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Membrane Aerated Biofilm Reactors (MABR) are gaining more and more acceptance in the plethora of wastewater process intensification technologies. Mathematical modelling has contributed to show their feasibility in terms of reduced energy consumption and footprint. Nevertheless, most simulation studies published until now are still focused on analyzing MABR as single units and not fully integrated within the flow diagram of the water treatment plant (WWTP). In this paper, the prediction capabilities of an integrated modelling approach is tested using full-scale data from Ejby Mølle WWTP+MABR site (Odense, Denmark). Mass balances, data reconciliation methods, process simulation and the different evaluation criteria were used to adjust influent, effluent and process indicators. Results show 10 % mismatch between flow, COD, N and P predictions and measurements in different plant locations. Using the adopted hydraulic retention time (HRT), nitrogen load (NL), membrane surface area (MA) and oxygen transfer rate (OTR), it was possible to predict nitrification rates (NR) within the interquartile range. This has been done under two different MABR operational conditions: with (#S2) and without (#S1) external aeration (EA) in the bulk liquid. The model provides additional process insights about biofilm structure, substrate gradients, weak acid base chemistry and precipitation potential. More specifically, simulations suggest the potential undesirable effects of sulfate (SRB) and iron reducing bacteria (IRB) on both microbial activity and composition of the biofilm. The latter may have a strong impact on ammonium (NHx), sulfate (SOx) and ferrous ion (Fe+2) conversion processes. The change of operational strategy in the scenario analysis highlights that the denitrifying activity of phosphorus accumulating organisms (PAOs) can enhance nutrient removal in MABR tanks. In addition, it was possible to assess the chance of success (in terms of energetic cost of nitrogen removal) of ad

Acord transformatiu CRUE-CSIC, Altres ajuts: Borja Solís is grateful for the PIF PhD grant funded by Universitat Autònoma de Barcelona., In this study, a plant-wide model describing the fate of C, N and P compounds, upgraded to account for (on-site/off-site) greenhouse gas (GHG) emissions, was implemented within the International Water Association (IWA) Benchmarking Simulation Model No. 2 (BSM2) framework. The proposed approach includes the main biological N2O production pathways and mechanistically describes CO2 (biogenic/non-biogenic) emissions in the activated sludge reactors as well as the biogas production (CO2/CH4) from the anaerobic digester. Indirect GHG emissions for power generation, chemical usage, effluent disposal and sludge storage and reuse are also included using static factors for CO2, CH4 and N2O. Global and individual mass balances were quantified to investigate the fluxes of the different components. Novel strategies, such as the combination of different cascade controllers in the biological reactors and struvite precipitation in the sludge line, were proposed in order to obtain high plant performance as well as nutrient recovery and mitigation of the GHG emissions in a plant-wide context. The implemented control strategies led to an overall more sustainable and efficient plant performance in terms of better effluent quality, reduced operational cost and lower GHG emissions. The lowest N2O and overall GHG emissions were achieved when ammonium and soluble nitrous oxide in the aerobic reactors were controlled and struvite was recovered in the reject water stream, achieving a reduction of 27% for N2O and 9% for total GHG, compared to the open loop configuration.

This study presents an extensive plant-wide model-based assessment of four alternative activated sludge (AS) configurations for biological nitrogen (N) and phosphorus (P) removal under uncertain influent loads and characteristics. Zeekoegat wastewater treatment plant (WWTP) in South Africa was chosen as case study due to its flexible design that enables operation in four different AS configurations: 3-stage Bardenpho (A2O), University of Cape Town (UCT), UCT modified (UCTM), and Johannesburg (JHB). A metamodeling based global sensitivity analysis was performed on a steady-state plant-wide simulation model using Activated Sludge Model No. 2d with the latest extension of physico-chemical processes describing the plant-wide P transformations. The simulation results showed that the predictions of effluent COD, N and P using the proposed approach fall within the interquartile range of measured data. The study also revealed that process configuration can affect: 1) how influent uncertainty is reflected in model predictions for effluent quality and cost related performances, and 2) the parameter rankings based on variance decomposition, particularly for effluent phosphate, sludge disposal and methane production. The results identified UCT and UCTM as more robust configurations for P removal (less propagated uncertainty and less sensitivity to N load) in the expense of incomplete denitrification. Moreover, based on the results of Monte-Carlo based scenario analysis, the balanced SRT for N and P removal is more sensitive to influent load variation/uncertainty for the A2O and JHB configurations. This gives a more operational flexibility to UCT and UCTM, where a narrow SRT range can ensure both N and P removal.

In this paper a set of mathematical tools are developed and assembled together to assess and predict mass and volumetric flows in waste treatment systems (WTS). The proposed approach is constructed upon a set of data reconciliation methods, influent fractionation routines and process simulations models (and model interfaces) to balance, analyze, reproduce and forecast the behavior of different compounds within treatment facilities. The proposed approach is tested on full-scale data collected after two five-week measuring campaigns at the largest industrial WTS in Northern Europe. Results show that the proposed reconciliation methodology based on the definition of the identity matrix, data curation, the estimation of missing fluxes and the calculation of Lagrange multipliers allowed to close flow and COD, N, P, S and multiple metals (Na, K, Ca, Mg and Al) mass balances. Plant-wide overall mass balance reveals that that: 1) 32% of the incoming COD is recovered mostly as methane, 2) 23% and 65% of COD and N are biologically removed and leave the system via the gas phase, 3) 32 % and 33% of COD and N are stored in the activated sludge, 4) > 70% of P, Ca, Mg and Al are accumulated in the bio-solids stream as precipitates and 5) > 70% of Na, K and S remain soluble and leave the plant via effluent. Plant measurements were allocated into the model states describing soluble/particulate and organic/inorganic loads arriving to the WTS under study. The average deviation between computer simulations and the result of the measuring campaign is 10.5%. This study also shows that the proposed approach is capable to reproduce main streams neutralization, volatile fatty acid production, particulate removal and nitrate denitrification in the anaerobic water line (buffer tank, primary clarifier, pre-acidification tank). It also correctly predicts organics transformation into biogas in the anaerobic granular sludge reactor. Lastly, it is possible to describe biological and chemical

Benchmarking has been a useful tool for unbiased comparison of control strategies in wastewater treatment plants (WWTPs) in terms of effluent quality, operational cost and risk of suffering microbiology-related total suspended solids (TSS) separation problems. This chapter presents the status of extending the original Benchmark Simulation Model No 2 (BSM2) towards including greenhouse gas (GHG) emissions. A mathematical approach based on a set of comprehensive models that estimate all potential on-site and off-site sources of CO2, CH4 and N2O is presented and discussed in detail. Based upon the assumptions built into the model structures, simulation results highlight the potential undesirable effects on increased GHG emissions when carrying out local energy optimization in the activated sludge section and/or energy recovery in the anaerobic digester. Although off-site CO2 emissions may decrease in such scenarios due to either lower aeration energy requirement or higher heat and electricity production, these effects may be counterbalanced by increased N2O emissions, especially since N2O has a 300-fold stronger greenhouse effect than CO2. The reported results emphasize the importance of using integrated approaches when comparing and evaluating (plant-wide) control strategies in WWTPs for more informed operational decision-making.

A modelling study is under way in preparation for a planned upgrade of the capacity of the kwaMashu WWTP in eThekwini, South Africa, from 50 to 80 ML/d. When the configuration of an existing plant is to be changed, the most critical part of the model calibration is the influent wastewater fractionation. However, the constantly varying characteristics of wastewater make experimental determination of an adequately representative set of components difficult, time-consuming and expensive, which constitutes significant barriers to the adoption of modelling by many municipalities. Compliance and process monitoring generate large sets of influent measurements of chemical oxygen demand (COD), free and saline ammonia (FSA), total suspended solids (TSS), etc., but these are insufficient for modelling purposes. In particular, biodegradability is not routinely measured. However, since influent fractionation is designed to predict the fate of material in the wastewater treatment process, it should be possible to infer the fractionation from a combination of influent and plant measurements. This case study demonstrates the application of a pair of modelling tools, a probabilistic influent fractionator and a simplified steady‑state plant‑wide model, to estimate the influent fractionation, together with certain unmeasured or unreliable operational parameters.