Development, implementation, and validation of a generic nutrient recovery model (NRM) library

The reported research developed a generic nutrient recovery model (NRM) library based on detailed chemical solution speciation and reaction kinetics, with focus on fertilizer quality and quantity as model outputs. Dynamic physicochemical three-phase process models for precipitation/crystallization, stripping and acidic air scrubbing as key unit processes were developed. In addition, a compatible biological-physicochemical anaerobic digester model was built. The latter includes sulfurgenesis, biological N/P/K/S release/uptake, interactions with organics, among other relevant processes, such as precipitation, ion pairing and liquid-gas transfer. Using a systematic database reduction procedure, a 3- to 5-fold improvement of model simulation speeds was obtained as compared to using full standard thermodynamic databases. Missing components and reactions in existing standard databases were discovered. Hence, a generic nutrient recovery database was created for future applications. The models were verified and validated against a range of experimental results. Their functionality in terms of increased process understanding and optimization was demonstrated

Comparison of Two Mathematical Models for Greenhouse Gas Emission from Membrane Bioreactors

In this study two mathematical models (Model I and Model II), able to predict the nitrous oxide (N2O) and carbon dioxide (CO2) emission from an University Cape Town (UCT) \u2013 membrane bioreactor (MBR) plant, have been compared. Model I considers the N2O production only during the denitrification. Model II takes into account the two ammonia-oxidizing bacteria (AOB) formation pathways for N2O. Both models were calibrated adopting real data. Results highlight that Model II had a better capability of reproducing the measured data especially in terms of N2O model outputs. Indeed, the average efficiency related to the N2O model outputs was equal to 0.3 and 0.38 for Model I and Model II respectively

Optimization methodology for high COD nutrient-limited wastewaters treatment using BAS process

Optimization of biofilm activated sludge (BAS) process via mathematical modelling is an entangle activity since economic, environmental objective and technical decision must be considered. This paper presents a methodology to optimize the operational conditions of BAS process in four steps by combining dynamic simulation techniques with non-linear optimization methods and with operative decision-making criteria. Two set of variables are separately prioritized in the methodology: essential variables related to physical operation to enforce established process performance, and refinement variables related to biological processes that can generate risks of bulking, pin-point floc and rising sludge. The proposed optimization strategy is applied for the treatment of high COD wastewater under nutrient limitation using an integrated mathematical model for COD removal that include predation, hydrolysis and a simplified approach to the limiting solids flux theory in the secondary clarifier in order to facilitate the convergence of the optimization solver. The methodology is implemented in a full-scale wastewater treatment plant for a cellulose and viscose fibre mill obtaining (i) improvement of the effluent quality index (Kg pollution/m3) up to 62% and, (ii) decrease the operating cost index (€/m3) of the process up to 30% respect the regular working operational conditions of the plant. The proposed procedure can be also applied to other biological treatments treating high COD nutrient-limited industrial wastewater such as from textile and winery production among others

Oxygen dependence of metabolic fluxes and energy generation of Saccharomyces cerevisiae CEN.PK113-1A

<p>Abstract</p> <p>Background</p> <p>The yeast <it>Saccharomyces cerevisiae </it>is able to adjust to external oxygen availability by utilizing both respirative and fermentative metabolic modes. Adjusting the metabolic mode involves alteration of the intracellular metabolic fluxes that are determined by the cell's multilevel regulatory network. Oxygen is a major determinant of the physiology of <it>S. cerevisiae </it>but understanding of the oxygen dependence of intracellular flux distributions is still scarce.</p> <p>Results</p> <p>Metabolic flux distributions of <it>S. cerevisiae </it>CEN.PK113-1A growing in glucose-limited chemostat cultures at a dilution rate of 0.1 h^-1with 20.9%, 2.8%, 1.0%, 0.5% or 0.0% O₂in the inlet gas were quantified by ¹³C-MFA. Metabolic flux ratios from fractional [U-¹³C]glucose labelling experiments were used to solve the underdetermined MFA system of central carbon metabolism of <it>S. cerevisiae</it>.</p> <p>While ethanol production was observed already in 2.8% oxygen, only minor differences in the flux distribution were observed, compared to fully aerobic conditions. However, in 1.0% and 0.5% oxygen the respiratory rate was severely restricted, resulting in progressively reduced fluxes through the TCA cycle and the direction of major fluxes to the fermentative pathway. A redistribution of fluxes was observed in all branching points of central carbon metabolism. Yet only when oxygen provision was reduced to 0.5%, was the biomass yield exceeded by the yields of ethanol and CO₂. Respirative ATP generation provided 59% of the ATP demand in fully aerobic conditions and still a substantial 25% in 0.5% oxygenation. An extensive redistribution of fluxes was observed in anaerobic conditions compared to all the aerobic conditions. Positive correlation between the transcriptional levels of metabolic enzymes and the corresponding fluxes in the different oxygenation conditions was found only in the respirative pathway.</p> <p>Conclusion</p> <p>¹³C-constrained MFA enabled quantitative determination of intracellular fluxes in conditions of different redox challenges without including redox cofactors in metabolite mass balances. A redistribution of fluxes was observed not only for respirative, respiro-fermentative and fermentative metabolisms, but also for cells grown with 2.8%, 1.0% and 0.5% oxygen. Although the cellular metabolism was respiro-fermentative in each of these low oxygen conditions, the actual amount of oxygen available resulted in different contributions through respirative and fermentative pathways.</p

Genome-Scale Reconstruction and Analysis of the Pseudomonas putida KT2440 Metabolic Network Facilitates Applications in Biotechnology

A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, 13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype–phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential

Monitoring biological wastewater treatment processes: Recent advances in spectroscopy applications

Biological processes based on aerobic and anaerobic technologies have been continuously developed to wastewater treatment and are currently routinely employed to reduce the contaminants discharge levels in the environment. However, most methodologies commonly applied for monitoring key parameters are labor intensive, time-consuming and just provide a snapshot of the process. Thus, spectroscopy applications in biological processes are, nowadays, considered a rapid and effective alternative technology for real-time monitoring though still lacking implementation in full-scale plants. In this review, the application of spectroscopic techniques to aerobic and anaerobic systems is addressed focusing on UV--Vis, infrared, and fluorescence spectroscopy. Furthermore, chemometric techniques, valuable tools to extract the relevant data, are also referred. To that effect, a detailed analysis is performed for aerobic and anaerobic systems to summarize the findings that have been obtained since 2000. Future prospects for the application of spectroscopic techniques in biological wastewater treatment processes are further discussed.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors also acknowledge the financial support to Daniela P. Mesquita and Cristina Quintelas through the postdoctoral Grants (SFRH/BPD/82558/2011 and SFRH/BPD/101338/2014) provided by FCT - Portugal.info:eu-repo/semantics/publishedVersio