Experimental analysis and novel modeling of semi-batch photobioreactors operated with Chlorella vulgaris and fed with 100% (v/v) CO2
Highlights
► A novel mathematical model for the growth of C. vulgaris under high CO2 concentration. ► The model is capable of simulating biomass concentration and pH evolution. ► The model is able to successfully describe and predict the experimental data.
Introduction
The production of biofuels from renewable feedstocks is recognized to be critical to fulfill a sustainable economy and face global climate changes [1]. When compared to first-generation biofuel feedstocks, microalgae are characterized by higher growth rates and lipid content which result in larger bio-oil productivities. Moreover, cultivation of microalgae can be carried out in less- and lower-quality lands, thus avoiding the exploitation of arable ones [2]. In addition, cultivation of microalgae might be coupled with the direct bio-capture of CO2 emitted by industrial activities that use fossil fuels for energy generation [3], [4], [5], [6]. Ultimately, when compared to first generation biofuels, microalgae are characterized by a greater environmental sustainability and economic viability [7]. For these reasons, the potential exploitation of microalgae as renewable resource for the production of liquid biofuels is receiving a rising interest mostly driven by the global concerns related to the depletion of fossil fuels supplies and the increase of CO2 levels in the atmosphere [8], [9]. The high potential of algae based biofuels is confirmed by the number of recent papers available in the literature [10] on the subject. In spite of such interest, the existing microalgae-based technology for CO2 sequestration and biofuels production is still not widespread since it is affected by economic and technical constraints that might limit the development of industrial scale production systems. In particular, the main obstacles are related to the extensive land’s areas needed as well as the estimated high costs of the operating phases of microalgae cultivation, harvesting and lipid extraction [11]. Therefore, in view of industrial scaling-up, the current technology should be optimized in terms of selected algal strains as well as design/operating parameters [12]. While the creation of new microalgal strains intrinsically characterized by high lipid productivities is an ambitious goal which can be achieved through genetic manipulation of existing strains [13], [14], the optimization of design and operating parameters may be accomplished by exploiting suitable process engineering techniques. To this aim, mathematical models, that are capable to quantitatively describe the influence of the crucial operating parameters (i.e. photobioreactors geometry, heat and mass transfer conditions, growth medium composition, pH, etc.) on microalgae growth and lipid accumulation, are needed. Several mathematical models of microalgae growth within photobioreactors have been proposed in the literature. So far, the basic characteristics of algal kinetics have been taken into account [15], [16], [17], [18], [19], [20], [21], [22]. In particular, most mathematical models available in the literature were capable of quantitatively describing the evolution of biomass concentration as a function of light density distribution within the culture [15], [16]. Other modeling efforts have been devoted to quantitatively describe the production of photosynthetic oxygen and the corresponding consumption of dissolved carbon dioxide within the culture [18], the pH evolution [21], the mass transfer phenomena [17] and the influence of hydrodynamic regime on light conversion [22]. Recently, the effect of cell size distribution on the nutrient uptake capacity of microalgae has been also simulated by means of suitable population balances [23]. However, in spite of the large number of mathematical analyses available in the literature, to the best of our knowledge, comprehensive models, which simultaneously account for all the above mentioned phenomena taking place, have not been proposed. In particular, very few models were able to quantitatively describe the evolution of pH during photosynthetic growth of microalgae [18]. Moreover, such models were typically characterized by the questionable assumption of steady state conditions and inorganic carbon species as the sole ones able to affect the solution pH [18], while the effect of other ionic species in solution was neglected. Nevertheless, the quantitative description of pH evolution during microalgal growth is crucial since it can influence photosynthetic phenomena in a number of ways. In fact pH can affect the distribution of carbon dioxide species and carbon availability, alter the speciation and thus the availability of macro and micronutrients, and potentially provoke direct physiological effects [24]. Moreover, in microalgal cultures, the hydrogen ion is recognized to be a non-competitive inhibitor near neutral conditions, while it can limit photosynthetic growth and substrate utilization rates at very low or very high pH levels [25]. Furthermore pH can affect the enzymatic activity of intra and extra-cellular carbonic anhydrase thus influencing the carbon capture mechanism of some microalgal strains [26].
Therefore, the quantitative description of pH evolution in microalgal cultures seems to be a key goal in order to properly control and optimize microalgae photobioreactors. Indeed pH variations not only represent a fundamental indicator of the evolution of photosynthetic activity but can also, in turn, strongly influence the growth kinetics of microalgae. In particular, this aspect is of crucial importance when high CO2 concentrated gases, such as flue gases, are used as carbon source. In fact in this case the medium pH can reach very low values that might inhibit microalgae growth. On the other hand, the potential exploitation of costless feedstocks such as flue gases as source of CO2 is one of the main targets of scientists and technicians operating in this field [5], [6]. In fact the use of flue gases as carbon source for microalgae might greatly improve the economic feasibility of the microalgae-based technology while simultaneously producing a positive impact on significant environmental concerns such as air pollution and climate changes. Thus, the correct evaluation of the effect of pH is critical also for assuring the possibility of exploiting/capturing CO2 from flue gases through microalgae. For the above mentioned reasons, microalgae strains capable to survive under elevated CO2 concentration might represent suitable candidate for the industrial cultivation of microalgae for biofuels production and CO2 capture. Among such strains the unicellular eukaryotic green alga Chlorella vulgaris is characterized by high growth rates [27], coupled with a significant lipid content [10]. Moreover C. vulgaris is tolerant to high-temperatures and toxic compounds such as NOx and SOx [28] and is capable to grow in inexpensive media such as wastewaters. In addition, according to Baba and Shiraiwa [29], C. vulgaris is one among those strains which is capable of developing suitable molecular mechanisms that allows its adaptation to extremely high CO2 concentrations. For all these reasons C. vulgaris is potentially one of the more useful strains for biofuels production and CO2 capturing from flue gases.
Consequently, the goal of the present work is to develop a rigorous and comprehensive mathematical model to quantitatively describe the growth of microalgae in semi-batch photobioreactors fed with pure CO2 (100% v/v). In order to validate model results specific experiments were performed with a strain of C. vulgaris previously acclimated to high CO2 concentrations.
Section snippets
Microorganism and culture medium
The fresh water algal strain C. vulgaris (Centro per lo Studio dei Microorganismi Autotrofi di Firenze, Italy) was investigated in this work. Stock cultures were propagated and maintained in Erlenmeyer flasks with a Kolkwitz Triple Modified (KTM-A) medium under incubation conditions of 25 °C, a photon flux density of 98 μmol m−2 s−1 provided by four 15 W white fluorescent tubes, and a light/dark photoperiod of 12 h. Flasks were continuously shaken at 100 rpm (Universal Table Shaker 709).
Strain acclimation to high CO2 concentrations
Acclimation of
Model equations
The approach to simulate the experimental data is based on the classical homogeneous model for stirred tank reactors operated in batch mode for the liquid phase and continuously for the gas phase. The mathematical model reported below is characterized by the following assumptions: constant pressure (P) within the reactor, ideal behavior of the gas phase, negligible gas film resistance, isothermal conditions. Moreover, by considering that pure CO2 was continuously bubbled in the growth medium
Results and discussion
The effect of several operating parameters on the growth kinetics of C. vulgaris was quantitatively simulated in this work. In order to validate model reliability, model results were compared with suitable experimental data. To this aim specific experiments were carried out by cultivating a C. vulgaris strain, previously acclimated to high CO2 concentrations, in a semi-batch stirred tank photobioreactor. First the operating conditions reported in the materials and methods section were adopted.
Conclusions
The mathematical simulation of the growth of high-CO2 acclimated C. vulgaris in a semi-batch photobioreactor fed by pure (100% v/v) CO2 is addressed in this work. In particular, the proposed model simulates temporal evolution of cells, light density and macronutrients concentration within the growth medium as well as carbon dioxide and oxygen concentration in liquid and gas phase. Moreover by taking advantage of comprehensive kinetics and taking into account the ion speciation phenomena taking
Acknowledgments
This work was carried out with the financial support of Sardinian Regional Authorities through the L.R. 7/2007 “Promozione della Ricerca Scientifica e dell’Innovazione Tecnologica in Sardegna – PO Sardegna FSE 2007–2013.
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