Flux balancing of light and nutrients in a biofilm photobioreactor for maximizing photosynthetic productivity

Abstract

This article reports a combined experimental and numerical study on the efficient operation of Porous Substrate Bioreactors. A comprehensive model integrating light transport, mass transport, and algal growth kinetics was used to understand the productivity of photosynthetic biofilms in response to delivery rates of photons and nutrients. The reactor under consideration was an evaporation driven Porous Substrate Bioreactor (PSBR) cultivating the cyanobacteria Anabaena variabilis as a biofilm on a porous substrate which delivers water and nutrients to the cells. In an unoptimized experimental case, this reactor was operated with a photosynthetic efficiency of 2.3%, competitive with conventional photobioreactors. Moreover, through a scaling analysis, the location at which the phosphate delivery rate decreased the growth rate to half of its uninhibited value was predicted as a function of microorganism and bioreactor properties. The numerical model along with the flux balancing techniques presented herein can serve as tools for designing and selecting operating parameters of biofilm based cultivation systems for maximum productivity.

Microscale profiling of photosynthesis‐related variables in a highly productive biofilm photobioreactor

“…Using the equation provided by Morel and Hering (), the total [DIC] at the biofilm surface can be calculated as (considering that the hydration of CO 2 at the biofilm surface is instantaneous, which is the ideal case): H CO2 is the Henry's constant for CO 2 , and has a value of 0.304 mM kpa −1 ; p CO2 is the CO 2 partial pressure in the gas phase, K a1 and K a2 are the dissociation coefficients of carbonic acid and bicarbonate ion, with value of 10 −6.3 and 10 −10.3 , respectively; pH surface is the measured pH value at the biofilm surface (Murphy and Berberoglu, ; Wolf et al, ). Distribution of the total [DIC] at depth x can be acquired from a transformation of mass balance equation: D e,DIC is the effective diffusion coefficient of DICs in biofilm, and was assumed to equal the value of bicarbonate ions, which has a value of 1.18 × 10 −9 m 2 s −1 in pure water (Murphy and Berberoglu, ). DIC speciation at depth x was calculated from the measured pH profiles: …”

“…An efficient type of biofilm bioreactor features a non‐submerged biofilm exposed directly to light and gas phase, and separated from the bulk of culture medium by a fine‐porous sheet‐like material (e.g., a microporous membrane). The principle of this biofilm bioreactor was introduced a decade ago by Podola and Melkonian () as the “Twin‐Layer” (Nowack et al, ), now referred to in a more general term as “porous substrate bioreactors” (PSBRs) (Murphy and Berberoglu, ). Compared to other photobioreactors (e.g.…”

Microalgae production in a biofilm photobioreactor

“…Therefore, photosynthetic sugar production (q s,p,ph ) is not only dependent on light but also on the DIC concentration. This dependency is described with the Monod Equation (Equation 6.1) (Li et al 2016;Murphy and Berberoglu 2014;Wolf et al 2007) for which a half saturation constant (K s,DIC ) measured under conditions with only HCO 3 -1 (Lin et al 2003) was employed which is most representative for DIC limitation in the deeper biofilm layers. Because multiplication of limiting factors can underestimate the productivity, the lowest sugar production rate (q s,p ) is selected by Equation 6.4 (Wolf et al 2007).…”

“…Monoalgal biofilm growth has been mathematically modelled for light and nutrient limited growth under continuous light by fitting the models to experimental data (Li et al 2016;Murphy and Berberoglu 2014). These studies focused on nutrient limitations inside the biofilm by including diffusion and convection driven nutrient transport through the biofilm (Li et al 2015a;Li et al 2016).…”

“…For microalgal biofilm cultivation, however, processes with minimal CO 2 loss have not been developed, though it has been demonstrated that elevated CO 2 levels are required for maximal productivity Ji et al 2013a;Schultze et al 2015). Models are available that can mathematically predict CO 2 limited biofilm growth (Li et al 2016;Murphy and Berberoglu 2014;Wolf et al 2007). By including additional mass balances, these biofilm models can be utilized to maximize CO 2 utilization and biomass productivity.…”