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Anaerobic co-digestion is an emerging practice at wastewater treatment plants (WWTPs) to improve the energy balance and integrate waste management. Modelling of co-digestion in a plant-wide WWTP model is a powerful tool to assess the impact of co-substrate selection and dose strategy on digester performance and plant-wide effects. A feasible procedure to characterise and fractionate co-substrates COD for the Benchmark Simulation Model No. 2 (BSM2) was developed. This procedure is also applicable for the Anaerobic Digestion Model No. 1 (ADM1). Long chain fatty acid inhibition was included in the ADM1 model to allow for realistic modelling of lipid rich co-substrates. Sensitivity analysis revealed that, apart from the biodegradable fraction of COD, protein and lipid fractions are the most important fractions for methane production and digester stability, with at least two major failure modes identified through principal component analysis (PCA). The model and procedure were tested on bio-methane potential (BMP) tests on three substrates, each rich on carbohydrates, proteins or lipids with good predictive capability in all three cases. This model was then applied to a plant-wide simulation study which confirmed the positive effects of co-digestion on methane production and total operational cost. Simulations also revealed the importance of limiting the protein load to the anaerobic digester to avoid ammonia inhibition in the digester and overloading of the nitrogen removal processes in the water train. In contrast, the digester can treat relatively high loads of lipid rich substrates without prolonged disturbances.

Anaerobic co-digestion allows for under-utilised digesters to increase biomethane production. The organic fraction of municipal solid waste (OFMSW), i.e., food waste, is an abundant substrate with high degradability and gas potential. This paper investigates the co-digestion of mixed sludge from wastewater treatment plants and OFMSW, through batch and continuous lab-scale experiments, modelling, and microbial population analysis. The results show a rapid adaptation of the process, and an increase of the biomethane production by 20% to 40%, when co-digesting mixed sludge with OFMSW at a ratio of 1:1, based on the volatile solids (VS) content. The introduction of OFMSW also has an impact on the microbial community. With 50% co-substrate and constant loading conditions (1 kg VS/m3/d) the methanogenic activity increases and adapts towards acetate degradation, while the community in the reference reactor, without a co-substrate, remains unaffected. An elevated load (2 kg VS/m3/d) increases the methanogenic activity in both reactors, but the composition of the methanogenic population remains constant for the reference reactor. The modelling shows that ammonium inhibition increases at elevated organic loads, and that intermittent feeding causes fluctuations in the digester performance, due to varying inhibition. The paper demonstrates how modelling can be used for designing feed strategies and experimental set-ups for anaerobic co-digestion.

Multi-objective performance assessment of operational strategies at wastewater treatment plants (WWTPs) is a challenging task. The holistic perspective applied to evaluation of modern WWTPs, including not only effluent quality but also resource efficiency and recovery, global environmental impact and operational cost calls for assessment methods including both on- and off-site effects. In this study, a method combining dynamic process models – including greenhouse gas (GHG), detailed energy models and operational cost – and life cycle assessment (LCA) was developed. The method was applied and calibrated to a large Swedish WWTP. In a performance assessment study, changing the operational strategy to chemically enhanced primary treatment was evaluated. The results show that the primary objectives, to enhance bio-methane production and reduce GHG emissions were reached. Bio-methane production increased by 14% and the global warming potential decreased by 28%. However, due to increased consumption of chemicals, the operational cost increased by 87% and the LCA revealed that the abiotic depletion of elements and fossil resources increased by 77 and 305%, respectively. The results emphasize the importance of using plant-wide mechanistic models and life cycle analysis to capture both the dynamics of the plant and the potential environmental impacts.

Gas–liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas–liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid–base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas–liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas–liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas–liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas–liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners.

The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like ‘black box’ models, computational fluid dynamics techniques, etc.? Can new data sources – e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis – keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.

Abstract There is a strongly growing interest for wastewater heat recovery (WWHR) in Sweden and elsewhere, but a lack of adequate tools to determine downstream impacts due to the associated temperature drop. The heat recovery potential and associated temperature drop after heat recovery on a building level is modelled for a case study in Linköping, Sweden. The maximum temperature drop reaches 4.2 °C, with an annual recovered heat of 0.65 kWh · person−1 · day−1. Wastewater temperature out from the heat exchanger was 18.0 °C in winter at the lowest. The drinking water source type can be an important factor when considering wastewater heat recovery.

Abstract:The objective of this paper is to model the dynamics and validate the results of nitrous oxide (N 2 O) emissions from three Swedish full-scale nitrifying/denitrifying, nitritation and anammox systems treating anaerobic digester sludge liquor. The Activated Sludge Model No. 1 is extended in order to describe N 2 O production by both heterotrophic and autotrophic bacteria. In addition, mass transfer equations are implemented to characterize the dynamics of N 2 O in the water and the gas phases. The biochemical model is simulated for two hydraulic patterns: 1) a sequencing batch reactor (SBR); and, 2) a moving-bed biofilm reactor (MBBR). Preliminary results show that the calibrated model is partly capable of reproducing the behaviour of N 2 O as well as the nitritation/nitrification/denitrification dynamics. However, the results emphasize that more work is required before N 2 O emissions from sludge liquor treatment plants can be generally predicted with certainty by simulations. Continued efforts should focus on determining the switching conditions for different N 2 O formation pathways and, if full-scale data is used, modelling of the measurement devices might improve the conclusions that can be drawn.