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Modeling alginate encapsulation system for biological hydrogen production
Author(s) -
Zhu Kuang,
Arnold William A.,
Novak Paige J.
Publication year - 2019
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.27152
Subject(s) - wastewater , process engineering , biomass (ecology) , hydrogen production , hydrogen , environmental science , chemical engineering , materials science , pulp and paper industry , chemistry , environmental engineering , ecology , organic chemistry , engineering , biology
Abstract Wastewater treatment using encapsulated biomass is a promising approach for high‐rate resource recovery. Encapsulation matrices can be customized to achieve desired biomass retention and mass transport performance. This, in turn, facilitates treatment of different waste streams. In this study, a model was developed to describe calcium‐alginate beads encapsulating hydrogen‐producing biomass, with the goal of enabling appropriate a priori customization of the system. The model was based on a classic diffusion‐reaction model, but also included the growth of encapsulated biomass and product inhibition. Experimental data were used to verify the model, which accurately described the effect of hydraulic retention time, bead size, and feed concentration on resource (hydrogen) recovery from brewery wastewater. Sensitivity analyses revealed that the hydrogen production rate was insensitive to substrate diffusivity and bead size, but sensitive to the substrate partition coefficient, initial encapsulated biomass concentration, and the total volume of beads in the reactor, demonstrating that this system was growth‐limited rather than diffusion‐limited under the tested conditions. Because the model quantifies the relationship between the hydrogen production rate and various input and operating parameters, it should be possible to extend the model to determine the most cost‐effective system for optimal performance with a given waste stream.