Lumped pathway metabolic model of organic carbon accumulation and mobilization by the alga Chlamydomonas reinhardtii

Abreast insights of harnessing microalgal lipids for producing biodiesel: A review of improving and advancing the technical aspects of cultivation

In the pursuit of alternatives for conventional diesel, sourced from non-renewable fossil fuel, biodiesel has gained attentions for its intrinsic benefits. However, the commercial production process for biodiesel is still not sufficiently competitive. This review analyses microalgal lipid, one of the important sources of biodiesel, and its cultivation techniques with recent developments in the technical aspects. In fact, the microalgal lipids are the third generation feedstock, used for biodiesel production after its benefits outweigh that of edible vegetable oils (first generation) and non-edible oils (second generation). The critical factors influencing microalgal growth and its lipid production and accumulation are also discussed. Following that is the internal enhancement for cellular lipid production through genetic engineering. Moreover, the microalgae cultivation data modelling was also rationalized, with a specific focus on growth kinetic models that allow for the prediction and optimization of lipid production. Finally, the machine learning and environmental impact analysis are as well presented as important aspects to consider in fulfilling the prime objective of commercial sustainability to produce microalgal biodiesel.

Theory of Stoichiometric Intraguild Predation: Algae, Ciliate, and Daphnia

Consumers respond differently to external nutrient changes than producers, resulting in a mismatch in elemental composition between them and potentially having a significant impact on their interactions. To explore the responses of herbivores and omnivores to changes in elemental composition in producers, we develop a novel stoichiometric model with an intraguild predation structure. The model is validated using experimental data, and the results show that our model can well capture the growth dynamics of these three species. Theoretical and numerical analyses reveal that the model exhibits complex dynamics, including chaotic-like oscillations and multiple types of bifurcations, and undergoes long transients and regime shifts. Under moderate light intensity and phosphate concentration, these three species can coexist. However, when the light intensity is high or the phosphate concentration is low, the energy enrichment paradox occurs, leading to the extinction of ciliate and Daphnia. Furthermore, if phosphate is sufficient, the competitive effect of ciliate and Daphnia on algae will be dominant, leading to competitive exclusion. Notably, when the phosphorus-to-carbon ratio of ciliate is in a suitable range, the energy enrichment paradox can be avoided, thus promoting the coexistence of species. These findings contribute to a deeper understanding of species coexistence and biodiversity.

Intensive Microalgal Cultivation and Tertiary Phosphorus Recovery from Wastewaters via the EcoRecover Process

Mixed community microalgal wastewater treatment technologies have the potential to advance the limits of technology for biological nutrient recovery while producing a renewable carbon feedstock, but a deeper understanding of their performance is required for system optimization and control. In this study, we characterized the performance of a 568 m3·day-1 Clearas EcoRecover system for tertiary phosphorus removal (and recovery as biomass) at an operating water resource recovery facility (WRRF). The process consists of a (dark) mix tank, photobioreactors (PBRs), and a membrane tank with ultrafiltration membranes for the separation of hydraulic and solids residence times. Through continuous online monitoring, long-term on-site monitoring, and on-site batch experiments, we demonstrate (i) the importance of carbohydrate storage in PBRs to support phosphorus uptake under dark conditions in the mix tank and (ii) the potential for polyphosphate accumulation in the mixed algal communities. Over a 3-month winter period with limited outside influences (e.g., no major upstream process changes), the effluent total phosphorus (TP) concentration was 0.03 ± 0.03 mg-P·L-1 (0.01 ± 0.02 mg-P·L-1 orthophosphate). Core microbial community taxa included Chlorella spp., Scenedesmus spp., and Monoraphidium spp., and key indicators of stable performance included near-neutral pH, sufficient alkalinity, and a diel rhythm in dissolved oxygen.

Effects of feast-famine nutrient regimes on wastewater algal biofuel communities

Microalgae accumulate lipids in response to nutrient deprivation, and these lipids are a biodiesel fuel stock. Algal cultivation with secondary wastewater effluent is one proposed platform for biofuel production, which provides nutrients to algae while further polishing wastewater effluent. Algal bioreactors were tested using a feast-famine feeding regiment in simulated secondary wastewater effluent to evaluate the effects on lipid content and algal community structure. Algal polycultures were inoculated into reactors fed with synthetic secondary wastewater effluent at pH 7.5 and 9 and operated under a feast-famine nutrient (N, P, and BOD) supply regime in sequencing batch reactors. Fatty acid methyl ester contents of the reactors were assessed, which showed a decrease in lipid content after the feast-famine cycling (from 12.2% initially to 5.2% after four cycles at pH 9). This decrease in lipid content was not correlated with an increase in carbohydrate storage within biomass, nor an increase in bacterial biomass abundance relative to algal biomass in the reactors. The eukaryotic microbial communities from reactors operated at pH 9 diverged from reactors operated at pH 7.5 during cycling, with the pH 9 reactors becoming dominated by a single Operational Taxonomic Unit aligning to the Scenedesmus genus. These results suggest that high pH and feast-famine nutrient cycling may select for a less diverse algal community with a lower lipid content within a secondary wastewater polishing scheme.

Solids Residence Time Impacts Carbon Dynamics and Bioenergy Feedstock Potential in Phototrophic Wastewater Treatment Systems

The use of wastewater-grown microalgae has the potential to reduce the cost of algae-derived biofuels while simultaneously advancing nutrient recovery at water resource recovery facilities (WRRFs). However, a significant barrier has been the low yield and high protein content of phototrophic biomass. Here, we examine the use of solids residence time (SRT) as a selective pressure in driving biochemical composition, yield, biofuel production, and WRRF nutrient management cost. We cultivated mixed phototrophic communities in controlled, laboratory-scale photobioreactors on the local WRRF secondary effluent to link SRT with biochemical composition and techno-economic analysis to yield insights into biomass composition and downstream processing effects on minimum fuel selling price. SRT significantly impacted biochemical composition, with total and dynamic carbohydrates the highest at low SRT (total carbohydrates being 0.60 and 0.32 mg-carbohydrate·mg-protein^-1 at SRT 5 and 15 days, respectively). However, there were distinct differences between extant, steady-state performance and intrinsic potential, and longer SRT communities were able to accumulate significant fractions (51% on an ash-free dry weight basis, AFDW %) of carbohydrate reserves under nutrient starvation. Overall, hydrothermal liquefaction (HTL) was found to be more suitable than lipid extraction for hydrotreating (LEH) and combined algal processing (CAP) for conversion of biomass to fuels, but LEH and CAP became more competitive when intrinsic carbon storage potential was realized. The results suggest that the use of algae for nutrient recovery could reduce the nutrient management cost at WRRFs through revenue from algal biofuels, with HTL resulting in a net revenue.

Sustainable disposal of excess sludge: Incineration without anaerobic digestion

Handling excess sludge produced by wastewater treatment is a common problem worldwide. Due to limited space available in landfills, as well as difficulties involved in using excess sludge in agriculture, there is a need for alternative disposal methods. Although anaerobic digestion (AD) is widely used in processing sludge, only partial energy recovery from methane and sludge volume reduction can be achieved, resulting in a substantial amount of sludge remaining, which needs to be disposed of. Direct incineration after sludge drying is one possible option, a practice that is already in place in some cities in China. A comparison between direct incineration and conventional AD (with or without pretreatment by thermal hydrolysis) has to be made with respect to the energy balance and investment & operational (I & O) costs. This comparison reveals direct incineration to have the lowest energy deficit and I & O costs. Therefore, it is expected that direct incineration without AD will become the preferred sustainable approach to handling sludge.

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.

Impact of solids residence time on community structure and nutrient dynamics of mixed phototrophic wastewater treatment systems

Suspended growth, mixed community phototrophic wastewater treatment systems (including high-rate algal ponds and photobioreactors) have the potential to achieve biological nitrogen and phosphorus recovery with effluent nutrient concentrations below the current limit-of-technology. In order to achieve reliable and predictive performance, it is necessary to establish a thorough understanding of how design and operational decisions influence the complex community structure governing nutrient recovery in these systems. Solids residence time (SRT), a critical operational parameter governing growth rate, was leveraged as a selective pressure to shape microbial community structure in laboratory-scale photobioreactors fed secondary effluent from a local wastewater treatment plant. In order to decouple the effects of SRT and hydraulic retention time (HRT), nutrient loading was fixed across all experimental conditions and the effect of changing SRT on microbial community structure, diversity, and stability, as well as its impact on nutrient recovery, was characterized. Reactors were operated at distinct SRTs (5, 10, and 15 days) with diurnal lighting over long-term operation (>6 SRTs), and in-depth examination of the eukaryotic and bacterial community structure was performed using amplicon-based sequencing of the 18S and 16S rRNA genes, respectively. In order to better represent the microalgal community structure, this study leveraged improved 18S rRNA gene primers that have been shown to provide a more accurate representation of the wastewater process-relevant algal community members. Long-term operation resulted in distinct eukaryotic communities across SRTs, independent of the relative abundance of Operational Taxonomic Units (OTUs) in the inoculum. The longest SRT (15 days, SRT 15) resulted in a more stable algal community along with stable bacterial nitrification, while the shortest SRT (5 days, SRT 5) resulted in a less stable, more dynamic community. Although SRT was not strongly associated with overall bacterial diversity, the eukaryotic community of SRT 15 was significantly less diverse and less even than SRT 5, with a few dominant OTUs making up a majority of the eukaryotic community structure in the former. Overall, although longer SRTs promote stable bacterial nitrification, short SRTs promote higher eukaryotic diversity, increased functional stability, and better total N removal via biomass assimilation. These results indicate that SRT may be a key factor in not only controlling microalgal community membership, but community diversity and functional stability as well. Ultimately, the efficacy and reliability of NH₄⁺ removal may be in tension with TN removal in mixed phototrophic systems given that lower SRTs may achieve better total N removal (via biomass assimilation) through increased eukaryotic diversity, biomass productivity, and functional stability.

Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review

Microalgal and cyanobacterial resource recovery systems could significantly advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology. The successful implementation of phytoplankton, however, requires the formulation of process models that balance fidelity and simplicity to accurately simulate dynamic performance in response to environmental conditions. This work synthesizes the range of model structures that have been leveraged for algae and cyanobacteria modeling and core model features that are required to enable reliable process modeling in the context of water resource recovery facilities. Results from an extensive literature review of over 300 published phytoplankton models are presented, with particular attention to similarities with and differences from existing strategies to model chemotrophic wastewater treatment processes (e.g., via the Activated Sludge Models, ASMs). Building on published process models, the core requirements of a model structure for algal and cyanobacterial processes are presented, including detailed recommendations for the prediction of growth (under phototrophic, heterotrophic, and mixotrophic conditions), nutrient uptake, carbon uptake and storage, and respiration.

Comparable Nutrient Uptake across Diel Cycles by Three Distinct Phototrophic Communities

The capacity of microalgae to advance the limit of technology of nutrient recovery and accumulate storage carbon make them promising candidates for wastewater treatment. However, the extent to which these capabilities are influenced by microbial community composition remains poorly understood. To address this knowledge gap, 3 mixed phototrophic communities sourced from distinct latitudes within the continental United States (28° N, Tampa, FL; 36° N, Durham, NC; and 40° N, Urbana, IL) were operated in sequencing batch reactors (8 day solids residence time, SRT) subjected to identical diel light cycles with media addition at the start of the nighttime period. Despite persistent differences in community structure as determined via 18S rRNA (V4 and V8-V9 hypervariable regions) and 16S rRNA (V1-V3) gene amplicon sequencing, reactors achieved similar and stable nutrient recovery after 2 months (8 SRTs) of operation. Intrinsic carbohydrate and lipid storage capacity and maximum specific carbon storage rates differed significantly across communities despite consistent levels of observed carbon storage across reactors. This work supports the assertion that distinct algal communities cultivated under a common selective environment can achieve consistent performance while maintaining independent community structures and intrinsic carbon storage capabilities, providing further motivation for the development of engineered phototrophic processes for wastewater management.

A Unified Modeling Framework to Advance Biofuel Production from Microalgae

Modeling efforts to understand the financial implications of microalgal biofuels often assume a static basis for microalgae biomass composition and cost, which has constrained cultivation and downstream conversion process design and limited in-depth understanding of their interdependencies. For this work, a dynamic biological cultivation model was integrated with thermo-chemical/biological unit process models for downstream biorefineries to increase modeling fidelity, to provide mechanistic links among unit operations, and to quantify minimum product selling prices of biofuels via techno-economic analysis. Variability in design, cultivation, and conversion parameters were characterized through Monte Carlo simulation, and sensitivity analyses were conducted to identify key cost and fuel yield drivers. Cultivating biomass to achieve the minimum biomass selling price or to achieve maximum lipid content were shown to lead to suboptimal fuel production costs. Depending on biomass composition, both hydrothermal liquefaction and a biochemical fractionation process (combined algal processing) were shown to have advantageous minimum product selling prices, which supports continued investment in multiple conversion pathways. Ultimately, this work demonstrates a clear need to leverage integrated modeling platforms to advance microalgae biofuel systems as a whole, and specific recommendations are made for the prioritization of research and development pathways to achieve economical biofuel production from microalgae.

Quantitative Evaluation of an Integrated System for Valorization of Wastewater Algae as Bio-oil, Fuel Gas, and Fertilizer Products

Algal systems have emerged as a promising strategy for simultaneous treatment and valorization of wastewater. However, further advancement and real-world implementation are hindered by the limited knowledge on the full energetic and nutrient product potentials of such systems and the corresponding value of these products. In this work, an aqueous-based system for the conversion of wastewater-derived algae and upgrading of crude products was designed and demonstrated. Bio-oil, fuel gas, and fertilizer products were generated from algal biomass harvested from a municipal wastewater treatment facility. Experiments showed that 68% of chemical energy contained in the algal biomass could be recovered with 44% in upgraded bio-oil and 23% in fuel gas (calculated as higher heating values), and 44% and 91% of nitrogen and phosphorus element contents in the original feedstock could be recovered as fertilizer products (ammonium sulfate and struvite), respectively. For 1,000 kg of such dry algal biomass, these products had an estimated total value of $427 (in 2014 U.S. dollars). For the first time, experiment-based energy and nutrient recovery potentials of wastewater-derived algae were presented in an integrated manner. Findings also revealed critical research needs and suggested strategies to further improve resource recovery and waste valorization in these systems.

Influence of solids residence time and carbon storage on nitrogen and phosphorus recovery by microalgae across diel cycles

Microalgal treatment systems could advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology, but their successful implementation requires an understanding of how design decisions influence nutrient uptake over daily (i.e., diel) cycles. This work demonstrates the ability to influence microalgal N:P recovery ratio via solids residence time (SRT) while maintaining complete nutrient removal across day/night cycles through carbon storage and mobilization. Experiments were conducted with two microalgal species, Scenedesmus obliquus and Chlamydomonas reinhardtii, in photobioreactors (PBRs) operated as cyclostats (chemostats subjected to simulated natural light cycles) with retention times of 6-22 days (S. obliquus) and 7-13 days (C. reinhardtii). Nutrient loading and all other factors were fixed across all experiments. Elevated SRTs (>8 days) achieved limiting nutrient concentrations (either N or P) below the detection limit throughout the diel cycle. N:P mass ratio in algal biomass was linearly correlated with SRT, varying from 9.9:1 to 5.0:1 (S. obliquus) and 4.7:1 to 4.3:1 (C. reinhardtii). Carbohydrate content of biomass increased in high irradiance and decreased in low irradiance and darkness across all experiments, whereas lipid dynamics were minimal over 24-h cycles. Across all nutrient-limited cultures, specific (i.e., protein-normalized) dynamic carbohydrate generally decreased with increasing SRT. Nighttime consumption of stored carbohydrate fueled uptake of nutrients, enabling complete nutrient limitation throughout the night. Dynamic carbohydrate consumption for nutrient assimilation was consistent with dark protein synthesis but less than that of heterotrophic growth, underscoring the need for algal process models to decouple growth from nutrient uptake in periods of low/no light. The ability to tailor microalgal N:P uptake ratio and target an optimal energy storage metabolism with traditional engineering process controls (such as SRT) may enable advanced nutrient recovery facilities to target continuous and reliable dual limitation of nitrogen and phosphorus.

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic performance of microalgae-based biofuel production. Models that estimate microalgal growth under different conditions can help to optimize PBR design and operation. To be effective, the growth parameters used in these models must be accurately determined. Algal growth experiments are often constrained by the dynamic nature of the culture environment, and control systems are needed to accurately determine the kinetic parameters. The first step in setting up a controlled batch experiment is live data acquisition and monitoring. This protocol outlines a process for the assembly and operation of a bench-scale photosynthetic bioreactor that can be used to conduct microalgal growth experiments. This protocol describes how to size and assemble a flat-plate, bench-scale PBR from acrylic. It also details how to configure a PBR with continuous pH, light, and temperature monitoring using a data acquisition and control unit, analog sensors, and open-source data acquisition software.

Towards a consensus-based biokinetic model for green microalgae - The ASM-A

Cultivation of microalgae in open ponds and closed photobioreactors (PBRs) using wastewater resources offers an opportunity for biochemical nutrient recovery. Effective reactor system design and process control of PBRs requires process models. Several models with different complexities have been developed to predict microalgal growth. However, none of these models can effectively describe all the relevant processes when microalgal growth is coupled with nutrient removal and recovery from wastewaters. Here, we present a mathematical model developed to simulate green microalgal growth (ASM-A) using the systematic approach of the activated sludge modelling (ASM) framework. The process model - identified based on a literature review and using new experimental data - accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae. Model parameters were estimated using laboratory-scale batch and sequenced batch experiments using the novel Latin Hypercube Sampling based Simplex (LHSS) method. The model was evaluated using independent data obtained in a 24-L PBR operated in sequenced batch mode. Identifiability of the model was assessed. The model can effectively describe microalgal biomass growth, ammonia and phosphate concentrations as well as the phosphorus storage using a set of average parameter values estimated with the experimental data. A statistical analysis of simulation and measured data suggests that culture history and substrate availability can introduce significant variability on parameter values for predicting the reaction rates for bulk nitrate and the intracellularly stored nitrogen state-variables, thereby requiring scenario specific model calibration. ASM-A was identified using standard cultivation medium and it can provide a platform for extensions accounting for factors influencing algal growth and nutrient storage using wastewater resources.

Modelling of Microalgae Culture Systems with Applications to Control and Optimization

Mathematical modeling is becoming ever more important to assess the potential, guide the design, and enable the efficient operation and control of industrial-scale microalgae culture systems (MCS). The development of overall, inherently multiphysics, models involves coupling separate submodels of (i) the intrinsic biological properties, including growth, decay, and biosynthesis as well as the effect of light and temperature on these processes, and (ii) the physical properties, such as the hydrodynamics, light attenuation, and temperature in the culture medium. When considering high-density microalgae culture, in particular, the coupling between biology and physics becomes critical. This chapter reviews existing models, with a particular focus on the Droop model, which is a precursor model, and it highlights the structure common to many microalgae growth models. It summarizes the main developments and difficulties towards multiphysics models of MCS as well as applications of these models for monitoring, control, and optimization purposes.

DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.

Energy positive domestic wastewater treatment: the roles of anaerobic and phototrophic technologies

The negative energy balance of wastewater treatment could be reversed if anaerobic technologies were implemented for organic carbon oxidation and phototrophic technologies were utilized for nutrient recovery. To characterize the potential for energy positive wastewater treatment by anaerobic and phototrophic biotechnologies we performed a comprehensive literature review and analysis, focusing on energy production (as kJ per capita per day and as kJ m(-3) of wastewater treated), energy consumption, and treatment efficacy. Anaerobic technologies included in this review were the anaerobic baffled reactor (ABR), anaerobic membrane bioreactor (AnMBR), anaerobic fluidized bed reactor (AFB), upflow anaerobic sludge blanket (UASB), anaerobic sequencing batch reactor (ASBR), microbial electrolysis cell (MEC), and microbial fuel cell (MFC). Phototrophic technologies included were the high rate algal pond (HRAP), photobioreactor (PBR), stirred tank reactor, waste stabilization pond (WSP), and algal turf scrubber (ATS). Average energy recovery efficiencies for anaerobic technologies ranged from 1.6% (MFC) to 47.5% (ABR). When including typical percent chemical oxygen demand (COD) removals by each technology, this range would equate to roughly 40-1200 kJ per capita per day or 110-3300 kJ m(-3) of treated wastewater. The average bioenergy feedstock production by phototrophic technologies ranged from 1200-4700 kJ per capita per day or 3400-13 000 kJ m(-3) (exceeding anaerobic technologies and, at times, the energetic content of the influent organic carbon), with usable energy production dependent upon downstream conversion to fuels. Energy consumption analysis showed that energy positive anaerobic wastewater treatment by emerging technologies would require significant reductions of parasitic losses from mechanical mixing and gas sparging. Technology targets and critical barriers for energy-producing technologies are identified, and the role of integrated anaerobic and phototrophic bioprocesses in energy positive wastewater management is discussed.