Biomedical subjects

C Picioreanu

Publications and source records attributed to C Picioreanu.

17 recordsLinked to original sources

PubMed2007

Kinetic model of a granular sludge SBR: influences on nutrient removal.

A mathematical model was developed that can be used to describe an aerobic granular sludge reactor, fed with a defined influent, capable of simultaneously removing COD, nitrogen and phosphate in one sequencing batch reactor (SBR). The model described the experimental data from this complex system sufficiently. The effect of process parameters on the nutrient removal rates could therefore be reliably evaluated. The influence of oxygen concentration, temperature, granule diameter, sludge loading rate, and cycle configuration were analyzed. Oxygen penetration depth in combination with the position of the autotrophic biomass played a crucial role in the conversion rates of the different components and thus on overall nutrient removal efficiencies. The ratio between aerobic and anoxic volume in the granule strongly determines the N-removal efficiency as it was shown by model simulations with varying oxygen concentration, temperature, and granule size. The optimum granule diameter for maximum N- and P-removal in the standard case operating conditions (DO 2 mg L(-1), 20 degrees C) was found between 1.2 and 1.4 mm and the optimum COD loading rate was 1.9 kg COD m(-3) day(-1). When all ammonia is oxidized, oxygen diffuses to the core of the granule inhibiting the denitrification process. In order to optimize the process, anoxic phases can be implemented in the SBR-cycle configuration, leading to a more efficient overall N-removal. Phosphate removal efficiency mainly depends on the sludge age; if the SRT exceeds 30 days not enough biomass is removed from the system to keep effluent phosphate concentrations low.

Ammonia↗

PubMed2006

Multidimensional modelling to investigate interspecies hydrogen transfer in anaerobic biofilms.

Anaerobic digestion is a multistep process, mediated by a functionally and phylogenetically diverse microbial population. One of the crucial steps is oxidation of organic acids, with electron transfer via hydrogen or formate from acetogenic bacteria to methanogens. This syntrophic microbiological process is strongly restricted by a thermodynamic limitation on the allowable hydrogen or formate concentration. In order to study this process in more detail, we developed an individual-based biofilm model which enables to describe the processes at a microbial resolution. The biochemical model is the ADM1, implemented in a multidimensional domain. With this model, we evaluated three important issues for the syntrophic relationship: (i) Is there a fundamental difference in using hydrogen or formate as electron carrier? (ii) Does a thermodynamic-based inhibition function produced substantially different results from an empirical function? and; (iii) Does the physical co-location of acetogens and methanogens follow directly from a general model. Hydrogen or formate as electron carrier had no substantial impact on model results. Standard inhibition functions or thermodynamic inhibition function gave similar results at larger substrate field grid sizes (> 10 microm), but at smaller grid sizes, the thermodynamic-based function reduced the number of cells with long interspecies distances (> 2.5 microm). Therefore, a very fine grid resolution is needed to reflect differences between the thermodynamic function, and a more generic inhibition form. The co-location of syntrophic bacteria was well predicted without a need to assume a microbiological based mechanism (e.g., through chemotaxis) of biofilm formation.

Bacteria, Anaerobic↗

PubMed2006

Global impact and application of the anaerobic ammonium-oxidizing (anammox) bacteria.

In the anaerobic ammonium oxidation (anammox) process, ammonia is oxidized with nitrite as primary electron acceptor under strictly anoxic conditions. The reaction is catalysed by a specialized group of planctomycete-like bacteria. These anammox bacteria use a complex reaction mechanism involving hydrazine as an intermediate. The reactions are assumed to be carried out in a unique prokaryotic organelle, the anammoxosome. This organelle is surrounded by ladderane lipids, which make the organelle nearly impermeable to hydrazine and protons. The localization of the major anammox protein, hydrazine oxidoreductase, was determined via immunogold labelling to be inside the anammoxosome. The anammox bacteria have been detected in many marine and freshwater ecosystems and were estimated to contribute up to 50% of oceanic nitrogen loss. Furthermore, the anammox process is currently implemented in water treatment for the low-cost removal of ammonia from high-strength waste streams. Recent findings suggested that the anammox bacteria may also use organic acids to convert nitrate and nitrite into dinitrogen gas when ammonia is in short supply.

Acids↗

PubMed2006

Role of nitrogen oxides in the metabolism of ammonia-oxidizing bacteria.

Ammonia-oxidizing bacteria (AOB) can use oxygen and nitrite as electron acceptors. Nitrite reduction by Nitrosomonas is observed under three conditions: (i) hydrogen-dependent denitrification, (ii) anoxic ammonia oxidation with nitrogen dioxide (NO(2)) and (iii) NO(x)-induced aerobic ammonia oxidation. NO(x) molecules play an important role in the conversion of ammonia and nitrite by AOB. Absence of nitric oxide (NO), which is generally detectable during ammonia oxidation, severely impairs ammonia oxidation by AOB. The lag phase of recovery of aerobic ammonia oxidation was significantly reduced by NO(2) addition. Acetylene inhibition tests showed that NO(2)-dependent and oxygen-dependent ammonia oxidation can be distinguished. Addition of NO(x) increased specific activity of ammonia oxidation, growth rate and denitrification capacity. Together, these findings resulted in a hypothetical model on the role of NO(x) in ammonia oxidation: the NO(x) cycle.

Ammonia↗

PubMed2005

Multidimensional modelling of anaerobic granules.

A multispecies, two- and three-dimensional model was developed, based on a previously published planar biofilm model, and the biochemical structure of the ADM1. Several soluble substrates diffuse and react in the granule. Local pH is calculated from acid-base equilibria and charge balance. The model uses individual-based representation of biomass particles within the granule (biofilm), and describes spreading by an iterative pushing technique. The overall computational domain consists of one granule, and is divided into a grid with Cartesian coordinates. The number of grid elements does not limit the number of biomass particles, and it is not necessary to use grid-spreading techniques, such as cellular automata, which result in Cartesian artefacts. The model represents both microscopic and macroscopic features in granule structure, previously observed using in-situ molecular techniques, and can be effectively used to interpret these results.

Acetates↗

PubMed2004

Comparing biofilm models for a single species biofilm system.

A benchmark problem was defined to evaluate the performance of different mathematical biofilm models. The biofilm consisted of heterotrophic bacteria degrading organic substrate and oxygen. Mathematical models tested ranged from simple analytical to multidimensional numerical models. For simple and more or less flat biofilms it was shown that analytical biofilm models provide very similar results compared to more complex numerical solutions. When considering a heterogeneous biofilm morphology it was shown that the effect of an increased external mass transfer resistance was much more significant compared to the effect of an increased surface area inside the biofilm.

Bacteria↗

PubMed2004

Modelling a spatially heterogeneous biofilm and the bulk fluid: selected results from benchmark problem 2 (BM2).

The numerical simulation of mass transfer and conversion in spatially heterogeneous biofilms on the meso-scale requires an accurate description of the hydrodynamics in the biofilm systems and of spatial effects. This leads to systems of three-dimensional nonlinear partial differential equations that are numerically very expensive to solve and to data requirements that are not easy to meet. In this paper several modeling approaches to reduce the physical complexity and, hence, accelerate the computation are compared. They range from a mere reduction of dimensionality by lumping the problem along a secondary flow direction to global mass balances or empirical correlations, at the core of which a one-dimensional boundary value problem must be solved. It is found that even strongly simplified models can describe the qualitative behaviour of the model with regard to variations in the geometrical and hydrodynamic model parameters quite well. In order to obtain also quantitatively reliable results the hydrodynamics must be considered in an appropriate manner.

Bacteria↗

PubMed2004

Results from the multi-species benchmark problem 3 (BM3) using two-dimensional models.

In addition to the one-dimensional solutions of a multi-species benchmark problem (BM3) presented earlier (Rittmann et al., 2004), we offer solutions using two-dimensional (2-D) models. Both 2-D models (called here DN and CP) used numerical solutions to BM3 based on a similar mathematical framework of the one-dimensional AQUASIM-built models submitted by Wanner (model W) and Morgenroth (model M1), described in detail elsewhere (Rittmann et al., 2004). The CP model used differential equations to simulate substrate gradients and biomass growth and a particle-based approach to describe biomass division and biofilm growth. The DN model simulated substrate and biomass using a cellular automaton approach. For several conditions stipulated in BM3, the multidimensional models provided very similar results to the 1-D models in terms of bulk substrate concentrations and fluxes into the biofilm. The similarity can be attributed to the definition of BM3, which restricted the problem to a flat biofilm in contact with a completely mixed liquid phase, and therefore, without any salient characteristics to be captured in a multidimensional domain. On the other hand, the models predicted significantly different accumulations of the different types of biomass, likely reflecting differences in the way biomass spread within the biofilm is simulated.

Bacteria↗

PubMed2004

Assessment of three-dimensional biofilm models through direct comparison with confocal microscopy imaging.

The mathematical modeling of spatial biofilm formation that provides the capability to predict biofilm structure from first principles has been in development for the past six years. However, a direct and quantitative link between model predictions and the experimentally observed structure formation still remains to be established. This work assesses the capability of a state-of-the-art technique for three-dimensional (3D) modeling of biofilm structure, individual based modeling (IbM), to quantitatively describe the early development of a multispecies denitrifying biofilm. Model evaluation was carried out by comparison of predicted structure with that observed from two experimental datasets using confocal laser scanning microscopy (CLSM) monitoring of biofilm development in laboratory flowcells. Experimental conditions provided biofilm growth without substrate limitation, which was confirmed from substrate profiles computed by the model. 3D structures were compared quantitatively using a set of morphological parameters including the biovolume, filled-space profiles, substratum coverage, average thickness and normalized roughness. In spite of the different morphologies detectable in the two independent short-term experiments analyzed here, the model was capable of accurate fitting data from both experiments. Prediction of structure formation was precise, as expressed by the set of morphology parameters used.

Bacteria↗

PubMed2002

Mathematical modelling of biofilm structures.

The morphology of biofilms received much attention in the last years. Several concepts to explain the development of biofilm structures have been proposed. We believe that biofilm structure formation depends on physical as well as general and specific biological factors. The physical factors (e.g. governing substrate transport) as well as general biological factors such as growth yield and substrate conversion rates are the basic factors governing structure formation. Specific strain dependent factors will modify these, giving a further variation between different biofilm systems. Biofilm formation seems to be primarily dependent on the interaction between mass transport and conversion processes. When a biofilm is strongly diffusion limited it will tend to become a heterogeneous and porous structure. When the conversion is the rate-limiting step, the biofilm will tend to become homogenous and compact. On top of these two processes, detachment processes play a significant role. In systems with a high detachment (or shear) force, detachment will be in the form of erosion, giving smoother biofilms. Systems with a low detachment force tend to give a more porous biofilm and detachment occurs mainly by sloughing. Biofilm structure results from the interplay between these interactions (mass transfer, conversion rates, detachment forces) making it difficult to study systems taking only one of these factors into account.

Bacteria↗

PubMed2001

Two-dimensional model of biofilm detachment caused by internal stress from liquid flow.

A two-dimensional model for biofilm growth and detachment was used to evaluate the effect of detachment on biofilm structures. The detachment process is considered to be due to internal stress created by moving liquid past the biofilm. This model generated a variety of realistic biofilm-formation patterns. It was possible to model in a unified way two different biofilm detachment processes, erosion (small-particle loss), and sloughing (large-biomass-particle removal). The distribution of the fraction from total biomass detached as a function of detached particle mass, gives indications about which of the two mechanisms is dominant. Model simulations indicate that erosion makes the biofilm surface smoother. Sloughing, in contrast, leads to an increased biofilm-surface roughness. Faster growing biofilms have a faster detachment rate than slow-growing biofilms, under similar hydrodynamic conditions and biofilm strength. This is in perfect accordance with the experimental evidence showing that detachment is dependent on both shear- and microbial-growth rates. High growth rates trigger instability in biofilm accumulation and abrupt biomass loss (sloughing). Massive sloughing can be avoided by high liquid shear, combined with low biomass growth rates. As the modeling results show, the causes for sloughing must be sought not only in the biofilm strength, but also in its shape. Several "mushroom-like" biofilm structures like those repeatedly reported in the literature occurred, due to a combined effect of nutrient depletion and breaking at the colony base. A rough carrier surface promotes biofilm development in hydrodynamic conditions in which the biofilm on a flat surface would not form. Although biofilm patches filled completely the cavity in which they started to grow, they were unable to spill over the carrier peaks and to fully colonize the substratum.

Algorithms↗

PubMed2001

Individual-based modelling of biofilms.

Understanding the emergence of the complex organization of biofilms from the interactions of its parts, individual cells and their environment, is the aim of the individual-based modelling (IbM) approach. This IbM is version 2 of BacSim, a model of Escherichia coli colony growth, which was developed into a two-dimensional multi-substrate, multi-species model of nitrifying biofilms. It was compared with the established biomass-based model (BbM) of Picioreanu and others. Both models assume that biofilm growth is due to the processes of diffusion, reaction and growth (including biomass growth, division and spreading). In the IbM, each bacterium was a spherical cell in continuous space and had variable growth parameters. Spreading of biomass occurred by shoving of cells to minimize overlap between cells. In the BbM, biomass was distributed in a discrete grid and each species had uniform growth parameters. Spreading of biomass occurred by cellular automata rules. In the IbM, the effect of random variation of growth parameters of individual bacteria was negligible in contrast to the E. coli colony model, because the heterogeneity of substrate concentrations in the biofilm was more important. The growth of a single cell into a clone, and therefore also the growth of the less abundant species, depended on the randomly chosen site of attachment, owing to the heterogeneity of substrate concentrations in the biofilm. The IbM agreed with the BbM regarding the overall growth of the biofilm, due to the same diffusion-reaction processes. However, the biofilm shape was different due to the different biomass spreading mechanisms. The IbM biofilm was more confluent and rounded due to the steady, deterministic and directionally unconstrained spreading of the bacteria. Since the biofilm shape is influenced by the spreading mechanism, it is partially independent of growth, which is driven by diffusion-reaction. Chance in initial attachment events modifies the biofilm shape and the growth of single cells because of the high heterogeneity of substrate concentrations in the biofilm, which again results from the interaction of diffusion-reaction with spreading. This stresses the primary importance of spreading and chance in addition to diffusion-reaction in the emergence of the complexity of the biofilm community.

Algorithms↗

PubMed2000

Effect of diffusive and convective substrate transport on biofilm structure formation: a two-dimensional modeling study.

A two-dimensional model for quantitative evaluation of the effect of convective and diffusive substrate transport on biofilm heterogeneity was developed. The model includes flow computation around the irregular biofilm surface, substrate mass transfer by convection and diffusion, biomass growth, and biomass spreading. It was found that in the absence of detachment, biofilm heterogeneity is mainly determined by internal mass transfer rate of substrates and by the initial percentage of carrier-surface colonization. Model predictions show that biofilm structures with highly irregular surface develop in the mass transfer-limited regime. As the nutrient availability increases, there is a gradual shift toward compact and smooth biofilms. A smaller fraction of colonized carrier surface leads to a patchy biofilm. Biofilm surface irregularity and deep vertical channels are, in this case, caused by the inability of the colonies to spread over the whole substratum surface. The maximum substrate flux to the biofilm was greatly influenced by both internal and external mass transfer rates, but not affected by the inoculation density. In general, results of the present model were similar to those obtained by a simple diffusion-reaction-growth model.

Algorithms↗

PubMed2000

A theoretical study on the effect of surface roughness on mass transport and transformation in biofilms.

This modeling study evaluates the influence of biofilm geometrical characteristics on substrate mass transfer and conversion rates. A spatially two-dimensional model was used to compute laminar fluid flow, substrate mass transport, and conversion in irregularly shaped biofilms. The flow velocity above the biofilm surface was varied over 3 orders of magnitude. Numerical results show that increased biofilm roughness does not necessarily lead to an enhancement of either conversion rates or external mass transfer. The average mass transfer coefficient and Sherwood numbers were found to decrease almost linearly with biofilm area enlargement in the flow regime tested. The influence of flow, biofilm geometry and biofilm activity on external mass transfer could be quantified by Sh-Re correlations. The effect of biofilm surface roughness was incorporated in this correlation via area enlargement. Conversion rates could be best correlated to biofilm compactness. The more compact the biofilm, the higher the global conversion rate of substrate. Although an increase of bulk fluid velocity showed a large effect on mass transfer coefficients, the global substrate conversion rate per carrier area was less affected. If only diffusion occurs in pores and channels, then rough biofilms behave as if they were compact but having less biomass activity. In spite of the fact that the real biofilm area is increased due to roughness, the effective mass transfer area is actually decreased because only biofilm peaks receive substrate. This can be explained by the fact that in the absence of normal convection in the biofilm valleys, the substrate gradients are still largely perpendicular to the carrier. Even in the cases where convective transport dominates the external mass transfer process, roughness could lead to decreased conversion rates. The results of this study clearly indicate that only evaluation of overall conversion rates or mass fluxes can describe the correct biofilm conversion, whereas interpretation of local concentration or flow measurements as such might easily lead to erroneous conclusions.

Biofilms↗

PubMed1998

Influence of biomass production and detachment forces on biofilm structures in a biofilm airlift suspension reactor

The influence of process conditions (substrate loading rate and detachment force) on the structure of biofilms grown on basalt particles in a Biofilm Airlift Suspension (BAS) reactor was studied. The structure of the biofilms (density, surface shape, and thickness) and microbial characteristics (biomass yield) were investigated at substrate loading rates of 5, 10, 15, and 20 kg COD/m3. day with basalt concentrations of 60 g/L, 150 g/L, and 250 g/L. The basalt concentration determines the number of biofilm particles in steady state, which is the main determining factor for the biofilm detachment in these systems. In total, 12 experimental runs were performed. A high biofilm density (up to 67 g/L) and a high biomass concentration was observed at high detachment forces. The higher biomass content is associated with a lower biomass substrate loading rate and therefore with a lower biomass yield (from 0.4 down to 0.12 gbiomass/gacetate). Contrary to general beliefs, the observed biomass detachment decreased with increasing detachment force. In addition, smoother (fewer protuberances), denser and thinner compact biofilms were obtained when the biomass surface production rate decreased and/or the detachment force increased. These observations confirmed a hypothesis, postulated earlier by Van Loosdrecht et al. (1995b), that the balance between biofilm substrate surface loading (proportional to biomass surface production rate, when biomass yield is constant) and detachment force determines the biofilm structure. When detachment forces are relatively high only a patchy biofilm will develop, whereas at low detachment forces, the biofilm becomes highly heterogeneous with many pores and protuberances. With the right balance, smooth, dense and stable biofilms can be obtained. Copyright 1998 John Wiley & Sons, Inc.

Journal Article↗

PubMed1998

Mathematical modeling of biofilm structure with a hybrid differential-discrete cellular automaton approach.

A hybrid differential-discrete mathematical model has been used to simulate biofilm structures (surface shape, roughness, porosity) as a result of microbial growth in different environmental conditions. In this study, quantitative two- and three-dimensional models were evaluated by introducing statistical measures to characterize the complete biofilm structure, both the surface structure and volume structure. The surface enlargement, coefficient of roughness, fractal dimension of surface, biofilm compactness, and solids hold-up were found to be good measures of biofilm structure complexity. Among many possible factors affecting the biofilm structure, the influence of biomass growth in relation to the diffusive substrate transport was investigated. Porous biofilms, with many channels and voids between the "finger-like" or "mushroom" outgrowth, were obtained in a substrate-transport-limited regime. Conversely, compact and dense biofilms occurred in systems limited by the biomass growth rate and not by the substrate transfer rate. The surface complexity measures (enlargement, roughness, fractal dimension) all increased with increased transport limitation, whereas the volume measures (compactness, solid hold-up) decreased, showing the change from a compact and dense to a highly porous and open biofilm.

Automation↗

PubMed1998

A new combined differential-discrete cellular automaton approach for biofilm modeling: application for growth in gel beads.

The theoretical basis and quantitative evaluation of a new approach for modeling biofilm growth are presented here. Soluble components (e.g., substrates) are represented in a continuous field, whereas discrete mapping is used for solid components (e.g., biomass). The spatial distribution of substrate is calculated by applying relaxation methods to the reaction-diffusion mass balance. A biomass density map is determined from direct integration in each grid cell of a substrate-limited growth equation. Spreading and distribution of biomass is modeled by a discrete cellular automaton algorithm. The ability of this model to represent diffusion-reaction-microbial growth systems was tested for a well-characterized system: immobilized cells growing in spherical gel beads. Good quantitative agreement with data for global oxygen consumption rate was found. The calculated concentration profiles of substrate and biomass in gel beads corresponded to those measured. Moreover, it was possible, using the discrete spreading algorithm, to predict the spatial two- and three-dimensional distribution of microorganisms in relation to, for example, substrate flux and inoculation density. The new technique looks promising for modeling diffusion-reaction-microbial growth processes in heterogeneous systems as they occur in biofilms.

Algorithms↗