This study aimed at investigating the potential of microalgae species grown on industrial waste water as a new source of natural antioxidants. Six microalgae from different classes, including Phaeodactylum sp. (Bacillariophyceae), Nannochloropsis sp. (Eustigmatophyceae), Chlorella sp., Dunaniella sp., and Desmodesmus sp. (Chlorophyta), were screened for their antioxidant properties using different in vitro assays. Natural antioxidants, including pigments, phenolics, and tocopherols, were measured in methanolic extracts of microalgae biomass. Highest and lowest concentrations of pigments, phenolic compounds, and tocopherols were found in Desmodesmus sp. and Phaeodactylum tricornuotom microalgae species, respectively. The results of each assay were correlated to the content of natural antioxidants in microalgae biomass. Phenolic compounds were found as major contributors to the antioxidant activity in all antioxidant tests while carotenoids were found to contribute to the 1,1-diphenyl-2-picryl-hydrazil (DPPH) radical scavenging activity, ferrous reduction power (FRAP), and ABTS-radical scavenging capacity activity. Desmodesmus sp. biomass represented a potentially rich source of natural antioxidants, such as carotenoids (lutein), tocopherols, and phenolic compounds when cultivated on industrial waste water as the main nutrient source.

Accurate prediction of algal biofuel yield will require empirical determination of physiological responses to the environment, particularly light and temperature. One strain of interest, Nannochloropsis salina, was subjected to ranges of light intensity (5-850 μmol m −2 s −1 ) and temperature (13-40 °C) and its exponential growth rate, total fatty acids (TFA) and fatty acid composition were measured. The maximum acclimated growth rate was 1.3 day −1 at 23 °C and 250 μmol m −2 s −1 . Fatty acids were detected by gas chromatography with flame ionization detection (GC-FID) after transesterification to corresponding fatty acid methyl esters (FAMEs). A sharp increase in TFA containing elevated palmitic acid (C16:0) and palmitoleic acid (C16:1) during exponential growth at high light was observed, indicating likely triacylglycerol accumulation due to photo-oxidative stress. Lower light resulted in increases in the relative abundance of unsaturated fatty acids; in thin cultures, increases were observed in palmitoleic and eicosapentaenoic acids (C20:5ω3). As cultures aged and the effective light intensity per cell converged to very low levels, fatty acid profiles became more similar and there was a notable increase of oleic acid (C18:1ω9). The amount of unsaturated fatty acids was inversely proportional to temperature, demonstrating physiological adaptations to increase membrane fluidity. These data will improve prediction of fatty acid characteristics and yields relevant to biofuel production. OPEN ACCESSEnergies 2012, 5 732

A microalgae biomass growth model was developed for screening novel strains for their potential to exhibit high biomass productivities under nutrient-replete conditions in photobioreactors or outdoor ponds. Growth is modeled by first estimating the light attenuation by biomass according to Beer-Lambert's Law, and then calculating the specific growth rate in discretized culture volume slices that receive declining light intensities due to attenuation. The model uses only two physical and two species-specific biological input parameters, all of which are relatively easy to determine: incident light intensity, culture depth, as well as the biomass light absorption coefficient and the specific growth rate as a function of light intensity. Roux bottle culture experiments were performed with Nannochloropsis salina at constant temperature (23°C) at six different incident light intensities (10, 25, 50, 100, 250, and 850 µmol/m(2)  s) to determine both the specific growth rate under non-shading conditions and the biomass light absorption coefficient as a function of light intensity. The model was successful in predicting the biomass growth rate in these Roux bottle batch cultures during the light-limited linear phase at different incident light intensities. Model predictions were moderately sensitive to minor variations in the values of input parameters. The model was also successful in predicting the growth performance of Chlorella sp. cultured in LED-lighted 800 L raceway ponds operated in batch mode at constant temperature (30°C) and constant light intensity (1,650 µmol/m(2)  s). Measurements of oxygen concentrations as a function of time demonstrated that following exposure to darkness, it takes at least 5 s for cells to initiate dark respiration. As a result, biomass loss due to dark respiration in the aphotic zone of a culture is unlikely to occur in highly mixed small-scale photobioreactors where cells move rapidly in and out of the light. By contrast, as supported also by the growth model, biomass loss due to dark respiration occurs in the dark zones of the relatively less well-mixed pond cultures. In addition to screening novel microalgae strains for high biomass productivities, the model can also be used for optimizing the pond design and operation. Additional research is needed to validate the biomass growth model for other microalgae species and for the more realistic case of fluctuating temperatures and light intensities observed in outdoor pond cultures.

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.

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