflows (CSOs) were used to investigate the comparability of both subsampling methods and conventional autosamplers (AS). Event mean concentrations (EMC) of total suspended solids (TSS) derived from homogenized LVS samples and AS pollutographs were comparable. TSS-EMC of homogenized and sedimented LVS samples were also comparable. However, differences were found for particle size distribution and organic matter content. Consequently, sedimented LVS samples, which contained solids masses in the range of 3–70 g, are recommended to be used for particle characterization. The differences between homogenized and sedimented LVS samples, e.g., the quality of homogenization and the stability of samples during sedimentation in LVS, should be further investigated. Based on LVS results, average TSS concentrations of 50–60 mg/L were found for CSOs from centralized treatment facilities in Bavaria. With a median share of 84%, particles <63 µm were the dominant fraction.

A Mixed Flow Analysis of Sewer Pipes with Different Shapes Using a Non-Oscillatory Two-Component Pressure Approach (TPA)

This paper aimed to justify the performance of a non-oscillatory TPA-based model proposed by the authors for capturing transient mix flow in sewer systems consisting of a variety of pipe shapes. The model utilizes a first-order Godunov Finite volume numerical scheme in which a Harten–Lax–van Leer (HLL) Riemann solver was used for calculating the fluxes at the cells’ boundaries. The spurious numerical solution associated with the transient mix flow analysis is suppressed by enhancing the numerical viscosity of the scheme when the pipe pressurization is imminent. Due to the lack of experimental data for systems with pipe shapes other than circular and rectangular, a hypothetical pipe system for which analytical solutions exist was employed to verify the model performance. The results reveal that for all pipe shapes considered, the model provides oscillation-free solutions even at a high acoustic speed of 1400 m/s. It is also observed that the numerical results are in perfect agreement with the analytical solution. The obtained results conclude that the proposed model can be utilized to capture transient responses of sewer systems with any pipe shape.

Novel Approaches for Biocorrosion Mitigation in Sewer Systems

Concrete sewer pipes can be corroded by the biogenic sulfuric acid (H2SO4) generated from microbiological activities in a process called biocorrosion or microbiologically induced corrosion (MIC). In this study, inhibitors that can reduce Acidithiobacillus thiooxidans growth and thus may reduce the accumulation of biofilm components responsible for the biodegradation of concrete were used. D-tyrosine, tetrakis hydroxymethyl phosphonium sulfate (THPS) and TiO2 nanoparticles were investigated as potential inhibitors of sulfur-oxidizing bacteria (SOB) growth. Results showed that most of the chemicals used can inhibit SOB growth at a concentration lower than 100 mg/L. TiO2 nanoparticles exhibited the highest biocide effect and potential biocorrosion mitigation activity, followed by D-tyrosine and THPS.