Modeling the effects of light and temperature on algae growth: State of the art and critical assessment for productivity prediction during outdoor cultivation

Spatiotemporal dynamics of succession and growth limitation of phytoplankton for nutrients and light in a large shallow lake

Understanding the limiting factors of phytoplankton growth and competition is crucial for the restoration of aquatic ecosystems. However, the role and synergistic effect of co-varying environmental conditions, such as nutrients and light on the succession of phytoplankton community remains unclear. In this study, a hydrodynamic-ecological modeling approach was developed to explore phytoplankton growth and succession under co-varying environmental conditions (nutrients, total suspended solids (TSS) and variable N:P ratios) in a large shallow lake called Lake Chagan, in Northeast China. A phytoplankton bloom model was nested in the ecological modeling approach. In contrast to the traditonal ecological modeling, competition between phytoplankton species in our study was modeled at both the species/functional group and phenotype levels. Six phytoplankton functional groups, namely diatoms, green algae, Anabaena, Microcystis, Aphanizomenon and Oscillatoria and each of them with three limitation types (i.e., light-limitation, nitrogen-limitation and phosphorus-limitation) were included in the bloom model. Our results demonstrated that the average biomass proportion of the three limitation types (light-limitation, nitrogen-limitation and phosphorus-limitation) in the six phytoplankton function groups accounted for approximately 50%, 37% and 23% of the total phytoplankton biomass, respectively. TSS suppressed the growth of diatoms and green algae, but favored the dominance of cyanobacteria in Lake Chagan, especially in the turbid water phase (TSS ≥ 60 mg/L). In addition, it was reported that the potential of either N-fixing or non-N-fixing cyanobacterial blooming along the gradients of N:P ratios could exist under the influence of the co-environmental factors in the lake. The proportion of non-N-fixing cyanobacteria (i.e., Microcystis and Oscillatoria) exceeded the proportion of N-fixing cyanobacteria (i.e., Anabaena and Aphanizomenon) when the N:P ratios exceeded 20. Non-N-fixing cyanobacteria would become dominant at higher TSS concentrations and lower light intensities in the turbid water. N-fixing cyanobacteria favored lower N:P ratios and higher light intensities in the clearwater phase (where TSS ≤ 60 mg/L). To sustain a good ecological status in the lake, our results suggest that nutrient and TSS levels in the lake should be maintained at or below the thresholds (TN ≤ 1.5 mg/L; TP ≤ 0.1 mg/L; N:P ratios between 15 and 20; and TSS ≤ 60 mg/L). These findings can help improve water quality management practices to restore aquatic ecosystems.

European Union Green Deal and the Opportunity Cost of Wastewater Treatment Projects

The European Union Green Deal aims at curbing greenhouse gas emissions and introducing clean energy production. But to achieve energy efficiency, the opportunity cost of different energies must be assessed. In this article, two different energy self-sufficient systems for wastewater treatment are compared. On the one hand, high-rate algal ponds system (HRAP) is considered; on the other hand, a conventional activated sludge system (AS) which uses photovoltaic power (PV) is studied. The paper offers a viability analysis of both systems based on the capacity to satisfy their energetic consumption. This viability analysis, along with the opportunity cost study, will be used in the article to compare these two projects devoted to the treatment of wastewater. In order to assess viability, the probability of not achieving the energy consumption threshold at least one day is studied. The results point that the AS+PV system self-sufficiency is achieved with much lesser land requirements than the HRAP system (for the former, less than 6500 m2, for the latter 40,000 m2). However, the important AS capital cost makes still the HRAP system more economic, although storage provides a great advantage for using the AS+PV in locations where a lot of irradiance is available.

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Investigating algae for CO2 capture and accumulation and simultaneous production of biomass for biodiesel production

Carbon capture and sequestration technologies are used to reduce carbon emissions. Membranes, solvents, and adsorbents are the three major methods of CO₂ capture. One of the promising methods is the use of algae to absorb CO₂ from flue gases and convert it into biomass. Algae have great potential as renewable fuel sources and CO₂ capture using photosynthesis for carbon fixation has also attracted much attention. This paper presents an extensive and in-depth report on the utilization of algae for carbon capture and accumulation. This is done in conjunction with cultivating the algae for the production of biomass for biodiesel production. Different systems are investigated for algae cultivation as well as carbon capture to effectively mitigate carbon emissions. The performance and productivity of these biosystems depend on various conditions including algae type, light sources, nutrients, pH, temperature, and mass transfer. Macroalgae and microalgae species were explored to determine their suitability for carbon capture and sequestration, along with the production of biodiesel. The steps for producing biodiesel were comprehensively reviewed, which are harvesting, dehydrating, oil extraction, oil refining, and transesterification. This technology combines active carbon capture with the potential of biodiesel production.

Modeling the Influence of Temperature, Light Intensity and Oxygen Concentration on Microalgal Growth Rate

Dissolved oxygen plays a key role in microalgal growth at high density. This effect was so far rarely quantified. Here we propose a new model to represent the combined effect of light, oxygen concentration and temperature (LOT-model) on microalgae growth. The LOT-model introduces oxygen concentration in order to represent the oxidative stress affecting the cultures, adding a toxicity term in the expression of the net growth rate. The model was validated with experimental data for several species such as Chlorella minutissima, Chlorella vulgaris, Dunaliella salina, Isochrysis galbana. It successfully predicted experimental records with an average error lower than 5.5%. The model was also validated using dynamical data where oxygen concentration varies. It highlights a strong impact of oxygen concentration on productivity, depending on temperature. The model quantifies the sensitivity to oxidative stress of different species and shows, for example, that Dunaliella salina is much less affected than Chlorella vulgaris by oxidative stress. The modeling approach can support an optimization strategy to improve productivity, especially for managing high oxygen levels.

Predictive model development and simulation of photobioreactors for algal biomass growth estimation

In the current scenario of energy requirement and the commercialization aspect of algal biofuel and biomass, it is important that means of predicting the production be available. In this paper, the mathematical models are developed for the tubular, bubble column and airlift photobioreactors to predict the productivity of the algal biomass. A modified Monod kinetic equation, incorporating the effect of nutrient and CO2 concentrations, light availability and oxygen built-up, is used to the estimate specific growth rate of the biomass. The light availability inside the reactor is defined in terms of the modified Beer–Lambert’s law as a function of distance from the surface where light is incident and the cell mass concentration. This allows a more accurate measurement of the shading effect. The equations are solved for different reactor types and their estimated productivities are successfully validated against values available in published literature. The model predicts comparatively better productivity for the tubular reactor (1.5 g/L day) than the bubble column and airlift reactor (1.42 and 1.35 g/L day respectively) because tubular reactor has shorter light/dark cycles and better light availability. The analysis is also done to identify the effect of nutrient, carbon dioxide, light and hydrodynamics on the overall productivity.

Prediction of maximum algal productivity in membrane bioreactors with a light-dependent growth model

Algal productivity in steady-state cultivation systems depends on important factors such as biomass concentration, solids retention time (SRT), and light intensity. Current modeling of algal growth often ignores light distribution in algal cultivation systems and does not consider all these factors simultaneously. We developed a new algal growth model using a first principles approach to incorporate the effect of light intensity on algal growth while simultaneously considering biomass concentration and SRT. We first measured light attenuation (decay) with depth in an indoor algal membrane bioreactor (A-MBR) cultivating Chlorella sp. We then simulated the light decay using a multi-layer approach and correlated the decay with biomass concentration and SRT in model development. The model was calibrated by delineating specific light absorptivity and half-saturation constant to match the algal biomass concentration in the A-MBR operated at a target SRT. We finally applied the model to predict the maximum algal productivity in both indoor and outdoor A-MBRs. The predicted maximum algal productivities in indoor and outdoor A-MBRs were 6.7 g·m^-2·d^-1 (incident light intensity 5732 lx, SRT approximately 8 d) and 28 g·m^-2·d^-1 (sunlight intensity 28,660 lx, SRT approximately 4 d), respectively. The model can be extended to include other factors (e.g., water temperature and carbon dioxide bubbling) and such a modeling framework can be applied to full-scale, continuous flow outdoor systems to improve algal productivity.

Real-time ensemble microalgae growth forecasting with data assimilation

Accurate short-range (e.g., 7 days) microalgae growth forecasts will be beneficial for both the production and harvesting of microalgae. This study developed an operational microalgae growth forecasting system comprised of the Huesemann Algae Biomass Growth Model (BGM), the Modular Aquatic Simulation System in Two Dimensions (MASS2) hydrodynamic model, and ensemble data assimilation (DA). The novelty of this study is the use of ensemble DA to sequentially update the BGM model's initial condition (IC) with the assimilation of measured biomass optical density to improve short-range biomass forecasting skills. The forecasting system was run in pseudo-real-time and validated against observed Monoraphidium minutum 26B-AM growth in two outdoor pond cultures located in Mesa, Arizona, United States. We found the DA forecasting system could improve the 7-day microalgae forecasting skill by about 85% on average compared to model forecasts without DA. These results suggest the potential accuracy of biomass growth forecasts may be sufficient to inform real-time operational decisions, such as pond operation and harvest planning, for commercial-scale microalgae production.

Assessment and management of lake eutrophication: A case study in Lake Erhai, China

Some wastewater sources, such as agricultural waste and runoff, and industrial sewage, can degrade water quality. This study summarises the sources and corresponding mechanisms that trigger eutrophication in lakes. Additionally, the trophic status index and water quality index (WQI) which are effective tools for evaluating the degree of eutrophication of lakes, have been discussed. This study also explores the main nutrients (nitrogen and phosphorus) driving transformations in the water body and sediment. Lake Erhai was used as a case study, and it was found to be in a mesotrophic state, with N and P co-limitation before 2006, and only P limitation since 2006. Finally, effective measures to maintain sustainable development in the watershed are proposed, along with a framework for an early warning system adopting the latest technologies (geographic information systems (GIS), remote sensing (RS)) for preventing eutrophication.

Indirect regulation of temperature in raceway reactors by optimal management of culture depth

Temperature and irradiance are the two most relevant factors determining the performance of microalgae cultures in open raceway reactors. Moreover, inadequate temperature strongly reduces the biomass productivity in these systems even if enough sunlight is available. Controlling the temperature in large open raceway reactors is considered unaffordable because of the large amount of energy required. This study presents an indirect method for temperature regulation in microalgae raceway reactors by optimizing the culture depth. First, the effect of the culture depth on the raceway temperature is analyzed for different seasons of the year. Afterward, a simulation study is presented where the proposed control approach is compared to the normal operation mode with constant volume in the reactor. This study is also extended to industrial scale. Relevant improvements on the temperature factor and biomass production are presented. The developed knowledge allows the improvement of the performance in open raceway reactors up to 12% without involving additional energy and costs, being a suitable solution for large industrial reactors that until now have no options for controlling the temperature.

Various potential techniques to reduce the water footprint of microalgal biomass production for biofuel-A review

Due to their rapid growth rates, high lipid productivity, and ability to synthesize value-added products, microalgae are considered as the potential biofuel feedstocks. However, among the several bottlenecks that are hindering the commercialization of microalgal biofuel synthesis, the issue of high water consumption is the least explored. This analysis, therefore, examines the factors that decide water use for the production of microalgae biofuel. Microalgae biodiesel water footprint varies from 3.5 to 3726 kg of water per kg of biodiesel. The study further investigates the cause for large variability in the estimation of the water footprint for microalgae fuel. Various strategies, including the reuse of harvested water, the use of high density cultivation that could be adopted for low water consumption in microalgal biofuel production are discussed. Specifically, the review identified a reciprocal relationship between biomass productivity and water footprint. On the basis of which the review emphasizes the significance of high density cultivation, which can be inexpensive and feasible relative to other water-saving techniques. With the setback of water scarcity due to the rapid industrialization in developing countries, the implementation of the cultivation system with a focus on minimizing the water consumption is inevitable for a successful large scale microalgal biofuel production.

Modeling of photosynthesis and respiration rate for microalgae-bacteria consortia

In this article, the influence of culture conditions (irradiance, temperature, pH, and dissolved oxygen) on the photosynthesis and the respiration rates of microalgae-bacteria consortia in wastewater treatment was analyzed. Specifically, some short photo-respirometric experiments, simulating outdoor raceway reactors, were performed to evaluate the response of microalgae, heterotrophic bacteria, and nitrifying bacteria to variations in environmental parameters. Results demonstrate that irradiance is the most dominant variable to determine microalgae photosynthesis rates. However, reduction in microalgae activity was not observed at higher irradiance, ruling out the existence of photoinhibition phenomena. Related to heterotrophic and nitrifying bacteria, their activities were strongly affected by the influence of temperature and pH. Moreover, the effect of dissolved oxygen concentrations on microalgae, and bacteria activities was studied, displaying a reduced photosynthetic rate at dissolved oxygen concentrations above 20 mg/L. Data have been used to develop an integrated model for each population (microalgae, heterotrophic bacteria, and nitrifying bacteria) based on considering the simultaneous influence of irradiance, temperature, pH, and dissolved oxygen. The models fit the experimental results in the range of culture conditions tested, and they were validated using data obtained by the simultaneous modifications of the variables. These individual models serve as a basis for developing a global biologic microalgae-bacteria model for wastewater treatment to improve the optimal design and management of microalgae-based processes, especially outdoors, where the cultures are subject to variable daily culture conditions.

Elucidating temperature on mixotrophic cultivation of a Chlorella vulgaris strain: Different carbon source application and enzyme activity revelation

With depletion of fossil fuel, microalgae is considered as a promising substitute due to high growth rate, efficient cost and high biofuels content. This study investigated the effect of temperature on mixotrophic cultivation of Chlorella vulgaris. In addition, the combination carbon source of inorganic (HCO₃^- or CO₃^2-) and organic (glucose or acetate) for microalgae cultivation was evaluated to obtain the optimum carbon source for mixotrophic cultivation. The results showed that the optimum temperature of microalgae cultivation was at the range of 15-20 °C. The activity of Rubisco was obviously inhibited at the temperature of 30 °C, however, citrate synthase was not susceptible to the increasing temperature. COD removal efficiency was all higher than 64.0%. Low temperature was benefit for protein formation, and the lipid accumulation occurred at high temperature. The results provide a fresh perspective between enzyme activity and temperature variation for product accumulation of microalgae.

Models of microalgal cultivation for added-value products - A review

Microalgae are considered a promising feedstock for biorefineries given that their chemical composition - rich in carbohydrate and lipid - can be directed towards the co-production of various value-added fuels and chemicals. Production of microalgal biomass for biorefinery purposes requires the identification and establishment of optimal cultivation systems, a crucial yet complicated task due to the numerous factors (e.g. media composition, light, temperature) that simultaneously regulate biomass growth and intracellular composition. Modelling these biological processes, taking into account a single or multiple growth-limiting factors, offers a valuable tool to simulate, design and optimise the dynamics of microalgae cultivation. This review provides an overview of existing models developed to describe microalgal growth processes at the macroscopic scale (also termed black-box models) and discusses their formulation in detail. The black-box kinetic modelling frameworks are compiled into single-factor (6 formulations) and multiple-factor (32 formulations - further divided into non-interactive, additive, and interactive) growth kinetic models, as reported in more than 80 studies, for the prediction of biomass growth as a function of major operational factors such as media composition (e.g. nutrient concentration) and environmental factors (e.g. transient light and temperature). In addition, the review focuses on those models that further account for the production dynamics of two microalgal intracellular products with renowned potential as biorefinery substrates: carbohydrate and lipid molecules. Models of microalgal cultivation dynamics offer a robust engineering tool to understand the natural yet complex responses of microalgae to their growing environment and can help - if used appropriately - to optimise microalgae cultivation and increase the economic viability and sustainability of microalgal systems.

Multiscale numerical workflow describing microalgae motion and light pattern incidence towards population growth in a photobioreactor

In this article, a numerical workflow describing the microalgal growth inside of a photobioreactor is proposed. CFD is used to compute reactor internal hydrodynamics taking into account marine impeller rotation and sparged bubbles motion. Lagrangian approach is used to track microalgae motion inside of the culture vessel. The illumination across the reactor is obtained using the classical Beer-Lambert's law. The combination of light field and cell motion allows to reconstruct the light history of each microalgae. These histories are then supplied to Han's model which predicts individual growth rate and experienced photodamages. Once computed, several thousands of trajectories are agglomerated at the population level yielding the photobioreactor performances. After having ensured properties convergence, this procedure is applied to a large range of optical density (0 to 4.0), i.e. cell concentration, and incident light intensities (0 to 2000 μmolPhoton/m2/s). From this exploration, it is possible to determine the photobioreactor response surfaces in terms of growth rate and photodamages. These are latter used to propose an optimal lighting strategy for biomass production - reducing photobioreactor operation time by 16% compared to classical two-step procedure - and assist light induced stress with the aim of triggering secondary metabolites production.

Selection of photosynthesis and respiration models to assess the effect of environmental conditions on mixed microalgae consortia grown on wastewater

This study aimed at evaluating the effects of different environmental conditions (irradiance, temperature, pH and dissolved oxygen) on a microalgae-bacteria consortium cultivated in a pilot-scale open pond and fed on the liquid fraction of anaerobic digestate. A standardized photo-respirometry protocol was followed to evaluate the activity of microalgae under different conditions. Two datasets (specific photosynthetic oxygen production rates and respiratory oxygen consumption rates) were obtained for each environmental parameter, throughout the entire range of conditions found in the outdoor cultivation system. Different kinetic models available in literature were fitted to experimental data and the resulting outputs were compared through model selection estimators, in order to select the most appropriate equations. The proposed set of equations constitute a modelling tool for the prediction of algal growth rates in algae-bacteria systems, as a function of environmental conditions.

Characterization of Chlamydomonas Very High Light-tolerant Mutants for Enhanced Lipid Production

Biodiesel production from microalgae is still not commercially realized due to the high cost of production. High light-tolerance has been suggested as a desirable phenotype for efficient cultivation in large scale production systems under fluctuating outdoor conditions. Nevertheless, it has not been shown if algae with such a phenotype would have better efficiency for lipid production. To determine lipid productivity in high light-tolerant mutants, and to understand the pathways involved in high light-tolerant phenotype, two very high light-tolerant mutants of the green alga Chlamydomonas reinhardtii - CAL028_01_28 and CAL034_01_48 - were selected from eighteen high light-tolerant mutants from the CAL collection. Under high light intensity conditions, and the presence of reactive oxygen species, which are conditions constantly experienced by algae growing in open-pond environments, these strains exhibited higher photosynthetic efficiency and improved survival. The physiological characterization of these mutants revealed that the detoxification of ROS by carotenoids and antioxidant enzymes is crucial for their growth under high light conditions. Neither mutant was affected in terms of its ability to accumulate lipid under nitrogen-depleted condition. More importantly, lipid productivity under high light conditions increased twofold in these mutants compared to that of the wild-type. Taken together, very high light-tolerant mutants confer a high potential for biofuel production under outdoor conditions, and their improved ability to survive under oxidative stress is an important key for efficient growth under outdoor conditions.

Sustainable Production of Nannochloris atomus Biomass Towards Biodiesel Production

Nannochloris atomus (QUCCCM31) is a local marine microalga showing potential to serve as renewable feedstock for biodiesel production. The investigation of the impact of temperature variation and nitrogen concentrations on the biomass and lipid productivities evidenced that biomass productivity increased with the temperature to reach an optimum of 195 mgL−1 d−1 at 30 °C. Similarly, the lipid content was strongly influenced by the elevation of temperature; indeed, it increased up to ~3 folds when the temperature increased from 20 to 40 °C. When both stresses were combined, triacylglycerols and lipid productivity reached a maximum of 45% and 88 mgL−1 d−1, respectively at 40 °C. Cultures under high temperatures along with Nitrogen-Depleted (ND) favored the synthesis of Fatty Acids Methyl Ester (FAMEs) suitable for high quality biodiesel production, whereas cultures conducted at low temperature coupled with Nitrogen-Limited (NL) led to a production of polyunsaturated fatty acids (PUFAs). Our results support the feasibility of cultivating the thermotolerant isolate QUCCCM31 year-round to meet the sustainability challenges of algal biomass production by growing under temperature and nitrogen variations. The presence of omega 3 and 9 fatty acids as valuable co-products will help in reducing the total process cost via biorefinery.

How suspended solids concentration affects nitrification rate in microalgal-bacterial photobioreactors without external aeration

The use of microalgae for the treatment of municipal wastewater makes possible to supply oxygen and save energy, but must be coupled with bacterial nitrification to obtain nitrogen removal efficiency above 90%. This paper explores how the concentration of Total Suspended Solids (TSS, from 0.2 to 3.9 g TSS/L) affects the nitrification kinetic in three microalgal-bacterial consortia treating real municipal wastewater. Two different behaviors were observed: (1) solid-limited kinetic at low TSS concentrations, (2) light-limited kinetic at higher concentrations. For each consortium, an optimal TSS concentration that produced the maximum volumetric ammonium removal rate (around 1.8–2.0 mg N L⁻¹ h⁻¹), was found. The relationship between ammonium removal rate and TSS concentration was then modelled considering bacteria growth, microalgae growth and limitation by dissolved oxygen and light intensity. Assessment of the optimal TSS concentrations makes possible to concentrate the microbial biomass in a photobioreactor while ensuring high kinetics and a low footprint.

Evolution in the photosynthetic oxygen rate of a Cd-resistant strain of Dictyosphaerium chlorelloides by changes in light intensity and temperature

Environmental factors such as temperature and light are the most determinants in the photosynthetic productivity in microalgae. However, under extreme of these conditions, certain resistant microalgae strains possess additional abilities such as growth in the presence of high concentrations of metals and some can improve in combinations of more than one abiotic stress. Therefore, the aim of this research was to evaluate the efficiency in photosynthetic production through the oxygen balance to variations in photon intensity, and under temperature changes in a Cd-resistant strain (Dc^RCd100) compared to the wild-type strain (Dc1M^wt) of Dictyosphaerium chlorelloides. The results showed that the Dc^RCd100 strain has the maximum efficiency at 200  μmol m^-2 s^-1 on photosynthesis net (Pn) (96.32 ± 3.63% nmol O₂ ml^-1 min^-1) as the threshold light saturation, and an adaptation to maintain this maximum photosynthetic gross (Pg) rate at 30 °C (94.99 ± 10.03% nmol O₂ ml^-1 min^-1) due to possible modifications in the photosynthetic apparatus that is reflected in the net evolution rate of O₂ to deal with such evaluated conditions. While, Dc1M^wt strain its maximum photosynthetic efficiency was at 300 μmol m^-2 s^-1 and 21 °C (97.72 ± 2.99 and 99.85 ± 0.30%nmol O₂ ml^-1 min^-1, respectively) and in optimal response to the oxygen balance that is normally achieved by this mesophilic genus. These results provide a new prediction of mechanisms in the oxygen evolution in photosynthesis that rules the correlation between resistance and adaptation to extreme abiotic conditions in metal resistant strains of eukaryotic microalgae.

Microalgal kinetics - a guideline for photobioreactor design and process development

Kinetics generally describes bio‐(chemical) reaction rates in dependence on substrate concentrations. Kinetics for microalgae is often adapted from heterotrophs and lacks mechanistic foundation, e.g. for light harvesting. Using and understanding kinetic equations as the representation of intracellular mechanisms is essential for reasonable comparisons and simulations of growth behavior. Summarizing growth kinetics in one equation does not yield reliable models. Piecewise linear or rational functions may mimic photosynthesis irradiance response curves, but fail to represent the mechanisms. Our modeling approach for photoautotrophic growth comprises physical and kinetic modules with mechanistic foundation extracted from the literature. Splitting the light submodel into the modules for light distribution, light absorption, and photosynthetic sugar production with independent parameters allows the transfer of kinetics between different reactor designs. The consecutive anabolism depends among others on nutrient concentrations. The nutrient uptake kinetics largely impacts carbon partitioning in the reviewed stoichiometry range of cellular constituents. Consecutive metabolic steps mask each other and demand a maximum value understandable as the minimum principle of growth. These fundamental modules need to be clearly distinguished, but may be modified or extended based on process conditions and progress in research. First, discussion of kinetics helps to understand the physiological situation, for which ranges of parameter values are given. Second, kinetics should be used for photobioreactor design, but also for gassing and nutrient optimization. Numerous examples are given for both aspects. Finally, measuring kinetics more comprehensively and precisely will help in improved process development.

Dynamic Modeling of Microalgae Growth and Lipid Production under Transient Light and Nitrogen Conditions

We developed a new dynamic model to characterize how light and nitrogen regulate the cellular processes of photosynthetic microalgae leading to transient changes in the production of neutral lipids, carbohydrates, and biomass. Our model recapitulated the versatile neutral lipid synthesis pathways via (i) carbon reuse from carbohydrate metabolism under nitrogen sufficiency and (ii) fixed carbon redirection under nitrogen depletion. We also characterized the effects of light adaptation, light inhibition hysteresis, and nitrogen limitation on photosynthetic carbon fixation. The formulated model was calibrated and validated with experimental data of Dunaliella viridis cultivated in a lab-scale photobioreactor (PBR) under various light (low/moderate/high) and nitrogen (sufficient/limited) conditions. We conducted the identifiability, uncertainty, and sensitivity analyses to verify the model reliability using the profile likelihood method, the Markov chain Monte Carlo (MCMC) technique, and the extended Fourier Amplitude Sensitivity Test (eFAST). Our model predictions agreed well with experimental observations and suggested potential model improvement by incorporating a lipid degradation mechanism. The insights from our model-driven analysis helped improve the mechanistic understanding of transient algae growth and bioproducts formation under environmental variations and could be applied to optimize biofuel and biomass production.

Effect of design dark fraction on the loss of biomass productivities in photobioreactors

Design dark fraction reflects the unlit part of a microalgal culture system, as for example a hydraulic loop used for temperature or pH regulation, or a circulating pump for mixing purposes. This study investigates the impact of design dark fraction on photosynthetic biomass productivity of the eukaryotic microalgae Chlorella vulgaris. The effect of the volume of the dark fraction and the residence time spent in this dark fraction was investigated with two different nitrogen sources (N-NH₄⁺, N-NO₃^-). Results showed a decrease of biomass productivity when the volume of the dark fraction and the dark residence time increased. Up to 47% loss of biomass productivity could be reached for a design dark fraction [Formula: see text] = 30% of the total culture system volume. This loss was explained as a result of metabolic reactions related to an increase of respiration activity or a decrease of photosynthetic activity in the cells.

Intrinsic kinetic model of photoautotrophic microalgae based on chlorophyll fluorescence analysis

As photoautotrophic microorganisms, microalgae feature complex mechanisms of photosynthesis and light energy transfer and as such studying their intrinsic growth kinetics is fairly difficult. In this article, the quantum yield of photochemical reaction was introduced in a study of microalgal kinetics to establish an intrinsic kinetic model of photoautotrophic microalgal growth. The blue-green algae Synechococcus sp. PCC7942 was used to verify the kinetic model developed using chlorophyll fluorescence analysis and growth kinetics determination. Results indicate that the kinetic model can realistically reflect the light energy utilization efficiency of microalgae as well as their intrinsic growth kinetic characteristics. The model and method proposed in this article may be utilized in intrinsic kinetics studies of photoautotrophic microorganisms.

Laboratory-scale photobiotechnology-current trends and future perspectives

Phototrophic bioprocesses are a promising puzzle piece in future bioeconomy concepts but yet mostly fail for economic reasons. Besides other aspects, this is mainly attributed to the omnipresent issue of optimal light supply impeding scale-up and -down of phototrophic processes according to classic established concepts. This MiniReview examines two current trends in photobiotechnology, namely microscale cultivation and modeling and simulation. Microphotobioreactors are a valuable and promising trend with microfluidic chips and microtiter plates as predominant design concepts. Providing idealized conditions, chip systems are preferably to be used for acquiring physiological data of microalgae while microtiter plate systems are more appropriate for process parameter and medium screenings. However, these systems are far from series technology and significant improvements especially regarding flexible light supply remain crucial. Whereas microscale is less addressed by modeling and simulation so far, benchtop photobioreactor design and operation have successfully been studied using such tools. This particularly includes quantitative model-assisted understanding of mixing, mass transfer, light dispersion and particle tracing as well as their relevance for microalgal performance. The ultimate goal will be to combine physiological data from microphotobioreactors with hybrid models to integrate metabolism and reactor simulation in order to facilitate knowledge-based scale transfer of phototrophic bioprocesses.

Photorespiration in an outdoor alkaline open-photobioreactor used for biogas upgrading

The rates of oxygenic and carbon fixation photosynthetic processes of a microalgae consortium were simultaneously evaluated under steady-state performance in an bench scale alkaline open-system exposed to outdoor conditions in Mexico City. A synthetic methane-free gaseous stream (SMGS) similar to biogas was used as inorganic carbon source and model of biogas upgrading. The microalgae CO₂ fixation rates were calculated through a novel methodology based on an inorganic carbon mass balance under continuous scrubbing of a SMGS similar to biogas, where the influence of pH and temperature time-depended oscillations were successfully incorporated into the mass balances. The oxygenic activity and carbon fixation occurred at different non-stoichiometric rates during the diurnal phase, in average carbon fixation predominated over oxygen production (photosynthesis quotient PQ≈ 0.5 mol O₂ mol^-1 CO₂) indicating photorespiration occurrence mainly under dissolved oxygen concentrations higher than 10 mg L^-1. The oxygen and inorganic carbon mass balances demonstrated that photorespiration and endogenous respiration were responsible for losing up to 66% and 7% respectively of the biomass grew at diurnal periods under optimal conditions. In favoring photorespiration conditions, the microalgae biomass productivity (CO₂ effectively captured) can be severely decreased. A kinetic mathematical model as a function of temperature and irradiance of the oxygenic photosynthetic activity indicated the optimal operation zone for this outdoor alkaline open-photobioreactor, where irradiance was found being the most influential parameter.

Long-term variation of phytoplankton biomass and physiology in Taihu lake as observed via MODIS satellite

Estimation of phytoplankton biomass (noted as phytoplankton carbon, C_phyto) and evaluation of phytoplankton physiology is central to the estimation of primary productivity and the carbon cycle. This issue has been widely considered in oceans but not in inland water. Here, we develop experiential and semi-analytical models, which validated by independent in situ measurement data, respectively, to derive C_phyto and phytoplankton absorption coefficient at 675 nm (a_ph(675)) from MODIS. The effects of nutrients and temperature on the seasonal variation of phytoplankton physiology were assessed through a novel proxy of C_phyto to a_ph(675) ratio (C_phyto/a_ph(675)) over the Lake Taihu, the third largest lake in China. Significant seasonal climatological cycles of C_phyto, a_ph(675) and C_phyto/a_ph(675) were observed in Lake Taihu, especially in Meiliang Bay and Zhushan Bay, where algal blooms occur frequently. The highest C_phyto and a_ph(675) values were observed in summer due to the growth of phytoplankton biomass and chlorophyll-a concentration. Lower values were observed in winter and spring, which are characterized by relatively high total nitrogen levels and low irradiance, owing to the low temperature astricts the algae growth. However, the C_phyto/a_ph(675) shows an opposite trend compared to C_phyto and a_ph(675), which have high values in winter and low values in summer. The analysis of C_phyto, a_ph(675) and C_phyto/a_ph(675) with total phosphorus (TP) levels and temperature indicates that TP are the main positive driver of the increase in C_phyto and a_ph(675) and negatively regulate C_phyto/a_ph(675). Warming promotes an increase in C_phyto and a_ph(675) and restricts C_phyto/a_ph(675) in summer. Biomass and nutrient levels are the primary drivers of the decrease of C_phyto/a_ph(675) in such a typical eutrophic lake. The results present some new findings compared to previous oceanic studies and expand our knowledge in the study of phytoplankton biomass and physiology in eutrophic lakes.

Hydrodynamic performance of floating photobioreactors driven by wave energy

BACKGROUND

Unlike conventional cultivation systems, liquid mixing in floating photobioreactors (PBRs) is solely induced by their hydrodynamic movement in response to waves, and this movement is affected by the wave conditions (wave height and wave period), the PBR configuration and the culture depth. However, to the best of our knowledge, a practical study of the hydrodynamic movements of PBRs has not been previously conducted.

RESULTS

This study aims to investigate the hydrodynamic performance of floating PBRs in response to wave conditions. First, the effects of the experimental wave height (2-10 cm) and wave period (0.8-1.8 s) on movement was investigated using two 1.0 m2 PBR models: a square PBR (1.0 m/1.0 m; length/width) and a rectangular PBR (1.7 m/0.6 m). The results indicated that wave movement became not only more intense with increasing wave height, but also less intense when the wave period decreased. However, the square PBR experienced more intense movement than the rectangular PBR, but also little mooring force. The effects of culture depth (0.5, 1.0 and 2.0 cm) were investigated and the results showed that the culture depth significantly affected the hydrodynamic movements of the PBRs; however, the mooring forces were unaffected. Finally, the movement and mooring-line forces of PBRs equipped with different mooring systems were investigated. The use of two different mooring systems had little effect on PBR movement; however, a mooring system with floaters was able to significantly reduce the mooring line forces compared to a system without floaters. During this study, the greatest force (10.5 N) was found for the rectangular PBR using a mooring system without floaters, whereas the lowest force (0.67 N) was observed for a rectangular PBR using a mooring system with floaters.

CONCLUSIONS

These studies have provided basic data describing the fluid dynamics of floating PBRs; as well as their structural design and scale up. These results also provide guidance for the selection of ocean fields with suitable wave conditions; as well as a proper mooring methods to ensure safe operation.