Using a carbon-based ASM3 EAWAG Bio-P for modelling the enhanced biological phosphorus removal in anaerobic/aerobic activated sludge systems

Trutnau, Mirko; Petzold, Martin; Mehlig, Lysann; Eschenhagen, Martin; Geipel, Katja; Müller, Susann; Bley, Thomas; Röske, I.

doi:10.1007/s00449-010-0470-2

Cited by 4 publications

(1 citation statement)

References 18 publications

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“…Even though many engineers rely on ASM to characterize bioreactors properties and design 11 , there is active research to introduce additional levels of detail 12 . Some of the limitations of ASM are due to oversimplified model representation (functional groups) and parameterization 13 .…”

Section: Mathematical Models In Environmental Biotechnologymentioning

confidence: 99%

Towards Predictive Models of the Human Gut Microbiome

Bucci

Xavier

2014

Journal of Molecular Biology

109

106

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The intestinal microbiota is an ecosystem susceptible to external perturbations such as dietary changes and antibiotic therapies. Mathematical models of microbial communities could be of great value in the rational design of microbiota-tailoring diets and therapies. Here, we discuss how advances in another field, engineering of microbial communities for wastewater treatment bioreactors, could inspire development of mechanistic mathematical models of the gut microbiota. We review the current state-of-the-art in bioreactor modeling and current efforts in modeling the intestinal microbiota. Mathematical modeling could benefit greatly from the deluge of data emerging from metagenomic studies, but data-driven approaches such as network inference that aim to predict microbiome dynamics without explicit mechanistic knowledge seem better suited to model these data. Finally, we discuss how the integration of microbiome shotgun sequencing and metabolic modeling approaches such as flux balance analysis may fulfill the promise of a mechanistic model of the intestinal microbiota.

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Section: Mathematical Models In Environmental Biotechnologymentioning

confidence: 99%

Towards Predictive Models of the Human Gut Microbiome

Bucci

Xavier

2014

Journal of Molecular Biology

109

106

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Activated sludge model 2d calibration with full-scale WWTP data: comparing model parameter identifiability with influent and operational uncertainty

Machado

Lafuente

Baeza

2013

Bioprocess Biosyst Eng

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The present work developed a model for the description of a full-scale wastewater treatment plant (WWTP) (Manresa, Catalonia, Spain) for further plant upgrades based on the systematic parameter calibration of the activated sludge model 2d (ASM2d) using a methodology based on the Fisher information matrix. The influent was characterized for the application of the ASM2d and the confidence interval of the calibrated parameters was also assessed. No expert knowledge was necessary for model calibration and a huge available plant database was converted into more useful information. The effect of the influent and operating variables on the model fit was also studied using these variables as calibrating parameters and keeping the ASM2d kinetic and stoichiometric parameters, which traditionally are the calibration parameters, at their default values. Such an "inversion" of the traditional way of model fitting allowed evaluating the sensitivity of the main model outputs regarding the influent and the operating variables changes. This new approach is able to evaluate the capacity of the operational variables used by the WWTP feedback control loops to overcome external disturbances in the influent and kinetic/stoichiometric model parameters uncertainties. In addition, the study of the influence of operating variables on the model outputs provides useful information to select input and output variables in decentralized control structures.

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