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Analysis and modeling of Nannochloropsis growth in lab, greenhouse, and raceway experiments

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Abstract

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.

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References

  • Auken OWV, McNulty IB (1973) The effect of environmental factors on the growth of a halophilic species of algae. Biol Bull 145:210–222

    Article  PubMed  Google Scholar 

  • Bartley ML, Boeing WJ, Dungan BN, Holguin FO, Schaub T (2013) pH effects on growth and lipid accumulation of the biofuel microalgae Nannochloropsis salina and invading organisms. J Appl Phycol. doi:10.1007/s10811-013-0177-2

    Google Scholar 

  • Batterton JC, Baalen CV (1971) Growth response of blue-green algae to sodium chloride concentration. Arch Microbiol 76:151–165

    CAS  Google Scholar 

  • Bernard O, Boulanger A-C, Bristeau M-O, Sainte-Marie J (2013) A 2D model for hydrodynamics and biology coupling applied to algae growth simulations. Esaim-Math Model Num 47:1387–1412

    Article  Google Scholar 

  • Boussiba S, Vonshak A, Cohen Z, Avissar Y, Richmond A (1987) Lipid and biomass production by the halotolerant microalga Nannochloropsis salina. Biomass 12:37–47

    Article  CAS  Google Scholar 

  • Briassoulis D, Panagakis P, Chionidis M, Tzenos D, Lalos A, Tsinos C, Berberidis K, Jacobsen A (2010) An experimental helical-tubular photobioreactor for continuous production of Nannochloropsis sp. Bioresour Technol 101:6768–6777

    Article  CAS  PubMed  Google Scholar 

  • Brock TD (1975) Salinity and the ecology of Dunaliella from Great Salt Lake. J Gen Microbiol 89:285–292

    Article  Google Scholar 

  • Burkhardt S, Zondervan I, Riebesell U (1999) Effect of CO2 concentration on C:N:P ratio in marine phytoplankton: a species comparison. Limnol Oceanogr 44:683–690

    Article  CAS  Google Scholar 

  • Cerco CF, Cole T (1994) Three-dimensional eutrophication model of Chesapeake Bay. US Army Corps of Engineers

  • Cerco CF, Cole T (1995) User’s guide to the CE-QUAL-ICM three-dimensional eutrophication model, Release Version 1.0. U.S. Army Corps of Engineers

  • Chisti Y (2007) Biodiesel from microalgae. Biotechnol Adv 25:294–306

    Article  CAS  PubMed  Google Scholar 

  • Cossins AR, Bowler K (1987) Temperature biology of animals. Chapman and Hall, New York

    Book  Google Scholar 

  • DiToro DM, O'Connor DJ (1975) Phytoplankton–zooplankton–nutrient interaction model for Western Lake Erie. Ecology 3:423–473

    Google Scholar 

  • DiToro D, O'Connor S, Thormann R (1971) A dynamic model of the phytoplankton population in the Sacramento-San Joaquin Delta. In: Nonequilibrium systems in water chemistry. American Chemical Society, Houston, pp 131–180

  • Eppley RW (1972) Temperature and phytoplankton growth in the sea. Fish Bull 70:1063–1085

    Google Scholar 

  • Fabregas J, Abalde J, Herrero C, Cabezas BV, Veiga M (1984) Growth of the marine microalga Tetraselmis suecica in batch cultures with different salinities and nutrient concentrations. Aquaculture 42:207–215

    Article  Google Scholar 

  • Fluent (2012) Fluent user's guide. 13.1 edn. ANSYS, Inc

  • García F, Freile-Pelegrín Y, Robledo D (2007) Physiological characterization of Dunaliella sp. (Chlorophyta, Volvocales) from Yucatan, Mexico. Bioresour Technol 98:1359–1365

    Article  PubMed  Google Scholar 

  • Guillard RRL, Ryther JH (1962) Studies of marine diatoms. I. Cyclotella nana Husdedt and Detonula confervacea (Cleve) Gran. Can J Microbiol 8:229–239

    Article  CAS  PubMed  Google Scholar 

  • Haaland DM, Easterling RG, Vopicka DA (1985) Multivariate least-squares methods applied to the quantitative spectral analysis of multicomponent samples. Appl Spectrosc 39:73–84

    Article  CAS  Google Scholar 

  • Hale GM, Querry MR (1973) Optical constants of water in the 200-nm to 200-μm wavelength region. Appl Optics 12:555–563

    Article  CAS  Google Scholar 

  • Hecky RE, Campbell P, Hendzel LL (1993) The stoichiometry of carbon, nitrogen, and phosphorus in particulate matter of lakes and oceans. Limnol Oceanogr 38:709–724

    Article  CAS  Google Scholar 

  • Hu Q, Sommerfeld M, Jarvis E, Ghirardi M, Posewitz M, Seibert M, Darzins A (2008) Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances. Plant J 54:621–639

    Article  CAS  PubMed  Google Scholar 

  • Huesemann MH, Wagenen JV, Miller T, Chavis A, Hobbs S, Crowe B (2013) A screening model to predict microalgae biomass growth in photobioreactors and raceway ponds. Biotechnol Bioeng 110:1583–1594

    Article  CAS  PubMed  Google Scholar 

  • Incropera FP (2007) Fundamentals of heat and mass transfer, 6th edn. John Wiley, Hoboken

    Google Scholar 

  • James SC, Boriah V (2010) Modeling algae growth in an open-channel raceway. J Comput Biol 17:895–906

    Article  CAS  PubMed  Google Scholar 

  • James SC, Janardhanam V, Hanson DT (2013) Simulating pH effects in an algal-growth hydrodynamics model. J Phycol 49:608–615

    Article  CAS  Google Scholar 

  • Katz A, Bental M, Degani H, Avron M (1991) In vivo pH regulation by a Na+/H+ antiporter in the halotolerant alga Dunaliella salina. Plant Physiol 96:110–115

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Kirst GO (1989) Salinity tolerance of eukaryotic marine algae. Annu Rev Plant Physiol 40:21–53

    Google Scholar 

  • Kou L, Labrie D, Chylek P (1993) Refractive indices of water and ice in the 0.65- to 2.5 μm spectral range. Appl Optics 32:3531–3540

    Article  CAS  Google Scholar 

  • Laurens LML, Dempster TA, Jones HDT, Wolfrum EJ, Wychen S, McAllister JSP, Rencenberger M, Parchert KJ, Gloe LM (2012) Algal biomass constituent analysis: method uncertainties and investigation of the underlying measuring chemistries. Anal Chem 84:1879–1887

    Article  CAS  PubMed  Google Scholar 

  • Lewis LA, Lewis PO (2005) Unearthing the molecular phylodiversity of desert soil green algae (Chlorophyta). Syst Biol 54:936–947

    Article  PubMed  Google Scholar 

  • Li Z, Wakao S, Fischer BB, Niyogi KK (2009) Sensing and responding to excess light. Annu Rev Plant Biol 60:239–260

    Article  CAS  PubMed  Google Scholar 

  • Liffman K, Paterson DA, Liovic P, Bandopadhayay P (2013) Comparing the energy efficiency of different high rate algal raceway pond designs using computational fluid dynamics. Chem Eng Res Design 91:221.226

    Article  Google Scholar 

  • Martin M, Berdahl P (1984) characteristics of infrared sky radiation in the United States. Sol Energy 33:321–336

    Article  Google Scholar 

  • Masojidek J, Vonshak A, Torzillo G (2010) Chlorophyll fluorescence applications in microalgal mass cultures. In: Suggett DJ, Prasil O, Borowizka MA (eds) Chlorophyll a fluorescence in aquatic sciences: methods and applications. Springer, Dordrecht, pp 277–292

    Chapter  Google Scholar 

  • Mata TM, Martins AA, Caetano NS (2010) Microalgae for biodiesel production and other applications: a review. Renew Sust Energ Rev 14:217–232

    Article  CAS  Google Scholar 

  • MATLAB (2013) MATLAB primer. R2013a edn. MathWorks, Inc

  • Mayer P, Cuhel R, Nyholm N (1997) A simple in vitro fluorescence method for biomass measurements in algal growth inhibition tests. Water Res 31:2525–2531

    Article  CAS  Google Scholar 

  • Mayo AW (1997) Effects of temperature and pH on the kinetic growth of unialga Chlorella vulgaris cultures containing bacteria. Water Environ Res 69:64–72

    Article  CAS  Google Scholar 

  • Mendoza JL, Granados MR, Godos I, Acién FG, Molina E, Banks C, Heaven S (2013) Fluid-dynamic characterization of real-scale raceway reactors for microalgae production. Biomass Bioenergy 54:267–275

    Article  CAS  Google Scholar 

  • Monod J (1949) The growth of bacterial cultures. Annu Rev Microbiol 3:371–394

    Article  CAS  Google Scholar 

  • Pal D, Khozin-Goldberg I, Cohen Z, Boussiba S (2011) The effect of light, salinity, and nitrogen availability on lipid production by Nannochloropsis sp. Appl Micro Cell Physiol 90:1429–1441

    CAS  Google Scholar 

  • Quinn J, Winter L, Bradley T (2011) Microalgae bulk growth model with application to industrial scale systems. Bioresour Technol 102:5083–5092

    Article  CAS  PubMed  Google Scholar 

  • Redfield AC (1934) On the proportions of organic derivatives in sea water and their relation to the composition of plankton. In: Daniel RJ (ed) James Johnstone memorial volume. University Press of Liverpool, London, pp 176–192

    Google Scholar 

  • Reichardt TA, Collins AM, Timlin JA, McBride RC, Behnke CA (2013) Spectroradiometric monitoring of open algal cultures. Conference on lasers and electro-optics. The Optical Society, San Jose

    Google Scholar 

  • Remias D, Lütz-Meindl U, Lütz C (2005) Photosynthesis, pigments and ultrastructure of the alpine snow alga Chlamydomonas nivalis. Eur J Phycol 40:259–268

    Article  CAS  Google Scholar 

  • Samuelsson G, Öquist G (2006) A method for studying photosynthetic capapcities of unicellular algae based on in vivo chlorophyll fluorescence. Physiol Plant 40:315–319

    Article  Google Scholar 

  • Serôdio J, Marquez da Silva J, Catarino F (2001) Use of in vivo chlorophyll a fluorescence to quantify short-term variations in the productive biomass of intertidal microphytobenthos. Mar Ecol Prog Ser 218:45–61

    Article  Google Scholar 

  • Singh J, Gu S (2010) Commercialization potential of microalgae for biofuels production. Renew Sust Energ Rev 14:2596–2610

    Article  CAS  Google Scholar 

  • Singh S, Ahmad Z, Kothyari UC (2012) Mixing coefficients for longitudinal and vertical mixing in the near field of a surface pollutant discharge. J Hydraul Res 48:91–99

    Article  Google Scholar 

  • Sukenik A, Beardall J, Kromkamp JC, Kopecky J, Masojidek J, Bergeijk S, Gabai S, Shaham E, Yamshon A (2009) Photosynthetic performance of outdoor Nannochloropsis mass cultures under a wide range of environmental conditions. Aquat Microb Ecol 56:297–308

    Article  Google Scholar 

  • Sun A, Davis R, Starbuck M, Ben-Amotz A, Pate R, Pienkos PE (2011) Comparative cost analysis of algal oil production for biofuels. Energy 36:5169–5179

    Article  Google Scholar 

  • Torzillo G, Accolla P, Pinzani E, Masojidek J (1996) In situ monitoring of chlorophyll fluorescence to assess the synergistic effect of low temperature and high irradiance stresses in Spirulina cultures grown outdoors in photobioreactors. J Appl Phycol 8:283–291

    Article  CAS  Google Scholar 

  • US-DOE (2009) National algal biofuels technology roadmap. Office of Energy Efficiency and Renewable Energy and Office of Biomass, Albuquerque

    Google Scholar 

  • Vyhnalek V, Fisar Z, Fisarova A, Komarkova J (1993) In vivo fluorescence of chlorophyll a: estimation of phytoplankton biomass and activity in Rimov Reservoir (Czech Republic). Water Sci Technol 28:29–33

    CAS  Google Scholar 

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Acknowledgments

The authors would like to thank Dr. Todd Lane and Pam Lane from Sandia National Laboratories for their guidance with the lab-scale algae growth and measurement methods, Brian Dwyer from Sandia National Laboratories for maintaining the greenhouse, Kathleen Alam from Sandia National Laboratories for providing access to her laboratory equipment enabling the absorptivity measurements, Dave van Norn at the University of New Mexico for lending data logging instrumentation for the greenhouse experiments, and the University of New Mexico Biology Analytical Annex for providing the C/N/P analysis of the media and biomass. This work was supported by the Laboratory Directed Research and Development program at Sandia National Laboratories. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

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Authors and Affiliations

  1. Sandia National Laboratories, PO Box 969, MS 9957, Livermore, CA, 94550, USA

    Patricia E. Gharagozloo

  2. University of Wisconsin, 460 Henry Mall, Madison, WI, 53706, USA

    Jessica L. Drewry & Christopher Y. Choi

  3. Los Alamos National Laboratory, Los Alamos, NM, 87545, USA

    Aaron M. Collins

  4. Arizona State University, 7418 E. Innovation Way South, ISTB-3 203G, Mesa, AZ, 85212, USA

    Thomas A. Dempster

  5. Exponent, Inc, 320 Goddard Way, Suite 200, Irvine, CA, 92618, USA

    Scott C. James

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  1. Patricia E. Gharagozloo
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  2. Jessica L. Drewry
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  3. Aaron M. Collins
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  4. Thomas A. Dempster
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  5. Christopher Y. Choi
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  6. Scott C. James
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Correspondence to Patricia E. Gharagozloo.

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Gharagozloo, P.E., Drewry, J.L., Collins, A.M. et al. Analysis and modeling of Nannochloropsis growth in lab, greenhouse, and raceway experiments. J Appl Phycol 26, 2303–2314 (2014). https://doi.org/10.1007/s10811-014-0257-y

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  • DOI: https://doi.org/10.1007/s10811-014-0257-y

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