FINAL REPORT 

to the 

. SOLAR ENERGY RESEARCH INSTITUTE 

under 

SUBCONTRACT XK-4-04136-06 

EFFECTS OF FLUCTUATING ENVIRONMENTS 

ON THE SELECTION OF HIGH YIELDING MICROALGAE 

John R. Benemann 

and 

David M. Tillett 

Schools of Applied Biology 

and Chemical Engineering 

Georgia Institute of Technology 

Atlanta, GA 30332 

February 27, 1987 
NOTICE 

This report was prepared as an account of work sponsored by the 

united states Government. Neither the United states nor the 

united states Department of Energy nor any of their employees, nor 

any of their contractors, subcontractors, or their employees, 

makes any warranty, express or implied, or assumes any legal 

liability or responsibility for the accuracy, completeness or usefulness of any information, apparatus, product or process disclosed, or represents that its use would not infringe privately 

owned rights. 
ABSTRACT 

Microalgae have the potential of producing biomass with a high 

content of lipids at high productivities using seawater or saline 

ground water resources. Microalgal lipids are similar to vegetable oils and suitable for processing to liquid fuels. Engineering 

Icost analysis studies have concluded that, at a favorable site, 

microalgae cultivation for fuel production could be economically 

viable. The major uncertainties involve the microalgae themselves: biomass and lipid productivity and culture stability. 

The mass culture of microalgae for low cost lipids production 

requires a detailed understanding of both the physiology of lipid 

biosynthesis by the selected algal strains and of the factors 

making these strains competitive in outdoor ponds. Mass culture 

systems will, because of climatic variability, the day-night 

cycle, and inherent design factors, exhibit fluctuations in key 

parameters affecting algal growth, productivity and competitiveness: temperature, pH, po?, pC02' light, and nutrient availability. This project has for ~ts overall objective to quantitate the 

effects of such fluctuations on culture productivity and species 

competitiveness. A second objective has been the development of 

basic information on algal physiology as it relates to lipid productivity. 

Species competition experiments with several strains of algae 

isolated by the SERI/DOE Aquatic Species Program, some of which 

were previously used in outdoor mass cultures, were carried out. 

In these experiments certain parameters proved to be more important then others in determining species succession: fluctuating 

p02 was more important than fluctuating temperature, which was 

more important than fluctuating pH. These results must be 

extended to other species and conditions to determine how far 

these findings can be generalized. Future work will concentrate 

on comparing unialgal to mixed culture experiments and on elucidating the specific environmental factors that impact on species 

productivity and competitiveness. 

To help guide this work, a computer model was developed capable 

of predicting the amplitude and frequency of the environmental 

parameters (p02' pH, PC02, temperature, and light intensity) over 

the diurnal cycle throughout the year at any location for which 

climatic data is available. This model must still be validated 

with data collected from operating ponds. 

Using one algal strain, "Nanno Q" (Nannochloropsis sp.), as a 

test organism we also have investigated strategies for maximizing 

lipid productivity. Our data suggest a two stage process: the 

first stage is operated at the highest density permitting maximal 

productivity and the second stage at a higher light input (lower 

standing biomass or cell density) and under conditions of 

nitrogen starvation. Such a two stage system is more productive 

than a continuous nitrogen limited culture process. Future work 

in this area should utilize algal strains that have previously 

been selected for their competitiveness under outdoor conditions. 
1.0 

2.0 

3.0 

4.0 

TABLE OF CONTENTS 

Cover •••.• 

Notice •••• 

Abstract •. 

Table of Contents •• 

List of Tables •• 

List of Figures •• 

Acknowledgments •• 

INTRODUCTION •.••••••••••••••.•• 

1.1 

1.2 

1.3 

1.4 

Microalgae Cultivation •••••• 

Microalgae Species Control •• 

Lipid Production by Microalgae •• 

contents of this Report ••••••••• 

GROWTH AND COMPETITION OF MICROALGAE IN 

CULTURES. 0 • • • • • • • • • • • • • 0 • • • • • • • • • • 

Introduction ....................... . 

Page 

. • •••• 1. 

· . ii 

.iii 

.iv 

• . v 

· • vi . .. . ix 

1 

1 

..5 

• •• 7 

• • • 8 

•• 9 

•••••• 09 

MASS 

2.1 

2.2 

2.3 

2.4 

2.5 

2.6 

2.7 

2.8 

The High Rate Pond Environment •••••• 

Theoretical Basis for Species Competition. 

.9 

· .11 

Light ••••.•• .16 

Temperature •• 

Oxygen •••.••• 

pH/pC02····· 

The Feasibility of Scale Down ••• 

MODELING THE ALGAL GROWTH POND ENVIRONMENT •• 

3.1 Introduction ••• 

3.2 Pond Design •••••••• 

3.3 Pond Models •••••••• 

3.4 Model Description •• 

3.4.1 Input Parameters •• 

3.4.2' Model Subroutines ••• 

3.5 Results ••••••••••••• 

3.5.1 

3.5.2 

3.5.3 

Introduction. 

Tempera ture ••• 

Oxygen . . . . 

3.6 

3.7 

3.5.4 Carbon Dioxide and pH •• 

Outdoor Pond Measurements •. 

Summary and Future Work ••••• 

• .22 

• .26 

.28 

· .31 

• .34 

· .34 

.35 

• .35 

• .38 

.38 

• .40 

.45 

.45 

• .45 

• .48 

• .50 

.55 

.57 

MICROALGAE COMPETITION STUDIES IN 

LABORATORY REACTORS •••.••••••••• . ....• . 60 

4.1 

4.2 

4.3 

4.4 

4.5 

Introduction •••••••••••••••• 

Fluctuating Temperature and Oxygen. 

Fluctuating pH ••••••••••••••••• 

Dilution Rate Experiment •••••• 

Conclusions and Future Plans •• 

• .60 

••• 60 

••• 66 

•• 66 

.72 
5.0 LIPIDS FROM MICROALGAE •.•••..•••...•.•.•••.•.•...• 74 

5 • 1 Introduction ................ ., II •••••••••••••• 74 

5.2 Review of Lipids and Nitrogen Deficient 

Growth of Microalgae ••••.•••.•••••••••..•••. 74 

5.2.1 Lipids from Microalgae ••••••.•••..•••. 74 

5.2.2 Factors affecting Lipid content 

of Microalgae ..... 0 •••••• c •••••••••••• 75 

5.2.3 Nitrogen Deficiency and Lipid 

content ........... ., ..... 0 ••••••••••••• 77 

5.2.4 Nitrogen Deficiency and Lipid 

Productivity ...... o ell. e· ••• ., ••••••••••• 77 

5.2.5 Nitrogen Metabolism and Nitrogen 

Deficiency ............................ 80 

5.2.6 Kinetics of Nitrogen Limited Growth ••• B3 

5.3 Lipid Induction and Productivity: 

Research Objectives ••••••••••••••••••••••••• B5 

5.4 Lipid Productivity in Nitrogen Deficient 

Culture of Nanno Q ...•.•..••.•.•.•••........ B6 

5 • 4 • 1 Introduction ••••••••••••••••••••.••••• B 6 

5.4.2 Growth-Rate Nitrogen Quota 

Relationship .......................... 86 

5.4.3 Chlorophyll a Content vs. Nitrogen 

Quota ........................ ., ........ 87 

5.4.4 Lipid content vs. Nitrogen Quota •••••• B7 

5.4.5 Lipid productivity vs. Nitrogen 

Quota .................... e •••••••••••• 87 

5.4.6 Heat of Combustion vs. Nitrogen 

Quota. ~ .............................. . 90 

5.4.7 Light Shift Experiment ••••••••.••••••• 90 

5.4.B Discussion and Conclusions ••.••••••.•• 94 

5.5 Lipid Induction in Nitrogen Limited 

continuous Cultures of Nanno Q •••••••••••••• 95 

5.5.1 Introduction •••••••••••••••••••••••••• 95 

5.5.2 Experimental Design ••••••••••••••••••• 95 

5.5.3 Light Limited Growth •••••••••••••••••• 96 

5.5.4 Nitrogen Limited Growth •••••••••••.••. 99 

5.5.5 Nitrogen Limited Growth vs. 

Cell Density ••••••.•••.•••••••••••••• 104 

5.5.6 continuous to Batch Induction o~ Lipic:;t •..... 0 ••••••• 0 .. 0 .. ., .................. 106 

5.5.7 D1Scuss10n •••••••••••••••••••••••••.• 106 

5.6 Summary and Conclusions ••••..••••••.••.••.• 10B 

REFERENCES ........................................................................ 109 

APPENDIX A: MATERIALS AND METHODS 
Table 

1.1 

2.1 

3.1 

3.2 

4.1 

5.1 

5.2 

5.3 

5.4 

5.5 

LIST OF TABLES 

Advantages and Disadvantages of Microalgae 

Technology. 

Feasibility of scaling Pond Environmental 

Parameters to Laboratory Reactors 

Summary of Input Parameters to the AGP Model 

Mass and Energy Balance Equations 

Summary of Experimental Conditions and Results 

for the continuous Multispecies cultures 

Algal Lipid Contents from Selected Literature 

Sources 

A Summary of Lipid Contents for strains Collected 

.by SERI Investigators 

Degree of Reduction, % Nitrogen and Heat of 

Combustion for Cultures of Nanno Q 

Steady State Results for Nitrogen Limited 

Cultures of Nanno Q 

Comparison of Maximum Observed Lipid Productivities 

(mgjljday) for a Variety of Conditions 

Page 

2 

31 

39 

43 

61 

79 

79 

91 

99 

108 
List of Figures 

Figure 

1.1 Commercial Microalgae Pond Systems in the u.s. 

2.1 Growth Rate - Substrate Relationships 

2.2 In vivo Absorption Spectra of Microalgae 

2.3 Photosynthesis vs. Irradiance and Depth 

Relationships 

2.4 Growth Rate - Temperature Relationship 

2.5 Sensitivity of Microalgae to 100 % 02 

Tensions 

2.6 Carbonate Species in Seawater at Equilibrium 

3.1 Algal Growth Pond and Paddlewheel Designs 

3.2 Diurnal variation of Climatic Inputs 

for Roswell, New Mexico in July 

3.3 Algal Growth Pond Model Flowchart 

3.4 Diurnal Temperature Profile for July at 

Roswell, New Mexico vs. Depth 

3.5 Diurnal Temperature Profile for July at 

Roswell, New Mexico vs. Evaporation Rate 

3.6 Seasonal Distribution of Max/Min Pond 

Temperature for Roswell, New Mexico 

3.7 Time Dependent Oxygen Profiles vs. outgassing 

at a Productivity of 30 g/m2/day 

3.8 C02 utilization Efficiency vs. Starting pH 

at 2, 10, and 30 roM Alkalinity 

3.9 Time Between Carbonation stations vs. Starting 

pH at 2, 10, and 30 roM Alkalinity 

3.10 pH-Alkalinity Relationship vs. Starting pH for 

Carbonation Intervals of 0.5, 1, 2, 4, 8 Hours 

3.11 Diurnal Temperature Profiles for 20 cm Ponds 

for september 1986 in Vacaville, CA 

Page 

4 

14 

18 

20 

23 

29 

30 

36 

41 

42 

46 

47 

49 

51 

52 

53 

54 

56 
3.12 Plot of Rate of Carbon Loss vs. C02 Driving 

Force for a 15 cm Pond Mixed at 30 cm/sec 

4.1 Dry Weight Curves for Cultures 131-134: 

Fluctuating Temperature and Oxygen 

4.2a Cell Concentration for Fluctuating Oxygen and 

58 

62 

Temperature Conditions(Culture 131) 63 

4.2b Cell Concentration for Fluctuating Oxygen and 

Constant Temperature(Culture 132) 63 

4.2c Cell Concentration for Fluctuating Oxygen and 

Fluctuating Temperature Conditions (Culture 133) 64 

4.2d Cell Concentration for Fluctuating Oxygen and 

Temperature and High Light Conditions (Culture 134) 64 

4.3a Cell Concentration vs. Time for pH = 7.1 67 

4.3b Cell Concentration vs. Time for Fluctuating 

Alkalinity 67 

4.3c Cell Concentration vs. Time for pH = 8.2 68 

4.3d Cell Concentration vs. Time for Fluctuating PC02 68 

4.4a Cell Concentration at a Dilution Rate of 1.23/day 69 

4.4b Cell Concentration at a Dilution Rate of 0.83/day 69 

4.4c Cell Concentration at a Dilution Rate of 0.33/day 70 

4.4d Cell Concentration at a Dilution Rate of 0.73/day 

with Gas Bubbler 70 

5.1 Growth Rate - Cell Quota Relationship During N 

Deficiency at One and Two Side Illumination 88 

5.2 Chlorophyll a Content vs. Cell Nitrogen 88 

5.3 Lipid content vs. Cell Nitrogen 89 

5.4 Lipid productivity vs. Cell Nitrogen 89 

5.5 Heat of Combustion vs. Cell Nitrogen 92 

5.6 Biomass yield During Light Shift 92 

5.7 Chlorophyll a Yield During Light Shift 93 

5.8 Lipid yield During Light Shift 93 
5.9 Lipid content as a Function of Dilution Rate 

for Light Limited continuous culture of Nanno Q. 

5.10 Chlorophyll a Content as a Function of Dilution 

Rate for Light Limited continuous Cultures of 

Nanno Q. 

5.11 Biomass and Lipid Productivity in Light Limited 

Continuous Cultures of Nanno Q. 

5.12a Ash Free Dry Weight History for Culture 266 

(D= 0.71/day). 

5.12b Ash Free Dry Weight History for Culture 267 

(D= O.lS/day). 

5.12c Ash Free Dry Weight History for Culture 26S 

(D= 0.44/day). 

5.12d Ash Free Dry Weight History for Culture 269 

(D= 0.20/day). 

5.13 A Comparison of Chlorophyll a Productivity in N 

97 

97 

98 

100 

100 

101 

101 

Sufficient and Deficient continuous Culture. 102 

5.14 A Comparison of Biomass productivity in N 

Sufficient and Deficient continuous Culture. 102 

5.15 A Comparison of Lipid Productivity in N Sufficient 

and Deficient continuous Culture. 103 

5.16 Biomass and Lipid Productivity in Nitrogen Limited 

Continuous Cultures at 0.5/day as a Function of 

Standing Biomass. 105 

5.17 Biomass yield vs. Tim~ in Batch Culture Following 

Pre-adaptation to Nitrogen Limitation. 107 

5.1S Lipid Yield vs. Time in Batch Culture Following 

Pre-adaptation to Nitrogen Limitation. 107 
ACKNOWLEDGMENTS 

We wish to thank Drs. Robins McIntosh, Ken Terry, Bill Barclay, 

and Donna Johnson of the Solar Energy Research Institute, for 

their interest in, and help with, this project. We also thank Ms. 

Kathy Kearny and Ms. Linda Vance for excellent technical assistance, Dr. Chris Newman for help with the CHN analysis, and Dr. 

Thomas Tornabene for making available space and facilities for 

this research. We gratefully acknwoledge the many useful discussions with Dr. Joseph C. Weissman and his assistance and hospitality with the collection of the outdoor pond temperature data. 
SECTION 1.0 INTRODUCTION 

1.1.MICROALGAE CULTIVATION 

Microalgae have the ability to convert sunlight, carbon dioxide, 

water and inorganic fertilizers into useful products: proteins, 

lipids, carbohydrates, pigments, vitamins, etc. Their commercial 

potential has attracted the attention of biochemists, microbiologists, chemical engineers, and, most recently, entrepreneurs. The 

appeal of microalgae is that "cheap" sunlight energy and carbon 

sources can substitute for the expensive fermentable substrates 

required in industrial microbiology. Advantages can also be cited 

for microalgal cultures over agricultural systems: very high 

yields (photosynthetic efficiencies), use of saline waters and 

marginal lands, and potential for continuous automated production. The ability to manipulate the metabolism of microalgae 

through control of the environment, resulting in overproduction 

of specific metabolites, is also appealing. The possibility of 

future improvements in productivity of algal mass culture systems by genetic engineering techniques is frequently suggested. 

However, significant disadvantages for microalgal systems are 

also apparent to even the casual observer: The use of sunlight 

requires reactors with extremely high ratios of surface area to 

volume, compared with conventional reactors. The lowest cost systems that achieve this requirement are simple open ponds which 

subject the cultures to contamination, a major technical difficulty. Microalgal cultures have very low volumetric productivities and low cell densities. Moreover, open ponds The harvesting 

of microalgae, from such dilute reactors, has proven to be a difficult problem to solve economically. C02 can be a major cost 

factor, commercial C02 can sometimes cost almost as much as 

fermentable substrates. Compared to agriculture the capital costs 

required to establish algal cUltivation systems have been very 

high. Table 1.1 summarizes the advantages and disadvantages of 

microalgae production. 

Up to the present the disadvantages have outweighed the advantages. The few commercial systems currently operating produce 

only high value products (> $10/kg of algal biomass, dry weight 

basis) primarily for the health food market. Almost forty years 

of applied research and development, involving many thousand 

scientist-years of effort and the investment of hundreds of millions of (current) dollars have not solved the fundamental problems which prevent the application of this technology to lower 

cost products - species control in outdoor mass cultures, harvesting of the biomass, C02 supply, low cost reactor (pond) 

designs, maximizing productivity, biomass processing, and development of marketable products. 

-1-
TABLE 1.1 ADVANTAGES AND DISADVANTAGES OF MICROALGAE TECHNOLOGY 

ADVANTAGES: 

o HIGH YIELDS (PHOTOSYNTHETIC EFFICIENCIES) 

o ENVIRONMENTALLY MANIPULATABLE 

o USES LOW QUALITY SALINE WATER 

o USES LOW QUALITY NON-ARABLE LAND 

o WATER LOSS BY EVAPORATION ONLY 

o NUTRIENT (FERTILIZER) RECYCLE POSSIBLE 

o LARGE PORTION OF BIOMASS UTILIZED 

o GENETIC IMPROVEMENTS NOT YET BEGUN 

DISADVANTAGES: 

o HARVESTING OF DILUTE CULTURES 

o C02 REQUIREMENTS 

o SPECIES CONTROL PROBLEMS IN OPEN PONDS 

o HIGH CAPITAL COSTS 

-2-
'. 

In 1953 the first comprehensive account of microalgal mass culture technology was published: "Algal Culture: from the Laboratory to the Pilot Plant" (1). That classic book, by its tile 

alone, already implied that the commercial development of microalgal systems was near at hand. The failure to realize these 

visions can be ascribed to a variety of factors: lack of sustained interdisciplinary research projects, emphasis on low cost 

commodities (foods, feeds, fuels, fertilizers) which were not 

realistically achievable in the near term, failure to develop low 

cost harvesting processes, the disappointingly low productivities 

observed with most outdoor pond systems, the difficulties inherent in processing the wet algal biomass into useful products, and 

the difficulties of reliably maintaining desirable algal species 

in outdoor ponds. In brief, development of microalgal mass culture proved more difficult than anticipated. For microalgae to 

become a source of low value, commodity type, products a large 

number of biological and engineering problems must be solved, and 

the solutions integrated into an overall process capable of producing algal biomass for less then $500/ton (ash-free dry weight 

basis) • 

As stated above, at present commercial microalgae production systems produce algal biomass, prior to processing and extraction, 

at a cost of above $10/kg. This has limited the worldwide commercial microalgal production to an aggregate of less then 50 hectares or 2,000 tons per year, the output of one mid-sized u.s. 

farm. Most of these (rather small, < 5 hal plants are located in 

the Japan and Taiwan, where Chlorella and Spirulina are cultivated and sold as "health foods". Spirulina production is also 

taking place in Mexico, Israel and the U.S., where a 4 hectare 

plant (Figure 1) has operated since 1981 near the Salton Sea in 

Southern California. Smaller scale commercial Spirulina production is also taking place in Hawaii, and Israel •. 

The discovery that some strains of Dunaliella salina have a high 

content (sometimes over 10%) of beta-carotene (2), a provitamin A 

and food color, with a value of over $300/kg (for the synthetic 

product) led to the expectation that this product would quickly 

become the first significant non-health food commercial product 

from microalgae. Although development was rather slow, several 

beta-carotene production plants are now operating, or are currently staring up, in Israel, the u.S. (California and Hawaii) 

(Figure 1) and Australia. However, even in this case production 

costs have turned out to be high, and the current plants can not 

yet compete with the synthetic product. The few other high value 

products (soil inoculum, aquaculture feeds, food colors, pigments) derived from microalgae are very small in scale «$1 million total). 

A recent engineering and cost analysis of the inherent economics 

of algal mass culture (3) concluded that no fundamental engineering or economic constraints prevent low cost « $500/ metric ton) 

microalgae production. This requires, however, simple, unlined, 

-3-
FIGURE 1.1 COMMERCIAL MICROALGAL POND SYSTEMS IN THE U.S. 

(Photos courtesy or Earthrise Farms, Inc. and Cyanotech, Inc.) 

l.la Earthrise Farms, Inc. Spirulina Plant, Salton Sea, Calif. 

l.lb Cyanotech,· Inc. Spirulina and Dunaliella Ponds, Hawaii 

-4-
large scale (>500 hectares) pond systems at sites with favorable 

climatic conditions, low cost water, and cheap carbon dioxide. In 

the u.s. such locations exist in Southern California and other 

Southern and western States. A high biomass productivity and low 

cost harvesting process are the key technical assumptions underlying such a cost analysis. If a high productivity of "lipids" 

(hydrocarbons or triglycerides) can be achieved, and the overall 

site and cost assumptions (e.g. capital charges) are favorable, 

liquid fuels could be produced from microalgae (3). 

Recent research sponsored by the SERI Aquatic species Program 

has demonstrated sustained high productivities with outdoor algal 

cultures (4,5). Low cost harvesting, either by bioflocculation 

(6) or chemical flocculation (7) has also been demonstrated. The 

development of low cost processes for algal production of lipids, 

still requires fundamental and applied R&D in the areas of algal 

species control and metabolic control of product formation. These 

are the objectives of this project. 

1.2. MICROALGAE SPECIES CONTROL 

Maintaining a monoalgal culture of a specific inoculated strain 

in outdoor ponds is necessary since only specific, genetically 

selected, algal strains will exhibit the high lipid productivities required for a practical process. The difficulty of cultivating one desired microalgal strain in the presence of innumerable potential contaminants, predators, and parasites, is indeed 

considered formidable (8). It is, however, not unlike the agricultural problem of growing crops in competition with weeds and 

pests. The solution in agriculture has been a combination of 

plant breeding, chemical inhibition of undesirable organisms 

(weeds, pests, diseases), and mechanical tillage and (where possible) weed removal. Species control (or, technically more correct, strain maintenance) in algaeculture will be inherently more 

difficult than in agriculture: mechanical weed removal is usually 

not feasible and chemical approaches suffer from dilution in the 

pond medium and potential contamination of the product more 

severe then with agricultural crops. 

Some limited advances in this area have been made. For example, 

it has been found that high ammonia or pH will inhibit most zooplankton infestations. However, in general, current methods for 

algal species control have relied on using extremes in environmental conditions which inhibit most other algae (and other 

organisms) and select for specific microalgae species: very high 

alkalinity selects for Spirulina and high salinity for Dunaliella, the two major species currently being cUltivated. These 

techniques are expensive, as they require large quantities of 

salts. They also result in severe reductions in algal productivities. 

-5-
Production of Chlorella, the other major species commercially 

mass cultured, suffered from severe contamination problems, 

solved only by the use of very large inoculum levels (produced 

under sterile conditions) and limited duration semi-batch operations, which reduce overall productivity and greatly increase 

costs. An even more extreme example are the diatoms and flagellates mass cultured for bivalve feed: Isochrysis, Tetraselmis, 

Chaetoceros, etc. These are grown under highly controlled, laboratory, conditions because of invasion by undesirable microalgae. 

Costs are very high (>$100jkg dry weight basis) and limit the 

application of algae feeds in aquaculture. 

Even though the problems of contamination and culture "crashes" 

have been frequently referred to in the literature on algal mass 

cultures, to date there have been few specific pUblications dealing with species control in algal mass cultures. No systematic 

investigation has been carried out into the factors determining 

species dominance in mass culture systems. The obvious solution 

to this problem is to identify strains which easily dominate 

under specific outdoor pond environments. Indeed this applies to 

the mass culture of Spirulina and Dunaliella, where the ionic 

environment overwhelms most (but not all) other environmental 

factors. 

Another example of this approach was the CUltivation of a Scenedesmus strain in Germany and other locations (9). This strain 

was apparently an isolate from one of the early mass culture 

ponds that was operated in Germany, and was successfully maintained in outdoor systems operated with similar media in a variety of locations. Only when it was attempted to mass culture this 

strain in Thailand, did the contamination problem become intractable and other algae became dominant (10). 

One of the objectives of this project is to identify factors 

which are important in determining selection and dominance of 

specific algal strains in outdoor systems. Although maximum 

growth rates under laboratory conditions (typically, 2SoC, low 

light) are often measured for algal species being screened for 

suitability for mass culture, these conditions have little, if 

any, relevance to outdoor pond situations, where high incident 

light intensities, dense cultures, light limited growth rates, 

and diurnally fluctuating environmental parameters present a very 

different situation from the conventional laboratory environment. 

However, not every environmental factor can be decisive, and the 

issue reduces to identifying which parameters affect algal strain 

competition to the greatest extent. The hypothesis being tested 

is that a few factors are critical in determining species dominance and maintenance, while others play a relatively minor role 

in the outcome of species ( s.train) competition. 

If this hypothesis is correct, it may be possible to select algal 

strains suitable for mass culture based on specific physiological 

adaptations, which might be reproduced in the laboratory, rather 

-6-
than depending on self-selecting strains in outdoor ponds. This 

would have significant advantages in the development of an algal 

technology, from the screening of strains for suitability for 

outdoor systems to their improvement for productivity and lipid 

formation through strain selection and genetic engineering. 

The approach followed by this project has been to model the outdoor cultivation environment as a function of climatic and system 

design related inputs and to predict the time behavior and magnitude of specific environmental parameters and their fluctuations. 

Specifically the variables of temperature, pH, dissolved oxygen, 

and light intensity have been modelled. Based on results from the 

model, these conditions can be reproduced in a laboratory reactor 

and species productivity measured under fluctuating conditions as 

a function of controllable variables (dilution rate, nutrient 

supply) for several algae. The basic outcome of these experiments 

is productivity as a function of the imposed variables. The basic 

assumption that productivity is synonymous with competitiveness 

in such systems can be validated with mixed culture experiments. 

When compared with data obtained by other researchers operating 

outdoor systems with the same species, the results of this work 

will determine whether it is possible to use laboratory systems 

to select and screen microalgal species that are suited for cultivation in outdoor ponds. If this is successful it would greatly 

simplify species screening, strain selection and genetic engineering of micr.oalgae useful in mass culture. 

1.3 LIPID PRODUCTION BY MICROALGAE 

The second objective of this project was to determine the effects 

of nitrogen deficiency on the kinetics of lipid biosynthesis and 

to develop an optimized process design for lipid production by 

microalgae. Nutrient supply, particularly nitrogen, is one pond 

operating parameters that can be relatively easily manipulated. 

Nitrogen starvation of algae causes a shift in their metabolism, 

from growth associated to storage pathways, carbohydrates and 

lipids, which can accumulate in large amounts. Although carbohydrate storage is more common than lipid storage, microalgae from 

several species that accumulate lipids in large amounts (up to 

and over 50% of dry weight) can be readily isolated. 

However, the effect of nitrogen limitation on productivity, which 

is central to the question of whether lipid production by microalgal cultures is technically feasible, is not understood. Previous work by a preceding contract (10), involving a survey of 

eight strains of algae indicated that one, Nannochloropsis Q had 

a rapidly inducible pathway of lipid biosynthesis. This was also 

reported by other groups working with this organism (11). We have 

subjected this strain to a detailed study of the interactions of 

nitrogen limitations and light supply on biomass and lipid productivity as a model of lipid production by microalgae. 

-7-
1.4 CONTENTS OF THIS REPORT 

In this Report we first review the problem of species control in 

microalgal mass culture to present a theoretical framework for 

the present and future work in this area (Section 2.0). Next we 

develop a computer model for the behavior of a mass culture 

(pond) system in terms of key environmental parameters (temperature, light, pH, P02) (Section 3.0) which can guide the laboratory experiments by setting realistic boundaries to the parameters that need to be considered in these studies. The experiments with mixed cultures and species competition are presented 

in section 4.0. A brief review of algal lipid content and productivity is presented in section 5.0, followed by the experimental results(Section 6.0). The final section (7.0) summarizes the 

results and the proposed future work for this project next year. 

-8-
SECTION 2.0 GROWTH AND COMPETITION OF 

MICROALGAE IN MASS CULTURES 

2.1 INTRODUCTION 

The problem of species dominance and competition in outdoor mass 

cultures is considerably simpler than the problem of phytoplankton species dominance and succession in natural bodies of water. 

The variations of biota, light, temperature, pH, and oxygen in an 

algal growth pond are more predictable, and less random, than in 

ponds, lakes, estuaries, or oceans. This is principally because 

of the control over nutrient supplies and the uniform mixing in 

the m~ss culture growth pond. 

Thus most of the problems that preoccupy phytoplankton ecologists 

and physiologists are not of direct concern in outdoor algal mass 

cultures. For example, the central problem for phytoplankton 

ecology is inorganic nutrient limitations. This can be avoided or 

controlled in algal cUltivation. Environmental patchiness, a 

major focus of much of the ecological literature, is also not an 

issue in mass culture ponds. Light limitation, the key limiting 

factor in algal mass cultures, is less frequently addressed as a 

primary limiting factor by phytoplankton ecologists. Nevertheless, any theoretical framework of algal species control in algal 

mass culture must draw from the enormous body of research on phytoplankton ecology, physiology, and biochemistry, that has accumulated, almost in exponential fashion, over the past few decades. 

This is the objective of this section. A brief review of the 

algal pond environment is presented first (see also Section 3.0). 

2.2 THE HIGH RATE POND ENVIRONMENT 

In essence the algal mass culture growth pond consists of a raceway type channel mixed by paddlewheels at between 15 and 30 

cm/sec. The depth of the cultures is generally 10 to 30cm. The 

channels can be quite wide and long with individual ponds, mixed 

by a single paddle wheel, up to 10 hectares in size, theoretically. In current practice, individual growth ponds would be 

about 3 to 4 hectares in size, maximally. The pond is supplied 

with C02 through a sump spanning the channel, preferably near the 

paddlewheel. Flow deflectors are used around bends and in other 

strategic locations to prevent dead spots. The culture is harvested on a daily basis, with anywhere from 20 to 70% of the culture liquid withdrawn and replaced with make-up water and media 

recycled from the harvesting system. Nutrients are supplied with 

the make-up water or added directly into the ponds. Although a 

-9-
number of variations are possible on this basic design, this is 

the essential algal production system envisioned in this project, 

as it is, in principle, of very low cost (3). It also has been 

adopted by most recent experimental projects and commercial ventures in algal mass culture, although the largest individual 

growth ponds currently existing are about 0.5 hectares in size. 

The size of the pond has significant effects on the environment 

experienced by the algae. For example, if only one C02 supply 

station is provided (which is likely the case, for economic reasons) then the larger the pond the larger the amplitude and 

longer the periodicities in pH fluctuations to which the algae 

will be subjected between C02 resupply events. Keeping the fluctuations in pH (and the associated changes in pC02) within 

acceptable limits, as dictated by considerations of species control and productivity, are a major factor in the design of the 

pond system. Thus the commonly observed dominance of the diatom 

Phaeodactylum tricornutum in seawater algal cultures has been 

ascribed to the high pH found in most such culture systems (11). 

Since this organism is usually not among those that would be 

desirable, a seawater system design and operation should avoid 

extremes in pH to the extent feasible. A key question in this 

case, as well as that of the other factors addressed below, is 

the effect of periodic fluctuations as compared to continuous 

steady state conditions. 

Besides pond size, factors affecting the pH range experienced by 

the algal cells in the culture are the mixing velocity, the outgassing coefficient, the alkalinity (and ionic composition) of 

the media, the productivity of the culture, and the efficiency of 

the carbonation system. Although there is some flexibility, the 

pH fluctuations in the ponds will to a large degree be predetermined by engineering and operating (that is economic) considerations. This suggests that the algal species to be cultivated 

must be either chosen or genetically selected to meet the pH/pC02 

constraints imposed by the mass culture system. To a greater or 

lesser degree, similar considerations apply to the other environmental factors affecting species competition and productivity. 

The key abiotic environmental parameters most likely to affect 

algal productivity and species competition are light, pH, pC02' 

temperature; p02' salts, dilution rate and nutrient levels. Some 

of these cannot be controlled to any significant extent (light, 

temperature), others to only a limited degree (pH, pC02' p02' 

salts), while some can be manipulated almost at will (nutrients, 

dilution rate). The abiotic pond environment can be modeled given 

detailed site specific climatic input parameters and assumptions 

about the design of the system (e.g. scale, ~ength to width 

ratio, pond depths, etc.), water quality, and system operations 

(dilution rate and schedules, nutrient supplies, mixing velocities, etc.). Such a model is presented in section 3.0. This Section reviews the effects of these key parameters, singly and in 

combination, on microalgal growth, productivity, and species 

competition. First some theoretical considerations are discussed. 

-10-
2.1 THEORETICAL BASIS FOR SPECIES COMPETITION. 

Darwin's basic observation about evolution was that a given environment will select for the most capable organism. Capable is 

defined as the ability to increase the number of decedents relative to other, competing, organisms. Competition refers to utilization of the resources which limit the overall population size 

and growth rate of the competing organisms. This is the fundamental concept underlying competition, selection, and evolution. 

In algal mass culture ponds the fundamental limiting factor 

should be, at all times, light. The cost of the biomass is very 

sensitive to the overall productivity (g/m2/day or mt/ha/yr) of 

the system, which can only be maximized by absorbing essentially 

all the light and utilizing it efficiently. It must, however be 

recognized, that efficiency of light utilization by the individual cell (the competing organism) does not translate into high 

productivity by the overall culture. This fundamental point is 

addressed further below. 

The environment of an algal mass culture pond is unlike that of 

any natural system in terms of the specific combination of factors that will affect growth rates and productivities by microalgae. Thus it is not surprising that the ecological literature has 

significant gaps that prevent a more detailed understanding of 

algal physiology and species dynamics in mass culture environments. Perhaps more importantly, algae isolated from natural 

environments are unlikely to be optimally adapted to the pond 

environment. This suggests that genetic selection may significantly improve future productivities by algal mass cultures and 

the ability to maintain monocultures. A major corollary of this 

hypothesis is that care must be taken to prevent the adaptation 

of unwanted organisms to the pond environment. 

At its most basic, when a single limiting resource exists such as 

a chemical substance (nutrient), then those organisms most capable of capturing that substance (and, but not necessarily, utilizing it most efficiently) will be better able to compete and 

eventually become dominant in the environment. However, if two 

organisms differ, through a hereditable genetic difference, in 

their capability for capture of the same limiting substance, then 

the one that is, even if only slightly, better at capturing the 

limiting nutrient will prevail in that environment. Eventually 

such a competition for one limiting factor results in a single 

type of dominant organism. Since for any individual organism, 

according to Liebing's Law of the Minimum, as applied by Gause 

(13) (see also Hardin [14] and Levins [15]) ), only a single factor can be limiting at one time, the logical result is that for 

each limiting factor or nutrient in the environment only one 

organism can win the struggle for survival. 

The obvious falsehood of this conclusion was pointed out for the 

specific case of microalgae in Hutchinson's famous paper on the 

"Paradox of the Plankton" (16). Since a single drop of water can 

-11-
contain dozens or even hundreds of different algal species and 

since in such environments only a relatively few nutrients (N, P, 

Fe, etc.) can possibly limit algal growth, the coexistence of so 

many different species can not be explained by the above arguments. Either the arguments are wrong or other factors must play 

a role in allowing so many species to survive, or both. 

One explanation for the Paradox of the Plankton was that resource - growth rate relationships were similar enough among different 

algae, and environmental conditions variable enough to prevent 

a final equilibrium result from occurring. The variation in conditions has been termed patchiness - with the implication being 

that each patch is its own ecological niche, a microcosm with 

different limiting nutrients from those of surrounding patches. 

As the patches decay and new ones form, the competition for 

resources never is carried out long enough to reach equilibrium, 

e.g. extinction of the majority of the species. Another, perhaps 

better, explanation was that different mechanisms for removal of 

organisms, particularly sinking and zooplankton grazing can 

reduce the yield of the most dominant species thus providing an 

increased resource base for the less capable. Inhibition of one 

organism by another through excreted substances (allelopathy) is 

another potential mechanism to allow coexistence of several 

species under conditions of a single nutrient limitation. These 

arguments were deemed sufficiently satisfactory explanations of 

the Paradox to concentrate most research into the questions of 

what the limiting factors were which caused the dominance of specific species and the frequent successions of species in nature. 

Another explanation for the Paradox has more recently been proposed: in a fluctuating temporal environment resource utilization 

is quite different from that in a steady state environment (as 

has been assumed by most models and laboratory studies). For 

example, during a diurnal light cycle some algae are better able 

to utilize a limiting nutrient (e.g. N) in the dark period and 

others in the light period. Thus both can coexist. If the 

nutrient itself is added in a cyclic fashion, different species 

may be adapted to preferential utilization during periods of high 

and low supply (17). Thus fluctuating environments essentially 

act to increase the number of potentially co-exisiting organisms. 

This may not be desirable in mass culture ponds, where a single 

species (strain) is to be maintained as a monoculture. However, 

the common observation is that upon nutrient enrichment of lakes 

or ponds,' or in mass culture one organism usually dominates (90%+ 

of the total biomass present) at a time. Thus, although theoretically many "niches" exist, allowing two or more algae to coexist, 

one strain usually has a sufficien~ advantage in the capture of 

most of the limiting nutrient (light) to prevent any significant 

competition. This is the major paradigm on which our research on 

species competition and control in algal mass cultures is built: 

the pond environment will select for a single species as an 

essential monoculture and species succession can be·prevented or 

minimized by adjustments in pond operations. 

-12-
The mathematical treatment of competition is a simple matter of 

writing the material balances for each species coupled with an 

accurate rate expression for growth (see Ref. 18). If necessary 

one can include terms for inoculum make-up, allelopathic or 

antagonistic interactions, and losses (predation, sinking). In 

the simplest case the competition between two organisms whose 

growth follows Monod kinetics can be easily modeled (19). Four 

different steady state results are possible: the trivial result 

of each population equalling zero, and the non-trivial cases of 

each population by itself dominating, or both populations codominating. Co-dominance is only possible in this model if the 

growth rate-substrate curves intersect (e.g. the substrate concentration at which both had identical growth rates) • (See Figure 

2.1c). But co-dominance at this point, although theoretically possible is inherently unstable as any small deviation in substrate 

concentration (e.g. dilution rate) or even stochastic events 

would result in an irreversible decline of one or the other of 

the organisms. However, if two different potentially limiting 

substrates are present and the two competing organisms differ in 

their affinity for the two substrates, then a stable coexistence 

is possible under conditions where the two organisms are limited 

by different nutrients. Small deviations in substrate levels 

would not result in long term changes in species composition. 

Tilman (20) tested the validity of this simple competition model 

by determining species dominance for two diatoms limited by different resources. The affinity constant for silicate for Asterionella formosa was higher than that for Cyclotella meneghiniana 

while the opposite was true for phosphorous. Maximum growth rates 

were essentially the same. By setting the two growth rate expressions equal he was able to predict under what concentration 

ratios of si and P co~dominance would be observed. He then verified this experimentally and found that experimental results for 

the mixed cultures agreed with the theoretical predictions form 

the unialgal culture experiments. Although expected, these 

results demonstrated that mixed culture experiments can in practice be predicted from unialgal culture data (e.g. growth rate 

vs. substrate concentrations). 

Of course, these results would not be obtained if there was 

interference between the organisms, specifically if allelopathic 

effects were involved. Allelopathic interactions between microalgae have been observed repeatedly (21) and would affect such 

studies. Allelopathic effects can be determined by growing the 

algae in the "spent" culture media (suitably fortified with the 

limiting nutrients) of each other. Any gross inhibition that 

could not be corrected by the addition of nutrients would reflect 

the presence of inhibitory compounds. It must be noted that for 

allelopathy to become a significant problem the inhibitory alga 

must have established a significant presence in the culture, as 

it acts through its metabolic products. Thus allelopathy and 

interference mechanisms generally could account for stable coexistence with only one limiting nutrient (22). In this case the 

starting point (e.g. the proportion of species initially present) 

determine the dominance pattern observ.ed at steady state. 

-13-
FIGURE 2.1 GROWTH RATE - SUBSTRATE RELATIONSHIPS 

A) K1< K2 I 

B) K1> K21 

a) 

b) 

U1max> u2max1 u = 0 at s = 0 

u1max> u2max1 u = 0 at s = 0 

2 

5 

-14-
Returning to Fig. 2.1b, for the case where u~max > u2~ax and 

K1 < K2' an argument can be made for stable coex~stence ~f the 

resource supply profile fluctuates from a low to a high concentrations in some time dependent manner. Under these conditions, 

assuming instantaneous adaptation to the nutrient level and 

coupled nutrient uptake and growth, organism a will grow faster 

during periods of low and organism b during periods of high 

nutrient concentrations. Depending on the amplitude of the fluctuations (but not the periodicity) one or the other or both of 

the organisms can stably coexist in the system. However since 

none of the assumptions is true in real life, an accurate determination of competitiveness must include adaptation (time lags) 

to the nutrient levels as well as distinction between the instantaneous growth rate and nutrient uptake rate (see discussion 

below). This would result in both the amplitude and periodicity 

of the fluctuations in nutrient supply determining the outcome of 

the competition for the resource. It could also result in more 

then two organisms coexisting on one fluctuating limiting factor. 

Another consideration is that for a given nutrient there may be 

more then one potential mechanism by which one organism can utilize it, resulting in a change in both Vmax and Km for the 

nutrient, depending on its concentration and the time allowed for 

the organism to metabolically adapt to it (as well as the organism's growth rate and other physiological characteristics at the 

time). For example if the resource was C02 supply, and it was 

suddenly changed from a high to a low concentration, an active 

bicarbonate assimilation mechanism may be induced utilizing the 

enzyme carbonic anhydrase and other (as yet unidentified) cell 

components. Since it may take from 30 minutes to several hours 

for such a shift in metabolism to develop, it is clear that the 

situation in the case of a fluctuating limiting nutrient can be 

indeed complex. Although it should be possible to predict the 

behavior of the organisms under such conditions, the amount of 

data required would be very large indeed. 

A further complication is that in many cases when a culture is 

exposed to a limiting level of a resource, a sudden increase of 

that resource will result in an overshoot in assimilation. These 

have time constants on the order of 30 minutes to several hours. 

Such an overshoot will then result in an undershoot, as the cell 

tries to adapt to the new environment. The result is an approach 

to the new equilibrium through a damped oscillation that may be 

detected for a considerable period of time. 

In conclusion, growth (and thus prediction of the outcome of 

competition) during the transient or fluctuating supply of a 

single limiting substrate will not be a straightforward extrapolation of steady state uptake kinetics for that nutrient, as they 

are affected by the adaptation and overshoot (or undershoot) time 

constants. In fact these time constants may be the most important 

selective force in determining species dominance, depending upon 

the frequency, amplitude, and variance of the fluctuations. 

-15-
Finally, another major complicating problem is that environmental 

factors tend to interact. Thus the results obtained with cultures 

subjected to variations in single factors under constant environmental conditions for other factors can not be extrapolated to 

what would be observed if under conditions where more then one 

factor was varied in a time dependent manner, as would be the 

case in mass culture ponds. 

Indeed it is often not even possible to predict how two invariant 

factors will interact. Although models for the interactions of 

limiting nutrients with temperature of the temperature effects 

and light limitations have been proposed (24,25), the actual 

(very limited) data collected have shown that neither multiplicative nor additive models can explain the interactions of temperature or light with nutrient (N or P) limitation (26,27). Varying 

two factors simultaneously resulted in larger effects on growth 

rates then would be predicted by such models. 

In conclusion, a logical approach to the study of algal mass culture is to carry out experiments under conditions that simulate, 

as much as possible, the dynamic environments observed or predicted in ponds and to determine the effects of specific variables, or combination of variables, that may be of interest in 

the operation, design, or siting of an algal mass culture facility. The results and predictions of single species experiments 

would then need to be confirmed, on a selected basis with mixed 

cultures. The key issue is whether it is indeed possible to simulate in a laboratory setting the conditions in outdoor ponds sufficiently closely to allow the collection of data that can be 

extrapolated to a mass culture situation. For this it is not only 

necessary to know or predict the actual environment in outdoor 

ponds but to also focus on the factors most likely to affect the 

growth rates and productivities of algal species. These factors, 

and their interactions, are reviewed in this chapter. 

2.3 LIGHT 

The specific problem addressed in species competition studies in 

mass cultures is competition with light as the primary growth 

limiting nutrient. Light is not a typical resource as it is not 

supplied with the media influent and it is not conserved, whatever is not immediately used is lost. Light, however, can be 

modeled satisfactorily with conventional saturation type growth 

kinetics (the P vs. I curve is similar to Figure 2.1). However, 

unlike most inorganic nutrients, there is often a detectable nonzero intercept of the P vs. I curve, with the intercept light 

intensity being the "compensation point", or the minimum light 

energy required to maintain the metabolism of the algae. It is 

thus, theoretically at least, for two algae to coexist with light 

as the sole limiting nutrient if their P vs. I curves intersect 

twice _ (This is, of course also possible for inorganic nutrients but in that case the maintenance nutrient level 

is generally so low as not to be detectable.) 

-16-
Light comes in packets of photons which have a characteristic 

wavelength-energy density pattern. The pigment complex of the 

cell will absorb the incoming radiation according to its absorption spectrum and utilize it according to its action spectrum 

(the two being generally close but not identical). Different 

algae have different absorption patterns (for example see Figure 

2.2) and different action spectra, that is photosynthetic rate as 

a function of wavelength. It is therefore the product of the 

light energy-wavelength relationship, the absorption spectrum and 

the action spectrum integrated over all wavelengths which results 

in the observed photosynthesis -irradiance relationship. Thus 

both light absorption and utilization efficiency are important. 

A consequence of this is that light acts not as a single nutrient 

but has the potential of behaving like multiple nutrients, such 

that more then one algal type can coexist under light limited 

conditions (Even if the P vs. I curves do not intersect twice). 

Indeed this can be observed in the case of the laboratory culture 

of Spirulina and Chlorella (28). A theoretical mathematical 

treatment of light as a multiple nutrient has been published 

(29). However, in practice, the coexistence generally is not 

co-dominance, the most efficient light capturing organism usually 

will make up over 90% of the total biomass, with the other algae 

capable, literally, of growing in the shadow of the dominant 

species, but representing a rather small fraction. 

As stated, mass cultures, to maximize productivity, operate under 

light limited conditions, usually at cell densities of > 200 ppm, 

and with a standing biomass of 50 to 100 g/m2/day. If light is 

the limiting nutrient for algal productivity, then, because of 

the law of the minimum the competition problem reduces to one of 

determining a given organisms ability to capture and utilize 

light under the conditions of the outdoor pond. It must be, however, again, be emphasized that light capture and utilization are 

not necessarily synonymous. Also, the reference here is to single 

individual cells, not the performance of a whole culture. A very 

competitive strain, which can rapidly become dominant in a culture may actually result in a decline in overall culture productivity, as explained next. 

Light capture (absorption) by algal cells is dependent on the 

total pigment content of the cell, while light utilization (photosynthesis) is dependent on number and turnover rates of the 

photosynthetic reaction centers and the activities of the enzymes 

of the dark reactions (C02 fixation) in each cell. High pigment 

content in algae is due to a large amount of "antenna" chlorophyll and accessory pigments (biliproteins and carotenoids) and 

results in saturation of photosynthesis by low light intensities. 

This is a competitive advantage under light limited conditions. 

However at the surface of the ponds sunlight intensities are well 

in excess of saturating light intensities. Light is nevertheless 

absorbed by the pigment system. A large fraction of this incident 

light, whatever is above the saturating intensity, can not be 

used fast enough in photosynthesis, and is wasted as fluorescence 

and heat. 

-17-
FIGURE 2.2 IN VIVO ABSORPTION SPECTRA OF MICROALGAE 

Algae Spectra are not corrected for scattering. 

300 400 500 600 700 

wavelength (nrn) 

-18-
Thus, as already recognized many years ago, productivity of algal 

mass cultures could be increased by simply using algal strains 

that have much lower antenna pigment concentrations, assuming 

that changes in other factors (e.g. compensation point) do not 

negate this advantage. Algae with lower antenna and accessory 

pigment contents would not shade out the underlying cells and not 

absorb more light then they need for maximal photosynthesis. However, such low pigment cells would have a disadvantage under conditions of light limitation, which apply throughout most of the 

pond depth profile (except in the top few cm or even rom). Because 

of the lack of the accessory pigments they would not be able to 

capture many photons in the dim depths of the ponds. They would 

individually grow slower then more pigmented cells at low light 

intensity. They would be quickly out-competed, by more pigmented 

cells. 

Only under dilute culture conditions would a reduction in accessory pigments be of advantage to the cells, to the extent that 

the additional metabolic investment into accessory pigment (and 

the effect of photoinhibition) would dictate. Indeed, there is a 

clear sun-shade adaptation phenomenon in most algae (30). However, use of dilute (low standing biomass) cultures would negate 

the objective of the mass culture, which is to maximize areal 

productivities, which can only be achieved by absorbing and utilizing as much light as possible. Dilute cultures would also 

have the additional severe disadvantage of requiring constant 

dilution and a large harvesting effort. If a strain of algae that 

naturally remains "sun" adapted 'even in light limitation, or has 

been genetically selected for reduced accessory pigment production were to be grown in outdoor ponds, it would be very quickly 

overtaken by shade adapted invading algae, which would have a 

significant advantage in terms of growth rate in such situations. 

Therefore mass cultures must be relatively dense and will select 

for high pigment cells, which will underutilize incident light at 

the surface and shade the underlying cells. Mathematically this 

can be represented by the "Bush equation" which combines the 

absorption of an algal culture with the P vs. I curve.(31). (See 

Figure 2.3) (33). The overall result is a reduction in culture 

productivity, of as much as 60 to 70 % for a culture with saturating light intensities of 15% of sunlight, as compared to 

achievable productivities if the same amount of light could be 

delivered at a lower (below saturating) intensity to the culture. 

One method for delivering sunlight in such an attenuated fashion 

is by producing a very high degree of turbulence, such that the 

algae will absorb the full sunlight intensity for only a small 

fraction of a second, sufficient only to trap one photon per photosynthetic unit (reaction center). This can be achieved in laboratory setting by either modulating the light into very short· 

bursts (a few msec) (33) or by very rapid stirring of the cultures (34). Neither is practical in a production pond. The effect 

of longer periodicities on productivity is controversial, with 

both data for and against positive and negative effects (35-37). 

-19-
FIGURE 2.3 PHOTOSYNTHESIS VS IRRADIANCE AND DEPTH RELATIONSHIP 

(Source: Ref. 33) 

A opt 

Absorbance Ah 

.------~~'---------------------~~-~Ir---- A X/ 7

'1 ,.."" ~ . 1

0

. 

I , IAn .,.. IA' 

I 

I 

I 

I 

I 

I 

I 

I 

/ 

fil g: 

I 

I 

, 

, 

I 

I 

I 

z 

I ' .,.. .,../ .. "" I .,.. .. 

/ \0· 

/ IA \""~ 

A 

/ 

I 

/ 

/ 

I 

/ 

/ 

I 

---Ah--..t-

/1 

/ I 

/ 

/ I 

I I I 1 

I 

/ I 

I , 

/ / I 

Aopt -----l'--~----=-- ---t" 

I 

I-

, .... ..... I ......... 

I 

I 

~------~------------------~--~I 

I k light Intensity 10 

-20-
From the perspective of this project, the key question is whether 

the specific light fluctuations likely to occur in ponds will 

have a significant effect on algal productivity and competitiveness and whether such fluctuations can be mimicked with sufficient accuracy in laboratory reactors. Equally important perhaps 

is how accurately the spectrum of sunlight, its intensity, and 

its diurnal, seasonal, and climatic (e.g. cloud cover) variability must be reproduced in the laboratory to allow conclusions 

regarding productivity and species competition that can be extrapolated, even in modified form, to outdoor systems. 

In practice it would be very difficult (expensive) to faithfully 

reproduce both the spectrum (particularly UV) and the intensity 

of sunlight and it would be almost impossible to reproduce the 

light fluctuations due to pond mixing. Thus one of the assumptions made in this project is that a high intensity fluorescent 

light source (Duro-Test Vita Lite) delivering about 40% of full 

sunlight intensity and a magnetic/gas mixing system will not 

affect the overall results to a significant extent. (Of course, 

productivities must be corrected for the incident light intensity, applying the Bush equation to the P vs. I curve). In support for this view is that even if mixing effects in the 0.1 to 

10 Hz range can be demonstrated they are likely to be small and 

more likely due to other factors then an·increase in photosynthesis per se (e.g. decrease in 02 tensions, reduction in photoinhibition, improved nutrient supply) which would not apply to the 

laboratory reactor, where these factors would be better controlled. 

Thus, in conclusion, the outdoor light environment will not be 

reproduced very faithfully in the laboratory systems, either in 

terms of incident intensity, light quality, or light periodicities, because the problems involved greatly outweigh the likely 

benefits. Although strong arguments can be made for this, it 

points to the need for a verification and calibration of any 

results obtained with the laboratory system. This issue is discussed at the end of this section. The light environment will, 

however, be reproduced in terms of two critical issues: hours of 

sunlight (diel periodicities) and, at least in the future, the 

increase and decrease in light intensity during the daylight 

hours. 

Of specific interest are the factors which affect the lightphotosynthesis relationship. These are, among others, temperature, oxygen, pC02 and pH. Because of the fluctuating nature of 

these factors, the relevance of steady state measurements in predicting integrated growth responses is questionable. In the following sections each of these parameters will be discussed in 

terms of their general role in growth and metabolism, their 

selective pressure in mixed cultures, the time constants involved 

in their adaptation to new conditions, and their interactions 

with light (and each other). In most cases the literature only 

allows a cursory and general description of these topics. 

-21-
2.4 TEMPERATURE 

There are a number of ways in which temperature may affect the 

productivity of an organism and thus its relative competitive 

ability. Abiotically, changes in temperature affect ionic 

equilibria, pH, and gas solubility which affect different species 

differently. Direct biotic effects of temperature include structural changes in membranes, proteins, and other macromolecules, 

and the rates of enzyme reactions. 

In plotting the growth rate vs. temperature, generally a more or 

less bell shaped curve is represented, with a certain optimum 

growth temperature 0 However, a closer inspection of such data, 

when available in sufficient detail (38) , reveals more fine 

structure (Figure 2.4): There is a broad region over which 

increases in temperature correspond to linear increases in the 

growth rate in an Arrhenius type of plot, indicating a constant 

energy of activation (and, presumably, the same limiting reaction). Usually, but not always, an inflection point is noted at 

low temperatures, indicating a change in energy of activation. Up 

to the temperature of maximal (e.g. optimal) growth rate, the 

growth of the organism is controlled by metabolic rates. Above 

the optimal temperature limit, usually within 2 to 30 C, a decline 

of growth rate is noted which drops to zero very quickly. The 

reason for this rapid decline is not quite clear, however it is 

evident that some limiting reaction mechanism is affected. 

The optimal growth rate temperature is usually measured under 

conditions of maximal growth rate (e.g. no nutrient limitations). 

However, temperature optima under conditions of nutrient limitation are different, because different metabolic activities have 

different temperature optima (and these, as may be expected, differ between species and strains). The effect of temperature on 

different metabolic pathways can result in countervailing 

effects: while increases in temperature enhance dark reaction 

enzyme activity (carbon dioxide reduction), they also increase 

the rate of respiratory processes(dark and light dependent respiration and glycolate excretion} (39). Thus the effect on productivity can be either positive or negative, depending on species. 

cultivation temperature may affect cell composition uptake rates, 

nutrient quota's, and photosynthetic performance(40-45}. In general, the cell quota for protein (44), carbon, nitrogen, and 

phosphorous all increase with temperature changes away from the 

optimum (45). Temperature and nutrient limitation interact to a 

lesser extent as the limitation becomes more severe. Nutrient 

uptake rates are not necessarily correlated with the optimum temperature for growth. Rhee and Gotham (41) found for a N limited 

Scenedesmus SPa the optimum uptake temperature was 5-10 °c below 

that for growth. On the other hand, optimal temperatures for 

growth rate and nutrient uptake were similar for P limited A. formosa~ 

-22-
2,& 

2,2 

1, 1,8 

-

-'" • 

o ~1~ • 

." 

::I.. 

o O. 10 

-

o,e 

0,2 

C D 

A 

I I J 

10 15 20 25 30 

35 

FIGURE 2.4 GROWTH RATE - TEMPERATURE RELATIONSHIP 

(Source: Ref. 38) 

-23-

' .... 

,·el 

rtO~TJ 
Changes in chlorophyll tend to be species specific and are 

closely related to photosynthetic performance (38,43). For most 

species it appears that chlorophyll content increases with 

decreasing temperature (46). This and an increase in dark fixation enzymes(RUBP) compensate for the reduction in the rate 

itself, thus allowing the photosynthetic process to continue 

unchanged on a per cell or dry weight basis (46). At incident 

intensities much less than saturating, temperature should not 

affect photosynthesis (47) because it is being regulated only by 

electron capture. At intensities greater than saturating, temperature will be important by regulating the activity of the C02 

fixing enzymes. The overall result in terms of net C02 fixation 

will be dependent upon the temperature mediated rates of light 

and dark respiration. In general this results in temperature 

effects on photosynthesis which are less then on other metabolic 

activities. However relatively few studies exist of temperature 

effects under light limited conditions of maximal photosynthetic 

productivity. 

Of specific interest in algal mass culture is the effect of diurnal temperature fluctuations in ponds, where the min-max temperature differential may easily exceed l50 C. These fluctuations are 

correlated with the diurnal light cycle, but dampened and 

delayed. This will have significant effects on algal productivity, however essentially no studies have been carried out on 

such diurnal temperature cycles. The reason is that in most natural environments (oceans, lakes, rivers) only seasonal temperature cycles, or temperature shocks are important. One recent 

study found that a six degree temperature differential (day 

night) actually increased growth rate (of Hantzschia) above the 

constant temperature control, but only within a rather narrow 

temperature range (48). The only other work found, goes back to 

the early studies of Tamiya (49) who carried out extensive 

studies during their development of a ChI orella production process. They reported that low night time temperatures significantly inhibited algal productivity by preventing cell division. 

This is corroborated from synchronous cultures, which show that 

there can be temperature sensitive stage during night time cell 

division (50). Obviously much more work is required in this area. 

One immediate question is to what extend the algae adapt physiologically to the diurnal temperature changes. 

The existence of temperature driven changes in structural and/or 

rate processes defines the two adaptive responses observed in 

algae. Temperature adaptation is reviewed by Li (38). To summarize, temperature changes which occur within the normal physiological range of the organism (ie. those described by a linear In 

u vs liT relationship), will result in an instantaneous response 

in the growth rate of the organism. Temperature changes outside 

of this range, will result in some damage to the cell, and an 

unpredictable outcome on growth. 

In the U. S. mass culture of algae may well be more limited by 

the m~n~mum night time temperatures to which the algae may be 

exposed then by limitations of solar radiation per se, or other 

-24-
climatic factors. Thus the resistance of algae to low temperatures is of interest. Harris (46) in his review of phytoplankton 

ecology concludes that microalgae are essentially chilling resistant plants, exPeriencing no permanent damage at temperatures as 

low as a few degrees C. However there is some evidence suggesting 

otherwise. Exposure to low temperatures of an high temperature 

strain of Chlorella resulted in bleaching of chlorophyll on a 

time scale of 15 hours at 100 C (50 % reduction in chlorophyll a) 

(51). Also Rao et ale (52) investigated the sensitivity of cold 

shock treatment as a function of the previous growth temperature 

and found that while cells grown at 25 °c were tolerant to exposure at 0 °C, those grown at 40 °c were killed after 5 minutes. 

Thus it appears that loss of cell viability after exposure to low 

temperature will be dependent on the previous growth temperature. 

In ponds, low temperatures will only result in the winter or 

transition months, where the mean temperature will already be 

significantly reduced. 

One of the few studies of temperature effects on species competition in outdoor ponds was carried out by Goldman and Ryther (53) 

who were studying temperature dependent species succession patterns in managed waste-water to aquaculture systems. Two, one 

meter deep, 15 square meter ponds were operated continuously with 

a combination wastewater-seawater feed, filtered to remove anything above 20 microns. Phytoplankton present in the feed were 

used as inoculum and the depth of the culture effectively dampened any daily fluctuations in temperature. These authors found 

that when the pond temperature remained below 25-30 °c diatoms 

dominated, above that, two chlorophytes were important. The 

organism Phaeodactylum tricornutum was the most common species 

and was displaced, in late spring, only after being predated upon 

by a "monad like flagellate". It was found to dominate in outdoor 

cultures over the temperature range of slightly less than 10 to 

20 °C. However when laboratory competition experiments were 

conducted, it was not the dominant organism at 100 C and its 

dominance at 15 and 200 C is uncertain due to methodological 

problems (41). The apparent disagreement between laboratory and 

outdoor results is not surprising when considering the significant differences in environments (the laboratory cultures were, 

for example, exposed to continuous low intensity light). From 

productivity vs. temperature experiments on mixed cultures the 

authors concluded that productivity was insensitive to temperature. 

A recent study from South Africa compared the productivity of 

algae cultures ( no species was specified!) in open heated and 

unheated (as well as covered) circular ponds (54). The unheated 

ponds exhibited lower productivities, which, however, were rather 

low « 20g/m2/day in all cases). Indeed, except during winter 

time, when minimum temperatures dipped to 40 C in the unheated 

ponds; the differences in productivities were rather small, considering a 7 to 10 °c temperature difference (max and min) 

between ponds. 

-25-
Tison et al.(55) have studied the influence of temperature fluc-

-tuations on species composition in cooling tower runoff from a 

nuclear power plant. In simulated ecosystems, they found that 

selection was based on the ability to survive at the extreme temperature swings(from ambient to >45 °C). Organisms that were commonly present in hot springs of similar temperatures were not 

found; therefore the fluctuation itself, or according to the 

authors, survivability at the low end of the temperature swing 

determined species composition. 

In conclusion, it appears that for temperature fluctuations 

within the normal physiological range of an organism the growth 

response integrated over the pond temperature during the lighted 

portion of the day will be predictive of competitiveness. Respiratory losses at night will similarly be determined by integrating over the temperature range experienced for that portion. If 

there are temperature excursions outside of this range, a discontinuity exists - the effect of which is unknown. The optimal temperature determined under constant laboratory conditions should 

be considered a maximal tolerated temperature. It is often 

remarked that the actual niche of a particular algal species is 

at temperatures significantly below the optimal measured in the 

laboratory. One explanation is that, since the lethal (or at 

least zero growth rate) temperature is close to the optimal, the 

optimal temperature is not really optimal but the maximal temperature. Thus, to a first approximation the "optimal" laboratory 

temperature determines the suitability of the algal species to 

summertime outdoor cUltivation conditions. Another area of concern is low night time temperatures, which may result in an upset 

of the normal cell division process and may affect productivity 

indirectly. Selection of algal species that divide during the 

daytime, or in the early dark phase (while temperatures are still 

relatively high) may be desirable. 

2.5 OXYGEN 

The presence of oxygen at levels far exceeding saturation in 

microalgae ponds (4,8) is due to high rates of photosynthesis, 

high cell densities, and the low gas transfer rates out of the 

pond. Oxygen is known to inhibit photosynthesis through a variety 

of mechanisms and therefore its high concentration represents a 

potential reduction in productivity. The earliest experiments of 

Warburg in the 1920's first demonstrated the inhibitory effect of 

100 % 02 on productivity. Glidwell and Raven (56) describe four 

oxygen consuming processes in algae; they are dark respiration, 

Mehler reactions, RUBISCO oxygenase, and glycolate metabolism. It 

is useful to briefly review each to learn of their possible role 

in determining productivity. 

The consumption of oxygen as a result of normal catabolic metabolism is called dark respiration. Its consumption typically represents about 10% of the total oxygen evolved, it is temperature 

-26-
(increasing exponentially with temperature)and growth rate dependent , but not oxygen dependent. Its rate is diminished in the 

light, apparently regulated by adenylate charge (46). Very low 

light intensities are required for inhibition. From short term 

incubations with labeled C02' it has been shown that no label 

appears in respired C02 therefore indicating a substrate far 

removed from recently fixed carbon (56). Because of its association with normal cell function and lack of sensitivity to oxygen 

it is not important in observed oxygen inhibition in ponds however is important in determining net productivity. It is commonly 

measured by short term incubations in an oxygen electrode. 

Light and oxygen dependent respiration is called photorespiration 

which is directly associated with RUBISCO oxygenase activity and 

glycolate metabolism. The term is generally applied whenever a 

decrease in the oxygen concentration results in an increase in 

C02 uptake. When cells grown on several percent C02 with air are 

exposed to high levels of oxygen an immediate reduction in carbon 

fixation occurs with measurable amounts of carbon being excreted. 

The excreted carbon is glycolate and reflects an accumulation 

within the cell. Glycolate formation is due to the oxygenase 

activity of the C02 fixing enzyme RUBISCO (Ribulose bisphosphate 

carboxylase-oxygenase). RUBISCO is an bifunctional enzyme with 

affinities for both C02 and 02. When catalyzing the oxygenation 

of RUBP (ribulose bisphosphate), glycolate is formed. Oxygenase 

activity is dependent upon high ratios of 02/C02 which can either 

be caused by high 02 or low C02 environments. 

Surprisingly when cells grown on air levels of C02 are exposed to 

high 02 tensions they do not show any of the common signs of 

photorespiration (decreased photosynthetic rate and glycolate 

excretion) (58). This is apparently the result of a "C02 Concentrating Mechanism" which enables cells to concentrate C02 at 

levels 2-3 orders of magnitude higher than the bulk -concentration. The enzyme carbonic anhydrase, which catalyzes the equilibration of bicarbonate ion and C02' is central to the operation 

of this pathway (59). Glycolate metabolism in algae is catalyzed 

by glycolate dehydrogenase to glyoxal ate -> glycine -> serine -> 

and PGA (60). When mutants of Chlorella containing excess 

amounts of the enzymes associated with the glycine-serine pathway 

were exposed to high oxygen, their rates of glycolate excretion 

were 3-4 fold less than the wild type. 

Because of the fact that carbon is lost from the cell, photorespiration is often considered to be a wasteful process. It does 

however serve to reduce the immediate high oxygen environment and 

perhaps protect the cell from a more damaging problem with photooxidation of its pigments or delivering reductant without any 

available C02. Thus while in the short term it is wasteful, over 

the long term it may be essential. After reviewing much of the 

literature on photorespiration, Raven and Beardall (61) concluded 

that RUDP oxygenase activity could not solely be responsible for 

the observed oxygen consumption. They suggested that a Mehler 

type reaction must be operative. 

-27-
Despite the fairly extensive biochemical studies, relatively few 

studies deal with the effects of oxygen on the productivity of 

algal cultures, and even fewer have been carried out under conditions of relevance to algal mass cultures. Pope (62) studied the 

oxygen sensitivity of four different strains of microalgae and 

found that at low light( 250 ft-c) oxygen inhibition was very 

small as compared to high light(3000 ft-c). A. nidulans fixed C02 

at a rate 20% of an oxygen free culture when exposed to only 60 % 

02 in high light. Phaeodactylum tricornutum and Dunaliella 

tertiolecta grew at rates 70 and 50 % lower than the control 

culture when exposed to 100% 02. A Cricosphaera Spa was found to 

be insensitive to oxygen at all light intensities. 

The question as to how reversible the features of 02 inhibition 

are following exposure to high oxygen concentrations is of obvious importance. Shelp and Canvin (58) found with Chlorella sp., 

that exposure at 50 % 02 was reversible after 20 minutes but a 

similar treatment at 100 % 02 was not. The process of respiration 

is a method for the cell to adjust its carbon balance. Respiratory process require substrate, therefore one would expect the 

size of the precursor pool to be important in determining the 

reversibility of oxygen inactivation. 

While there has been no direct evidence of oxygen having a role 

as a selection force in open ponds, there is evidence that high 

oxygen tensions affect species differently. In Figure 2.5 is 

shown a summary of some experiments carried out by Weissman and 

Goebel (4) on six different strains of microalgae. They compared 

both maximum growth rate and productivity at either air levels or 

100% 02 in batch cultures exposed to continuous light. It is evident that high O? tensions appear to affect species differently 

with the greens be~ng particularly sensitive, while the diatoms 

are not •. These authors have found a good correlation between oxygen sensitivity in laboratory environments and poor competitiveness in outdoor ponds; however they have not found these strains 

to show particular sensitivity to oxygen when cultured outdoors. 

~ In summary it is clearly evident that oxygen can inhibit photosynthesis in a selective manner. The mechanism through which 

this occurs can be a combination of photooxidation of pigments, 

photorespiration and Mehler type reactions. The degree of inhibition is more severe at high light intensities and temperatures. 

Because the pond environment will commonly attain high temperature, high light, and high oxygen during the afternoon, it is 

argued that oxygen sensitivity of an organism will be an important selective force in algal growth ponds. 

2.6 pH/C02 

In weakly buffered systems, pH and dissolved C02 are coupled 

through the bicarbonate equilibria as shown in Figure 2.6 for 

seawater in equilibrium with air (63) • Carbon dioxide .consump-

-28-
.. 

o 

lC 

o 

E 

::r.. 

50~ AIR SAruRATION / AIR SATlIRATICH 

1.2 

1.1 

1.0 

0.9 

0.5 

0.7 

0.5 

0.5 

0.4 

0.3 

0.2 

0.1 

0.0 

I2Z.:J jJ max 628S! AVE. PRODUCTIVITY 

Figure 3-1. Oxygen Inhibition of Laboratory Algal Cultures 

1. Nannocloropsis sp. 21 

2. Oocystis Spa 

3. Tetraselmis suecica 

4. Chiorella ellipsoidea 

5. Ankistrodesmus Spa 

6. Scenedesmus quadracauda 

7. Chaetoceros gracilis 

8. Chaetoceros S/CHAEI-2 

9. Cyclotella SPa 

10. Amphora Spa 

FIGURE 2.5 SENSITIVITY OF MICROALGAE TO 100 % OXYGEN TENSIONS 

(Sourc~: Ref. 4) 

-29-
() 

z 

82 

en 

UJ 

-() 

UJ4 

CL 

en 

a 

~ -

gs 

2 4 8 10 

~------~~---------

FIGURE 2.6 CARBONATE SPECIES IN SEAWATER AT EQUILIBRIUM 

(Source: Ref. 63) 

-30-

12 
tion during the day, and evolution at night by algae are primarily responsible for the pH changes observed in ponds. The supply of C02 is periodic, depending on the size of the pond (or the 

spacing between carbonation stations) and the mixing velocity 

(see section 3.0) The C02 supply to the algae thus depends on the 

actual amount of C02 stored in the bicarbonate-carbonate buffer 

and the pH of the pond. Although the rate of H2C03 formation from 

bicarbonate is nearly instantaneous, the actual conversion to 

free C02 is not. However algae (like most living organisms) 

possess carbonic anhydrase which is able to catalyze the hydration-dehydration reaction of CO? It is, however, unclear at what 

concentration C02 becomes limit1ng. The fact that pC02 drops to 

almost vanishing levels at high pH and that algae adapt to such 

low PC02 tensions by induction of an active bicarbonate uptake 

system suggests that this is of major import to the cell. 

Thus the pH fluctuations that will be typically encountered in 

mass cultures must be constrained within the physiological and 

competitive limits of the organism being cultivated. Elucidations 

of these limits must be one objective of any screening program. 

It must be pointed out however that low cost production of algae 

will also constrain the allowable pH levels and fluctuations in 

terms of C02 losses from the ponds, alkalinity requirements etc. 

This issue is further addressed in the next section 

2.7 THE FEASIBILITY OF SCALE DOWN 

The entire discussion up to this section has been an attempt to 

demonstrate the importance of the fluctuating environment on 

strain productivity and dominance. We have focused on the fluctuating conditions because they represent the outdoor cUltivation 

environment. The objective is to be able to reproduce the outdoor 

environment in its essential elements in laboratory cultures - e.g. to scale down the pond environment to a 1 liter laboratory 

reactor. In this section we discuss the reasonableness of the 

basic assumptions underlying the scale down approach. 

Table 2.1 summarizes the key pond environmental parameters, their 

typical values for laboratory cultures, the range of the values 

for the outdoor system, the time period over which changes occur, 

and an estimate as to the feasibility of scaling that parameter. 

Temperature, dissolved oxygen, pH, and water chemistry (alkalinity) can all be ,scaled effectively. The first three by maintaining feedback control loops using heater inputs, and gas composition as the controlled variables and the last one by using media 

which matches site water composition. 

Reproducing the appropriate light environment is somewhat more 

difficult. The incident light intensity, cell density, and mixing 

pattern will all combine to give the light distribution pattern 

for a culture. Algae simply don't average the light intensity for 

-31-
TAFL~ 2.1 

FEASIBILITY OF SCALING POND ENVIRONMENTAI .. PARAMETERS 

TO LABORATORY REACTORS. 

PARAMETER units TYPICAL LAB. OUTDOOR TIME SCALE 

VALUE (CONST. ) RANGE PERIOD DOWN 

(hr) 

Temperature oC 20 to 30 10-40 24 YES 

Dis. Oxygen ppm 6 to 15 O~40 24 YES 

pH logH+ 7 to 9 7-10 >l. YES 

Alkalinity mM 0 to 50 0-50 none YES 

Light r E/ m2/ s <300 0-2000 24 ? 

Cell Density mg/l 100-2000 50-500 minor ? 

Mixing fast slow const. NO 

Shear high low const. NO 

Surface:Vol. m-1 50 5 const. NO 

Biota (Invasians) - low high canst. NO 

-32-
a given environment but respond more or less instantaneously to 

intensity changes. The photosynthetic processes of light absorption and charge transfer occur at time scales several orders of 

magnitude smaller than the time it takes for an alga to be carried into and out of the light even in very turbulent of systems. 

As discussed above, algae are sensitive however to the light dark 

pattern and its frequency. Without a suitable model it is difficult to predict what the effect of the different mixing-light 

regimes will have on the photosynthetic response. At the mixing 

velocities (20 cm/s) and channel width (10 m) and depth (.2 m) 

common for a typical pond, a Reynolds Number of 80,000 is calculated. This is well into the turbulent flow regime and therefore 

a random light/dark periodicity can be assumed. 

Another significant time constant is the daily light/dark cycle 

which varies between 9 to 15 hours light (and corresponding dark) 

periods. These can of course be easily reproduced in the laboratory as can, to a first approximation, the diurnal light cycle 

(e.g. the light intensity is raised and lowered gradually). The 

length of the dark night cycle can be important, as is amply 

demonstrated in the literature, for algal productivity (and presumably competition). 

certain parameters related to the light environment and culture 

mixing can not be scaled adequately in laboratory reactors: light 

intensity, light quality, light variance due to mixing (even if 

turbulent), shear effects, and secondary factors such as cloud 

covers. As discussed above, we consider that these parameters are 

of secondary importance and that valid conclusions can be reached 

in the absence of complete mimicry between the laboratory and 

mass culture systems. Indeed, there will always be differences 

that even the most sophisticated laboratory system would not be 

able to reproduce: surface to volume ratios, biotic contaminations, cell sedimentation, dispersion coefficients, etc. In the 

next section we develop a computer model of the pond system which 

is able to predict the abiotic environment of a mass culture system. 

-33-
SECTION 3.0 

MODELING THE ALGAL GROWTH POND ENVIRONMENT 

3.1 INTRODUCTION 

~he cultivation of microalgae on a large scale requires that all 

incident light be utilized as efficiently as possible. The standing biomass (more accurately, standing pigments) must therefore 

be high enough to absorb all (98%+) of the incident light energy. 

Generally this will be about 20 to 30 g/m2 of algal biomass (ash 

free dry weight). However, a higher standing biomass is desirable 

since it would entail less harvesting and dilution effort, a 

major consideration in system design optimization. The cultures 

must also be as shallow as possible, for the same reasons. The 

optimization of these two parameters, standing biomass and depth, 

is one objective of R&D of microalgal biomass systems. 

Culture standing biomass is limited by productivity considerations. Although standing biomass ~ productivity is generally 

represented as a gaussian type curve with an optimum near half 

the maximal (non-light limited) growth rate (64,65), in actuality 

the maximal productivity range extends over a fairly broad range 

of dilution rates. As dilution rates, within this optimal productivity range, are inversely proportional to standing biomass, it 

is possible to optimize both the productivity and design considerations (minimum harvesting and hydraulic dilution) in algal 

mass culture. Indeed this is clearly apparent from batch cultures 

where there is a fairly long phase of arithmetic growth for most 

algal species. At some point, however, respiration becomes a 

significant fraction of primary productivity, at which point culture productivity declines. Respiration is, of course, affected 

by the pond environmental parameters (02' temperature, etc.), and 

their fluctuations, just as much as photosynthesis is. 

Depth, the other primary design parameter under discussion, is 

limited by considerations of head losses (which are related to 

pond size and mixing velocities), carbon storage, and temperature 

profiles (4,66).·Reduction of depth will result in each of these 

factors becoming more unfavorable, increases in depth require 

larger harvesting and water pumping efforts. 

For the unaided mind, it is difficult to simultaneously consider 

all of the potential inputs (eg. climatic, design, operational, 

biological, etc.) required for optimization of depth and standing 

biomass (detention time), or even to predict the extent of their 

effects and interactions. This is, of course, also true of the 

many other environmental and design factors to be considered. In 

this context a model serves as a tool to study operating strategies, for predicting conditions for different site locations, and 

for determining the dynamic aspects of the physico-chemical environment. The development of such a model is presented. 

-34-
· , '3.2. POND DESIGN 

Some of the early pond designs were first discussed in Burlew's 

book (1); other more recent reviews are also available (67,68). 

The general picture that emerges is that of many small scale systems of diverse designs reflecting a lack of concern for economics. As the system designs became larger (over several hundred 

m2 ) they have tended to converge to the High Rate Pond (HRP) 

design. 

This design was first used by Oswald and colleagues in the early 

1950's in their research on wastewater and scaled up to a 0.5ha 

system in the early 1960's. (69). A major modification was made 

about this time by the German group at Dortmund who introduced 

paddlewheels for mixing. The HRP pond design is characterized by 

its raceway track type of layout (Figure 3.1) (67) which allows 

it to be scaled to a large size, limited only by considerations 

of mixing (e.g. dispersion coefficient and mixing). As discussed 

elsewhere (66) these limitations are not severe up to a scale of 

several hectares for a single pond if mixing velocities are moderate (below 30 cm/sec) and depth are above 10 to 15 cm. These 

moderate mixing velocities and depths are also essential from the 

point of view of power requirements for mixing and silt suspension in unlined ponds (3) and for minimizing the temperature 

variations and maximizing carbon storage in ponds (see below). 

Other designs involving shallower and faster mixed cultures have 

been proposed because of their alleged ability to increase biomass productivity (see 68 for a review). However no evidence for 

such increased productivity has been obtained. A number of circular systems were built in the 1960's in Japan, but that design 

has been essentially abandoned. Tubular reactors are likewise of 

little practical use at least in large scale, low cost systems, 

except, possibly, for inoculum production. 

In summary, the basic algal production reactor design used by all 

recent commercial plants, and most pilot scale projects over the 

past two decades, is a paddlewheel mixed raceway type pond system. The ponds are operated at a depth of 10 to 30 cm and an 

aspect ratio of about 1:10 or larger. This design is both 

simple, flexible in operation, and can be easily scaled up from 

small experimental or pilot units to full scale systems of one 

hectare or larger. Before presenting the model we review the 

prior literature in this area. 

3.3. POND MODELS 

Models of pond reactors have been developed for a variety of 

applications including waste treatment (71,72), solar heating 

(73), and algae CUltivation (74,75). There are many similarities 

in terms of the balance equations and empirical expressions in 

these model descriptions and even those not specifically dealing 

with algal growth ponds are relevant to the present effort. 

-35-
( 

( 

"nAil A DETAil B 

. EPEfii.li SEem 

I FUM EXAINSION ~ TAA\{lUNG ii ~ J 

( 0"""'"'''''''''' flOW '""NO "'"'r--":.=::EN!.!.T~ER:.!:WAl~l L-If-:::-JQb:::::;' t' ~S=:I."'iO 

CQMJIION'MU; 

__ -----------1ff ACCESS ROAD 

~ LEGEND 

m SEALED A.c. AlVEIlENT OR 

LINING AElllfOICEIIEIIT 

~ SEALED A.C. OR COlIC. PAVEIIOT 

A.C.. ASPHAlT COIICAETE 

BAFflE 

FIGURE 3.1 ALGAL GROWTH POND (a) AND PADDLEWHEEL (b) DESIGN 

(source: Ref. 69) 

-36-
Markl and Mather (74) presented calculations of oxygen and carbon 

dioxide balance equations for an 85 square meter pond located in 

Peru (as part of the German-Peruvian project). Their analysis was 

limited due to the small size of the pond, a questionably high 

kla value, and by their assumption that no exchange of carbon was 

occurring between the buffer and the carbon dioxide pools. Di 

Toro (76) has shown this to be an acceptable assumption below pH 

values of 7.0; however above this the error becomes increasingly 

large(50 % at a pH of 8.0) as the pH. increases. Since most ponds 

operate at pH's above 8.0, this error is unacceptable. Their predictions for the need to replenish C02 (carbonation intervals) of 

less than 2 minutes is thus incorrect, by a large factor. This 

would severely constrain any pond system to only a very small 

size «1,000 m2 ). Additionally because of the high assumed kla 

value their calculations of maximum oxygen concentrations in the 

ponds were also quite low at 2.5 times air saturation. 

Another pond model for algae cUltivation was developed by Hubka 

for the Solar Energy Research Institute (82). The main emphasis 

of this work was to make predictions concerning areas of cost 

reduction in pond design. The objective of this model was thus 

quite different from the present one and it is not directly 

applicable to the model developed here. However it represents one 

of the few prior publications dealing specifically with modeling 

of an algal mass culture system. 

Physical rate expressions are found in two separate models of 

waste stabilization ponds. Ferrara and Harleman (71) developed a 

dynamic model of a waste stabilization pond that included consideration of virtually all of the physical, chemical, biological, 

and hydraulic features. Inorganic carbon species and pH were predicted using alkalinity, bacterial respiration, algal uptake of 

C02, and surface gas exchange as inputs and the equilibrium 

expressions of stumm and Morgan (63). Dissolved oxygen was not 

treated. All rate and equilibrium expressions were temperature 

dependent with temperature being an input variable. The authors 

did carry out one case study using a set of empirical equations 

developed by octavio- et ale (77) and found good steady state 

agreement for a 1.2 m deep pond(for temperature predictions). 

The model of Fritz et ale (70) was similar to the above except 

more attention was paid to the energy balance calculations. They 

developed an energy balance expression including terms for short 

and long wave radiation (solar and atmospheric), pond radiation, 

convective exchange, evaporation, and hydraulic flows. When 

tested against measurements recorded for a 1 m deep pond in New 

Mexico, the steady state tempera~ure predictions were quite good. 

Another model of a waste stabilization system was that of Incropera (72) who analyzed the efficacy of using waste heat generation 

in a closed loop exchange with a stabilization pond. The energy 

balance included the same flows as Fritz et ale (70) but also 

contained terms for conduction exchange with the pond surfaces 

-37-
and the heat exchanger surface. Diurnal temperature predictions 

for the month of July gave a temperature variation of 2 °c for a 

2 m deep pond. The model predicted that using waste heat effluent 

at 40 °c in a single pass heat exchanger, was capable of maintaining pond temperature above 25 °c for the entire year. Performance was very dependent upon fouling of the exchanger surface. 

3.4 MODEL DESCRIPTION 

3.4.1 Input Parameters 

Table 3.1 summarizes the major input parameters to this model. 

The general growth pond input parameters of size, channel length 

to width ratio, depth, and mixing velocity, were mentioned above. 

The specific pond system that is modeled here consists of a one 

hectare raceway type pond with a channel to width ratio of 20. 

Mixing and C02 supply are not specified as such, but would 

involve the use of paddlewheels for mixing (alternatively, air 

lift or screw pumps could also be used) and a sump (or any suitable system) for C02 delivery (the carbonator). 

We assume a single carbonator spanning the entire width of the 

channel and that in one pass through the carbonator all the C02 

used by the algae since the prior pass could (and would) be 

recharged into the media. utilization of C02 by the algae causes 

a pH rise in the ponds and a decline in the free C02 (C02 and 

H2C03) level in the culture medium. Either or both these factors 

eventually leads to a decline in productivity. Here we assumed 

that this point is reached at the e~ilibrium partial pressure of 

C02 with the atmosphere, about 10- M. This is a species and 

strain dependent property which would need to be modified as more 

information became available. 

To calculate C02 and 02 mass balances a broad range of outgassing 

coefficients were used, as the actual values are relatively 

uncertain. The range of pH's experienced by the culture before 

and after C02 supply at the carbonation station (pH START and pH 

END), are inputs to the model. These, together with alkalinity 

determine the pond C02 storage capacity and, thus, overall pH 

fluctuations in the ponds. As any two (pH, alkalinity, C02 storage) fix the third, and as C02 storage capacity must equal or 

exceed that required by photosynthesis between carbonation 

events, the actual choice of variables is alkalinity or/and pH 

range. Constraints on the choices will be the loss of C02 due to 

outgassing, the cost of supplying the needed alkalinity (or the 

natural alkalinity present in the make-up water times the blow 

down factor) and, as indicated above, the tolerance and competitiveness of the desired algal species to the variations in pH and 

pCO? (The size, aspect, mixing velocities, and dispersion coeffic1ent of the pond are additional parameters to be considered, 

but are either preset or ignored in this model, at its current 

state of development.) 

-38-
Table 3.1 Summary of Innut Parameters to Ar.P Model 

VALUE UNITS 

Geoqraohical 

Latitude ALAT 33.24 Degrees Longitude ALONG 104.32 Degrees Elevation EL.c.'"V 1103 rreters 

CliInatic 

Air Temperature TA data file a: Wind Speed W1ND data file nph Relative Humidity RH data file % 

Total Solar P3diat. 'IOI'FAD 10803-29624 KJ!rrf 

Desian 

Pond Size AREA 10,000 m2 

I.e.1"J.gth: Width LIN 20 

Pond Depth DEl? 10-30 em 

Mix. Velocity VEL 20 em! sec 

Phvsical 

1-10xlO- Outgassing Coeff. KLAPOND 5 mls Alkalinity ALI< 0-0.030 roles! 1 Starting pH PF..5'I'Rr 7.0-9.0 pH £r'l.ding pH PRENO 7.5-10.0 pH 

Bioloaical 

Productivity POOD 30 g!m2-day Carron Yield Yc 0.042 roles C! g algae Oxygen Yield Yo 0.042 " It 

-39-
For the initial exercise of the model a site in Roswell New Mexico was selected. The primary rationale for this was the interest 

by the Solar Energy Research Institute in setting up a demonstration facility for algal mass culture at this site during 1987. 

The climatic data collected at the Roswell New Mexico Airport 

were obtained from the National Climatic Center, for the year of 

1985 on magnetic tape. The data was used to calculate hourly 

averages of each climatic parameter - wind speed, air temperature, and relative humidity - for an average day for each month 

(Figure 3.2). Average values of the daily total solar radiation 

for Roswell for each month (averaged over the years 1940 to 1971) 

were obtained from Cinquemani et ale (78) and hourly solar radiation data calculated according to Collares-Pereira and Rabl (79). 

Finally the productivity of the algal culture was used as a model 

input, at 30g/m2/day of ash free dry weight for the month of 

July, with constant hourly productivity over a 14 hour daylight 

period. This productivity input is conservative and based on 

recent results from outdoor ponds (Weissman, personal communication). 

3.4.2 Model Subroutines 

The model consists of nine separate subroutines which are flowcharted in Figure 3.3. The differential equations used for biomass, C02' 021 and energy, used in this model, are given in Table 

3.2. These were integrated by the program at a time interval of 

one second. 

READIN/WRTOUT The READIN and WRTOUT routines carryout all I/O 

operations. Data is read in from a separate data file which is 

organized similar to the blocks of inputs shown in Table 3.3. 

Outputs are time, incident light intensity, air and pond temperatures, pH, oxygen, and algae concentration. These are printed at 

an interval prescribed by the user. 

CLIMATE Hourly meteorological observations of air temperature, 

relative humidity and wind speed are interpolated to give instantaneous estimates of each required for solution of the energy 

balance(subroutine HEAT). 

SOLAR Instantaneous estimations of the incident light intensity 

are generated by a semi-empirical formula (79). The required 

inputs are site latitude, Julian day, and the total radiation 

received over a single day (78). The amount of light actually 

absorbed by the culture will be reduced by back reflection and 

scattering. The transmission of the light into the pond is determined by applying Fresnell's equation for the direct beam component of the light and assuming 93% of the diffuse radiation will 

be transmitted (80). The 93% transmission term was obtained by 

integrating the Fresnell equation over the full sky assuming an 

even radiation intensity. Outputs of this subroutine are directed 

to subroutine GRATE and HEAT. 

-40-
I 

~ 

....... 

I 

o 

d 

o 

.... 

e 

ci 

co 

we 

:::>' -1g 

~ 

o 

w 

~ 

:::> 

(/}o <{, 

W O ~..,. 

o 

ci 

N 

a 

Figure 3.2 Diurnal variation of Climatic Inputs 

for Roswell, New Mexico in July 

AIR TEMPERATURE(F) 

~~ ~~~~------------- -- ... "'''' ---- ... ~ -' -- , ' ---- , , , " -' ' " ------' 

" - -----,' ----- . .................... . .- ... ,,- ". 

.............. . .......... . ...... . ... .. ' ". ..... . ..... 

'. '. ". ........... 

'. '. '. 

...................... 

RELATIVE HUMIDITY(%) 

........ .' 

.. ' 

. .......... . 

..' ..' ........ 0 ............. • .. • 

WIND SPEED(knots) 

.' 

O~-----------------r----------------~-----------------,------------------r-----------------------------------
Figure 3.3 Algal Growth Pond Model Flowchart 

READIN 

DO 10 t = 1,86400 

BALANCE 

PHV 

WRTOUT 

L----------l 10 CONTINUE 

-42-
TABLE 3.2 MASS AND ENERGY BALANCE EQUATIONS 

Algae: 

dX/dt = FXl + (U-D)X 

u = U(T,I) 

Carbon Dioxide: 

dC02/dt = FC02i - DC02 - kla/d(C02 - C02 * ) - CUR 

CUR = Yc x U x X 

Oxygen: 

d02/dt = F02i - D02 - kla/d(02 - 02 * ) + OER 

OER = Yo x U x X 

Energy: 

dT/dt 

Enet 

= F(T' - T) + Enet/(Cp x rho x d) .l. 

= Ell.o + Elwr - (Eevp + Erad + Ecnd + Ecnv) 

variables: 

rho = density(g/m3 ) 

F = specific inflow rate(l/sec) 

CUR = carbon uptake rate(moles/l/hr) 

OER = oxygen evolution rate(moles/l/hr) 

Cp = heat capacity(J/g/K) 

d = depth(m) 

Subscripts/Superscripts: 

i = inflow 

c = carbon 

0 = oxygen 

lio = solar radiation term 

lwr = long wave atmospheric radiation 

evp = evaporation 

rad = pond surface radiation 

cnd = conduction 

cnv = convecction 

-43-
_ HYDRAUL. This subroutine calculates any net exchange of media to 

or from the pond based upon a given input/output schedule and 

specific rates of inflow or outflow. New estimates of the volume 

and depth are calculated and any flow terms used in the 

mass/energy balances are initialized. Also as part of this routine the total amount of time required for recirculation based 

upon design specifications is determined as well as that for carbonation based upon carbonator size. 

PONDLOC. This routine keeps track of the location of the fluid 

element and indicates whether it resides within the carbonator 

zone or the open pond. It also determines whether to inject C02 

(to lower the pH) based upon the culture pH and -a predetermined 

upper pH value(PHSET). In its present configuration the pond pH 

value is simply shifted to PHSTRT when carbonation is required. 

GRATE. A mean value of the growth rate is determined using pond 

temperature, incident light intensity, extinction coefficient, 

pond depth, cell density, saturating light intensity, maximum 

growth rate, and minimum, maximum and optimum temperature values. 

This is done by determining the mean light intensity at 1 cm 

depth intervals and integrating the calculated growth rates over 

the entire depth to obtain a mean estimate of the growth rate. No 

particular growth rate model is indicated here due to the fact 

that we have only considered cases of constant productivity in 

this analysis. 

HEAT. The heat balance contains terms for solar radiation 

absorbed, net long wave radiation, radiation from the -pond surface, evaporation, convection, and conduction. For the most part 

this analysis follows that described by Fritz et. ale (70) for 

predicting temperature profiles in waste stabilization ponds. The 

differences- are in calculating the solar radiation term and the 

inclusion of conduction exchange with the earth surrounding the 

pond. Because of the small time intervals this was treated by the 

classical representation for heat transfer in a semi-infinite 

slab experiencing a step change in its surface temperature (81). 

Thermal conductivity and diffusivity values were used for that of 

a 50% clay/soil mixture that was saturated with water(k=3.3W/m/K 

and 1.3 x 10-6 m2/s (82). Inputs are the current estimates of air 

temperature, wind speed, and relative humidity from subroutine 

CLIMATE, the incident light intensity from subroutine SOLAR and 

the previous estimate of the pond temperature. Based on this, 

individual terms of the energy balance are calculated and the net 

heat exchange is determined (HNET). This is then passed to subroutine BALANCE to solve the energy balance equation. 

BALANCE. The equations for algae, C02' oxygen, and temperature 

are integrated over one time interval using the IMSL subroutine 

DGEAR. Inputs, in addition to previous estimates of each state 

variable and the time interval, are growth rate, flow terms, kIa, 

equilibrium concentrations for C02 and 02 in seawater at the 

current temperature, and the net heat exchange term from subroutine HEAT. outputs are the current estimates of the state .variabIes. 

-44-
PHV. Returns a current estimate of the pH based upon changes 

which occur in the total carbon concentration of the system. Specifically, the outgassing rate and carbon uptake rate are used to 

determine the net carbon lost from the system over one time 

interval. The carbon dioxide acidity is then determined by the 

difference between total carbon and alkalinity. Solution for a pH 

involves finding the zero of a 4th order polynomial in hydrogen 

ion concentration (83). The concentration of individual carbon 

species is then determined using the equilibrium expressions 

given in stumm and Morgan (63). The 1st and 2nd dissociation constants and the ion product of water are all for seawater and temperature dependence is included. 

3.5 RESULTS 

3.5.1 Introduction. 

Here is presented the initial results of a general Algae Pond 

Model (APM) , as it applies to one specific site, Roswell, New 

Mexico, and a specific pond system design. Examples of model outputs for temperature, oxygen, and pH profiles are presented. 

Also, some validation measurements and experiments on the small 

ponds of Microbial Products, Inc. at Fairfield Calif. is presented. 

3.5.2 Temperature 

solutions for the diurnal pond temperature were obtained for the 

month of July, using averaged diurnal ambient temperature data 

for that month, for pond depths of 10, 20, and 30 cm (Figure 

3.4). It is a evident that there is a significant dampening 

effect due to depth of the pond which is a natural result of the 

increased thermal capacity of the system. For the worst case 

(10cm depth) a temperature amplitude of 300 C is predicted over 

roughly a 10 hour period (heating phase) This amplitude is 

reduced by half for the 20cm case ( T= 150 C and by one third for 

the 30cm case (T=10oC). While this specific case possibly represents an extreme because both heating (radiation inputs) and 

cooling (evaporative losses) rates are at a maximum during July, 

it nevertheless points out the very large diurnal fluctuations in 

pond temperatures possible. 

In order to visualize the influence of evaporation rate on the 

temperature profile a series of simulations were run where the 

wind term in the evaporation rate expression was varied from zero 

to 15mph. The resulting evaporation rates ranged from 0 to 0.72 

cm/day. (The model assumes no convection term for air and thus 

results in an infinite boundary layer above the ponds at zero 

wind speed). The predicted temperature profiles are shown in Figure 3.5. 

-45-
,',':' 

,f / 

/ I " ;I I : I I • 

/;' I i I I : , I 

I I I I 

I I I , 

I \ , \' 

\ \. 

\ \ , \ , \ , ,. " \ " \ 

"" , , ", " ", , ,', ... " . " ,\. ... ,. 

'" "','\ '~" 

'\. 

.~~, 

." ... ''',', ", 

." ... .. , ...... 

'" " 

0; 

°i 

E: 

',\ " 

',\ " . \ ... "\ , '" ' ~ \ "" . \ \ '\ , : I \ 

: I \ 

: I \ : I , 

I I 

I E I 

, 0 ' , I 

I 0 I 

ttl: : I N I I I 

· 

· 

· 

I I 

I I 

I I 

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o 

(.) 

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I I 0 

~------__ ------~--------------~~~/--------'~----------------~--------------~c) I I 

O'OS O'Oy 0'0£ o·oz: O'OL 0'0 

(J)3~nl't~3d~31 

-46-

-

( --

C 

( 

l 

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..-

... 
/ I C 

I 

I 

I 

+l I 

I I C1j 

I 

I 

~ I 

( ~ I 

;::1 (l) , 

I-J+l , C1j \ 

)..j~ \ C 

\ 

\ ~ 0 \ , <1-1 . \ 

0.. \ , (l) C1j \ 

~:> \ 

\ \ , ..... ~ \ <1-1 , 0 \ " 

)..j rn \ 

\ , fl.t :> , 

, (l) 0 , . )..j C) , 

\ c , ;::1 ..... \ I:' +l >< , '. .. C1j (l) \ 

, 

\ )..j~ , (l) \ 

0..:3 \ 

\ l=l (l) , 

\ (l)Z , 8 , 

\ 

.-I~ \ 

C1j~ , 

\ c (l) , 

, 

)..j :3 I C 

;::1 rn I !Xl ..... 0 I 

1 Q~ 

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(l) I 

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, 0 I . 0 

O'OL 0'09 O'OS 0'07 O'O~ O'Ol: oom ero (:J)3~nlVCi3d~31 

-47-
The curve representing 0.54 cm/day was obtained from the averaged hourly wind speed data and corresponds to the 20cm pond 

depth case in the prior Figure (Fig. 3.5). Since the shape of the 

diurnal curves is similar in all cases, it appears that averaging 

wind speed on a daily rather the hourly, basis is not a major 

determinant of diurnal pond temperature profiles. The model does 

not contain a term for wind fetch over the ponds, thus wind 

direction is not a variable in it. The results suggest that evaporation rate is the major determining factor of the average and 

maximum-minimum diurnal pond temperature but does not greatly 

affect the amplitude of the temperature range as such. 

As an estimate of the reasonableness of the evaporation rate predictions the "average" rate of evaporation was calculated each 

month and an integrated value determined for the year. This calcUlation yields an evaporation rate of 140 cm/year, which is 

roughly 25 % lower than the rates published for Pan A evaporation 

for this location of the country (84). Although the predicted 

values for evaporation may be low, and thus the predicted temperature profiles may be slightly high, pan A evaporation rates can 

not be easily extrapolated to ponds and this issue requires further investigation. 

Finally, temperature profiles were simulated for each month of 

the year in order to estimate the duration of, and limitations 

on, the growing season for this particular site. The results are 

shown in Figure 3.6 (again for a pond a of 20 cm depth). It is 

reasonable to expect that once average pond temperatures begin to 

fall below 200e in the daytime and 100e at night, significant 

declines in productivity will take place, possibly sufficient to 

make pond operations uneconomical. This would reduced the growing 

season to the march-october period, or about seven months of the 

year. .However there is uncertainty regarding the actual temperature extremes that may be tolerated by potential candidate algal 

species and there may be techniques to better manage the heat 

budget to the ponds. Thus a growing season of eight to nine 

months may be possible at this site. Obviously, temperature 

responses of the algal species are of great interest. 

3.5.3 Oxygen 

Perhaps one of the most important environmental factors affecting 

pond performance is the oxygen buildup that occurs during the 

daylight hours as a result of photosynthesis. Depending upon productivity and outgassing (including at the carbonator) dissolved 

oxygen may reach up to 500% of equilibrium (with air) oxygen tensions (4). The outgassing coefficient is subject to great uncertainties, and will be influenced by a number of variables in pond 

design and operation (mixing velocity, depth, surface roughness, 

salinity, temperature, etc.). In principle the kla will depend on 

any physical or chemical factor that reduces the effective film 

transfer thickness. The Parkhurst Pomeroy correlation (85) predicts a value of lxlO-5 m/sec for a channel depth of 20cm, flowing at 20cm/sec. 

-48-

Our measurements indicated that this value is roughly 3.4 times 

too low (see section 3.5.6). Other values in the literature range 

up to 9x10-5m/sec (74,85,86). Since it was difficult to assign a 

specific outgassing coefficient to predict 02 profiles in the 

ponds, a range of coefficients was used to predict maximum 02 

tensions for a20 cm deep pond (at the standard productivity of 

30g/m2/day as a function of time (starting from air saturation 

levels). It is evident from the results presented in Figure 3.7 

that very high 02 tensions can be reached, up to ten fold air 

saturation, in the case of the lowest kla assumed. Although such 

high levels have not been observed, and are unlikely to be 

reached in practice due to nucleation effects that lead to 

enhancement of oxygen desorbtion, oxygen levels of up to 500% of 

saturation are predicted by the model and have been observed in 

practice (4, see above). 

3.5.6 Carbon Dioxide and pH 

Culture C02 levels, and hence pH, will be dependent upon alkalinity, pond depth, outgassing coefficient, and productivity. 

Alkalinity and pond depth combine to determine the total carbon 

storage pool (for any given pH range), while productivity and 

outgassing determine the rate at which the pool is reduced. The 

efficiency of C02 utilization (e.g., the fraction of total C02 

supplied incorporated into biomass by the algae) therefore will 

be highest where conditions restrict the degree of outgassing 

(i.e. at low dissolved pressures of C02' low turbulence). 

This is shown in Figure 3.8 for three different alkalinities, at 

a kla of 3x10-5m/sec, a constant productivity of 30 g/m2/day and 

a 20 cm depth. This data was generated by using the pHV subroutine and assuming a final dissolved C02 level of lxl05 M (the 

equilibrium C02 level with air). For a given alkalinity curve a 

lower value of the starting pH represents a larger total carbon 

storage capacity, and subsequently a longer time between carbonation stations (as shown in Figure 3.9). 

It is evident that the utilization efficiency declines fairly 

significantly at the lower pH and higher alkalinity. At a pH of 

7 and an alkalinity of 30 mM/l, the utilization efficiency would 

be .only 63%. At the same pH for an alkalinity of 2 mM/l, the utilization efficiency would be 85%. At the high end (pH=8.0), there 

is much less of a differential in the efficiency and even 30 mMolar has a value exceeding 90%. This analysis illustrates the 

advantage, in terms of reducing potential C02 losses, of operating at higher pH ranges (ie. pH > 8). This would be reflected in 

a smaller storage capacity which is demonstrated graphically in 

Figure 3.9. 

The specific trade-offs between pH range and alkalinity will be 

determined by the relative optimization between the costs of C02, 

capital costs for carbonators, and productivity reduction due to 

biological intolerance to pH extremes. A variety of pH-Alkalinity 

curves are presented in Figure 3.10, which correspond to differ-

-50-
I 

111 

I-' 

I 

Figure 3.7 Time Dependent Oxygen Profiles vs. Outgassing 

at a Productivity of 30 gjm2jday 

~,-------------------------------------------------------------------------------------.., 

-::J' 

o . .-

~«O Ed 

"'-" z 

o 

~ 0:: 

l-co 

z· 

W O 

U 

z 

o 

u 

w. z~ 

(!)O 

r 

a 

N 

ci 

TEMP;:: 25 C 3~_9 ~ 1Q~~ !'DIs 

PROD;:: 30 g/sq.m./day 

5.0 X 10-5m/s 

, 1.0 X 10-4 mjs . . - - .... 

° I , 

ci 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7~ 8.0 

~nIID, AT POf"'lnll(,TI\IITV 
~ ~ 

C 

I 0 

lJ1 :;: N D I N 

--

+- -

::J 

N 

a 

0 

Figure 3.8 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

o 

7.0 7.2 

C02 utilization Efficiency vs. starting pH 

at 2, 10, and 30 roM alkalinity 

7.4 7.6 7.8 

starting pH 

8.0 
I 

VI 

W 

I 

:c 

0. 

Figure 

o 

3.9 pH-Alkalinity Relationship vs. Starting pH for 

Carbonation Intervals of .5,1,2,4,8 hours 

d~--------------------------------------------------------------------------------------------------~ ... 

10 

oj 

o 

oj 

10 

00-

o 

00 

10 

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-~ ----------

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",' ' 

",,' 

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KLA = 3.p X 10-5 m/s 

PROD= 30 g/sq.m./day 

,,' ' TEMP= 25 C 

",' 

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,,' "' 

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0.000 0.003 0.006 0.009 0.012 0.015 0.018 0.021 0.024 0.027 0.030 A II/A I IUITvh j II \ 
~ 

IX) 

..-

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:::> 

0 

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Figure 3.10 

I I 

7.0 7.2 

Time Between Carbonation stations vs. starting 

pH at 2, 10, and 30 roM alkalinity 

ALK = 30.0 mt-{ 

ALK :r:: ]0.0 wN 

ALK :01 2.0 ml-'f 

7.4 7.6 7.8 

STARTING pH 

8.0 
ent cases of available carbon storage as measured by the time 

between carbonations. The single solid line (top curve) represents a dissolved C02 concentration of 1 x 10-5 moles/l and thus 

indicates the pH endpoint for a given carbonation cycle. The 

resulting pH range at a specified culture alkalinity is easily 

predicted depending upon the frequency of carbonation. For cultures with low alkalinities, close to that of seawater (2mM/L), 

fairly large fluctuations will occur and recarbonation would have 

to be at intervals less than one hour. This would restrict the 

maximum size of one pond (with one carbonator) to about 1 haG 

3.6 OUTDOOR POND MEASUREMENTS 

The utility of any model is limited unless the data upon which it 

is based is physically sound and the predictions derived are reasonable in light of available information. For these reasons an 

effort(somewhat limited at this stage) was made to measure oxygen 

and temperature profiles in a small 1.2 m2 experimental pond (pH 

was controlled between 7.5 and 7.8). In addition, experiments 

were performed to determine the mass transfer coefficient for the 

pond. These experiments were carried out in Fairfield California 

using the experimental ponds operated by Dr. J. C. Weissman of 

Microbial Products, Inc. 

Dissolved oxygen was monitored over the course of the day at 15 

minute intervals. The probe could not be left unattended because 

rapid fouling affected the readings. The pond was 15 cmdeep, 

mixed at 30 cm/sec, and had a cell density of 200 mg/l of Chaetoceros SPa When measurements were begun at 8:30 AM (one hour 

after sunrise) the DO was already at 50% above saturation. Readings went off scale at 12:30 PM representing a DO of greater than 

400 %. By 5 PM it was back on scale ending at about 100 % saturation by 7 PM (one hour after sunset at this site). The following 

morning a point was taken at 7 AM and it was slightly below saturation. 

Shown in Figure 3.11 are the temperature profiles collected for 

two ponds operated at 10 and 20 cm. The mixing speed was 20 

cm/sec. The initial points, starting at 8 AM were a little high 

because a heater was left on in the pond for the two previous 

hours. On the following morning(data not shown) the temperature 

at 6 AM was 14 °c and 16 °c for the 10 and 20 cm ponds respectively. The maximum temperatures were 32 and 30 degrees C and 

therefore the amplitude of the temperature fluctuations were 18 

and 14 °C. There was roughly a four hour portion of the day, 

centered around 4 PM, where the temperature remained at its maximum for the 10 cm pond. The 20 cm pond slowly reached its maxi~~m 

at 5:30 PM. The ambient temperature peaked at 37 °c from 3 until 

5 PM, thus the shallower pond appears to have tracked the ambient 

temperature more closely. The small difference in temperature 

profiles as compared to that shown in Figure 3.4 indicates a 

problem with the model. Even though the environmental condi-

~5-
Figure 3.11 Diurnal Temperature Profiles for 20 em Ponds 

for September 1986 in Pleasants Valley, CA 

40 

38 -

36 -

34 -

32 -I COOOOOOO 

0 + + 0 

30 0 + + + + + IIJ 

" C + + lP 0 

~ 28 w + 

+ I n: 0 + Vi :J 26 0'\ [] 

I 

~ [] + 

0:: + + 

w 24 [] + 

0.. IJ 

w 

~ 22 D + 

I- + 

20 ijJ 

18 1o~m 

16 -

14 -

12 -

10 I I I 1 I 

8 10 12 14 16 18 20 22 24-

HOUR OF DAY 

0 10 em + 20 em 
,. tions were not identical, they were similar enough to raise doubt 

concerning model performance, thus reinforcing the need for model 

validation. However, it must be pointed out that these small 

ponds have edge effects that may make a significant difference in 

the model. 

Figure 3.12 is a plot of the rate of carbon loss from the pond as 

a function of the C02 driving force. The data represents two 

separate experiments carried out on a 1.2 m2 pond over the pH 

ranges 6.77 to 7.59 at 15 cm depth. These experiments were performed by injecting C02 into freshwater of known alkalinity{determined to be 2.67 roM) and following the pH change as a 

function of time. Using the KLA.FOR program the pH values were 

converted into dissolved C02 and total dissolved carbon. The rate 

of change in total dissolved carbon was then plotted against the 

calculated average C02 driving force for that pH interval. 

Henry's law was used to calculate the equilibrium C02 concentrations. Its value as well as the dissociation constants and the 

ion product of water were corrected for temperature(26-30 C). The 

slope of the data shown in Figure 3.11 was .0136 +/-11.4% which 

translates into a kla value of 3.4 x 10-5 m/sec. 

3 • 7 SUMMARY AND FUTURE WORK. 

A model of a shallow, well mixed, raceway type algae cUltivation 

pond has been developed which uses geographical, climatic, 

design, physical, and biological inputs to predict diurnal and 

seasonal variation of temperature, oxygen, and pH/C02. Specific 

cases of diurnal temperature patterns and monthly max/min temperature profiles have been solved for a potential algae cUltivation 

site in the U.S. Southwest. More general treatments of oxygen 

buildup and pH/C02 behavior under a variety of conditions are 

also given. It has been shown that significant fluctuations in 

all of these variables may exist with periodicities and magnitude 

determined by operating/design assumptions. For example it was 

found that both evaporation rate and outgassing coefficient 

affected model predictions significantly, thus pointing to a need 

to measure these parameters under real operating environments. 

Finally the existence of a rather dynamic environment, as would 

be present in the system described here, indicates a need to better understand the biological response to these transients and 

its effect on both species productivity and dominance. 

Future work on the model will focus on the energy balance section 

and validating predictions with available data sets. One such set 

has been collected by Dr. J. Weissmann of Microbial Products on 

the 1.2 m2 experimental ponds at Pleasants Valley over this past 

summer. This data set includes maximum and minimum temperatures, 

daily evaporation rates, and daily insolation totals. These ponds 

were heated for several hours in the morning with a 500 W heating 

coil (to bring their temperature up to 25 C) and this will have 

to be taken into account. 

-,57-
One particular problem with the model is the accuracy of the evaporation expression. In general these equations tend to be specific to the body of water they originally correlated. Algae 

ponds aren't well represented by either shallow lakes and reservoirs or pan A estimates. To make the model more tractable to a 

given location, estimates of daily evaporation rates(for that 

location) will be used in the model. Daily evaporation rates will 

be differentiated into instantaneous (minute intervals) rates by 

solving the evaporation equation iteratively, using the vapor 

pressure gradient as representing the driving force. A solution 

will be obtained when the integrated evaporation rate equals the 

input value. A further search of the literature for a more appropriate rate expression, to be used in the absence of evaporation 

data, will also be undertaken. 

After the temperature predictions of the model have been validated, an analysis of temperature profiles for two separate sites 

of different climatic conditions will be performed. This analysis 

will include the monthly distribution of max/min temperatures and 

the diurnal variation of temperature as a function of depth and 

season. A final area of investigation will be to determine to 

what extent dilution rate "profiling"(over the course of the day) 

can improve the temperature balance of the pond. For example 

diluting the pond during the middle of the day may decrease the 

maximum temperature of the pond (assuming makeup media is at a 

lower temperature). 

o 

o 

•• 

.... 

• • 

• o 

o~----~--~~--~----~----~""'---T-----r----~,~---"----~ 0.0 1.0 . 2.0 3.0 4.0 5.0 6.0 

CO - CO (moles/I) 

7.0 a.o 9.0 

FIGURE 3.12 PLOT OF RATE OF CARBON LOSS VS. C02 DRIVING FORCE 

FOR A 15 cm POND MIXED AT 30 cm/sec 

-58-
SECTION 4.0 

MICROALGAE COMPETITION STUDIES IN LABORATORY REACTORS 

4.1 INTRODUCTION 

A series of species competition experiments were carried out with 

mixed cultures in order to estimate the selective importance of 

the pond environment. Three experiments will be presented here; 

another experiment (testing the relative competitiveness of several species of algae) is in progress and will be reported in the 

Final Report. We chose to investigate transient conditions of pH, 

temperature, and dissolved oxygen in factorial design experiments. In these studies we relied upon an experience base of 

pond conditions (rather then the results from the model presented in section 3.0) in order to assign culture conditions. 

Each experiment consisted of combining either 3 or 4 different 

algal strains at equal cell densities (100 ppm) and following 

their individual cell concentrations as a function of time. Overall culture dry weight and dilution rate were also recorded. 

Determination of success at a particular condition was measured 

by equilibrium cell concentrations, which at the minimum was 

taken to be 21 days (>12 residence times). The experimental 

design and the final results of the species competitions are summarized in Table 4.1. In the following sections the results of 

each experiment will be discussed and then a final summary section and future work plan will be presented. Details of the 

experimental apparatus and the methods are presented in the 

Appendix. 

4.2 FLUCTUATING TEMPERATURE AND OXYGEN 

In this experiment the effect of fluctuations in oxygen, temperature, and light on the competitiveness of Chlorella, Chaetoceros, 

and Cyclotella was investigated. A summary of the experimental 

conditions and results is given in Table 4.1a. In Figure 4.1 are 

shown the dry weight curves for each culture and in Figures 

4.2a-d the cell count results. 

One general observation for each of the cultures was that while 

significant cell concentration differences began to appear in the 

cultures between roughly 6 to 9 days(4-6 residence times) the 

final "equilibrium" result was not apparent until after 18 

days (12 residence times). 

For culture 131, kept at air levels of oxygen and constant temperature, a codominance between the Chlorella and Chaetoceros was 

observed. The about 3 fold decline in Chlorella between day 9 and 

-59-
Jl 

1f 

1 

2 

3 

4 

1 

2 

3 

4 

Jl 

r. 

1 

2 

3 

4 

TABLE 4.1 SUMMARY OF EXPERIMENTAL CONDITIONS AND RESULTS 

FOR THE CONTINUOUS MULTISPECIES CULTURES 

FLUCTUATING TEMPERATURE AND OXYGEN MIXED CULTURE EXPERIMENT 

(Cell counts in million/ml at beginning and end of experiment) 

TEMP LIGHT OXYGEN CHLORELLA CIIAETOCEROS eYCLOTELLA. 

oC E/m2/s Beg. End Beg .. End Beg. End 

30 550 AIR 4 36 2: ~7 0.3 .06 

30 550 AIR/02 5 3 2 .30 0 .. 6 0.9 

20-32 550 AIR/02 4 7 1.5 33 0.3 0 

20-32 550+SPOT AIR/02 4 94 1 72 2 0 

FLUCTUATING pH EXPERIMENT 

(Cell . Counts in million/ml at beginning and after. 

ALI{ pC02 pH CHLORELLA CHAETOCEROS ANIcrSTl 

mM %AIR Beg. End Beg. End Beg .. E 

1 .35 7.1 2 13 2 14 a 0 

1-10 • .35 7.1-8.2 3 14 2 21 3 0 

10 .35 8.2 2 11 2 15 .3 0 

10 .04-4.0 7.1-80'2 .3 16 2 14 3 0 

DILUTION RATE AND SPARGER DESIGN EXPERIMENT 

(cell counts in million/ml at beginning and after 18 days) 

DILUTION SPARGER CHLORELLA CHAETOCEROS ANKIST. NAVICULA RATEC1/d) beg end beg end beg end beg end 

1.23(.05) fritted 1.8 13 1.0 9.6 .. 95 .03 .59 .. 20 

0.83(.01) " 2.0 60 1.0 .19 .91 .02 .59 0 

0033(.03) " 2.1 110 .88 .76 .94 .54 .59 .17 

0.73(.02) bubbler 2.1 13 .91 22 .94 .16 .6]. .58 

-60-
Figure 4.1 Dry Weight Curves for Cultures 131-134: 

Fluctuating Temperature and Oxygen 

00 • y--• 

~ 

to 

or.! 

N 

yoS 

~ 

~O! ?;O 

~ to 

• o 

til 

• o 

a 

• 

/0-\ --0-'\ /0\ ~. / G--8 

/ . . 'G"-.,./ • /-", 

."" . /0 ."" .-0 • 

/0"--0 __ 0 0-°, --0 /ci ,o>1:l otl, 0-0" /0-0-0 /O~~[]_D ° p. ~o-B-O-o-HLd ~o, 0-0 P_~_~ ·0 11---._ I UAl--..a. C- '0-[(- . IJ~ ./ ~-:-IiI_______ / D III 

0/ - "~ g'"1I-U--1I ""'\1II?1I_'I1~- . ii(' 

\-u-a-I C 

II =: 131 [] = 132 

° = 133 

• = 134 

C)~----------?---------~----------~----____ ~ __________ ~ ________ ~~ ________ ~ ________ ~ 

0.0 5 .. 0 10.0 15.0 ?n.o ?~_n :Jtnn .':1;:t; n -<-'til n 
FIGURE 4.2a CELL CONCENTRATION FOR LOW OXYGEN AND CONSTANT 

TEMPERATURE CONDITIONS (CULTURE 131) 

a Chlorella 

o Chaetoceros 

o Cyclotella 

.. "'0_ 

~ r-----.-----~------r-----._----~------~----_., -----,------, 

0.0 3.0 6.0 9.0 12.0 15.0 18.0 ,21.0 24.0 

FIGURE 4.2b CELL CONCENTRATION FOR FLUCTUATING OXYGEN 

AND CONSTANT TEMPERATURE (CULTURE 132) 

• 

11-111 ----.-- ~ 

.~ 

III Chlorella 

o Chaetoceros 

o Cyclotel/g 

II 

27.0 

"'0_ 

~.~---~---~--'-----r----.---.---~~---~~ 0.0 3.0 6.0 9.0 12.0 15.0 18.0 21.0 Z~.D 

-62-
FIGURE 4.2c CELL CONCENTRATION FOR FLUCTUATING OXYGEN 

AND FLUCTUATING TEMPERATURE CONDITIONS (CULTURE 133) 

x 

r= 

--E.."'o ==11"::"-

'--" 

ti 

c: 

o 

u 

"iii 

u 

"'0 

.-

0.0 3.0 6.0 9.0 12.0 15.0 

Davs 

• Chiarella 

Cl Chaetaceros 

o Cyclatello 

18.0 , 

FIGURE 4.2d CELL CONCENTRATION FOR FLUCTUATING OXYGEN AND 

TEMPERATURE AND HIGH LIGHT CONDITIONS (CULTURE 134) 

I 

'" '" I 

"'0 

.- m ___ a---m---D ___ ======~=====g ~u- . ~ 

__ -11""'-

II Chiarella 

D Chaetoceros 

o Cvclo"tella 

0_ 

.- r-----.------.------r-----.-~--_.------r_----_r----~-----., 

0.0 3.0 6.0 9.0 12.0 15.0 18.0 21.0 24.0 27.0 

nny~ 

-63-
15 is believed to have been the result of a wall growth problem 

(which is specific to Chlorella). Chaetoceros increased three 

fold during this period. The exchange of reactor vessels at this 

point (day 15) resulted in an increase in total biomass and the 

gradual increase in the Chlorella concentration. By day 25 of the 

experiment it was roughly equal in biomass density as the Chaetoceros. All this occurred while no outward changes of the culture were noted. A cell count taken on day 45 (the final day of 

the experiment) gave cell concentrations of 34, 16, and 0.2 million cells per ml for Chlorella, Chaetoceros, and Cyclotella 

respectively. These results agree closely with those for day 25. 

One clear observation of culture 131, was that the Cyclotella did 

poorly under this condition declining from day 7 (at 3.8 million 

cells/ml) to a final steady state cell concentration of about 

0.05 million cells/ml by day 15. Thus under these conditions 

Cyclotella is not competitive with either Chaetoceros or Chlorella and that these two species are about equally favored. 

Culture 132 tested the effects of a periodic high oxygen environment, while maintaining a constant temperature as in 131. For 

this condition, the Chaetoceros clearly dominates over both the 

Chlorella and Cyclotella. After day 18, there is an additional 

increase in the Chlorella concentration which by day 45 was at 

2.2 million cells/mI. The Cyclotella, while still being a poor 

competitor did roughly an order of magnitude better than in the 

low oxygen case(where Chlorella had been more competitive). A 

similar pattern as in culture. 131 is seen: a rapid increase in 

all cell counts, but with Chlorella favored followed (day 7-10) 

by a crash in Cyclotella and a subsequent rise in Chaetoceros, 

which remained dominant. 

Culture 1~3 was designed to evaluate, in addition to high oxygen 

tensions, the effect of a fluctuating temperature (on a diurnal 

cycle). Similar to culture 132, Chaetoceros is the dominant 

species after 10 days of growth with cell concentrations more or 

less the same as in culture 132. Chlorella growth is again 

depressed presumably due to the high oxygen tension. The major 

influence of the temperature fluctuation was the disappearance of 

Cyclotella, which may be an indication of this organisms sensitivity to the temperature regime. 

culture 134 was designed to determine the combined effect of high 

light, high oxygen and fluctuating temperature. Cell densities 

were considerably higher in this culture reaching over 100 million cells per mI. Under this condition both Chlorella and Chaetoceros did very well. As compared to culture 133 (without the 

high intensity spot) Chlorella was significantly more competitive, occupying approximately 25-35 % of the biomass compared to 

less than 10 % in culture 133. Cyclotella disappeared from culture after 13 days(as in culture 133) so the higher light environment had no measurable effect on it. 

-64-
'The codominance between Chlorella and Chaetoceros, seen in all 

cases studied, suggest competition for different resources. This 

would result if the two had different spectral absorption patterns and therefore be utilizing separate regions of the radiation spectrum. While it is difficult to measure an organisms 

absorption pattern accurately, because of light scattering, a 

semi-quantitative result can be obtained when neglecting the 

scattering effects. This has been done and is shown in Figure 4.3 

Even though the units are somewhat arbitrary, distinctly different patterns are obtained for each strain. Additionally, the 

effect of the high light (in culture 134) was to favor Chlorella, 

which one would expect due the red spectral emphasis of the 

quartz spot lamp. Thus this experiment, while not conclusive, 

does support the contention that codominance may exist between 

strains with different absorption patterns. 

4.3 FLUCTUATING pH 

For the most part, pH changes in engineered systems are the 

result of C02 gas transfer and photosynthesis, while alkalinity 

remains constant. Deleterious effects of the pH fluctuations 

could either be the result of changes in the concentration of 

dissolved C02 or the hydrogen ion concentration itself. In this 

experiment, pH fluctuations at one hour intervals, were applied 

by either step changes in the alkalinity(.5 to 10 roM) or by varying the pC02 concentration from air levels(.035%) to 3-4 %. Mixed 

cultures containing the organisms, Chaetoceros, Chlorella, 

Cyclotella, and Ankistrodesmus were tested. A summary of the 

experimental conditions and results is shown in Table 4.2. Cell 

counts for each condition are shown in Figures 4.3a-d. 

The most general observation that can be made from these results 

is that Chaetoceros was dominant for all conditions and Ankistrodesmus was noncompetitive for all conditions. The fact that Chlorella was not dominant is inconsistent with all other experiments 

tested at low oxygen and this dilution rate. The reason for its 

lack of competitiveness is unclear, but may be the result of the 

larger proportion of Cyclotella present in these reactors. There 

were no significant differences in productivity between reactorsthey were all 400 mg/l/day. Furthermore there were no obvious 

differences in species outcome for the varied pH environments, 

perhaps signifying the lack of pH sensitivity of the organisms 

tested within the range experienced. 

4.4 DILUTION RATE EXPERIMENT 

The objective of this experiment was to test the sensitivity of 

the experimental design to. changes in dilution rate and sparger 

design. Dilution rates of 1.23, 0.83, and .33 day-l were established on cultures containing Chlorella, Chaetoceros, Ankistrodesmus, and Navicula. The results for each dilution rate are 

shown in Figures 4.4a-d and a summary of experimental conditions 

and results are given in Table 4.1c. 

-65-
FIGURE 4.3a CELL CONCENTRATION VS. TIME FOR pH = 7.1 

g 

'8l~ I 

-iJ1---~D--- ~ D o~ ___________ n 

o m 

_11 __ 1]-- ---.. --8 

~ '/ ~I~ 

'--" 

"'0 ,... 

0-_--- 111 --- 0------0-----0---0 ---«1------

~~~------'j------~i------~----·-· ~'------~,------r-----~--.----~----~ 0.0 2.0 4.0 ~.O 8.0 10.0 li.o 14.0 1~.0 lA.D 

DAYS 

FIGURE 4.3b CELL CONCENTRATION VS. TIME FOR FLUCTUATING ALKALINITY 

-----a-----u--------.-----~ 

-----o~.----__ .----.-----------o 

"'0 

.-

"0_ 

,... r------r----~r-----_r----~------~----~ __ ----~--~~----___ 0.0 2.0 4.0 6.0 n.') 10.0 12.0 14.0 15.0 18.0 

nAve: 

-66-
..... 0 

.- . 

0.0 

FIGURE 4.3c CELL CONCENTRATION VS. TIME FOR pH = 8.2 

--0 

~8 • _____________ • 

. ~ -----.-----.-----.-----.-----

I 

2.0 

• 

----e 

II CHLORELLA 

ft~m~ 

I 

4.0 I 

6.0 I I 

0.0 10.0 

DAYS 

-----e-----e--____ _ 

-------. 

i 

12.0 14.0 16.0 18.0, 

FIGURE 4.3d CELL CONCENTRATION VS. TIME FOR FLUCTUATING pC02 

"'0 

.-

rJ CHLORELLA 

o-CHAnbc""E""'R=OS=--

. a ANKfsTRcf!5ESMDS 

lICYCLpitLLA 

~. 

---B ------ . 

_-.---e ______ ~~--. . 

--------

a 

·~-~-----r------~-----'------~------~----~-----~I~---~----~ 0.0 2.0 4.0 6.0 B.O 10.0 12.(1 1'1.0 15.0 

-67-
FIGURE 4.4a CELL CONCENTRATION AT A DILUTION RATE OF 1.23/day 

~ --o~ <~---~------~ ~1iI_==--_____ 1I 

4-

/19 

.- • 

. ----. 

. ---.-----------

'" 

124----~------~-----.--~·~·--r_----_r------r_----_r----_,r_--__, 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 

DAYS 

FIGURE 4.40 CELL CONCENTRATION AT A DILUTION RATE OF O.73/day 

WITH A GAS BUBBLER 

_~-D .- ______ D------~~ 

II CHLORELLA 

o CHAETOCEROS 

""6"ANRfsTRODESMliS 

• NAVICULA 

-0 

__ --11---11 

_____ ilII 

/8 _______ . 

124-----~------~-----.------~----~------r_----_r------r_--__, 0.0 2.0 4.0 6.0 !I.O 10.0 12.0 14.0 16.0 18.0 

DAYS 

-68-
FIGURE 4.4c CELL CONCENTRATION AT A DILUTION RATE OF O.33/day 

"0 

.-

"'0 

..... 

____ D 

• 

o 

/ ~O ____ O--O ____ 

-0 0 ____ 

II CHl.ORELLA 

o cHAETocrnDsOANKisTR-ootsMUS 

o NAVICUl,A 

.---------

Ii) 

12~Ir-----'I------'I------'I~~--~'------~I------TI------~I------~I------ 0.0 2.0 4.0 6.0 0.0 10.0 12.0 14.0 16.0 113.0 

DAYS 

FIGURE 4.4d CELL CONCENTRATION AT A DILUTION RATE OF O.83/day 

"0 

.-

~ 

~ 

"" ::tI:: 

'-" 

cJ"'o z ..... 0 

() 

..J 

Q 

u 

"0 

0-

J T0.0 

I 

2.0 

.lL,!::HLORELLA 

o CHAETOCE-ROSo ANKISTRODESMTIS .. NAVICU...!:L __ 

4.0 6.0 

I I 

8.0 10.0 

DAYS 

-69-

I 

12.0 

-----g----------
"Chlorella and Chaetoceros codominated with Chaetoceros maintaining as larger proportion of the biomass (ca. 60%). The other 

strains, Navicula and Ankistrodesmus, competed very poorly both 

declining in cell number. At a dilution rate of 0.83 day-I, 

Chlorella was clearly the dominant organism after 10 days of 

growth. Chaetoceros while competitive in the early stages of the 

experiment, was diluted significantly following the snarp 

increase in Chlorella. The overall patterns of for Navicula and 

Ankistrodesmus were similar to that observed at the higher dilution rates. At the lowest dilution rate (0.33 day-I), a pattern 

quite similar to that observed for the intermediate dilution rate 

was obtained. Chlorella again became dominant after roughly ten 

days of growth. Chaetoceros competed well initially, but declined 

significantly after 10 days. Ankistrodesmus and Navicula again 

competed poorly. 

In planning this experiment it was expected that changes in dilution rate would only affect the amount of time required to obtain 

the steady state result. These results clearly show that this is 

not the case. Most importantly differences between the fastest 

(1.23 day-l) and intermediate (0.83 day-l) dilution rates were 

significant and would have led to opposite conclusions regarding 

strain dominance. Moreover the transition from Chaetoceros dominated growth to Chlorella dominated occurs after the same period 

of time for the low and intermediate dilution rates. Thus overall 

culture age appears more important than the growth rate of the 

culture itself in establishing the amount of time required for a 

steady state result. 

The reason for the differences observed between the highest dilution rate and the lower dilution rate cultures may be explained 

by differences in the degree of light limitation. At the highest 

dilution rate, the cell density hovered a little above 400 ppm, 

while at the intermediate and low dilution rates the cell densities were roughly 600 and 1100 ppm respectively. Therefore it is 

implied that the rate of pigment synthesis or light utilization 

efficiency is greater in Chlorella than Chaetoceros. 

coincident with the dilution rate experiment, a fourth culture 

was used to compare the effects of sparger design on the dominance patterns. In previous work it has been observed that a 

significant amount of cell debris can accumulate above the gas 

liquid interface presumably stripped out of culture by the high 

gas liquid interfacial area. It was of interest therefore to 

determine whether the sparger itself was applying an additional 

selective pressure. In the test culture(#4) a gas bubbler was 

used instead of the standard course sintered glass cylinders usually used. The gas bubbler consisted of a 1/8 in. ID glass tube 

with one end closed and formed into a small sphere with 6-7 Imm 

holes along its perimeter. Bubble sizes are roughly 1 order of 

magnitude larger than those from a sintered cylinder. The dilution rate was 0.73 day-l,and therefor~ i~ comparable to the 0.83 

day-l culture. From F~gure 4.4d ~t ~s clear that Chaetoceros 

-70-
remained dominant in this culture for an extended period of time, 

in contrast to what was observed in the cylinder sparged culture. 

The Chlorella maintained a relatively constant cell concentration, with no sudden expansion in cell number being observed. 

There was no foaming and very little cell material deposited 

above the liquid level. 

The results from this experiment indicate that light limitation 

influences species dominance patterns. This is logical and suggests that future experiments operate only under light limitation 

it correlates with growth conditions in outdoor ponds. within 

light limited growth, differences in dilution rate appeared to 

have little effect on actual cell concentration patterns. Thus 

little bias is introduced into the dominance patterns as a result 

of dilution rate variations. Gas sparger design appears to have a 

significant effect on species outcome presumably due to differences in the shearing forces exerted upon a culture. Because open 

ponds experience primarily a low shear environment, with periodic 

high shear at the gas transfer stations, the gas bubbler is considered most representative of the pond environment, although 

power densities are well above those found in mass culture 

ponds. 

4.5 CONCLUSIONS AND FUTURE WORK 

It has been demonstrated that fluctuations in oxygen, temperature, and, to a lesser extent, pH fluctuations are all important 

features of microalgae cUltivation systems in terms of both productivity and species dominance patterns. In light of the discussion in Section 2.0, a new approach will be pursued in the 

remaining experiments under this contract (currently underway) 

and future research in this project. Specifically, future experiments will emphasize more work with monoalgal cultures, with 

mixed culture experiments being designed primarily for validation 

of monoculture results. 

The basic hypothesis to be tested is that there is little if any 

interaction between algal cultures (e.g. allelopathy or other 

interferences) and that mixed culture results can be predicted 

from unialgal cultures. Thus, dominance in mixed cultures should 

be predictable from the productivity (in terms of light absorbance units) of the cultures. This should be established, at 

least on a preliminary basis by the current, ongoing, experiments 

in which several species are being operated under both unialgal 

and mixed culture conditions. 

In the current and next few sets of experiments planned two general conditions will be tested: the standard, non fluctuating,' 

condition and a simulated outdoor condition reflecting the 

results from the AGP model. The currently ongoing experiments are 

designed to allow the selection of three species which will be 

used for future experiments and which have a high promise for 

outdoor cUltivation. 

-71-
These experiments involve the operation of five monoalgal continuous cultures at a detention time of 0.7 day-1 under conditions 

of fluctuating temperature (nighttime dropping down to 150 C, 

daytime maximum of 32oC) , high 02 (8 hours of 100% 02 gas phase 

during the daylight hours), fluctuating pH (7.5-8.5, 1hr cycles), 

and a high light intensity illumination on a 14hr light:10 hr 

dark cycle. The light intensity to the culture is increased in 

four steps over a 2 hour period at the start and end of the 14/10 

hr day-night cycle. The maximum intensity reaches 700-800 E/m2/s 

using Vitalite VHO fluorescent lamps. These lamps reproduce the 

true solar spectrum better than any other on the market. One 

additional flask is used as a mixed culture control, with all 

five strains inoculated at the same time. The first run will be 

completed in December and the second in early January. 

The data should allow establishment of which culture is the most 

productive and competitive (which should be the same one) under 

these conditions. A final selection of the three algal species to 

be selected for further work will be carried out based not only 

on the data from the above reported (and the ongoing) experiments 

but also on the information available from other SERI subcontractors and the SERI researchers. Work in the coming year will concentrate on the three selected algae. 

The objectives of the future research are: 1} To validate the 

fact that monoalgal cultures will consistently be predictive of 

competitiveness in mixed culture experiments; 2} To test the physiological limitations of the selected algae in terms of the seasonal extremes in the outdoor ponds for a selected location (Roswell New Mexico, where SERI will locate its algal mass culture 

systems Demonstration project) based on the results of the AGM; 

and 3) To determine which individual factors (pH, P02' daylength, 

temperature) have the greatest influence on culture productivity. 

The reactor system, as configured has the capability of running 

six cultures simultaneously. The experimental design will test 

the growth of the three strains as a function of both fluctuating 

and steady state conditions, in both unialgal and mixed cultures. 

The e¥periments will be carried out at a dilution rate of 0.7 

days-1 and last for approximately 10 residence times, thus 

requiring two weeks. Together with start-up time and allowances 

for failed experiements one run per month can be carried out. 

Daily measurements will include 0.0., dry weights, and, where 

required, cell counts (primarily for mixed culture experiments). 

Twice or three times a week pigments and total dissolved organic 

carbon (TOC) will be measured. After each culture has reached 

steady state, dark respiration, and the maximum rate of photosynthesis will be measured and cells will be harvested for protein, 

carbohydrate, and CHN. Three strains will be tested following 

this protocol with a total of four runs planned, including the 

mixed culture experiments and replicates. The results of these 

experiments will allow the determination of factors most influencing productivity and competitiveness (and whether these are synonymous). Further experiments will involve changing the conditions to those expected from seasonal extremes. 

-72-
SECTION 5.0 

LIPIDS FROM MICROALGAE 

5.1 INTRODUCTION 

Historically microalgal lipids have been of interest since World 

War II when von witsch proposed them as a source of vegetable 

oils and beta carotene (88). Even before the war the relationship 

between nitrogen nutrition and lipid content of algae was already 

recognized (89). After the war the study of microalgae lipids was 

pursued by groups in Germany (90), England (91), and, the U.S. 

(92). The report by Sphoer and Milner (92), that, Chlorella could 

accumulate up to 80% of its dry weight in the form of lipids, 

attracted considerable attention and their procedure, involving 

nitrogen starvation, was even patented (93). However, since the 

early 1950's the study of algal lipids has been primarily associated with taxonomic or biochemical studies of metabolism (94,95). 

The energy shortage of the mid 70's resulted in a renewed interest in algal lipids as a source of fuels (96) and prompted the 

DOE to establish a program to develop microalgae technology, 

which has been under SERI management since 1979. A major focus 

of the SERI/DOE program has been to identify high lipid yielding 

strains and develop the technology for producing an algal derived 

liquid fuel. This chapter begins with a literature review of 

lipids in general, the algal lipids and fatty acids in particular, nitrogen deficiency as a promoter of lipid formation in 

algae, and, models of nitrogen deficient growth is also presented. The results of the experiments carried out are then presented followed by discussions of their significance. 

5.2 REVIEW OF LIPIDS AND NITROGEN LIMITED GROWTH OF MICROALGAE 

5.2.1 Lipids from Microalgae 

Lipids are a class of molecules that, together with proteins and 

carbohydrates, broadly define overall cellular composition. Operationally they are defined as any cellular compound extractable 

in an organic solvent such as chloroform, or a mixture of chloroform and methanol. Their specific solubility properties are 

dependent upon the relative proportions of polar and nonpolar 

residues in the lipid molecules. Thus, some lipoproteins and glycolipids found in cells can be extracted into nonpolar solvents 

due to their lipid residues or side-chains. In the present context lipids are defined as all cell constituents that are 

extracted into the chloroform-methanol solvent mixture of the 

Bligh-Dyer method. (See the Appendix). 

-73-
Lipids can by classified as both polar and non-polar. The polar 

'lipids are comprised of the phospholipids (phosphotidyl choline, 

PC: phosphotidyl serine, PSi phosphotidyl glycerol, PGi phosphotidyl inositol, PI; and phosphotidyl ethanolamine, PEl and glycolipids (mono and digalactosyldiglyceride, MGDG, DGDG; and sulphoquinosyl diglyceride, SL) and are functionally associated with 

membrane structure and fluidity. Nonpolar lipids are primarily 

mono, di and triglycerides but also certain pigments, vitamins, 

wax esters, sterols, and cyclic and acyclic hydrocarbons. 

The triglycerides have been considered an energy storage reserve 

due to their high specific caloric value(9.3 kcal/g) as compared 

with protein and carbohydrate(5.1 and 4.5 kcal/g respectively). 

Indeed, triglycerides are clearly an energy reserve in higher 

organisms, and even in algae there is evidence of triglyceride 

breakdown during periods of energy limitation (96). From the perspective of fuel production the microalgal triglycerides, because 

of their prevalence and similarity with the vegetable oils, are 

of greatest interest. Hydrocarbons, such as those produced by 

Botryococcus braunii would also be of interest. However they are 

produced in quantity by only by that one species which grows 

slowly and can not be mass cultured. Thus, we emphasis in our 

discussion only the glycerides and fatty acids from microalgae. 

The algal fatty acid containing lipids are composed of PC, PE, 

PG, PI, MGDG, DGDG, SL, and triglycerides. Free fatty acids (FFA) 

are usually present at roughly 1-5% of the total lipid fraction. 

Saponifiable lipid make up roughly 30-40% of the total lipid. 

Fatty acid composition has been studied quite extensively since 

the 1950's and has been reviewed by several authors (95,97,98). 

All classes of algae contain large proportions of saturated 

C16's, however the remainder are very much class specific. Green 

algae (Chlorophytes) have the bulk of their fatty acids as saturated and unsaturated C18's. Their composition is very similar to 

that of vegetable oils. Diatoms (Bacillariophyceae) contain some 

monounsaturated C18's and also unsaturated C20's (20:4,20:5) and 

saturated C14. Golden-Brown algae (Chrysophytes) have lipid patterns similar to the diatoms, and also contain unsaturated C22's. 

The unsaturated C20's and C22's (omega-3 fatty acids) are of considerable current commercial interest because diets high in these 

have been linked to reduced heart and other diseases. 

5.2.2 Factors Affecting the Lipid content of Microalgae. 

Factors such as temperature, light intensity, and, most markedly, 

nutrient supply have been shown to affect composition of microalgae overall lipid composition and content. The effect of light 

intensity on fatty acid and lipid compositio~ has been studied by 

several authors. Constantopoulos and Bloch (99) found that in 

Euglena gracilis lipid content paralleled light intensity which 

was the result of decreasing chlorophyll content and its associated lipids. They also found that the degree of unsaturation 

decreased and in particular the palmitic acid content of the 

chloroplast lipids declined sharply while on a whole cell basis 

it changed very little. 

-74-
opute (100) found that the diatom Nitzschia palea changed its 

unsaturated to saturated fatty acid ratio from 2 to 1.3 between 

roughly 2% to 0.2% sunlight intensity. He also found that in low 

light very little triglycerides were formed and attributed this 

to the preferential synthesis of the necessary structural lipids 

in an energy limited environment. In the same study, he compared 

heterotrophic y§ autotrophic grown cultures of Navicula muralis 

and found that the dark grown cells had roughly twice the amount 

(on a relative basis) of saturated fatty acids as compared with 

light grown cells. He concluded as others (101) that there was 

some functional coupling between photosynthetic processes and the 

degree of unsaturation of the fatty acids. 

supporting this was the work of Pohl and Wagner (102) who reported 

that when cultures of Euglena gracilis were grown with sufficient nitrogen in the light, the fatty acids were highly unsaturated and the primary lipids were MGDG, DGDG, PG, and SL while 

dark grown , low nitrogen, or DCMU treated light grown cells had 

a higher percentage of saturated fatty acids and a higher content 

of the nonpolar lipids PC, and PEe In reviewing this area Pohl 

(96) concluded that the formation of polyunsaturated fatty acids 

and chloroplast lipids are favored by increasing light intensity. 

Fatty acids appear to increase in unsaturation as temperature 

decreases. It has been suggested in the literature that this is 

due to the need to maintain mobility of the lipoprotein complexes 

for proper cell function. Patterson (103) determined the fatty 

acid distribution for a high temperature strain of Chlorella at 

seven temperatures between 14 and 3SoC. He found that the degree 

of unsaturation did increase with decreasing temperature until 

220 C after which unsaturation decreased. It may be that temperatures below 220 C was too far out of the organisms normal metabolic range and the response was of a seconda~ nature. In addition he noted that the total lipid content did not change as a 

function of temperature. Materassi et al.(104) studying two 

strains of Scenedesmus, reported that saturated fatty acids 

increased lS to 32% in going from 20 to 35 °C. 

In synchronized cultures, storage compounds such as carbohydrates 

and lipids tend to accumulate on a per cell basis during the 

lighted portion of the growth period. Sundberg and NilshamanHolmvall (105) have described this for Scenedesmus by electron 

microscope observations. Shifrin and Chisholm (106) have found a 

similar pattern for synchronized Ochromonas polymorpha by direct 

measurements. Their data show however that while changes occur on 

a per cell basis, very little change in the lipid fraction occurs 

for the total population(on a weight basis). 

Of all environmental parameters, nutrient deficiency appears to 

be the most effective means for inducing changes in the lipid 

content and composition. Silicon limitation in diatoms (107) and 

severe P deficiency (lOS) are reported to increase lipids in 

microalgae. These are of minor importance, however, compared to 

the general increase in lipids observed upon nitrogen deficiency. 

-75-
5.2.3 Nitrogen Deficiency and Lipid content 

Increases of over 100% in lipid content are commonly reported in 

response to limiting the nitrogen supply to algal batch cultures. 

The first recognition that nitrogen limitation increased the 

lipid content of algae was made by von witsch (89) who observed a 

positive relationship between culture age (and diminished culture 

nitrogen) and lipid content. At the same time Spoehr and Milner 

(90) demonstrated that a nitrogen starved Chlorella reached 86% 

lipid while containing only 5% in exponential cultures. Many 

other reports of lipid induction by nitrogen deficiency are found 

in the literature in the 1950's and 1960's. A selected overview 

of the literature is presented in Table.501. 

More recently, Shiffrin and Chisholm (106) studied 30 different 

species of marine and freshwater chlorophytes and diatoms and 

found that for log phase cultures diatoms contained on average 

36% lipid as compared to 19% for chlorophytes (ash free basis). 

Cultures exposed to nitrogen starvation resulted in changes of 

-40% to +320% their log phase values after one week of starvation. Most notable was that while the diatoms had high log phase 

lipid contents they responded rather poorly to nitrogen starvation. On average there was very little change in lipid content. 

The greens however displayed a wide variety of responses ranging 

from a slight reduction in cellular lipid (Dunaliella) to 

increases of 2 to 3 times log phase values (Chlorella vulgaris). 

Some methodological problems with this study limit its value: 

inoculum sizes varied and, due to experimental design, cultures 

only grew to 2-3 times their inoculum density; the nitrogen mass 

balances (as calculated from the reported data) show large losses 

or gains in many of their cultures, thus the actual nitrogen status of these cultures is uncertain; and the lipid extraction 

methodology resulted in the inclusion into the lipid fraction of 

the solvent interface fraction, which would tend to increase 

lipid contents (Tornabene, personal communication). The data 

collected did not allow conclusions regarding lipid productivity. 

Much of the current work on lipid induction in algae is being 

carried out under the support of the SERI. Table 5.2 summarizes 

some of the work collected by investigators associated with this 

program. In general the data supports earlier studies on the 

importance of the nitrogen nutrition on lipid content. However 

the key issue of lipid productivity is still an open problem. 

5.2.4 Nitrogen Deficieny and Lipid productivity 

While nitrogen starvation in batch cultures (called herein 

nitrogen deficiency, as compared to nitrogen limitation in continuous cultures) increases lipid content in many microalgal 

species, particularly the green .algae, it is also correlated with 

a reduction in biomass productivity. In order to evaluate a 

microalgae based lipid production process, both content and productivity will be important. Indeed, an optimization between the 

two will be required: high content is desirable from the perspective of efficient extraction technology and high 'productivity is 

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Table 5.1 Algal Lipid contents from Selected Literature Reports 

SPECIES 

Chlorella pyrenoidosa .. II 

.. 

.. 

.. II 

.. 

II 

.. sp. strain A .. strain 10-11 

Bracteacoccus minor 

Chlorella vulgaris 

Nitzchia palea 

Chlorella pyrenoidosa 

Oocystis polymorpha 

Monollanthus salina 

Nannochloris sp. 

Scenedesmus obliquus 

ChI orella vulgaris 

LIPID 

NS 

20(80) 

18(?) 

25(?) 

20(?) 

25 (?) 

20(log) 

19(1og) 

25(?) 

27-33(?) 

22 (log) 

14(log) 

13 (log) 

41(log) 

20 (log) 

26(log) 

24 (log) 

CONTENT 

ND 

35(17) 

65(?) 

40(?) 

70(?) 

35(4) 

45-53(17-26) 

18-26(5) 

33(?) 

54(?) 

39(7-9) 

36(7-9) 

35(11) 

72(11) 

48(11) 

47(22) 

64.5(28) 

REFER. 

91 

91 

89 

109 

110 

111 

111 

112 

112 

100 

106 

106 

106 

106 

113 

113 

NS - nitrogen sufficient, ND - nitrogen deficient; numbers in 

parenthesis represent days of batch or logarithmic growth. 

Table 5.2 Lipid content of SERI Culture Collection Algal Strains 

SPECIES 

GROWTH 

CONDITION 

Amphora sp. 

Ankistrodesmus 

Boekilovia sp. 

Boekilovia sp. 

Botryococcus braunii 

Chaetoceros gracilis 

Chaetoceros sp. 

Chlorella sp. - Chlorella ellipsoida 

Cyclotella sp. 

Isochrysis(Tahitian) 

Monoraphidium sp. 

Nannochloropsis sal. 

Nannochloropsis sp. 

Navicula sp. 

Nitzschia sp. 

Nitzschia dissipata 

Oocystis pusilla 

Phaeodactylum trio 

Tetraselmis ape 

B,B 

B,BW 

B,BW 

C(?),BW 

B,FW 

B,SW 

B,BW 

B,FW 

B,BW 

B,BW 

B,SW 

B,BW 

B,SW 

B,SW 

B,BW 

B,SW 

B,-SW 

B,BW 

C(. 25) ,SW 

SC,SW 

LIPID CONTENT 

NS ND 

4.1 

24 

28 

23-29 

44 

15 

10 

16 

13 

7 

21 

29 

28 

32 

27 

26 

10 

20 

18 

14 

40 

36 

42 

54 

28 

33 

34-48 

21-30 

4.2 

26 

25 

60 

53 

58 

66 

23 

15 

SOURCE 

Benemann, 1986 

BenAmotz, 1984 

Benemann, 1986 

SERI 

BenAInotz, 1984 

Benemann, 1986 

SERILien, 1985 

SERI 

Tadros, 1985 

BenAmotz, 1984 

Benemann, 1984 

Tornabene, 1984 

Benemann, 1984 

SERI 

Thomas, 1983 

Tadros, 1985 

SERI 

Thomas, 1983 

Laws, 1981 

FW, BW, SW represent fresh, brackish and seawater respectively; 

B, C, SC batch, continuous and semicontinuous modes of growth. 

-77-
the primary concern in the economic feasibility of these systems. 

'Although the specific considerations in such an optimization can 

not yet be specified, as they will depend on many factors that 

are not at present quantitated (extraction technology and costs, 

C02 costs, by-product values, etc.), it is clear that a detailed 

understanding of the factors impacting on both lipid content and 

productivity are of central importance to this project. 

The issue of lipid productivity was already clearly stated over 

thirty years ago, when it was pointed out that the production of 

lipids would likely be most economical with nitrogen sufficient 

cells having a low lipid content rather then by nitrogen deficient cells which, despite their much higher lipid content,'had 

such a low productivity that total lipid yields were negligible 

(114). This particular issue seems to have been essential overlooked since then. 

For example, Shiffrin (98) commented that the organism Monalanthus 

salina would be" ••• a worthy prospect for further consideration ••• "(as a lipid producer). However the data (106) reveals 

that while M. salina achieved a lipid content of over 70% its 

lipid productivity was practically zero after nitrogen depletion. 

On the other hand a Scenedesmus sp. had the highest lipid productivity for all of the species studied before and after nitrogen 

deficiency, however this organism was not even mentioned as a 

good lipid "producer". 

Recently, Lien and Roessler (unpublished) reported results for 

five species undergoing nitrogen starvation in batch culture. 

They measured biomass and lipid productivities as well as the 

photosynthetic efficiencies for various cellular components. In 

two of the five strains, Boekilovia sp. and Cyclotella, lipid 

productivity decreased after nitrogen limitation. In Cyclotella, 

biomass productivity dropped from 400 to 20 mg/l/day. The other 

organisms studied showed moderate (Chlorella ,25%; and Ankistrodesmus, 17%) and substantial (Nanno Q, 90%) increases in lipid 

productivity. Photosynthetic efficiency and biomass and lipid 

productivity all appeared to be closely coupled. Significantly, 

photosynthetic efficiency actually increased for Nanno Q for the 

early stages of nitrogen deficiency, while decreasing between 20 

and 90% for the other strains. 

Our own, independent, studies have also demonstrated the relative 

uniqueness of Nanno Q in lipid production (11) and again illustrated the variability which exists between species in their 

response to nitrogen deficiency. This variability exists not 

only between species but also within species, as Opute's study of 

40 species of Chlorella demonstrated: some exhibited only carbohydrate storage and others lipid storage in response to nitrogen 

limitation. Thus any survey for high lipid producers can not rely 

on using representative strains of different species. 

The biochemical basis for lipid storage is poorly understood. 

However, it must have an evolutionary and selective basis. One 

suggestion has been that a high lipid content would allow algae 

-78-
to regulate their buoyancy. However this can be dismissed, (perhaps Botryococcus is an exception) on the basis of hydrodynamic 

arguments. Lipids do not sufficiently alter cell buoyancy to 

affect their settling behavior in most cases. Thus the best 

explanation is that lipids indeed serve as an energy reserve. 

Since lipids are much more concentrated energy forms then carbohydrates (almost nine fold on a hydrated weight basis) there is 

an advantage to store lipids for long term utilization. However 

this has not yet been demonstrated experimentally. 

5.2.5 Nitrogen Metabolism and Nitrogen Limitation 

Nitrogen deficiency in algae causes a variety of responses dependent upon species, growth history, and severity of the depletion. 

Breakdown of chlorophyll is the most visible sign of nitrogen 

limitation, although this can also be observed in response to 

other environmental stresses. The storage of carbon is a major 

and universal response to nitrogen limitation. This may be partially the result of a simple overflow metabolism of carbon fixation into cellular components not containing nitrogen. A rapid 

reduction in protein content and a redistribution of enzymes also 

occurs although there is little information concerning specific 

enzymology. 

Thurston and Rulands (115) have found specific protein decay 

rates of 12-40% in N starved cultures of Chlorella. On a culture 

basis protein synthesis continues until the nitrogen supply is 

exhausted. Activity of the enzymes of the nitrate assimilation 

pathway are all increased rapidly due to nitrogen depletion. 

Coupled with this is an increase in specific rates of uptake of 

nitrogen which occurs both by a reduction in cell nitrogen and an 

increase in the absolute rate of assimilation (115). The increasing enhancement in Vmax correlates well with decreasing growth 

rate (116). One interesting point is that nitrogen limitation 

results induction of enzymes (e.g. nitrate reductase, hydrogenase) which normally require an inducer without any inducer (or 

inducing condition) being present either before or after nitrogen 

limitation (117) • 

Chlorophyll content decreases as a function of cellular nitrogen; 

correspondingly per cell or per weight estimates of maximum rates 

of photosynthesis also decrease (118,119). On a per weight chlorophyll basis however, Pmax values are unchanged. Thus the generalized reduction in photosynthesis does not appear to be due to a 

loss of specific proteins involved in carbon fixation. Finally 

the light intensity at which photosynthesis is saturated remains 

unchanged as a function of deficiency (118). 

In some strains carbohydrate levels can reach above 70% without 

reduction in culture productivity (Weissman and Benemann in preparation). This occurs relatively rapidly« 1day). More slowly(> 

1day), lipid content increases anywhere from 0 to 200 % of 

healthy cultures. This has already been discussed and will not be 

elaborated on here. 

-79-
until now this discussion has not clearly differentiated between 

nutrient limited (continuous, e.g., chemostat) and nitrogen deficient (e.g. starved, batch) cultures even though there are significant differences between them, as discussed next. 

A nutrient limited culture is one growing in an external environment of constant, but insufficient levels of a limiting nutrient. 

The resulting intracellular levels of that nutrient will be 

dependent on its extracellular concentration and, in turn, specify the actual growth rate at which the organism grows. Operationally this is achieved in inverse order: the hydraulic dilution rate of the continuous culture imposes a growth rate on the 

organism, since slower growth leads to wash out and faster growth 

to population (cell density) increases until growth is balanced 

with dilution rate. Indeed, initially upon start-up of a chemostat, cell density increases until competition for nutrient is 

severe enough to reduce the incoming (in the dilution media) 

nutrient concentration to a level low enough to support growth 

only at the rate at which it is supplied (e.g. the hydraulic 

inflow). The chemostat is essentially a selfregulating growth 

rate control mechanism. 

In practice there is considerable initial fluctuation in cell 

density during a start-up, as overshoots (and subsequent undershoots) result from the organisms attempting to adapt their metabolism to the external environment (which, of course, is subjected to similiar, but inverse, fluctuations in limiting 

nutrient concentrations.) These oscillations however dampen out 

in short order (a few detention times) and thereafter balanced 

growth (= dilution rate) is maintained. 

Only when the influent nutrient concentration is high enough to 

support such a cell density that some other factor becomes limiting (e.g. oxygen supply or, in case of algae, light) do extracellular nutrient levels increase above the low levels normally present in a chemostat. Indeed, extracellular nutrient levels are 

often so low as to be below detection (by any but the most sophisticated analytical methods) levels. This is particularly true 

for algae growing on phosphate or nitrate as limiting nutrients 

below their half maximal growth rates (eg. at external nutrient 

concentrations below the Ks). 

In essence, the chemostat (or its variations, turbidostats, etc.) 

sets the growth rate of the culture and thereby the equilibrium 

extracellular nutrient concentration, which matches cell growth 

rates and dilution rates. The nutrient concentration in the feed 

will set the overall cell density. Of course, the metabolic 

(genetic) capabilities of the organism itself determine the 

exact extracellular concentration at any particular detention 

time (growth rate). 

In contrast, a starved batch culture does not have the ability to 

adjust its cell density to cope with declining nutrient supply 

nor is it receiving a continuous supply of the limiting nutrient. 

Therefore continued cell growth in batch cultures, once the 

-80-
, external supply is exhausted, occurs at the expense of the limit- ~ng nutrient stored in the cells. The metabolic consequences 

become increasingly more severe as a function of time after 

nutrient depletion. Growth rate continuously declines as intracellular nutrient concentrations drop and become zero (maximum 

standing biomass) at a certain minimum intracellular concentration (% of the biomass) of the nutrient. 

One significant difference between these two modes of growth lies 

in the ability of the chemostat cultures to adapt to the nutrient 

limitation. We consider continuous cultures to be adapted to 

their environment, as, by definition in a steady state situation, 

there is constant growth rate equal to the hydraulic dilution 

rate. Thus such adapted cells partition and prioritize the use of 

the limiting nutrient among the various' metabolic requirements 

according to its availability, resulting in an overall growth 

rate that reflects their genetic and metabolic capabilities. 

An important point to remember here is that in mixed cultures in 

nutrient limited continuous culture systems, efficient nutrient 

utilization (e.g. low q - the nutrient quota, as % nutrient in 

the biomass, or any other convenient unit) is not important in 

determining the outcome of species competition. An efficient 

uptake system (e.g. low Ks, the nutrient concentration at half 

maximal growth rate) is the determinant of success in a competition between two or more species in a nutrient limited chemostat. 

In the case of an intermittent nutrient supply a high Vmax (maximal nutrient uptake rate) and possibly a low Km (half saturation 

concentration of nutrient for Vmax , which could be different from 

Ks) may become critical, their relative importance depending on 

nutrient supply fluctuation frequencies, amplitudes, and time 

delay constants. (See Section 2. ) The maximum growth rate (umax) 

is only of significance in the case of competing organisms with 

intersecting u vs S curves (Figure 2. ). Thus maximal growth 

rate determinations could be of value, but only in the context of 

also knowing Ks (under balanced growth situations). The main 

conclusion is that in continuous cultures frugality is not important, efficiency in uptake is what counts. The same arguments 

hold in the case of light, where a low Ik is more important than 

a high Pmax • 

Batch cultures, by contrast, have little if any chance to adapt 

to the transient conditions they experience. There is a relatively rapid transition from fast, nutrient non-limiting growth 

to severe nutrient deficiency. Thus competition for a limiting 

nutrient never becomes an issue in a mixed culture. 

In the case of nitrogen, the difference between the maximum 

(nutrient sufficiency) and minimum (extreme deficiency) N contents (or cell quota) is about three to five. Thus a batch culture doubles in biomass about twice before growth ceases completely. Since biomass does not correspond to cell numbers in 

such conditions, and since the critical nitrogen content ( cell 

quota or % N of the biomass at which point growth rate is first 

reduced) is only a factor of about two to three above the minimum 

-81-
"nitrogen content, the transition between maximal growth and zero 

growth rates often takes place in the period of one cell generation, or even less. Thus there is only limited time for the cultures to adjust physiologically to the new situation. In any 

event, the adaptations that will take place are clearly quite 

different from those of a continuous culture, even one at very 

long detention times. Thus kinetic models of nutrient limited 

cell growth developed for continuous cultures are not applicable 

to batch growth. 

5.2.6 Kinetics of Nitrogen Limited Growth 

The most popular model of nutrient limited growth is that of 

Monod (120) which relates uptake rate to a hyperbolic function of 

the limiting nutrient. This has been discussed above and in Section 2.0. During nutrient sufficient growth the maximum uptake 

rate for the nutrient equals the growth rate, but this is not 

true during nutrient limited growth when Vmax is much higher then 

umax , and the Ks can differ from Km. Furthermore Vmax is very 

sensitive to the measurement protocols, as the initial kinetics 

can be' complex. Thus, the relationships between growth and 

nutrient uptake during nutrient deficient balanced growth are 

everything else being equal, not straight forward. 

The Monod model, with its close identification with the Michaelis-Menten equation, has been proven both popular and adequate 

for many batch and continuous culture studies. The Monod expression, in combination with a biomass balance and yield coefficient 

for the limiting nutrient allows the determination of overall 

culture productivity for a range of nutrient inputs and hydraulic 

detention times, the two major control variables in conventional 

microbial reactors. However, Monod kinetics are only applicable 

under conditions where the assimilation of nutrient is directly 

proportional to the production of biomass (balanced growth) and 

for within a range of growth rates in which the yield coefficient 

does not change and for which the basic Michaelis-Menten assumptions apply (e.g. E«S). Therefore, even in balanced growth, 

Monod kinetics may not be applicable at very slow growth rates 

(long detention times) where nutrient concentrations are below 

O.lKm (eg. u < O.lumax). Furthermore, if the nutrient concentrations fluctuate (or other environmental factors are not at steady 

state) and if adaptation to nutrient levels are not instantaneous, then Monod kinetics may also not be applicable, even 

though the culture may appear to be in balanced growth. These 

caveats significantly restrict the usefulness of this approach, 

particularly to microalgae which are subject to large variations 

in environmental parameters over seasonal, diurnal, and even 

shorter time periods. 

In general it has been found that nutrient limited growth is 

more accurately represented by internal, not external, concentrations of nutrient (121,122). Droop (123) introduced the cell 

quota (nutrient content per cell) concept, already used in different form with higher plants for many years, which was an outgrowth of his observation with vitamin B12 limited algal growth. 

-82-
Droop proposed that the growth rate (u) obeyed the following 

relationship to the cell quota: 

u = um(1-qm/q) 5-1 

(where qm is the minimum cell quota, q the actual cell quota, um 

the extrapolated maximum growth rate at infinite cell quota for 

that nutrient). This equation adequately correlated his data. 

Others (118,124) have corroborated this relationship. 

Goldman and McCarthy (125) noted, however, that the utility of 

equation 5-1 is limited by the fact that the maximum growth rate 

in this expression (um) is actually not the true maximum growth 

rate (umax) (under the experimental conditions) but is a function 

of the prevailing culture conditions in the absence of nitrogen 

limitation. They have proposed the following relation: 

5.2 

where q~ and Q are the actual (for the prevailing conditions) 

true min1mum and maximum cell quotas respectively, and u~ax is 

the true growth rate. Values for qm and umax can be determ1ned in 

batch cultures under exponential growth using what are presumed 

to be optimal conditions. Goldman (126) noted that the reason the 

Droop equation describes Vitamin B12-deficiency is the result of 

the algae storing large amounts of the vitamin and being able to 

grow below its um over a wide range of intracellular concentrations of that nutrient (> one order of magnitude). On the other 

hand, nitrogen content varies much less (usually from about 10 to 

2%) during nitrogen limitation. Thus the transition from nitrogen 

sufficiency (maximum growth) and nitrogen starvation (zero 

growth) is much more rapid. The same difficulty is observed with 

Si limitation. In general, the adequacy of applying the cell 

quota theory diminishes as a function of the plasticity of the 

nutrient pool (eg. carbon limited growth cannot be modeled this 

way), as already pointed out by Droop (121). 

A more detailed model was developed by Grenny et al. (127) who 

recognized that_ the entire nitrogen pool was not necessarily an 

indicator of growth rate, but certain compartments within that 

pool. They divided intracellular nitrogen into inorganic, and 

organic forms, and protein, and extracellular-nitrogen into inorganic and excreted forms. Growth was considered dependent on both 

intracellular and extracellular inorganic nitrogen. Correlation 

with the data of Caperon and Meyer (122) was good, but not significantly different from the Droop model. While introducing 

structure into nitrogen limited growth models is desireable, this 

representation overlooked one important feature of uptake kinetics: the energy dependence of most of the transport and reduction 

reactions. Essentially this model is similar to Droops's in that 

the parameters are still dependent upon the particular growth 

environment. Furthermore these models do not recognize explicitly 

the effect of nutrient storage, which results in some nutrient 

quota variations not affecting growth rate and in time lags during nutrient limitation. 

-83-
One final note on uptake kinetics concerns the kinetic response 

under transient conditions of nutrient supply. cunningham and 

Maas (23) studied transients of dilution rate (hence growth rate) 

in nitrogen limited continuous cultures. They found that while 

cell quota and growth rate were still coupled, the response in 

growth lagged by roughly 10 hours behind changes in cell quota. 

In general it is known that growth (photosynthetic biomass production) under nutrient limited conditions is actually inhibited 

for a period after the addition of the limiting nutrient. 

5.3 LIPID INDUCTION AND PRODUCTIVITY: RESEARCH OBJECTIVES. 

Due to the economic limitations inherent in any fuel production 

process the key issue in the production of lipids by microalgae 

is the overall productivity of the process, suitably optimized. 

To a first approximation it can be assumed that lipid productivity should be maximized for a biomass containing about half of 

fixed energy in the form of extractable and utilizable lipids. 

Allowing for inevitable losses, about 35 to 40% of the dry weight 

of the algae should be total lipids. This is higher than the 

lipid content found, with few exceptions, in algae grown under 

nitrogen sufficient (light deficient) conditions. 

One approach could, therefore, be to investigate the exceptional, 

constitutively high lipid, algal strains. However, as the case 

of Botryococcus makes clear, high lipid content would entail 

relatively poor competitiveness in outdoor cultures. Too large a 

fraction of photosynthetic reductant is diverted to the production of unproductive biomass away from cell growth. In a light 

(energy) limited environment this would make such cells highly 

uncompetitive. Only in batch cultures, as long as a high enough 

inoculum were to be present initially, could a culture with a 

high lipid content be produced in outdoor ponds subject to contamination. Production of such an inoculum would, however, be limiting. 

Thus investigation of lipid formation rates under nitrogen deficiency, and the underlying kinetic features, required the identification of a suitable strain that could serve as model for the 

process that is being developed. specifically the model strain 

would have to exhibit relatively rapid and a high degree of lipid 

induction, with high overall biomass and lipid productivities 

during the initial stages of nitrogen deficiency. Toward this 

end, eight strains of microalgae from as many genus [ Ankistrodesmus, Boekelovia, Chaetoceros, Chlorella, Cyclotella, 

Isochrysis galbana(Tahitian), Nannochloropsis sp.(Q strain), and 

Thallasiosira sp.]. were screened. They include examples from the 

chlorophyceae, eustigmatophyceae, and bacillariophyceaeo Screening 

involved measuring lipid (and biomass) productivity under conditions of batch growth with a limiting amount of nitrogen, such 

that the nitrogen would become limiting in the early to mid linear growth phase (eg. after light became limiting). The results 

were reported in last years Final Report (11). 

-84-
_ Of the eight strains, Nanno Q proved to have a high lipid content 

under both nitrogen sufficient (30%) and deficient (50%+) conditions and, most important, the highest lipid productivity after 

transfer to a nitrogen deficient condition. Thus it was selected 

for more detailed studies on the kinetics of lipid production 

during this transition. It must be emphasized that this organism 

is only a model system with which to demonstrate the basic feasibility of lipid production with microalgae. It is unlikely to 

have any potential for outdoor mass cUltivation. Thus what is 

learned with it will need to be applied to other strains, which 

have been proven to be suitable for outdoor cUltivation. 

The approach taken by this project was to separate the main biomass production phase from the lipid production phase, using 

nitrogen deficiency as the environmental factor that controls 

algal lipid biosynthesis and content. The objective thus is to 

determine how to best optimize such a two stage process in which 

lipid induction takes place after a light limited growth phase. 

It is important to note that to maximize overall lipid productivity the lipid induction phase must also be operated under light 

limitation. The conventional kinetic models of algal growth are 

not applicable under such conditions of dual nitrogen and light 

limitation. This defines a second objective of our research: to 

determine the effects of dual nitrogen and light limitations on 

lipid induction. Of course, an overall goal is to demonstrate 

experimentally that the two stage approach is preferable to a 

single stage continuous culture, limited for either light or 

nitrogen (or both). 

In the following sections we 

batch and continuous, light and 

Nanno Q. We conclude with a 

results. 

report our experimental data on 

nitrogen limited, cultures of 

summary and discussion of our 

5.4. LIPID PRODUCTIVITY IN NITROGEN DEFICIENT BATCH CULTURES 

OF NANNO Q 

5.4.1 Introduction 

Biomass and lipid productivities were investigated in batch cultures containing between 25-105 mg/l nitrogen (added as nitrate) 

with either one or two side illumination of 250 E/m2/s. The 

objective of these experiments was to determine how nitrogen 

quota (%N of afdw) , lipid content, and lipid and biomass productivity, varied as a function of total light input into the cultures. The experimental protocol is given in the Appendix. 

5.4.2 Growth-Rate Cell Quota Relationship 

In order to demonstrate that light did indeed affect the nitrogen 

quota - growth rate relationship, cultures were grown at 45 mg/l 

nitrogen in the media with either single or double sided light 

inputs. The growth rates, as calculated from daily productivi-

-85-
ties, are shown in Figure 5.1. It is clear that nitrogen quota is 

a function of the light supply rate and therefore of the biomass 

density at which nitrogen deficient growth is established. For 

example a nitrogen content of 5 % of afdw, at one side illumination, will result in a growth rate of 0.18/day vs 0.33/day for 

two side illumination. This is a demonstration that cells which 

are experiencing nitrogen deficiency can not simply be described 

by a single limiting nutrient approach. Thus the interpretation 

of the experimental results must account for the manner in which 

light regulates the growth rate in nitrogen deficient (batch) 

cultures. 

5.4.3 Chlorophyll a Content vs Cell Nitrogen 

In Figure 5.2 the data of percent chlorophyll a vs. percent 

nitrogen (as calculated by mass balance) is summarized. Nitrogen 

sufficient, light limited cultures contained up to 4.3 % chlorophyll a while deficient cultures went as low as 0.4 %. The 

chlorophyll a values were correlated tightly with cell nitrogen 

below nitrogen values of 6 %. Above this the previous light environment appeared to control the chlorophyll content as evidenced 

by the scatter at the high nitrogen values. 

5.4.4 Lipid content vs Cell Nitrogen 

Lipid content as a function of calculated cell nitrogen is shown 

in Figure 5.3. While there is a high degree of scatter, a general 

trend between lipid content and cell nitrogen is observed. Maximum lipid contents were slightly greater than 50 %. Two points at 

a cell nitrogen of 6% show a lipid content of 50-53% - they 

appear to be anomalous. Nitrogen sufficient lipid contents averaged about 28 %. The scatter in the correlation can be a reflection of eithe~ the assay or the culture environment or both. 

There is no systematic difference between external light environments, however much of the variation can be accounted for by 

variation in culture densities and hence the trajectory of the 

culture, e.g. variations in light-nitrogen limitations during the 

growth of the culture. 

5.4.5 Lipid Productivity vs 'cell Nitrogen 

Running three day averages of lipid productivity were calculated 

for N deficient batch cultures at two side illumination. These 

results are presented in Figure 5.4 as a function of cell 

nitrogen. Maximum lipid productivities were greater than 150 

mg/l/day occurring at roughly 5-6 % cell nitrogen, while nitrogen 

sufficient productivities were less than 100 mg/l/day. The relationship appears to be independent of cell density except for the 

25 mg/l case. One point worth noting however is that all cultures 

(except for the 25 mg/l culture) achieved a maximum lipid productivity of 150 mg/l/day. A similar, but lower, productivity maximum (at 5-6% N) was obtained for the single side illuminated cultures (data not shown). 

-86-
FIGURE 5.1 GROWTH RATE - CELL QUOTA RELATIONSHIP DURING N 

DEFICIENCY AT ONE AND TWO SIDE ILLUMINATION 

.:j< 

o 

o 

o 

• • 

• 

ONE SIDE ILLUMINATION 

TWO SIDE ILLUMINATION 

•• • 

o 

ci_~------~------~------~--------T-------~------~--------~----~ 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 

1/Q 

FIGURE 5.2 CHLOROPHYLL a CONTENT VS. CELL NITROGEN 

« 

::i >-0 it,.; 

o 

a::: 

g 

:::t: 

U 

1-0 

~N< 

u 

a::: 

w 

a. 

o -'-

o 

• = DOUBLE ILLUMINATION 

0= SINGLE ILLUMINATION 

o 

o 0 

•• 

o • 0 

o 

[J • 

o tb 

o 

• 

• 

o 

o 

o 

o 

• 

45.0 

II 

II 

ci.~ __________ ~ ____________ ~ ____________ ~ ____________ ~ __________ ~ 

0.0 2.0 4.0 6.0 8.0 10.0 

PERCENT NITROGEN 

-87-
o c:i 

It) 

o c:i 

" 

Cl 

a: 

::J 

I-C! ZO 

W.., 

U 

~ 

w 

a. 

o c:i 

N 

o 

go 

FIGURE 5.3 LIPID CONTENT 

0 

• DO • 

• 0 

• ".' r. .-. -0 0 

0 [8 80 

0 o 0 

• 

8 = DOUBLE ILLUMINATION 

0= SINGLE ILLUMINATION 

f] 

8 

0 

8 • 0 

vs. CELL NITROGEN 

o • 

0 8 

0 

II • • 8 • 00 

0 0 B 

0 0 

c:i.r-------------r-------------r-------------~------------~----------__4 0.0 2.0 4.0 6.0 8.0 

PERCENT NITROGEN 

FIGURE 5.4 LIPID PRODUCTIVITY VS. CELL NITROGEN 

'>: 

o 

~ 

o c:i 

O' 

N 

"-0 0) • 

E~ )::' 

ls: 

t3 

=>0 Cl. 

0 0 

~sa 

a. 

Cl 

a: 

::J 

o 8 c:i 8 It) 

o 

CD 

~ __ - _ • _C. 

o 

• 

• 

• o 

.=25 mg/I N 

0=45 II 

0=65 .. .=85 II 

0=105 " 

10.0 

( I 

o 

c:i1-------~--------~------~~----~~------~------_T--------r_------~ 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 

PERCENT NITROGEN 

-88-
- 5.4.6 Heat of Combustion vs. Cell Nitrogen 

Cultures were grown up in sufficient quantities (400 mg/sample) 

and harvested at different intracellular levels of nitrogen in 

order to correlate heat of combustion, cell nitrogen, and degree 

of reduction. The data is shown in Table 5.3 and the heat of combustion vs cell nitrogen results are plotted in Figure 5.5. As 

expected, the heat of combustion and degree of reduction both 

increase with decreasing cellular nitrogen. The degree of reduction is defined as the number of electrons available for oxidation (129). When calculated, ignoring the contribution of the N 

source, the degree of reduction is found to correlate many organic compounds, as well as biomass generally, with the equation: 

hc = 27.5G kcal/mole. 

Where, G = 4 + H - 20, H is the moles of hydrogen and 0 is the 

moles of oxygen (128). The final column in Table 5.3 shows close 

agreement with the coefficient( ~7.5 vs 27.6) and therefore is a 

suitable .method for determining hc for nitrogen deficient Nanno 

Q. The correlation between cell nitrogen and hc is quite good and 

would also be a useful predictor of the heats of combustion. 

5.4.7 Light Shift Experiment 

In order to test the idea that nitrogen deficient lipid productivity may be in part regulated by the cells ability to carry out 

photosynthesis, an experiment was performed where the supply of 

light to the culture was increased, by a factor of two, after the 

onset of N deficiency. This was accomplished by switching the 

culture from one side to two side illumination (of the same 

intensity of light). The analogy to an open pond culture would be 

to double the pond area for the second stage, that is the pond 

area used for lipid induction would be twice that of the biomass 

production ponds). 

A plot of biomass yield is shown in Figure 5.6. Light limited 

linear growth starts around 300 mg/l which occurred between days 

2 and 3. The light shifted culture therefore experienced roughly 

one day of light limitation before it was switched to two sided 

illumination on day 4. The effect of this one day of light limited growth "is demonstrated in Figure 5.7 showing the culture 

chlorophyll concentrations. The single side illuminated and the 

shifted cultures reached a maximum chlorophyll at 18 mg/l vs the 

double side illuminated culture at 13-14 mg/l. Chlorophyll following this maximum initially declined but then leveled off. This 

constant concentration during a period of increasing biomass concentration indicates that on a per culture weight basis chlorophyll was decreasing. continued growth would eventually dilute the 

chlorophyll to such a degree that growth would cease completely. 

In Figure 5.8 lipid yield is plotted. It is apparent that lipid 

yield is the same for the double side and light shifted cultures 

by day 8 (880 mg/l). While the single illumination is roughly 

half that(400mg/l). Thus an additional 1-2 days of light energy 

-89-
TABLE 5.3 DEGREE OF REDUCTION, % NITROGEN, AND HEAT OF 

COMBUSTION FOR NANNO Q CULTURES 

_:'9~.:21~ /~:~ -~ h e:rp (kc al/molel h exp/ ~ -c c 

209 9.44 . 4.94 134.8 27.29 

_ 

') ..." \ .Jt.; 8.09 1+.97 137.6 27.69 

214 8.32 5.002 l38.9 27.77 

211 5.63 5.028 141.0 28.04 

210 6.36 5.039 140.3 27.84 

_.1<_ ?''> 5.03 5.051 142.2 28.15 

215 4.71 5.131 142.5 27.77 

23l 3.60 5.140 142.3 27.68 

216 3.10 5.18 144.8 27.95 

217 3.20 5.24 140.7 26.85 

213 2.96 5.24 141.2 26.94 

x = 27.63 + .43 

-90-
FIGURE 5.5 HEAT OF COMBUSTION VS. CELL NITROGEN 

III 

C'I 

" 11.1 

.--.. 

~o _0 II o . u~ 

ec .. .Q 

-1/111) 

:J~ 

.Qui 

E • 0 

u 

.... • 0 0 .... 11) II Oui 

Q) 

:::c 

II 

II) II C'I 

ui 

~I m '. 

j j I j j I j 2.0 3.0 4.0 5.0 6.0 7.0 B.O 9.0 

%N 

FIGURE 5.6 BIOMASS YIELD DURING LIGHT SHIFT 

o 

g~----------------------------------------------------~---------, N 

o 

o 

o· 

~ 

o 

o 

o· 

!!1 

o 

'-"'0 ""-.0 

Olt:! 

.s 

3:

o 0 . ...... 0 

<!~ 

o 

o 

o 

'" 

D= ONE SIDE 

0= ONE->TWO SIDE 

0= TWO SIDE 

, 

• ~ .1-----:;:.-----:2r""0----3TO---..1.,4-0----:S:r"0:----:TS

.":'0----::7:r.0

:----;!8.0 0.0 1.0 . . . . DAYS 

-91-

I 

iO.O 
o 

0. 

N 

o 

~-

o cO· 

o 

-.¢. 

o 

FIGURE 5.7 CHLOROPHYLL a YIELD DURING LIGHT SHIFT 

• ONE SIDE 

DOiiIE - >TWm"'o"'s'"'Ib""£ 

o rWOSTbE 

./ 

o ......... ---..,.-----,..-----;,.----.,----""T"'---__r----r-----i 0.0 

o 

o 

o· 

eQ 

o 

o 

o 

N 

o 

1.0 2.0 3.0 4.0 

DAYS 

5.0 6.0 

FIGURE 5.8 LIPID YIELD DURING LIGHT SHIFT 

.= ONE SIDE 

0= ONE->TWO SIDE 

0= TWO SIDE 

7.0 B.O 

o .. ~------~-------,..------~------~~------_r------__r--------r_----__4 

0.0 1.0 2.0 3.0 

-92-

4.0 

DAYS 

5.0 6.0 7.0 B.O 
(from one side) was unnecessary to attain the same lipid yield. 

The lipid productivity was 180 mg/l/day in the shifted culture as 

compared to 150 mg/l/day in the two side illuminated culture. 

This experiment was repeated with virtually identical result 

(data not shown). 

5.4.8 Discussion and Conclusions 

It must be recognized that although lipid induction by microalgae 

is a widespread phenomenon among certain classes of algae a high 

lipid productivity during lipid induction in response to nitrogen 

limitation appears to be (unlike carbohydrate productivity) the 

exception rather then the rule. However, too little data presently exist to allow quantitation of this extrapolation. Thus, 

selection of Nanno Q as a model system for lipid induction was 

based simply on the fact that both our work [and that by the SERI 

researchers (Lien and Roessler, unpublished)] demonstrated that 

this organism is suitable for such studies. 

Nitrogen deficient batch culture experiments with Nanno Q were 

carried out at initial nitrogen concentrations of 25 to 105 mg~l. 

This translated into "stationary" biomass concentrations rangl.ng 

from 500 to 2400 mg/l. A combination of single and/or double 

illumination with 250 E/m2/s was used to investigate the inter-· 

action of light and nitrogen on culture performance. It was 

demonstrated that light supply (total area exposed), or the 

severity of the light limitation (cell concentration at the onset 

of nitrogen limitation) affected the organism requirement for 

nitrogen and thus the growth rate- nitrogen quota relationship. 

This a logical qonsequence of the energetic requirements for 

nitrogen metabolism. One interesting question is whether this 

relationship would have changed if another nitrogen source (ammonia, urea) which require less metabolic energy had been utilized. 

Heat of combustion, lipid, and chlorophyll a all correlated with 

the nitrogen quota. Severely deficient cultures of Nanno Q had a 

heat of combustion of 7.5 kcal/g vs. 6.0 kcal/g for light limited 

cultures. Lipid content ranged from 28 to over 50 % with increasing nitrogen deficiency. Chlorophyll a content was found to correlate with cell nitrogen below 6 % and in that region was independent of light supply. Lipid productivity was demonstrated to 

have a maximum of 150 mg/l/day at 5 to 6 % cell nitrogen and was 

apparently independent of light supply and cell density (when 

initial nitrogen concentrations exceeded 25 mg/l). The lower 

boundary for maximizing lipid productivity appears to occur coincident with that of biomass productivity. That is, a high enough 

cell density must first be established, prior to nitrogen deficiency, such that light limited growth and biomass productivity 

was maximized. 

within the nitrogen levels used the upper boundary for lipid productivity had not been reached. It could be as high as the cell 

density at which light limited productivity begins to decline 

(due to maintainance requirements). The implication is that in 

mass cultures, where cell density must be maximized to reduce 

-93-
costs for the harvesting process, nitrogen limited cultures could 

operate at a high a cell density, before productivity losses due 

to respiration become significant. 

Finally, it was demonstrated by the three experiments that for 

nitrogen deficient cultures, an increase in the light supply 

(doubling the exposed surface area) results in overall lipid productivities significantly greater than those obtained for cultures kept at the higher light supply on a constant basis. It is 

reasoned that this may be due to an increased concentration of 

chlorophyll, in the shifted culture, thus enabling a higher relative rate of electron capture and, therefore, supply of reductant. This result suggests that an optimum process design should 

include an initial period of light limitation to increase culture 

chlorophyll, followed by a second stage, after nitrogen deficiency has begun, where the light supply would be increased. In a 

pond environment this could be done by decreasing the culture 

depth or density (by dilution) of the second stage thereby making 

the pond areas for the second stage larger then the first stage. 

The overall effect would be to increase lipid productivity, as 

the total pond area for both stages would be minimized relatively 

to the alternative of keeping the light input constant. 

5.5 LIPID PRODUCTIVITY IN NITROGEN LIMITED CONTINUOUS CULTURES 

OF NANNO Q 

5.4.1 Introduction 

In the above experiments, the lipid and biomass productivities, 

nitrogen content, degree of reduction, heat of combustion, as 

well as compositional changes were investigated in nitrogen deficient (starved) batch cultures of Nanno Q, demonstrating the limits of efficiency of converting light energy into lipid for batch 

cultures. Once conclusion form this work was that some degree of 

light limitation is advantageous in order to maximize lipid formation. The work reported on in this section had the following 

objectives: 

1. Determine whether lipid biosynthesis can be increased in continuous cultures by nitrogen limitation and compare productivities between batch and continuous cultures; 

2. Investigate the effects of dual light and nitrogen limitation 

on lipid formation in continuous cultures; and 

3. Determine lipid formation rates in nitrogen starved (batch) 

cultures derived from preconditioned nitrogen limited (continuous) cultures. 

5.5.2 Experimental design 

Conventional chemostat experiments designed for determining 

nutrient limited growth kinetics are normally carried out at a 

single feed concentration of the limiting nutrient and varying 

dilution rates. The culture therefore adjusts its cell density to 

-94-
reflect the nitrogen supply rate (at u<umax and Km«S, where S is 

the influent nutrient concentration). Thus each different imposed 

growth rate is limited at different external nutrient concentrations and at different cell densities. For microalgae, if the 

light intensity is not significantly above the saturation value 

(lk), some degree of light limitation will exist, becoming more 

severe as a function of cell density. Thus, unlike for heterotrophic systems, cell density is important. 

In ecologically oriented research this problem is avoided by use 

of very low nutrient concentrations in the feed and, therefore, 

very low «10' mg/l) algae concentrations in the culture. This 

minimizes light absorption «10% of incident light) and avoids 

variations in the light absorbed per algal cell. However, in mass 

culture type of work, the effects under conditions of complete 

light absorption (>95%) are of interest. Even if it is argued 

that at incident light intensities below Ik light absorption per 

se is not an important variable, the practical constraints of 

providing sufficient sample size for the various required analysis suggest that dense cultures be used. 

Dense nutrient limited continuous cultures will superimpose light 

limitation on nutrient limited growth. This results in two simultaneous variables, light and (in this case) nitrogen limitation. 

This problem can be overcome by operating the chemos tats at (more 

or less) fixed culture densities, as estimated by chlorophyll 

concentration. This has the advantage of enabling operation at 

higher cell densities which decreases the volume requirements for 

sampling, but has the disadvantage of requiring manual adjustments of feed nitrogen levels. A combination of the two above 

mentioned approaches, constant feed supply and constant cell density, was used in the experiments reported on in this section. 

Using the Droop equation and estimates of umax and the minimum 

nitrogen quota from previous experiments, feed rates and nitrogen 

concentration required to maintain an approximately constant cell 

density were estimated. Below we report on biomass and~ lipid 

productivity in nitrogen and/or light limited continuous cultures of Nanna Q operated at a hydraulic detention time of 0.17 

to 0.9 day-1. The data reported is preliminary and does not 

represent all the completed experiments. Nitrogen and some lipid 

analysis remain to be completed. 

5.5.3 Light Limited Growth 

Data was collected for seven distinct steady state conditions in 

which growth was limited by light not nitrogen supply. A summary 

of this data is shown in Figures 5.9-5.11. It was found that 

regardless of dilution rate, lipid content remained relatively 

constant at about 30% (Fig. 5.9). This compares quite closely 

with what is observed for nitrogen sufficient batch cultures (see 

figure 5.3). Chlorophyll g content as a function of dilution rate 

is shown in Figure 5.10. Maximum chlorophyll a reached around 4 % 

and began to decrease above 0.5/day. Biomass and lipid productivity are plotted as a function of growth rate in Figure 5.11. 

-95-
FIGURE 5.9 LIPID CONTENT AS A FUNCTION OF DILUTION RATE FOR A 

LIGHT LIMITED, NITROGEN SUFFICIENT CONTINOUS CULTURE OF NANNO Q 

40 

0 

0 °.0 30 0 

0 0 

"....., 

~ 

'"" +' 20 C 

II 

.. 

C 

0 

U 

;!2 10 a. 

:J 

0 

0 0.2 0.4 0.6 0.8 

Dilubor. Rate(1/day) 

FIGURE 5.10 CHLOROPHYLL g CONTENT AS A FUNCTION OF DILUTION RATE 

FOR LIGHT LIMITED, NITROGEN SUFFICIENT CONTINOUS CULTURES OF NANNO Q 

4 0 

00 

CI 

3 c 

........ 

~~ 

'-" +' 

C 

II 

... 

C 

0 

/) " ... 

~ 0 

G 

o 

o 0.2 0.4- 0.6 0.8 

Dilutior. Rate(l/doJr) 

-96-
--->, 

0 

'0 

"-

"-C> 

E 

'-:' 

" 0 

IIl. 

320 

300 

280 

260 

240 

220 

200 

180 

160 

140 

120 

.100 

80 

60 

40 

20 

0 

0 

Continuous Culture 

Nitrogen Sufficient 

/ o....---....o~ 0 

o 

o 

0.2 0.4 0.6 

Dilution Rote(l!doy) 

D~ 

+ 

0.8 

Figure 5.11 Biomass and Lipid Productivity in Light Limited 

continuous Cultures of Nanna Q. 

-97-
They both display roughly the same optimum, somewhere between 

0.25 and 0.45/day. Maximum biomass productivity reached 280 

mg/l/day which is less than the 350 mg/l/day observed for light 

limited batch cultures. Maximum lipid productivity was 80-90 

mg/l/day, slightly less than the 100 mg/l/day achieved in 

nitrogen sufficient batch cultures. 

5.5.4 Nitrogen Limited Growth 

In one experiment, nitrogen limited cultures were established at 

low cell densities by varying the nitrogen concentration in the 

feed. This data is shown in Table 5.4. By adjusting the feed 

nitrogen and hence the cell density it was possible to eliminate 

any compounding effect of decreasing light supply - on a per cell 

basis as growth rate decreased - that would have resulted if a 

constant nitrogen feed concentration was used. Growth rates ranging between .28 and .81/day at cell densities less than 200 ppm 

were investigated. Cell nitrogen has not been determined as yet, 

the numbers reported in Table 5.4 are calculated on a mass balance basis assuming negligible abiotic nitrogen. Lipid content 

was significantly increased over nitrogen sufficient cultures. It 

varied between 44 and 36 % for dilution rates of 0.28 and 

0.81/day respectively, or between 5 and 7 % cell nitrogen. These 

values are similar to those observed for batch cultures. 

TABLE 5.4 STEADY STATE RESULTS FOR NITROGEN LIMITED CULTURES OF 

NANNO Q. (Number in parentheses are 2x st.dev.) . 

Dilution %N. Density Pbio Percent Percent PI' Pchla 

Rate mg/l mg/l/day Lipid ChI a mg/17~ mg/l/d 

0.28(.02) 5.1 150(20) 42 (6) 44(12) .58(.08) 19(5.6) .25(.05) 

0.52(.07) 4.6 200(20) 100(20) 43(9) .86(.32) 43(10) .82 ( .05) 

0.81(.06) 7.1 170(20) 140 (14) 36(3) 1.7(.3) 50(7) 2.4(.4) 

Another experiment, conducted at higher cell densities and with 

lesser degree of nitrogen limitation was carried out on cultures 

that were previously nitrogen sufficient. The complete history 

for these cultures is given in figures 5.12a-d. The arrow is an 

indication of the start of nitrogen deficient media inflow, the 

two marked regions indicate the collection of points comprising 

the steady states., Because nitrogen analysis are incomplete, it 

is only possible to discuss these results in terms of their general response to nitrogen limitation(Figures 5.13 -5.15). 

The cultures displayed some variety in their responses but where 

clearly nitrogen limited due to their decreased rates of chI a 

synthesis. Biomass productivity decreased in three of the cul-

-98-
FIGURE 5.12 a ASH FREE DRY WEIGHT HISTORY FOR CULTURE 266 

,..... 

"' "" "oJ 

'" .. 

"0 

c 

G 

Q 

«i 

I..l 

"..., 

"-Ol ....., 

.. >-

"0 

c 

G 

0 

«i 

0 

0.9 

0.8 

0.7 IJ 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0 

2 S 10 14 18 23 27 1 5 9 13 17 21 25 29 2 S 10 14 

Dote 

FIGURE 5.12b ASH-FREE DRY WEIGHT HISTORY FOR CULTURE 267 

1.8 

1.7 

1.6 

1.5 

1.4-

1.3 

, .2 

, .1 

0.9 

0.8 

0.7 

0.6 

0.5 

IJ 

a IJ 

o o c 0 

o a CDC 

o 0 0Cb Q Cb 

o iJ 0 !i:J Cb rfDO 0 a 0 

o 0 O~ 0 

00 00 

o 0 _....c 

qp IJ 0 

OJ 0 cPO 09J O O 

COO 

o [J 

2 6 10 14 18 2327 1 5 9 13 17 21 25 29 2 0 10 14 

Dote 

-99-
FIGURE 5.12c ASH-FREE DRY WEIGHT HISTORY FOR CULTURE 268 

1 . I 

1.6 

1.5 

1.4 

" "- 1.3 Cl' 

'-" >, 1.2 

!:! 

'" 1.1 c 

II 

0 1 

,I) 0.9 

0 

0.8 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

a 

~c o 

o c:c 

o 

~ 

o 

o 

o a 

I:l 

ttJ 

o 

o 

o 

o 

:2 S 10 14 18 23 '27 1 5 9 13 17 21 25 29 2 6 10 14 

Date 

FIGURE 5.12d ASH-FREE DRY WEIGHT HISTORY FOR CULTURE 269 

1.8 

1.7 

1.6 

1.5 

, " 1.4 Cl' 

'-" >, 

.. 1.3 

'0 

c: 

II 

0 

1.2 

Ii 1 . t 

0 

0.9 

0.8 

0.7 

0.6 

0.5 

to 0 o 

cP 

o 

I:l DO 

DOD 0 C D 

o D of

o 

cOO 0 

CO Doo 0 

D 

o 

o [J:J DO CL 0n..J:] 

o --u o'"1To 

D 

2 6 tOt 4 18 2.3 27 1 5 9 13 17 21 25 29 :2 6 10 14 

Date 

-100-
FIGURE 5.13 A COMPARISON OF CHLOROPHYLL g PRODUCTIVITY IN N 

SUFFICIENT AND DEFICIENT CONTINUOUS CULTURES 

13 ,.... 

>, 

0 12 'tI 

"- 11 

"-0 10 

E 

'-" 9 >, 

+' 

-; 8 

::; 

0 7 :::J 

'tI 

0 6 ~ 

CI. 5 

.!:! 

.s:: 4 

U 

3 

2 

a 

0.1 a 0.2 0.44 0.71 

Dilution Rote(1 / doy) 

FIGURE 5.14 A COMPARISON OF BIOMASS PRODUCTIVITY IN N SUFFICIENT AND DEFICIENT CONTINUOUS CULTURES 

.300 

'"' >,

0 250 'tI 

"-

"-0 

E .....,. ,200 ~ 

~ .. 

0 

:::J 

'tI 

0 150 ~ 

CI. 

1/1 

III 

0 

E 100 

.9 

tIl 

50 

o 

0.18 0.2 0.44 0.71 

Dilution Rote(l/doy) 

-101-
FIGURE 5.15 A COMPARISON OF LIPID PRODUCTIVITY IN N SUFFICIENT 

AND DEFICIENT CONTINUOUS CULTURES 

180 

170 

160 

150 

140 

1.30 ........ 

>. 

c 120 'tI 

"'- 110 "-C> 100 E 

'-J 90 "" ... 

'> 

;; 80 u 

~ 70 'tJ 

0 

'" 60 Il. 

'tJ 50 a. 

oJ 40 

30 

20 

10 

0 

0.18 0.2 0.44 0.71 

Dilution Rote(l / d<Jy) 

-102-
tures, however increased in one culture operated at the highest 

dilution rate (0.71/day). This result, while appearing anomalous, 

may in fact be an indication of a unique physiological state. 

Evidence supporting this view is the significantly lower lipid 

content this culture possessed as compared with the other N limited cultures (13 vs 25 %). Additionally another N limited culture in a separate experiment displayed a biomass productivity of 

290 mg/l/d, with a small Chlorophyll a productivity (3.2) and 

again a very low lipid content (9 %) (data not shown). 

It can be argued that nitrogen limitation may aid in the reduction of accessory pigments and thus increase the light utilization efficiency for the entire culture by a decrease in the 

extinction coefficient. This of course would have to be coupled 

with no significant reduction in enzyme levels. The fact that 

lipid productivity is substantially less in these two cultures is 

significant and indicates a metabolic adjustment which allows a 

higher carbon fixation rate. These two cases are by no means sufficient to draw any general conclusions from, however do suggest 

a worthwhile area of future investigation. 

Finally, lipid productivity decreased in all cultures relative to 

the nitrogen sufficient case as shown in Figure 5.15. The maximum productivity for both the sufficient and deficient cases was 

coincident with maximum biomass productivity and was only 50 

mg/l/day. One point of uncertainty is the lower lipid contents 

achieved in these cultures(ca. 25%) as compared with those in 

Table 5.4 (ca. 40%). 

5.5.5 Nitrogen Limited Growth vs. Cell Density 

In order to test the idea that cell density may affect the 

nitrogen limited productivity of lipid (by affecting the lipid 

content), cultures were operated at the same dilution rate but 

with varying nitrogen supply rates (feed nitrogen concentrations). In theory, this experimental design allows cell density 

to be an independent variable, with the nitrogen quota being the 

same in all cultures. Figure 5.16 is plots biomass and lipid 

productivity for three nitrogen limited cultures (AFDW < 420 ppm) 

and one nitrogen sufficient culture (AFDW = 570 ppm). The first 

three biomass productivity points should, by definition, fallon 

a straight line. The observation that the final point also is 

predicted by the same line(ie. u = 0.5/day) is an indicator of 

experimental consistency. The curve for lipid productivity is 

also linear, therefore indicating little, if any, change in lipid 

content as a function of cell density. Thus nitrogen limitation 

appears to decrease lipid productivity relative to nitrogen sufficient and light limited cultures operated at the same dilution 

rate. 

5.5.6 continuous to Batch Induction of Lipid 

The process alternative for a microalgal lipid production which 

we favour would use a first stage pond, operated at maximum biomass productivity, followed by a second stage for lipid induction. 

-103-
FIGURE 5.16 BIOMASS AND LIPID PRODUCTIVITY IN N LIMITED CONTINUOUS 

CULTURES AT DoS/day DILUTION RATE AS A FUNCTION OF STANDING BIOMASS 

-, --I 

320 

300 

2S0 

0 

260 

240 

..... 220 >. 

a 

'tI 200 0 '" 

"-0> 180 

E 

'-' HlO >. 

:! 

> 

~ 140 u 

:J 

'tI 120 0 

l.. a ~ 100 / aD + 

60 

40 0 

20 

0 

+~ 

0 200 400 600 

Culture DensitylrTl9!I) 

-104-
The first stage in principle should be operated at a point as 

close to nitrogen limited growth as possible. This may involve 

either (semi)batch or continuous cultures. It is therefore of 

interest to study the batch induction kinetics following a preadaptation to nitrogen limited continuous culture and to compare 

these to the prior results with lipid induction and productivity 

in batch cultures. This was done for eight separate continuous 

cultures, representative results from two of these are presented 

here. 

Biomass and lipid yield are shown as a function of time for two 

cultures experiencing batch growth following nitrogen limited 

culture (Figures 5.17 and 5.18). The top curves represent a 

lower dilution rate and hence a higher cell density in the continuous cultures. The conditions of preadaptation were 0.17 and 

0.69/day (dilution rate) and calculated nitrogen contents of 7.5 

and 5.1% respectively. 

In all cultures studied thus far, a period of significantly 

reduced lipid production occurs following batch induction as evidenced by the near zero slope for the two days after induction 

(Figure 5.18). Steady state lipid productivities were 50 and 36 

mg/l/day and 31 and 22 mg/l/day for the following three day 

period. Biomass productivity was similar to that obtained for 

the nitrogen limited cultures and roughly the same for both the 

high and low dilution rate cases. The constant rate however is 

impressive as towards the final day of the experiment cell 

nitrogen should have been close to its minimum. 

The reason for the period of essentially zero lipid 

productivity following preadaptation to nitrogen limitation is 

unclear. It may be that the cells ability to adapt to the changing nutrient condition is impaired by the previous period of 

nitrogen limited growth by the reduction/elimination of some precursor. Regardless of the underlying physiological principle, these 

results indicate that the preadaptation condition can not be 

overlooked in process development studies. 

5.5.6 Discussion 

The results from the continuous culture studies indicated that 

nitrogen limitation does not result in an increase in lipid productivity. Since apparently contradictory results were obtained 

concerning N deficient lipid content as a function of cell density, any conclusion must await future analysis of nitrogen content. Light limited cultures had optimum lipid and biomass productivities at detention times between 2.5 and 4 days and were 

higher than nitrogen limited cultures. In two cases nitrogen limitation resulted in higher biomass productivities and this was . coupled with a significant reduction in lipid synthesis. Lastly 

it was shown that very low rates'of lipid induction were observed 

following nitrogen limited growth. 

-105-
FIGURE 5.17 BIOMASS YIELD VS. TIME IN BATCH CULTURE FOLLOWING 

PREADAPTATION TO NITROGEN LIMITATION IN CONTINUOUS CULTURES 

(Culture was shifted from continuous to batch mode on day 14) 

2 

1.8 

16 

'"' 1.4 

"-0> 1.2 ........ 

:;: 

Cl 

It.. 

<! 

~D 

o 

o.S 

0.6 

A.'" o 

0.2 

a 

13 15 17 

Days 

FIGURE 5.18 LIPID YIELD VS. TIME IN BATCH CULTURE FOLLOWING 

PREADAPTATION TO NITROGEN LIMITATION IN CONTINUOUS CULTURES 

(Culture was shifted from continuous to batch mode on day 14) 

400 

Joo 

200 

100 

o 

13 15 17 

Days 

-106-
5.6 SUMMARY AND CONCLUSIONS 

Table 5.5 summarizes the lipid productivity results as a function 

of the variety of culture environments tested. The general conclusion can be made that lipid productivity was greater under all 

environmental conditions in batch rather than continuous cultures. The maximum lipid productivity, for all conditions, 

occurred in batch cultures experiencing a transient increase in 

their light supply rate during nitrogen deficiency. A more 

detailed discussion of these results will be presented in the 

technical publications. 

Table 5.5. Comparison of Maximum Observed Lipid Productivities 

(mg/ljday) for a Variety of Growth Conditions. 

Condition 

Nitrogen 

Sufficient 

Nitrogen 

Deficient 

Light 

Shift 

continuous 

to Batch 

-107-

Batch Continuous 

100 90 

150 50 

180 

20-30 
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-116-
APPENDIX. MATERIALS AND METHODS 

I.1 strains of Microalgae 

All strains referred to in this report have been obtained from 

Dr. Bill Barclay as part of the SERI culture collection. Further 

information concerning each can be obtained through the SERI culture collection catalogue (Barclay,1986). 

I.2 Dry Weights 

Dry weights were determined by centrifuging a volume of culture corresponding to 10 mg of ash free dry weight for 20 minute 

at 15000 rpm(some pellets required longer times). Supernatents 

were decanted and the tubes were rinsed with distilled water in 

order to remove residual drops of media(being careful to avoid the 

pellet). The pellets were then removed by using several small 

washes of distilled water(1-3 mls each) into preashed, preweighed 

aluminum drying boats. Water was evaporated from the boats over a 

hot plate(60-70 C) for about 20 minutes. The boats were 

subsequently dried in a forced air convection oven at 103 C for 

two hours, weighed and then ashed in a muffle furnace at 505 C for 

30 minutes and weighed again. The ash free dry weight represented 

the difference between the dried and ashed weights. 

The average error of duplicate dry weight determinations was 

below 2%. For 54 samples randomly chosen, only ten samples 

exceeded 1 % variance arid only three had error between 10 and 20%. 

I.3 Protein Assays 

Proteins were assyed by the Folin Lowry Method ( 

1971). The procedure involved cent:ifuging 10 ml samples of cultures, resuspending the pellet 1n 5 mls of distilled water and 

digesting 4.5 ml of that volume with 0.5 ml IN NaOH in a boiling 

water bath for 1 hour. This digestion time was found to give the 

maximum protein content in a time course experiment. After cooling, two aliquots of the digestion mixture were diluted with 0.5 

ml 1N NaOH. Alkaline CuS04 solution and Folin reagents were added 

sequentially and this mixture was read at 650 nm on a Bausch and 

Lomb spectrophotometer. Protein content was determined by comparison with Bovine albumin standard (Sigma Chemical). 

I.4 Carbohydrates 

Carbohydrates were determined by the phenol-sulfuric acid 

method (Herbert,1971). The procedure involved centrifuging 10 mls 

of culture, resuspending the pellet in 5 mls of distilled water, 

and digesting 0.5 mls of that in 4.5 mls of 1.1 N HCI for one hour 

at 100 C. Sample volumes were removed from the digestion mixture 

and diluted into distilled water to 1 mI. One ml of 5 % phenol 

solution was added and the test tube was mixed on a vortex mixer. 

-117-
Immediately following this 5 mls of sulfuric acid were added and 

the tube mixed again. Samples were left at room temperature for 20 

minutes to develop color and were then read on a "Spect 20" at 

488 nm. Carbohydrate content was determined by comparison against 

a glucose standard (Sigma Chemical). 

I.5 Chlorophyll a 

One to ten mls of culture were filtered under vacuum onto a 

4.7 cm glass fiber filter. The retained cells and filter paper 

were suspended in 10 mls of methanol and sonicated for 30 seconds. 

This mixture was then placed in a 65 C water bath for 3 minutes, 

followed by one minute in an ice bath. The material was filtered 

through a 2.4 cm glass fiber filter and the filtrate was collected 

and read on a Band L spectrophotometer against a MeOH blank at 

665 nm. Chlorophyll a concentration was then determined using an 

extinction coefficient of 77.6 abs/g chI a. The assay was carried 

out in dim light and extracts were kept in the dark until being 

read« 10 minutes). 

I.6 Lipids 

Lipid analysis was carried out along the lines as described in 

Tornabene and Ben-Amotz(1983). Forty to fifty mg's of cells were 

harvested from culture by centrifuging at 4000 RPM for 20 minutes. 

The pellets were then resuspended in 10 mls of distilled water. 

These samples were than frozen until ready for analysis. Upon analysis, they were thawed and 25 mls of MeOH was added, followed by 

12.5 mls of CHC13. The samples were swirled a few times and 

allowed to sit overnight. The following day the samples were centrifuged at 1000 RPM for 10-15 minutes. The supernatent was transferred to 250 ml separatory funnels trying to transfer as little 

of the pellet as possible. A second extraction of the cell pellet 

was performed for 3 hours. This was then centrifuged for 15 minutes at 1000 RPM and transferred to the separatory funnels. The 

10:5:4 MeOH:CHC13:H20 solvent ratio was then adjusted to 10:10:9 

by adding CHC13 and H20, and the mixtures were swirled. Phase separation was allowed to occur overnight. The lower CHCl3 fraction, 

containing lipid, was then drawn off into a round bottom flask. 

Additional CHCl3 was added to the separatory funnels to wash the 

partitioning phase. Two hours were allowed for phase separation 

and the CHCl3 phase was again drawn off and into the round bottom 

flask. The CHCl3 phases were then concentrated by rotoevap to 

about 1-2 mls. The concentrate was transferred to preweighed 

weighing flasks using CHC13 and evaporated to dryness under a 

stream of Nitrogen. The flasks were stoppered immediately and 

transferred to a dessicator. The stoppers were then cocked 

slightly and the dessicator was aspirated for 15 minutes followed 

by vacuum pump for another 15 minutes. The vacuum was released by 

pumping in Nitrogen. At this point the weighing flasks were sealed 

and weighed. The difference between the dried weight and the original preweighed flask was due to lipid. Following weighing samples 

were resuspended in CHCl3 and stored in the freezer. 

-118-
I.7 CHN Analysis 

Analysis of carbon, hydrogen, and nitrogen was 

Model 240 Perkin-Elmer CHN 

1.8 Cell Counts 

performed on a 

Analyzer. 

A 1 ml sample is withrawn from the reactor and exactly 10 

drops from a long neck Pasteur pipet of Lugols solution are ~dded 

to immobilize the algae. These samples are then either read ~mmediately or stored in the refrigerator until analyzed. Counts were 

performed using a Brightline Hemacytometer and a Officine Galileo 

Microscope at 520X magnification. Somewhere between 500 to 1000 

cells were counted for each measurement. The major source of variability in the measurement comes from the slide preparation. For 

this reason at least four individual preps were performed, typically counting 200 cells per field. Each field contained 1 x 10-4 

mls of sample - cell concentrations were corrected for the addition of the Lugols solution. 

1.9 Protocol for Lipid Induction Studies 

Batch Cultures:The batch lipid induction studies were carried 

out in 1 liter Roux bottles, innoculated with previously adapted 

batch grown cultures to a final cell density of around 50 mg/l. 

The initial nitrate concentration was dependent upon the experiment, the amount being calculated by consideratiqn of the desired 

cell concentration when deficiency would begin ( @ roughly 8 % 

nitrogen). All experiments were conducted using a 1 % c02/Air gas 

stream with gas bubblers as spargers. All cultures had 5 roM bicarbonate alkalinity and were grown in either MSW or MSW/2(half 

strength) media (see Table A.1). Culture bottles were illuminated 

from either one or two sides with 40 W Vitalite Fluorescent lamps. 

The intensity at the reactor surface was 250 E/m2/s. The exposed 

surface was carefully controlled by keeping the cultures planar 

surface perpendicular to the light beam and by covering all other 

surfaces (sides and top) with black cloth or electrical tape. 

These precautions are necessary if calculations of energetic efficiency are to be carried out. Culture temperature fluctuated 

between 26 - 29 °c with the light/dark cycle. 

Daily measurements of the culture included pH, 00, dry weight, 

and Chlorophyll a(in later experiments). Dry weight samples were 

taken by sampling directly from the culture bottle using a sterile 

pipet. Lipid, protein, carbohydrate, and CHN were sampled for 

after the onset of nitrogen deficiency. 

continuous Cultures: Nitrogen limited continuous cultures were 

carried out in 0.8 1 working volume reactors as shown in figure 

A.2. Environmental conditions were identical to that used in the 

batch cultures; similarily the culture flasks were taped with 

black tape to allow an accurate calculation of the light energy 

recieved by the culture. Dilution was carried out only during the 

lighted portion of the day(shifted by 1/2 hour). Effluent was 

collected into darkened containers kept in an ice bath. All 

-119-
samples were taken from these containers- the accuracy of which 

was verified by sampling both from the effluent and directly from 

the culture vessel for dry weight and chlorophyll a( see figure 

A.3). Measurements of pH, effluent volume and dry weight were 

recorded daily, at steady state, additional samples of chlorophyll 

a, CHN, and lipid were taken. 

I.10 system Design for Species Competition Studies 

The system design for the planned scale down experiments is 

shown diagrammatically in figure A.1. Dotted lines indicate transfer of signals to and from the Data Aquisition System (DAS). Only 

one reactor is shown for clarity - the system as designed operates 

with four reactors in parallel (for reactor design see Figure 

a.2). All four reactors are immersed in a temperature bath which 

is controlled by a combination of a cooling loop and immersion 

heater. Power to the immersion heater (200W) is from a power output board that is interfaced with the DAS. In this way temperature 

can be controlled by turning power to the heater on or off. Temperature is sensed using a type J thermocouple immersed within the 

bath. Cultures are sparged with a mixture of C02 and air, with the 

capability of diluting/substituting the air for N2 or 02' Gas Flow 

and composition are regulated by Mass Flow Contollers (Tylan 

Corp.). Effluent gas from each culture is measured by a mass flow 

meter (Tylan Corp.). Following this the gas stream is split by 

adjustable rotameters such that roughly 2/3 of it goes to an 

Infrared C02 Analyzer (IRGA) and the remainder to a paramagnetic 

Oxygen Analyzer (POA). The concentration ranges for both analyzers 

must be calibrated every 12 hours. 

Culture pH is monitored by routing probe signals through a 

high impedence multiplexer(custom design) and these signals are 

then sent to the DAS. Probes are calibrated, using a BASIC program 

called CALPROBE, which operates very much like microprocessor 

based pH meters. In experiments conducted over a period of one 

month, recalibration of the pH probes on a 2-3 day interval was 

adequate to maintain accuracy. The data aquisition system is a 

System 520 from Kiethley with the following features: 16 single 

ended low level A/D, 32 single ended high level A/D with cold 

junction compensation for thermocouple use, 5 channels of 0-5 VD 

D/Af 32 channels of Digital I/O, and 16 channels of switched controlled 120 VAC output. 

I.11 Protocols for Mixed Cultures Experiments: 

Fluctating Temperature and Oxygen Experiment: Four cultures(131-134) were inoculated at roughly equivalent cell densities of Chlorella B.L., Cyclotella, and Chaetoceros (Hawaiin 

strain) to give a combined density of 100 ppm. Dry weight and cell 

counts were followed for a period of 40 days. A summary of the 

experimental conditions is given in Table A.2. All cultures were 

expoosed to a 14/10 hour light/dark cycle. For cultures 132-134, 

the cultures were sparged with pure oxygen for eight hours during 

the "afternoon". Cultures 133 and 134 were subjected to a temperature cycle that varied between 20C during the dark period and 32 C 

-120-
d,uring the light period. The time constant for these temperature 

changes was roughly one hour. 

The light intensity incident on culture 134. was increased by 

shining a 150 W flood lamp mounted approximately 8 inches from the 

culture. A one inch thick water filter was placed in between for 

heat absorption. All cultures recieved 550 E/m2/s on one side 

from VHO Sylvania "Daylight" flourescent lamps. The cultures were 

diluted during the illuminated portion of the day (shifted 1/2 

hour) at a rate of .67 day-1. The media used was MSW/2 with 5mM 

alkalinity as bicarbonate. Dry weight samples, as well as pH and 

OD's were taken daily and cell counts every other day. 

pH Fluctuation Experiment: In this experiment the temperature 

was controlled between 28-29.5 C, the light intensity was 550 

E/m2s and air levels of 02 were used for sparging. Equal cell 

densities of Chlorella, Chaetoceros, Ankistrodesmus, and 

Cyclotella were innoculated into each reactor(221-224) at a total 

concentration of ca. 100 ppm. Sampling schedules were similar as 

to that described. for the fluctuating' temperature and oxygen 

experiment. The control of a pH setpoint was better than .05 pH 

units. pH was measured with either a "pencil" thin combination 

electrode (Fisher) or a larger fermentation grade electrode from 

Phoenix Electrode. A special high impediance op amp circuit was 

constructed similar in design to that described by Terry and Hock 

(1985) which has the capability of recieving ten input signals. pH 

control was either by alkalinity or pC02 adjustments. In the case 

of alkalinity, either 2N Na2C03 or 1N HCI were dosed to the 

culture by peristaltic pumps (Masterflex) • In the case of C02' 

changes in the gas concentration were made by a 0-100sccm mass 

flow controller(Tylan Corp.). Specifically a PO controller was 

used to adjust voltage signals to the desired setpoint. All cultures utilizing alkalinity control were sparged with .35% C02/air 

mixture. The media fed to the low pH (#221) and fluctuating alkalinity (#222) cultures had an alkalinity of 1mM NaHC030 The high pH 

(#223) and fluctuating PC02 (#224) cultures were fed MSW/2 with 10 

roM alkalinity. 

Dilution Rate and Sparger Design: Methodology and experimental 

conditions were similar to the previously discussed experiments 

except for the following differences. Cultures 250-252 were run at 

different dilution rates ranging from .33 to 1.22 per day. Culture 

253 was operated at a dilution rate of .73 and was sparged with a 

bubbler rather than the commonly used( as in all previous experiments) glass fritted cylinder (course grade). A summary of conditions (with standrad deviations) is given in Table A.4. 

Table A.4. Summary of Conditions for Dilution Rate Experiment 

Culture 

250 

251 

252 

253 

Air 

Air 

Air 

Air 

Temperature Ie Elms) 

28-29.5 

28-29.5 

28-29.5 

28-29.5 

-121-

550 

550 

550 

550 

pH ueday-11. 

7.63(.10) 1.23(.05) 

7.65(.14) 0.83(.01) 

7.82(.14) 0.33(.03) 

7.78(.13) 0.73(.02) 
IBM 

PC 

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