ORCID Profile
0000-0003-0780-4661
Current Organisation
AquaInSilico Lda
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Publisher: Elsevier BV
Date: 05-2022
DOI: 10.1016/J.SCITOTENV.2022.153492
Abstract: In next-generation water resource recovery facilities (WRRFs), it is becoming increasingly important to save energy costs and promote resource recovery of valuable products. One way of reducing the substantial aeration energy costs at WRRFs is to employ shortcut N removal, while polyhydroxyalkanoate (PHA) production and recovery as bioplastic is a promising means of recovering a valuable product from biosolids. Both objectives can be achieved simultaneously through the Short-Cut Enhanced Phosphorus and PHA Recovery (SCEPPHAR) process. However, current mathematical models have not previously been employed to describe the behavior of such a process, which limits engineering design and optimisation of process operation. This work focusses on extending the ASM3 model towards the description of short-cut nitrogen removal and simultaneous PHA recovery in a sidestream treatment process. The calibrated and validated model described very well the nitritation process coupled with the aerobic feast/anoxic famine process for the selection of PHA producing organisms at a pilot-scale facility operated in Carbonera, Italy, where the normalised root mean squared error (NRMSE) was consistently <20%. Furthermore, the model applied to the PHA selection stage could effectively describe the PHA accumulation stage without recalibration. A simulation study was performed using the modified ASM3 model to assess the relative benefits of the SCEPPHAR process strategy as compared to the fully aerobic selection process for mixed culture PHA production. While the level of PHA production was found to be 34% lower with SCEPPHAR, a 43% savings in volatile fatty acids (VFAs) demand, a 15% decrease in Total suspended solids (TSS) production and a 28% decrease in oxygen demand were also achievable, which could lead to savings in operational costs. This study facilitates the design and optimisation of WRRFs that integrate short-cut N removal with PHA production, saving aeration energy costs while achieving resource recovery.
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.WATRES.2019.115373
Abstract: This study demonstrates that META-ASM, a new integrated metabolic activated sludge model, provides an overall platform to describe the activity of the key organisms and processes relevant to biological nutrient removal (BNR) systems with a robust single-set of default parameters. This model overcomes various shortcomings of existing enhanced biological phosphorous removal (EBPR) models studied over the last twenty years. The model has been tested against 34 data sets from enriched lab polyphosphate accumulating organism (PAO)-glycogen accumulating organism (GAO) cultures and experiments with full-scale sludge from five water resource recovery facilities (WRRFs) with two different process configurations: three stage Phoredox (A2/O) and adapted Biodenitro™ combined with a return sludge sidestream hydrolysis tank (RSS). Special attention is given to the operational conditions affecting the competition between PAOs and GAOs, capability of PAOs and GAOs to denitrify, metabolic shifts as a function of storage polymer concentrations, as well as the role of these polymers in endogenous processes and fermentation. The overall good correlations obtained between the predicted versus measured EBPR profiles from different data sets support that this new model, which is based on in-depth understanding of EBPR, reduces calibration efforts. On the other hand, the performance comparison between META-ASM and literature models demonstrates that existing literature models require extensive parameter changes and have limited predictive power, especially in the prediction of long-term EBPR performance. The development of such a model able to describe in detail the microbial and chemical transformations of BNR systems with minimal adjustment to parameters suggests that the META-ASM model is a powerful tool to predict and mitigate EBPR upsets, optimise EBPR performance and to evaluate new process designs.
Location: Portugal
Location: Portugal
Location: Portugal
Location: Portugal
No related grants have been discovered for Jorge Santos.