Limiting the introduction of excess nitrogen to natural water sources is a growing priority for water security and environmental health. This poses particular difficulties in urban environments where available land for potential solutions is limited. A promising option is the integrated fixed-film activated sludge (IFAS) process that requires only a small footprint and is capable of high total nitrogen (TN) removal through multiple pathways. In light of the sustainable development goals set out by the United Nations, the present work has sought to compare the sustainability of two TN removal pathways by comparing the technical, economic and environmental performance of their optimum configurations. Through modelling, a single-stage configuration demonstrated the capacity to achieve an effluent TN concentration of 8.7 mg/L by the simultaneous nitrification denitrification pathway when a dissolved oxygen concentration of 3.5 mg/L was provided. Addition of a post-anoxic stage at equal volume to the aerobic stage (1:1 aerobic to anoxic ratio) to target conventional nitrification denitrification could realise an effluent TN concentration of 4.2 mg/L when DO was increased to 4.5 mg/L, although 5.8 mg/L of effluent TN could be achieved with only a 5:1 ratio. In terms of environmental burden and economic costs, analysis of the system's life-cycle under these different configurations indicated considerable asymmetry of the two pathways during the operational phase due mainly to the increased aeration. However in spite of this, the two conventional configurations were ultimately both shown to be more sustainable than that of the simultaneous pathway due to the greater TN removal capacity afforded.

IFAS systems are inherently complex due to the hybrid use of both suspended and attached bacterial colonies for the purpose of pollutant degradation as part of wastewater treatment. This poses challenges when attempting to represent these systems mathematically due to the vast number of parameters involved. Besides becoming convoluted, large effort will be incurred during model calibration. This paper demonstrates a systematic approach to calibration of an IFAS process model that incorporates two sensitivity analyses to identify influential parameters and detect collinearity from a subset of 68 kinetic and stoichiometric parameters, and the use of the Nelder–Mead optimization algorithm to estimate the required values of these parameters. The model considers the removal of three critical pollutants including biochemical oxygen demand (BOD), total nitrogen (TN) and total suspended solids (TSS). Results from the sensitivity analyses identified four parameters that were the primary influence on the model. The model was found to be most sensitive to the two stoichiometric parameters including aerobic heterotrophic yield on soluble substrate whose total effects were responsible for 92.4% of the model’s BOD output sensitivity and 92.8% of the model’s TSS output sensitivity. The anoxic heterotrophic yield on soluble substrate was observed to be responsible for 54.3% of the model’s TN output sensitivity. To a lesser extent the two kinetic parameters, aerobic heterotrophic decay rate and reduction factor for denitrification on nitrite, were responsible for only 8.0% and 13.1% of the model’s BOD and TN output sensitivities respectively. Parameter estimation identified the need for only minor adjustments to default values in order to achieve sufficient accuracy of simulation with deviation from observed data to be only ± 3.6 mg/L, ± 1.3 mg/L, and ± 9.5 mg/L for BOD, TN and TSS respectively. Validation showed the model was limited in its capacity to predict system behaviour under extreme dissolved oxygen stress.

This paper proposes a new method to identify the near-optimal response to failures in water distribution networks in near real time. The response method is formulated as a two-objective optimization problem with objectives being the minimization of failure impacts and related operational costs. The new heuristics-based method is developed and used to solve this optimization problem. The method comprises three steps. In the first step, the initial list of available interventions is identified offline. In the second step (online), the narrowed-down list of interventions considered in the optimization is identified. Finally, in the last step (online), a novel heuristic algorithm is applied to identify near-optimal solutions in near real time. The new optimization method was validated and demonstrated in two case studies, a semireal case study based on a C-Town network and an assumed failure event (pipe burst), and a real UK case study involving a complex real pipe network and event caused by shutting down the Water Treatment Works. The Pareto front of response interventions identified by the new heuristics method approximates well the non-dominated sorting genetic algorithm II Pareto front in both cases with the largest differences measured in terms of end-impacts (between relevant solutions for the same cost) being 4% and 9%, respectively. In addition, the new heuristics method is able to identify near-optimal response solutions in a computationally fast manner (15 min and 1 h for the two cases). Therefore, the heuristics method can be used in near real time in real-life situations.

In the plight for sustainable development and to support net zero ambitions for climate change mitigation, a broad range of aeration strategies have been developed with the hope of improving efficiency to minimize environmental and economic costs associated with the wastewater treatment processes. However, a balance is levied between reducing oxygen availability and hindering aerobic processes thus compromising performance. In the present work, we evaluate and compare the sustainability of a range of investigated strategies including continuous aeration (CA) at different dissolved oxygen (DO) setpoints (0.5 mg/L, 2.5 mg/L, 4.5 mg/L) and intermittent aeration (IA) at different oxic-anoxic portions (2.5 h on/0.5 h off, 2.0 h on/1.0 h off, 1.5 h on/1.0 h off). To achieve this, an eco-efficiency assessment is performed based on the results of previous life cycle impact and costing analyses for each strategy, while also incorporating a third factor to account for their respective treatment performance. The results demonstrate a clear pattern of increased sustainability for the IA strategies (0.54–0.56 Pt/m³), compared to the CA strategies (0.76–0.77 Pt/m³). While only negligible difference was observed within each aeration type, the trade-off between environmental and economic efficiency and treatment performance was distinct in CA strategies. At the individual pollutant level, IA strategies demonstrated decreasing sustainability for total phosphorous (TP) removal as the anoxic cycle portion increased, while CA at 0.5 mg/L was shown to be the most sustainable strategy for the removal of this pollutant (0.61 Pt/m³). Further work is suggested to incorporate the relative N₂O emissions generated by each strategy and to investigate other strategies based on automated control.

Emerging contaminants (ECs) continue to threaten our fragile ecosystem, yet their mitigation remains limited by economic factors. Meanwhile, a relatively expensive material, Graphene Oxide (GO), has shown promise as a solution for EC removal following further development into three graphene-based materials (GBMs): Porous graphene adsorbent (PGa), Graphene-oxide foam adsorbent (GOFa), and the hybrid filter. Due to the nuances of each synthesis process, financial costs will differ throughout the GBMs’ life cycle which have been quantified and compared in the present work at a range of possible breakthrough times. Finally, economic and environmental costs have been combined for each technology to compare eco-efficiency. Results demonstrated a substantial economic advantage of the GBMs when compared to alternative technologies, most notably the GOFa filter that incurred the lowest life-cycle costs at $1.73 ± 0.09/m³. This was mainly attributed to the lower demand of GOFa on the most expensive material required for material synthesis, hydra-zine. In addition, the material demands of GOFa were more evenly distributed which suggest a higher resilience of the overall costs to price hikes of individual materials required for synthesis. In terms of eco-efficiency the GOFa filter also demonstrated the greatest improvement when compared to the reference technology These results have provided robust total investment costs for several technologies that can now offer contrast to other EC-removal solutions.

Intermittent water supply (IWS) is widely used around the world, and with the increase in population and predicted future water scarcity, IWS applications seem to continue. While most of the existing studies on water supply concentrate on continuous water supply (CWS), the research focused on the IWS is now becoming mainstream. Hydraulic modelling is an effective tool for the process of planning, design, rehabilitation, and operation of water distribution systems. It helps significantly in engineers’ decision-making processes. The necessity of modelling IWS systems arises from the complexity and variety of problems caused by intermittency. This paper offers a review of the state-of-the-art IWS modelling and identifies the key strengths and limitations of the available approaches, and points at potential research directions. Currently, neither computer software nor a practically used approach is available for modelling IWS. For a rigorous simulation of IWS, system characteristics first need to be understood, i.e., the user behaviour under pressure-deficient conditions, water losses, and filling and emptying processes. Each of them requires further attention and improvement. Additionally, the necessity of real data from IWSs is stressed. Accurate modelling will lead to the development of improved measures for the problems caused by intermittency.

Near-real-time event detection is crucial for water utilities to be able to detect failure events in their water treatment works (WTW) quickly and efficiently. This paper presents a new method for an automated, near-real-time recognition of failure events at WTWs by the application of combined statistical process control and machine-learning techniques. The resulting novel hybrid CUSUM event recognition system (HC-ERS) uses two distinct detection methodologies: one for fault detection at the level of individual water quality signals and the second for the recognition of faulty processes at the WTW level. HC-ERS was tested and validated on historical failure events at a real-life UK WTW. The new methodology proved to be effective in the detection of failure events, achieving a high true-detection rate of 82% combined with a low false-alarm rate (average 0.3 false alarms per week), reaching a peak F₁ score of 84% as a measure of accuracy. The new method also demonstrated higher accuracy compared with the CANARY detection methodology. When applied to real-world data, the HC-ERS method showed the capability to detect faulty processes at WTW automatically and reliably, and hence potential for practical application in the water industry.

With the aim of reducing the environmental burden of decentralized wastewater treatment plants in India, this project investigated five primary materials (stainless steel (SS), mild steel (MS), glass fibre reinforced polymer (GFRP), high density polyethylene (HDPE), and reinforced concrete cement (RCC)) in terms of the relative environmental impact that each would incur across 13 midpoint and 4 endpoint impact categories during the early life stages. The results showed that SS demonstrated substantially higher impact in total (5.47 Pt) and across each of the endpoint categories, most notably human health (3.12 Pt). Further investigations demonstrated that this was largely fed by the respiratory inorganics midpoint category that accounted for 50 % of the total impact (2.75 Pt), while global warming (0.93 Pt), non-renewable energy (0.70 Pt) and terrestrial ecotoxicity (0.62 Pt) were the only other considerable impacts. GFRP incurred the second greatest impact overall (2.32 Pt), while MS, RCC and HDPE followed with 1.82 Pt, 0.78 Pt, and 0.39 Pt respectively. HDPE afforded the greatest efficiency in all midpoint categories except carcinogens where RCC incurred the least environmental cost. Results were then compared with previous work and likely causal factors highlighted. Further study is recommended to investigate the longevity of the alternative materials in a wastewater containment role to support these results.