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Seasonal variation in microalgal biomass production is a well-known challenge when optimizing economics for algal fuel conversion, especially given the fluctuation in biomass production between win...

Seasonal variation in microalgae productivity is a significant barrier to economical production of algae biofuels and chemicals. Summer production can be 3-5 times higher than in the winter resulting in uneven feedstock supplies at algae biorefineries. A portion of the summer production must be preserved for conversion in the winter in order to maintain a biorefinery running at capacity. Ensiling, a preservation process that utilizes lactic acid fermentation to limit microbial degradation, has been demonstrated to successfully stabilize algae biomass (20% solids) and algae-lignocellulosic blends (40% algae-60% lignocellulosic biomass, dry basis) for over six months, resulting in fuel production cost savings with fewer emissions. Preservation of algae as blends could be beneficial to biorefineries that utilize thermochemical approaches to fuel production as co-processing of algae and lignocellulosic biomass has been observed to enhance biocrude yield and improve oil quality. This study conducts a resource assessment of biomass residues in the southern United States to identify materials available during peak algae productivity and in sufficient quantity to meet the algae storage needs of an algae biofuel industry. Eight feedstocks met the quantity threshold but only three, distillers grains, haylage, and yard waste, were also available in season. Storage experiments utilizing both freshwater and marine strains of microalgae – Scenedesmus acutus, Chlorella vulgaris, Chlorella zofingiensis, Nannochloropsis gaditana, and Porphyridium purpureum – and yard waste were conducted for 30 days. Storage losses were less than 10% in all but one case, and the pH of all but one blend was reduced to less than 4.7, indicating that yard waste is a suitable feedstock for blending with algae prior to storage. To better understand whether the benefits to conversion realized by processing blends might be affected by storage, elemental analysis and bomb calorimetry of pre- and post-storage algae-yard waste blends were conducted to characterize changes occurring during storage. Storing algae biomass as blends with lignocellulosic biomass could be an effective method of mitigating seasonal variability in algae biomass production while retaining the synergistic effect of co-processing algae blends in thermochemical conversion.

Upgrading of bio-oil obtained from hydrothermal liquefaction (HTL) of algae is necessary for it to be used as a fuel. In this study, bio-oil obtained from HTL of Nannochloropsis sp. was upgraded using five different catalysts (Ni/C, ZSM-5, Ni/ZSM-5, Ru/C and Pt/C) at 300 °C and 350 °C. The upgraded bio-oil yields were higher at 300 °C; however, higher quality upgraded bio-oils were obtained at 350 °C. Ni/C gave the maximum upgraded bio-oil yield (61 wt%) at 350 °C. However, noble metal catalysts (Ru/C and Pt/C) gave the better upgraded bio-oils in terms of acidity, heating values, and nitrogen values. The higher heating value of the upgraded bio-oils ranged from 40 to 44 MJ/kg, and the nitrogen content decreased from 5.37 to 1.29 wt%. Most of the upgraded bio-oils (35–40 wt%) were in the diesel range. The major components present in the gaseous products were CH4, CO, CO2 and lower alkanes.

The model euryhaline cyanobacterium Synechococcus sp. PCC 7002 has potential as a platform for biotechnological applications because of its genetic amenability and fast growth rates. The purpose of this work was to measure the outdoor productivity metrics of Synechococcus sp. PCC 7002, which we tested by cultivation in 110 L flat-panel photobioreactors and 1025 L open raceway ponds at the Algae Testbed Public Private Partnership (ATP3) algae culturing testbed site at the Arizona Center for Algae Technology and Innovation (AzCATI). This work was carried out during the summer growing season when ambient temperatures and light availability are highest to support maximum photoautotrophic biomass yields. Modifications to the traditional A+ laboratory growth media for Synechococcus sp. PCC 7002 included the use of urea as a nitrogen source, and CO2 sparging for automated pH control in open ponds. Synechococcus showed robust growth in flat-panel photobioreactors, which are suited for the containment of modified organisms; however, cultivation in the open-raceway pond system was challenging due to pond crashes. We investigated the microbiota associated with Synechococcus pond cultures using Illumina amplicon sequencing of the 16S rRNA genes of bacteria and archaea and the 18S rRNA genes of microbial eukaryotes, to identify potential competitor and predator genera. These results pointed to likely predation of Synechococcus by a ciliated protozoan of the genus Euplotes. Development of crop protection strategies will be crucial for enabling the mass cultivation of Synechococcus in open pond systems.

Well-controlled experiments that directly compare seasonal algal productivities across geographically distinct locations have not been reported before. To fill this gap, six cultivation testbed facilities were chosen across the United States to evaluate different climatic zones with respect to algal biomass productivity potential. The geographical locations and climates were as follows: Southwest, desert; Western, coastal; Southeast, inland; Southeast, coastal; Pacific, tropical; and Midwest, greenhouse. The testbed facilities were equipped with identical systems for inoculum production and open pond operation and methods were standardized across all testbeds to ensure accurate measurement of physical and biological variables. The ability of the testbed sites to culture and analyze the same algal species, Nannochloropsis oceanica KA32, using identical pond operational and data collection procedures was evaluated during the same seasonal timeframe. This manuscript describes the results of a first-of-its-kind coordinated testbed validation field study while providing critical details on how geographical variations in temperature, light, and weather variables influenced algal productivity, nitrate consumption, and biomass composition. We found distinct differences in growth characteristics due to the geographic location and the resulting climatic and seasonal conditions across the sites, with the highest productivities observed at the desert Southwest and tropical Pacific regions, followed by the Western coastal region. The lowest productivities were observed at the Southeast inland and Midwest greenhouse locations. These differences in productivities among the sites correlated with the differences in pond water temperature and available solar radiation. In addition two sites, the tropical Pacific and Southeast inland experienced unusual events, spontaneous flocculation, and unusually cold and wet (rainfall) conditions respectively, that negatively affected outdoor algal growth. In addition, minor variability in productivity was observed between the different experimental treatments at each site, much smaller compared to differences due to geographic location. Finally, the successful demonstration of the coordinated and standardized operation of the testbed sites established a rigorous basis for future validation of algal strains and operational conditions and protocols across a geographically diverse testbed network.

To address challenges in early detection of pond pests, we have extended a spectroradiometric monitoring method, initially demonstrated for measurement of pigment optical activity and biomass, to the detection of algal competitors and grazers. The method relies upon measurement and interpretation of pond reflectance spectra spanning from the visible into the near-infrared. Reflectance spectra are acquired every 5 min with a multi-channel, fiber-coupled spectroradiometer, providing monitoring of algal pond conditions with high temporal frequency. The spectra are interpreted via numerical inversion of a reflectance model, in which the above-water reflectance is expressed in terms of the absorption and backscatter coefficients of the cultured species, with additional terms accounting for the pigment fluorescence features and for the water-surface reflection of sunlight and skylight. With this method we demonstrate detection of diatoms and the predator Poteriochromonas in outdoor cultures of Nannochloropsis oceanica and Chlorella vulgaris, respectively. The relative strength of these signatures is compared to microscopy and sequencing analysis. Spectroradiometric detection of diatoms is then further assessed on beaker-contained mixtures of Microchloropsis salina with Phaeodactylum tricornutum, Thalassiosira weissflogii, and Thalassiosira pseudonana, respectively, providing an initial evaluation of the sensitivity and specificity of detecting pond competitors.

This study describes the makeup of and results from a simulation consisting of a lumped thermal model integrated with a dynamic algae growth model to simulate the microalgae productivity of an open-channel raceway cultivation system. The thermal model considers the dynamic effects of weather, light absorption, convective heat transfer, radiation heat transfer, conductive heat transfer, thermal capacitance, and water control strategies. The dynamic algae growth model solves a set of ordinary differential equations consisting of growth functions dependent on incident radiation, temperature, nutrient availability, basal metabolism, and losses due to dark- and photo-respiration. Relative errors in the predicted ash-free dry weight of Nannochloropsis oceanica are 12.5%, −6.1%, and 4.4% for three separate replicates of cultivation cycles (~4.2 m2) performed at AzCATI during the ATP3 Unified Field Studies in Fall, Spring, and Summer. This research demonstrates that thermal modeling is an essential contributor to the validation of microalgae growth models.

National scale agronomic projections are an important input for assessing potential benefits of algae cultivation on the future of innovative agriculture. The Algae Testbed Public-Private Partnership was established with the goal of investigating open pond algae cultivation across different geographic, climatic, seasonal, and operational conditions while setting the benchmark for quality data collection, analysis, and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework, the Unified Field Studies were designed for algae cultivation during all 4 seasons across the testbed network. With increasingly diverse algae research and development, and field deployment strategies, the challenges associated with data collection, quality, and dissemination increase dramatically. The dataset presented here is the complete, curated, climatic, cultivation, harvest, and biomass composition data for each season at each site. These data enable others to do in-depth cultivation, harvest, techno-economic, life cycle, resource, and predictive growth modelling analysis, as well as development of crop protection strategies throughout the algae cultivation industry.

Hydrothermal liquefaction (HTL) of nine algae species were performed at two reaction temperatures (280 and 320°C) to compare the effect of their biomass composition on product yields and properties. Results obtained after HTL indicate large variations in terms of bio-oil yields and its properties. The maximum bio-oil yield (66wt%) was obtained at 320°C with a high lipid containing algae Nannochloropsis. The higher heating value of bio-oils ranged from 31 to 36MJ/kg and around 50% of the bio-oils was in the vacuum gas oil range while high lipid containing algae Nannochloropsis contained a significant portion (33-42%) in the diesel range. A predictive relationship between bio-oil yields and biochemical compositions was developed and showed a broad agreement between predictive and experimental yields. The aqueous phases obtained had high amount of TOC (12-43g/L), COD (35-160g/L), TN (1-18g/L), ammonium (0.34-12g/L) and phosphate (0.7-12g/L).

Efficient production of algal biofuels could reduce dependence on foreign oil by providing a domestic renewable energy source. Moreover, algae-based biofuels are attractive for their large oil yield potential despite decreased land use and natural resource (e.g., water and nutrients) requirements compared to terrestrial energy crops. Important factors controlling algal lipid productivity include temperature, nutrient availability, salinity, pH, and the light-to-biomass conversion rate. Computational approaches allow for inexpensive predictions of algae growth kinetics for various bioreactor sizes and geometries without the need for multiple, expensive measurement systems. Parametric studies of algal species include serial experiments that use off-line monitoring of growth and lipid levels. Such approaches are time consuming and usually incomplete, and studies on the effect of the interaction between various parameters on algal growth are currently lacking. However, these are the necessary precursors for computational models, which currently lack the data necessary to accurately simulate and predict algae growth. In this work, we conduct a lab-scale parametric study of the marine alga Nannochloropsis salina and apply the findings to our physics-based computational algae growth model. We then compare results from the model with experiments conducted in a greenhouse tank and an outdoor, open-channel raceway pond. Results show that the computational model effectively predicts algae growth in systems across varying scale and identifies the causes for reductions in algal productivities. Applying the model facilitates optimization of pond designs and improvements in strain selection.

Rapid growth, fixation of carbon dioxide, and little competition with food plus some species possessing high lipid content make microalgae a suitable feedstock to produce biodiesel. However, high cost related to dehydration, lipid extraction and conversion to biodiesel hampers industrialization of biodiesel production from microalgae. The objective of this study was to develop a biodiesel production procedure directly from wet microalgae. The system was operated under atmospheric pressure without requiring any specific apparatus. Wet microalgae (Chlorella vulgaris) was pretreated by radio frequency (RF) heating to disrupt cell walls first, followed by esterification and transesterification with relatively small amount of methanol and catalyst (either HCL or NaOH) assisted by RF heating at 55 °C for only 20 min. The fatty acid methyl esters (FAME) yield reached as high as 79.5 ± 3.0%. The two major factors impacting biodiesel yield are catalyst and methanol. Also, scanning electron microscope (SEM) was used to investigate morphology of the algae before and after the RF heating pretreatment. The SEM images visually verified the significant effect of cell disruption by the pretreatment. Although this pathway was developed for Chlorella vulgaris, it can be applied to any other microalgae which are rich in both free fatty acids and triglycerides.

Algal biomass compositional analysis data form the basis of a large number of techno-economic process analysis models that are used to investigate and compare different processes in algal biofuels production. However, the analytical methods used to generate these data are far from standardized. This work investigated the applicability of common methods for rapid chemical analysis of biomass samples with respect to accuracy and precision. This study measured lipids, protein, carbohydrates, ash, and moisture of a single algal biomass sample at 3 institutions by 8 independent researchers over 12 separate workdays. Results show statistically significant differences in the results from a given analytical method among laboratories but not between analysts at individual laboratories, suggesting consistent training is a critical issue for empirical analytical methods. Significantly different results from multiple lipid and protein measurements were found to be due to different measurement chemistries. We identified a set of compositional analysis procedures that are in best agreement with data obtained by more advanced analytical procedures. The methods described here and used for the round robin experiment do not require specialized instrumentation, and with detailed analytical documentation, the differences between laboratories can be markedly reduced.

Current molecular methods to characterize microalgae are time-intensive and expensive. Matrix Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) may represent a rapid and economical alternative approach. The objectives of this study were to determine whether MALDI-TOF MS can be used to: 1) differentiate microalgae at the species and strain levels and 2) characterize simple microalgal mixtures. A common protein extraction sample preparation method was used to facilitate rapid mass spectrometry-based analysis of 31 microalgae. Each yielded spectra containing between 6 and 56 peaks in the m/z 2,000 to 20,000 range. The taxonomic resolution of this approach appeared higher than that of 18S rDNA sequence analysis. For example, two strains of Scenedesmus acutus differed only by two 18S rDNA nucleotides, but yielded distinct MALDI-TOF mass spectra. Mixtures of two and three microalgae yielded relatively complex spectra that contained peaks associated with members of each mixture. Interestingly, though, mixture-specific peaks were observed at m/z 11,048 and 11,230. Our results suggest that MALDI-TOF MS affords rapid characterization of individual microalgae and simple microalgal mixtures.

Microalgae from natural saline habitats in the southwestern United States were isolated and screened for rapid growth potential and ability to store intracellular neutral lipid, a precursor for renewable liquid fuel sources. After preliminary screening of isolated strains, Nitzschia communis (Rabenhorst) was selected for optimization of growth rate and lipid yield. Nitzschia communis was subjected to two media types (SERI I, II) with different major ion compositions designed to mimic natural saline groundwater aquifers in the arid Southwest. Growth rates were determined through 4 days of logarithmic growth, followed by 2 days of physiological stress (nitrogen deprivation) and subsequent measurement of neutral lipid accumulation. Poststress intracellular neutral lipid increases were documented by utilizing the fluorochrome Nile Red with fluorometric analysis and epifluorescent microscopy. Growth rate was slightly higher in SERI Type I medium, whereas lipid yield was higher in SERI Type II medium. Rapid growth and appreciable lipid yields were observed over a broad range of temperatures (20°–30° C) and specific conductances (10–70 mS·cm−1). The highest lipid yields were observed at elevated conductances (between 40 mS·cm−1 and 70 mS·cm−1). Substitution of individual salt concentrations from SERI Type II into SERI Type I medium indicated that increased lipid yield in Type I medium was associated with a reduction in MgCl2 concentration.

Accurate compositional analysis in biofuel feedstocks is imperative; the yields of individual components can define the economics of an entire process. In the nascent industry of algal biofuels and bioproducts, analytical methods that have been deemed acceptable for decades are suddenly critical for commercialization. We tackled the question of how the strain and biochemical makeup of algal cells affect chemical measurements. We selected a set of six procedures (two each for lipids, protein, and carbohydrates): three rapid fingerprinting methods and three advanced chromatography-based methods. All methods were used to measure the composition of 100 samples from three strains: Scenedesmus sp., Chlorella sp., and Nannochloropsis sp. The data presented point not only to species-specific discrepancies but also to cell biochemistry-related discrepancies. There are cases where two respective methods agree but the differences are often significant with over- or underestimation of up to 90%, likely due to chemical interferences with the rapid spectrophotometric measurements. We provide background on the chemistry of interfering reactions for the fingerprinting methods and conclude that for accurate compositional analysis of algae and process and mass balance closure, emphasis should be placed on unambiguous characterization using methods where individual components are measured independently.

The search is on for new renewable energy and algal-derived biofuel is a critical piece in the multi-faceted renewable energy puzzle. It has 30x more oil than any terrestrial oilseed crop, ideal composition for biodiesel, no competition with food crops, can be grown in waste water, and is cleaner than petroleum based fuels. This project discusses these three goals: (1) Conduct fundamental research into the effects that dynamic biotic and abiotic stressors have on algal growth and lipid production - Genomics/Transcriptomics, Bioanalytical spectroscopy/Chemical imaging; (2) Discover spectral signatures for algal health at the benchtop and greenhouse scale - Remote sensing, Bioanalytical spectroscopy; and (3) Develop computational model for algal growth and productivity at the raceway scale - Computational modeling.

Frequent episodes of algal-related tastes and odors (T & O) in drinking waters in metropolitan Phoenix, Arizona prompted initiation of a three-year project in July 1999 to investigate the occurrence of T & O metabolites and to develop a comprehensive management strategy to reduce the problems in drinking water supplies in arid environments. Two metabolites, 2-methylisoborneol (MIB) and geosmin, have been identified as compounds responsible for the earthy-musty tastes and odors in water supplies. Both were detected in the water supply system, including source rivers, reservoirs, canal delivery system and water treatment plants. Higher concentrations of MIB and geosmin occurred in distribution canals than in the upstream reservoirs indicating that significant production of the T & O compounds occurs within the canal system. A baseline-monitoring program has been established for the complex water supply system, with special emphasis on the canal system. Efforts are underway to investigate possible correlations between physical/chemical parameters, algal composition and biomass, with the occurrence of MIB and geosmin. In addition, several physical and chemical treatments are planned for the canal system to reduce algal growth and related MIB and geosmin concentrations.