Elsevier

Renewable Energy

Volume 181, January 2022, Pages 1034-1045
Renewable Energy

Three-dimensional modeling of photo fermentative biohydrogen generation in a microbioreactor

https://doi.org/10.1016/j.renene.2021.09.120Get rights and content

Highlights

  • Present a refined model of biohydrogen production during photo fermentation.

  • Evaluate the effects of illumination, geometry and velocity on photo fermentation.

  • Accounts for photosynthetic bacteria growth and illumination energy conversion.

  • Provide an integrated modeling tool to improve design of photo microbioreactors.

Abstract

Photo fermentation is an emerging approach of biohydrogen production as it is energy saving and environmentally friendly. Understanding mechanisms of controlling the bacteria growth and biohydrogen production is critical for effective improvements in energy harvest and waste treatment in photo fermentative bioreactors. In this study a comprehensive three-dimensional numerical platform of photo fermentation was developed, based on lattice Boltzmann method coupled with cellular automata. The model accounts for photosynthetic bacteria growth, illumination energy conversion by photosynthetic bacteria, and light transfer under biofilm growth. The results showed a threshold of illumination intensity. Below this threshold, the bioreactor performance increased as the illumination intensity increased. Above the threshold, the performance declined if the illumination intensity rose. The normalized average biohydrogen production at the illumination intensity of 6000lx, increased about 66.31%, 13.82% and 13.12%, respectively, compared to ones at 4000lx, 5000lx and 7000lx. An increase in inlet glucose concentration could increase biohydrogen concentration and extraction but dwindled biohydrogen yield. It was found that a lower inlet velocity had higher biohydrogen production rate and concentration but lower biohydrogen extraction and yield. The results demonstrate that the present LBM-CA platform can be a tool to study and enhance the photo fermentative production of biohydrogen.

Introduction

Hydrogen is a carbon free clean energy source that only produces water without any release of carbon dioxide to the atmosphere during combustion. Besides, it has some other key advantages including high stability of combustion, high efficiency, high energy density (122 kJ/g) and storage. Hence, hydrogen would play a pivotal role in replacing fossil fuels in future biofuel and renewable energy economy [1,2]. However, there are some concerns associated with main conventional processes of hydrogen production, such as cracking of natural gas or residual oil, coal gasification and water electrolysis, as these processes consume large amount of fossil fuels, leading to an increase of the greenhouse gas emissions [[2], [3], [4]]. To solve these problems, some environmentally friendly bioconversion technologies are developed, such as anoxic/oxygenic photosynthesis, dark fermentation and photo-fermentation [[5], [6], [7], [8], [9]]. Because bioconversion processes use a wide variety of feedstock, this characteristic makes it possible to produce biohydrogen for increasing energy and economic security in almost every region of earth [3]. Especially, using waste for hydrogen production has two-fold benefits: energy harvest and waste treatment. Consequently, numerous studies have been conducted to study the effects of different parameters on photo fermentation [[10], [11], [12], [13]].

Compared to dark fermentation, a photo fermentation by photosynthetic bacteria (PSB) has demonstrated higher theoretical substrate conversion efficiency, much higher rate of hydrogen production, and less by-product formation without involving oxygen [5,6,14,15]. Light and solar energy can be used in increasing hydrogen production from biomass using photosynthetic bacteria [16]. Due to this special capability, it is believed that renewable energy sources could be efficiently recovered from organic waste using photo fermentation [14]. Tian et al. [17] used a photobioreactor to study the effects of different parameters on biohydrogen production using a cell immobilization technique. They found that the optimal performance was reached at the glucose concentration of 0.12 M, the wavelength of 590 nm, and the pH of 7 when the light illumination intensity was at 5000 lx. Liu et al. [18] investigated the effects of substrate concentration and enzyme load on biohydrogen production through photo-fermentation from microalgae biomass. Their results agreed well with the Gompertz model. Policastro et al. [19] investigated the effects of initial chemical oxygen demand and the available nitrogen source on the photo fermentative biohydrogen production from winery wastewater. Their results showed that the winery wastewater was a promising substrate for photo fermentation processes.

However, photo fermentation has some disadvantages, including high energy requirement during nitrogenase-catalyzed reaction and low biohydrogen production efficiencies. Budiman and Wu [20] indicated the important effects of different chemical addition on biohydrogen in photo fermentation processes. It is also found that low biohydrogen production rate of PSB is mainly due to low cell growth rate and inefficient light energy utilization. Therefore, many efforts have been made to find solution in increasing the biohydrogen yield of photo fermentation and light conversion efficiency achieving an industrial feasibility [20]. Increasing biomass retention and light efficiency are two main approaches [[21], [22], [23], [24], [25], [26], [27]]. The immobilization process of biomass could be an effective tactic in increasing biomass volumetric retention and biohydrogen production in bioreactor [17,21]. The renewable solar energy could be utilized as a luminous energy. Some multi-layered photobioreactors (MLPR) have been developed to increase light conversion efficiency in hydrogen production [28]. Kondo et al. [28] showed that the hydrogen productivity in the MLPR was twice as much as that in a plate-type reactor. Chen and Chang [27] implemented three strategies to enhance biohydrogen production: 1) acetate used as the sole carbon substrate, 2) addition of solid carriers (activated carbon, silica gel, and clay) to fermentation broth, and 3) internal optical-fiber illumination system. Their results demonstrated that a high efficiency of photo fermentative production was stably sustained for more than 17 days. Liao et al. [21] investigated experimentally the effects of operational parameters on biohydrogen production performance. They showed that the performance was greatly dependent to the illumination conditions. The highest hydrogen production rates were observed under 590 nm wavelength and 5000 lx illumination.

However, because biofilm growth needs relatively long time to be completed (in order of several hours), large-scale experiments of photo fermentation could be expensive. Furthermore, due to effects of a number of parameters, including their low throughput, the need of large volumes of species (that are usually expensive), these make it difficult to control spatial and temporal distribution of biofilm community formation [29]. Fortunately, microfluidic devices such as microbioreactors are considered as a promising solution to address the mentioned problems associated with large scale experimental setups because of their small volumes and sizes and higher surface-to-volume ratios. Because photo fermentation process is a complex interaction among species (substrates and products) mass transport, bioreactions and biofilm growth, luminous energy calculation, and fluid flow, it is crucial to understand how microbioreactor performance is affected by operating parameters such as nutrients concentration, temperature and fluid velocity. For example, it was shown that increasing fluid velocity had different effects on the efficiency of bioreactor [9,30]. While the velocity increased the species mass transport for proper biofilm growth and fermentation, it could cause a higher shear stress, leading to lower biofilm growth due to an increase of detachment of biofilm. Therefore, even though a high efficiency of light to hydrogen conversion was observed in the laboratory scale, the efficiency might be reproduced under industrial applications. There is a need to improve the organisms and the reactor system performance.

Direct simulation of the biofilm growth is promising for the scaling-up of bioreactors. Based on the concept of distribution function, lattice Boltzmann model (LBM) is mesoscopic approach that can recover governing equations of transport phenomenon, including momentum, energy and mass transfer. Compared to traditional computational fluid dynamics (CFD) methods, LBM benefits from some key advantages, including easy handling of complex geometries and boundary condition, pressure field (no need to solve the computationally expensive Poisson equation), and interface interactions. Liao et al. [5,6] used LBM to study the effects of fluid velocity, illumination intensity, and accumulation mode of particles on fluid flow and photo biohydrogen production in a packed bed bioreactor. They found the highest performance was at an illumination intensity of 6000 lx. Increasing influent velocity decreased the performance. Despite success, the above LBM for hydrogen production did not consider the effects of biofilm growth. Particularly, the biofilm growth could significantly affect substrate transport. This in turn affects biohydrogen productivity. In the recent years, cellular automata (CA) have been coupled with LBM to simulate biofilm growth at lattice grids if a set of rules is given [9,30]. In this type of coupled models of biofilm growth, the spatiotemporal fields of velocity and species concentration could be simulated using LBM while the pattern of biofilm growth is captured using CA. This makes it attractive to study pattern changes in phenomenon, such as biofilm growth, shrinkage and detachment. As a result, a coupled LBM and CA approach is suitable tool for modelling of biofilm growth in a system of fluid, biomass and solid [9,[30], [31], [32]]. To the best of our knowledge, no studies have been reported that a coupled LBM and CA platform is used for the simulation of coupled biofilm growth and photo fermentation. Therefore, three issues remain to be addressed in modelling photo fermentation within a coupled LBM and CA platform: 1) illumination energy conversion by photosynthetic bacteria, 2) light transfer under biofilm growth, and 3) coupling photosynthetic bacteria growth with LBM and CA.

In this study, a numerical platform based on lattice Boltzmann method coupled with cellular automata is developed to investigate photo fermentative biohydrogen production in an obstacle microbioreactor. This is the first time that using a 3D pore-scale model of photo fermentation investigates effects of opacity and shading of obstacles and biofilm growth on photo fermentative biohydrogen production in a microbioreactor. The platform is used to evaluate the effects of different illumination intensity, inlet velocity and concentration on biofilm growth and biohydrogen production.

Section snippets

Photo fermentation model

In a single-stage photo fermentation, a range of suitable substrates including industrial waste, sugars, organic acids, agricultural waste and acidic effluents can be used for hydrogen production [24]. Photo fermentation uses photosynthetic bacteria (PSB) to produce biohydrogen through a light-driven biochemical route [33,34]. A group of phototrophic bacteria enables for photosynthesis. Bacteria commonly used in photo fermentation are Enterbacter aerogens, Clostridium butyricum, Enterobacter

Results and discussion

In this section, the main processes characterizing the micro scale biofilm growth and biohydrogen production during photo fermentation in a microbioreactor are examined in detail in terms of effects of illumination, inlet fluid velocity and glucose concentration. To better compare the effects of investigated parameters, the parameters are normalized using their base model (the model based on values in Table 1) as below:

Normalized time, t=ttmax

Normalized biohydrogen production rate in the

Conclusion

Photo fermentation is promising to produce hydrogen, as a carbon free, high energy density source, through an integrated utilization of the solar energy and bioconversion of waste treatment. In this study, a LBM-CA platform was developed for numerical simulation of photo fermentative processes. The model was successfully implemented to evaluate the effects of illumination density, inlet velocity, and inlet concentration on both biofilm growth and biohydrogen production in a 3D microbioreactor.

CRediT authorship contribution statement

Mojtaba Aghajani Delavar: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing – original draft, Visualization. Junye Wang: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing – review & editing, Supervision, Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by Natural Sciences and Engineering Research Council of Canada (No.: RGPIN-2019-07071) and Compute Canada.

References (41)

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