Comprehensive modeling of methanogenic biofilms in fluidized bed systems: Mass transfer limitations and multisubstrate aspects

Abstract

A cognitive model for anaerobic digestion in fluidized bed reactors is developed. The general pathway of the process is divided into five main reactions performed by different bacterial groups. Molecular diffusion of each substrate involved in the reaction scheme is described. Effectiveness factor calculations are performed in steady state for each bacterial group taken into account in the process. The case of a single substrate removal is discussed, and optimal biofilm sizes are found. Sequential substrate removal is investigated, and different kinetic regimes are characterized. The influence of biofilm size and primary substrate removal is discussed in the case of standard concentrations in the liquid phase. This study shows that, according to the theoretical model the limiting step of the process may be different and depends in a large way on mass transfer effects. Finally, importance of biofilm size is compared for acidogenic and methano-genic steps: each reaction is found to be optimized for different biofilm thicknesses. This result may be of interest for design purposes and further dynamic modeling. Concluding remarks concerning the validation of the model are made, and a comparison to experimental data from the literature is presented. (c) 1995 John Wiley & Sons, Inc.

Magnetic Resonance Imaging of Structure, Diffusivity, and Copper Immobilization in a Phototrophic Biofilm

“…Although the key transport medium within a biofilm is water, the molecular diffusion of a molecule through a biofilm is commonly slower than it is in free water due to the lower permeability of the biofilm and the tortuous nature of any pathways. Consequently, the diffusion of nutrients (or indeed contaminants) can be the rate-limiting step in biofilm performance and can lead to steep chemical and redox gradients through the community (4,6,9,17,23). For that reason, direct measurements of biofilm diffusion properties are highly desirable when modeling biofilm function (3,40).…”

Application of Paramagnetically Tagged Molecules for Magnetic Resonance Imaging of Biofilm Mass Transport Processes

“…5B. A linear least-squares fit to these data gives R ϭ 1.7125S ϩ 6.5306 (8) where S is the solids content of the biofilm. The solids content of the actual biofilm sample used during the flowthrough experiment was measured to be 1.2%, and from the above linear relationship (equation 8), the R value of that biofilm sample was estimated as 8.58 s Ϫ1 mM Ϫ1 .…”

“…The rate at which these metabolites are transported through the biofilm can be critical in controlling the performance of the biofilm (5,8,13,31). Equally, the rate at which the biofilm can sequester nonmetabolizable pollutants, such as nonmetabolizable heavy metals and recalcitrant organics, is also mediated by the transport rate (9,28).…”

To the mathematical modeling of microbial community of methane cycle

“…328] и ссылки там). Во-вторых, для описания роста метанотрофов с помощью уравнения Моно накоплено большое количество экспериментальных данных (см., например, [Buffiere et al, 1995;Grant and Roulet, 2002]), что позволяет проверять качество используемых в модели параметров. Результаты и обсуждение Важнейшим требованием к математической модели является требование ее адекватности (правильного соответствия) изучаемому реальному объекту относительно выбранной системы его свойств.…”

“…Но и в немногих структурных моделях (например, [Cao et al, 1995[Cao et al, , 1998Arah and Stephen, 1998;Glagolev, 1998;Walter and Heimann, 2000]), где более подробно описываются процессы образования, окисления и транспорта метана, авторы в лучшем случае рассматривают лишь физику процессов транспорта, почти не касаясь специфики микробиологических механизмов образования и окисления СН 4 . На наш взгляд незаслуженно мало внимания при моделировании цикла метана в природных экосистемах было уделено структурным микробиологическим моделям (таким как, например, "Ecosys" [Grant, 1998;Grant and Roulet, 2002] и "Methane" [Vavilin et al, 1994]), основанным на детальном описании микробиологических процессов и с успехом применявшихся ранее при математическом моделировании биореакторов, систем анаэробной очистки воды и полигонов захоронения твердых бытовых отходов (см., например, [Эндрюс, 1981;Vavilin et al, 1994;Buffiere et al, 1995;El-Fadel et al, 1996]). …”