<%BANNER%>

Dynamic Modeling and Validation of Growth of Synechococcus BG 0011 Using Laboratory Scale Studies

Permanent Link: http://ufdc.ufl.edu/UFE0045625/00001

Material Information

Title: Dynamic Modeling and Validation of Growth of Synechococcus BG 0011 Using Laboratory Scale Studies
Physical Description: 1 online resource (52 p.)
Language: english
Creator: Murali, Raghavendran
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2013

Subjects

Subjects / Keywords: algae -- cyanobacteria -- modeling
Chemical Engineering -- Dissertations, Academic -- UF
Genre: Chemical Engineering thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Thereis no doubt that mankind’s continued reliance on fossil fuels has hadsignificant effects on almost everything from our quality of life to, mostimportantly, the global climate scenario. Fossil fuels, being non-renewable,are expected to run out in a matter of years, 40 in case of oil if we areconservative. Most studies report that the world has reached its peak in oilproduction and is entering a terminal decline. Furthermore, the use of fossilfuels has resulted in an enormous increase in anthropogenic carbon dioxideemissions, which in turn worsens the situation by contributing to climatechange. The need for a shift of focus to renewable sources of fuel has beenhigher than ever before. This project is aimed at taking those first few stepstowards the same. The algal strain being studied in this work can (1) fix itsown nitrogen (2) produce a highly viscous polymer that can be downstreamprocessed into a useful derivative (3) grow in a range of environmentalconditions. Synechococcus BG0011 is a cyanobacteria isolated from the FloridaKeys that can fix its own nitrogen. This project focuses on the growth of thestrain, effect of change in conditions on growth and primarily on modeling thegrowth based on observed experimental data. Additionally, the model is used tovalidate a few characteristic parameters and finally a brief sensitivityanalysis is carried out to study the various influences of the parameterscalculated.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Raghavendran Murali.
Thesis: Thesis (M.S.)--University of Florida, 2013.
Local: Adviser: Svoronos, Spyros A.
Local: Co-adviser: Pullammanappallil, P C.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2013
System ID: UFE0045625:00001

Permanent Link: http://ufdc.ufl.edu/UFE0045625/00001

Material Information

Title: Dynamic Modeling and Validation of Growth of Synechococcus BG 0011 Using Laboratory Scale Studies
Physical Description: 1 online resource (52 p.)
Language: english
Creator: Murali, Raghavendran
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2013

Subjects

Subjects / Keywords: algae -- cyanobacteria -- modeling
Chemical Engineering -- Dissertations, Academic -- UF
Genre: Chemical Engineering thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Thereis no doubt that mankind’s continued reliance on fossil fuels has hadsignificant effects on almost everything from our quality of life to, mostimportantly, the global climate scenario. Fossil fuels, being non-renewable,are expected to run out in a matter of years, 40 in case of oil if we areconservative. Most studies report that the world has reached its peak in oilproduction and is entering a terminal decline. Furthermore, the use of fossilfuels has resulted in an enormous increase in anthropogenic carbon dioxideemissions, which in turn worsens the situation by contributing to climatechange. The need for a shift of focus to renewable sources of fuel has beenhigher than ever before. This project is aimed at taking those first few stepstowards the same. The algal strain being studied in this work can (1) fix itsown nitrogen (2) produce a highly viscous polymer that can be downstreamprocessed into a useful derivative (3) grow in a range of environmentalconditions. Synechococcus BG0011 is a cyanobacteria isolated from the FloridaKeys that can fix its own nitrogen. This project focuses on the growth of thestrain, effect of change in conditions on growth and primarily on modeling thegrowth based on observed experimental data. Additionally, the model is used tovalidate a few characteristic parameters and finally a brief sensitivityanalysis is carried out to study the various influences of the parameterscalculated.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Raghavendran Murali.
Thesis: Thesis (M.S.)--University of Florida, 2013.
Local: Adviser: Svoronos, Spyros A.
Local: Co-adviser: Pullammanappallil, P C.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2013
System ID: UFE0045625:00001


This item has the following downloads:


Full Text

PAGE 1

1 DYNAMIC MODELING AND VALIDATION OF GROWTH OF S ynechococcus BG0011 USING LAB ORATORY SCALE STUDIES By RAGHAVENDRAN MURALI A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQU IREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2013

PAGE 2

2 2013 Raghavendran Murali

PAGE 3

3 To my Mom and Dad

PAGE 4

4 ACKNOWLEDG E MENTS I would like to first thank my parents for their unwavering suppo rt of my education without them and I owe them everything I have accomplished until now. I would like to thank all the members of my supervisory committee, Dr. Spyros Svoro nos, Dr. Pratap Pullammanapallil, Dr, Edward Phlips, for the unconditional support and guidance during the entire period. I would also I would also like to thank Dr. Edward Phlips for providing the algal culture for the experiments, without which this wou to thank Ms. Bailey Trump and all members of the Fisheries Department Lab for providing us with the chemicals to prepare the culture media and allowing us to use their equipment. I would like to acknowle dge Brian Wolfson, for his immense help in building the reactors and the whole setup, Samriddhi Buxy, for always pointing us in the right direction whenever we needed it, Cesar Moreira, for his help in almost everything, and Qilong Ma, Longhua Piao and Ced ric Ferrus for their assistance with laboratory work.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGEMENTS ................................ ................................ ......................... 4 LIST OF TABLES ................................ ................................ ................................ ...... 7 LIST OF FIGURES ................................ ................................ ................................ .... 8 ABS TRACT ................................ ................................ ................................ ............... 9 CHAPTER 1 INTRODUCTION ................................ ................................ .............................. 11 1.1 Cyanobacteria ................................ ................................ ............................. 11 ................................ ................................ ............ 12 1.1.2 What are Cyanobacteria? ................................ ................................ .. 12 1.1.3 Diversity of Cyanobacteria ................................ ................................ 13 1.1.3.1 Geothermal springs ................................ ................................ .. 14 1.1.3.2 Cyanobacteria in wa ter bodies ................................ ................. 15 1.1.3.3 Cyanobacteria in deserts ................................ ......................... 16 1.1.3.4 Cyanobacteria in extreme cold ................................ ................. 17 1.1.3.5 Cyanobacteria in urban environments ................................ ...... 19 1.2 Emiss ions and Fossil Fuels ................................ ................................ ........ 21 1.2.1 A Little Bit of History ................................ ................................ .......... 21 1.2.2 Emissions and its effects ................................ ................................ ... 23 1.2.3 End of an Era ................................ ................................ .................... 24 1.3 Enter Cyanobacteria ................................ ................................ ................... 27 1.3.1 Polysaccharide Production ................................ ................................ 29 1.3.2 Scope of Work ................................ ................................ ................... 30 2 MATERIALS AND METHODS ................................ ................................ .......... 3 1 2.1 Synechococcus BG0011 ................................ ................................ ............. 31 2.2 Process Description ................................ ................................ .................... 31 2.2.1 Stages of growth ................................ ................................ ............... 32 2.2.2 Reactor setup ................................ ................................ .................... 32 2.3 Sampling ................................ ................................ ................................ ..... 35 2.4 Modeling ................................ ................................ ................................ ..... 36 2.4.1 Characteristic equations ................................ ................................ .... 36 2.4.2 Model Objectives ................................ ................................ ............... 37 3 RESULTS ................................ ................................ ................................ ......... 38 3.1 Model Output ................................ ................................ .............................. 39 3.2 Comparison of Strain Characteristics ................................ .......................... 43

PAGE 6

6 4 DISCUSSIONS ................................ ................................ ................................ 45 4.1 Model Performance ................................ ................................ ..................... 45 4.2 Future Work ................................ ................................ ................................ 45 APPENDIX A MODEL CODE ................................ ................................ ................................ .. 47 LIST OF REFERENCES ................................ ................................ ......................... 50 BIOGRAPHICAL SKETCH ................................ ................................ ...................... 52

PAGE 7

7 LIST OF TABLES Table page 3 1 Comparison of strain charateristics ................................ .............................. 44

PAGE 8

8 LIST OF FIGURES Figure page 1 1 Electron mi crograph of a section through Anabaena revealing the photosynthetic membranes and numerou s ribosomes. ................................ 13 1 2 Endolithic cyanobacteria in a sandstone rock from the McMurdo Dry Valleys ................................ ................................ ................................ .......... 19 1 3 Plot showing the relative time left for complete exhaustion of fossil fuels ..... 25 1 4 Total Energy Consumption with split up o f Renew able Sources as of 2010 26 1 5 A Nomarski contrast photomicrograph of a sheathed Chroococcus sp. (1000x) ................................ ................................ ................................ ......... 29 2 1 Picture showing one of the reactors and the control ................................ ..... 34 3 1 Experimental data used in optimization of model ................................ ......... 39 3 2 First run with estimates for parameter values. The dots represent the experimental curve which is what we are aiming at. The black plot is the model output for biomass growth in terms of absorbance measurements. Yellow line corresponds to the substrate consumption rate. ......................... 40 3 3 Second run of model with minimization of error resulting in a good fit with experimental observations. ................................ ................................ ........... 41 3 4 Third model run with Ysx = 4.67 ................................ ................................ ... 42

PAGE 9

9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science DYNAMIC MODELING AND VALIDATI ON OF GROWTH OF Synechococcus BG0011 USING LABORATORY SCALE STUDIES By Raghavendran Murali May 2013 Chair: Spyros Svoronos Cochair: Pratap Pullammanapalil Major: Chemical Engineering as had significant effects on almost everyth ing from our quality of life to, most importantly, the global climate scenario Fossil fuels, being non renewable, are expected to run out in a matter of years, 40 in case of oil if we are conservative. Most stud ies report that the world has reached its peak in oil production and is entering a terminal decline. Furthermore, the use of fossil fuels has resulted in an enormous increase in anthropogenic carbon dioxide emissions, which in turn worsens the situation by contributing to climate change. The need for a shift of focus to renewable sources of fuel has been higher than ever before. This project is aimed at taking those first few steps towards the same. The algal strain being studied in this work can (1) fix it s own nitr ogen (2) produce a highly viscous polymer that can be downstream processed into a useful derivative (3) grow in a range of environmental conditions. Synechococcus BG0011 is a cyanobacteria isolated from the Florida Keys that can fix its own nitro gen. This project focuses on the growth of the strain, effect of change in conditions on growth and primarily on modeling the growth based on observed experimental data.

PAGE 10

10 Additionally, the model is used to validate a few characteristic parameters and finall y a brief sensitivity analysis is carried out to study the various influences of the parameters calculated.

PAGE 11

11 CHAPTER 1 INTRODUCTION 1.1 Cyanobacteria Some say that the cyanobacteria are one of the oldest inhabitants of Earth stretching beyond even scienti fic study. Many still believe that this is an open question. Geologists and geochemists all agree that cyanobacteria have had a long evolutionary history. There have been findings of ancient rocks dating back 1.5 billion years that have some tracks of coup the modern day cyanobacteria (Benson et al ., 2007). Some even go so far as to through photosynthesis (Haselkorn, 2009). There might be a grain of truth in that as recent genomic analysis, in particular the analysis of sequences of proteins that make up the photosynthetic apparatus, has established that a cyanobacterium provided the ancestor of the chloroplast. Cyanob acteria are arguably the most successful group of microorganisms on earth. They are the most genetically diverse; they occupy a broad range of habitats across all latitudes, widespread in freshwater, marine and terrestrial ecosystems, and they are found in the most extreme niches such as hot springs, salt works, and hypersaline bays. Photoautotrophic, oxygen producing cyanobacteria created the conditions in the planet's early atmosphere that directed the evolution of aerobic metabolism and eukarotic photosy nthesis. Cyanobacteria fulfill vital ecological functions in the world's oceans, being important contributors to global carbon and nitrogen budgets. Stewart and Falconer ( 1990 ) Cyanobacteria can be found in almost every te rrestrial and aquatic habitat; oceans, freshwater bodies, rocks, soil they all have cyanobacteria in some form or the

PAGE 12

12 other. Most commonly seen cyanobacteri a are the aquatic ones, known for their highly visible and extensive blue green blooms in both freshwater and marine environments 1.1 .1 Cyanobacteria are also called blue green bacteria, blue green algae and Cyanophyta. In the olden days they were classified along with green algae, red algae and brown algae as photos ynthetic microbes. It was generally agreed upon that all of these carried out the process of green plant photosynthesis, fixing Carbon Dioxide and generating Oxygen from water. It was only in the 1960s that people started taking a second look at the classification of cyanobacteria. As Robert Haselkorn p uts it: But in the 1960s it became apparent, from new biochemical evidence, that the blue green algae, unlike the other algae, are really bacteria: they are sensitive to penicillin because of their peptidoglycan cell walls; they have bacterial sized riboso mes sensitive to the usual antibiotics; and they do not contain organelles such as chloroplasts and mitochondria. (Haselkorn, 2009) The major outcome of this redefinition was that cyanobacteria entered the world of microbiology from the realm of botany. 1 1. 2 What are Cyanobacteria? Cyanobacteria are photosynthetic prokaryotes that have the ability to synthesize chlorophyll. a Typically water is the electron dono r during photosynthesis, resulting in the evolution of Oxygen. Until recently cyanobacteria hav e also been characterized by their ability to form the phycobilin pigment, phycocyanin. It is the high concentration of this pigment under certain conditions which leads to the bluish color of the organisms giving rise to the name blue green algae. However increasing scientific evidence suggests that some prokaryotes that do not possess phycobilins form some type of chlorophyll and are closely related to organisms wit h phycocyanin (Whitton and Potts,

PAGE 13

13 2012). Due to some shortcoming s in molecular evidence th ese organisms are also classified as members of cyanobacteria in a broad sense. Figure 1 1 Electron micrograph of a section through Anabaena revealing the photosynthetic membranes and numerous ribosomes (Photo courtesy of Haselkorn, 2009) 1. 1. 3 Diver sity of Cyanobacteria As briefly touched upon before, cyanobacteria are found in almost all types of habitat, both terrestrial and aquatic, showing in part their resilient nature. It is no surprise then that s cientists have been able to recover over 35 str ains of cyanobacte ria from the coldest continent on earth, the Antarctica The physiological characteristics of

PAGE 14

14 the isolated cyanoba cteria strains showed that n itrogen fixation, n itrate uptake, n itrate reduction, a mmonium uptake and photosynthesis was unaf fected at low temperature (5 degrees C) which indicated low temperature adaptation for Antarctic cyanobacteria (Singh and Elster, 2007 ). Interestingly t his phenomenon was not evident in different strains of tropical origi n. Reports suggest that t he optimum temperature for n itrogen fixation for the different Antarctic cyanobacterial strains was in the range of 15 25 degrees C The low endergonic activation energy exhibited overall reinforced the notion that cyanobacteria were very much adapted to the Antarct ic ecosystem. It is interesting to take a look at the different terrains and climatic conditions where cyanobacteria thrive all around the world. 1. 1. 3.1 Geothermal springs heat rise up to the ground. Many geothermal springs emit water near the boiling point. Reports of microorganisms positioning themselves on the outflow channels of geothermal springs according to temperature gradients have established that 73 74C is the maximu m temperature enabling development of cyanobacteria (Ward et al ., 2012). Cyanobacteria belonging to the genus Synechococcus (Thermosynechococcus), are the most thermophilic. A striking anomaly suggesting geographically restricted distributions of thermophi lic cyanobacteria is that all forms of thermophilic Synechococcus appear to be absent from Icelandic hot springs, although numerous springs exist there that appear to be chemically suitable. Thermophilic Synechococcus have been found to occur in New Zealan d and European springs, but these include only forms that grow up to a maximum temperature of 58 62 degrees C. Forms of Synechococcus that grow in

PAGE 15

15 nature up to limits of 73 74 degrees C in the western contiguous United States and south into Central and S outh America, are absent in the geographic regions mentioned above, although they extend into eastern Asia and China (Ward et al ., 2012) It is fascinating to note that two factors that do not play a significant role in the distribution of thermophilic cya nobacteria are latitude and day leng th since many cyanobacteria resembling those of lower latitude springs have been found to occur in the hot springs of the east coast of Greenland at 70 71N (Ward et al ., 2012). In winter, t hese springs experien ce compl ete darkness while summer sees constant daylight for the entire region. 1. 1. 3.2 Cyanobacteria in water bodies A great and sometimes dominant portion of phototrophic biomass and primary biomass production in ponds, streams lakes at high latitudes and wetla nds is comprised of cyanobacteria A striking dissimilarity is observed in the polar seas, where the cyanobacteria are generally sparse in population or completely absent with the exception of some regions. Mat for ming cyanobacteria are found to be pervasi ve in polar aquatic ecosystems including lakes, ponds, streams and seeps. Tolerance to continuous low temperature, freeze thaw cycles, high and low irradiances, des i c cation and UV exposure are characteristic feature that make them suitable for life in the extreme polar environment (Vincent and Quesada, 2012). E xplorers who noticed unusual biological communities growi ng on or under neath the ice in Polar Regions provided the very first reports of cyanobacteria in those areas (Vincent and Quesada, 2012). Durin g an expedition to explore the McMurdo Dry Valleys, Antarctica in 1909, Griffith Taylor wrote:

PAGE 16

16 We came across a lake two miles long. It was of course frozen, but beneath the ice the water was very deep a nd we c ould see extensive water plants Biologically most aquatic cyanobacteria can be put into three functional groups: picocyanobacteria, bloom formers, and mat formers. Picocyanobacteria are prevalent in th e oligotrophic freshwaters in high latit ude regions, and there have been reports of e xtremely high co ncentrations in certain locations Intriguingly, the adjacent polar oceans have little or no population of picocyanobacteria. The second of the cyanobacterial groups, the bloom forming cyanobacteria, are as of now not to be found in mos t polar aquatic envi ronments, but they have been observed in subarctic waters and the changes in environment around the Polar Regions might be able to increase their numbers (Vincent and Quesada, 2012). Mat forming species are the most successful cyanobacteria in terms of bio mass levels at high latitudes. T hey are more common ly present as mm thick mats, fi lms and aggregates, and can also be associated with aquatic mosses 1. 1. 3.3 Cyanobacteria in deserts Cyanobacteria inhabiting hot deserts experience a variety of environmenta l challenges. In addition to aridity and temperature extremes, they are also subject to high light intensity and, in some cases, high salinity. Studies of soil microalgae and cyanobacteria from hot deserts have revealed that they have several mechanisms to deal with extreme conditions (Hu et al ., 2012). Unsurprisingly, water availability, which includes precipitation, condensation, and water vapor, is the most important factor in limiting the growth of desert microorganisms. The study of cyanobacterial grow s deserts, even though, deserts being devoid of moisture, they are restricted to situations

PAGE 17

17 where sufficient moisture is retained for occasional growth to occur, point out one particular aspect of these organisms that has made them omnipresent their outstanding ability to adapt and survive in some of the harshest environments. One prime example is the use of polysaccharide by the cyanobacteria. The productio n of exocellular polysaccharide in most cases is thought t o be a form of nutrient storage. However, in arid conditions the polysaccharide actually help s the organisms withstand desiccation (Flechtner, 2007; Hu et al ., 2012) They are composed of compounds which tend to be hygroscopic and are often pigmented. In arid and semiarid areas where soil cover is sparse and patchy, open soil supports the development of microbiotic crusts. Microbiotic crusts are mixed communities of organisms which may include various combinations of bacteria, cyanobacteria, eukaryotic mi croalgae, lichens, fungi, mosses, and leafy liverworts. The relative proportion of these components is influenced by temperature, water availability, and soil type. Cyanobacteria can withstand the harshest conditions and generally dominate in poor sandy so ils with neutral or slightly alkaline pH. They are less prevalent in acid soils (Flechtner, 2007) 1. 1. 3.4 Cyanobacteria in extreme cold It is a common misconception to think that cyanobacteria are prevalent only in those regions that are blessed with sunl ight and heat things that one might think are absolutely essential for growth of these organisms. But as briefly mentioned before, cyanobacteri a have the ability to survive in extreme environments environments with high salinity, environments with almos t no water and even oil polluted environments. One such extreme environment is the cryosphere which is characterized by harsh freezing temperatures and scarcity of liquid water. Cryosphere is defined here as

PAGE 18

18 regions that have temperatures below 0 degrees c entigrade for most of the year, most notably the alpine regions and the Arctic and Antarctic. As with other seemingly inhospitable surroundings, cyanobacteria have found some way or the other to grow and achieve remarkable biomass concentrations. The reall y interesting part is that research has shown that the strategy to microbial success in these harsh environments is not adaptation towards optimal growth at low temperatures but tolerance to environmental extremes. This complete non existence of adaptive r egulation to a low temperature regime may prove to be an ideal strategy in these ecosystems where a few hours are enough to witness widely fluctuating temperatures (Quesada and Vincent, 2012) reaching high values at which organisms fully adapted for growt h in the cold could suffer severe physiological stress and mortality. In such sub par growth conditions cyanobacterial growth rate is decent to say the least. But in spite of this, it is possible a chieve con spicuously large standing crops and colonization o f most habitats (Quesada and Vincent, 2012) Another important feature is the ability to survive prolonged dormancy, accounting for widespread occurrence of cyanobacteria in such environments. Some of the strategies used by the cyanobacteria include living inside rocks where humidity can be higher and thermal variations can be buffered and forming dark colored mats on or within ice that absorbs sunlight, which increases temperatures enough to melt the ice in summer providing liquid water conditions. Figure 1 2 shows endolithic cyanobacteria growing inside a sandstone rock recovered from the McMurdo Dry Valleys, a row of ice laden valleys located in

PAGE 19

19 Figure 1 2 Endolithic cyan obacteria in a sandstone rock from the McMurdo Dry Valleys (Photo courtesy of Quesada and Vincent, 2012) In order t o decrease the damage produced by both osmotic shock and physical disruption Polar Regional cyanobacteria have come up with some interesting strategies Production of exocellular polysaccharides is thought to be a primary mechanism of protection. This reportedly helps by reducing the water loss and by restricting ice crystal form ation to exterior cell sites So me cyanobacteria also produce int racellular proteins which regulate the osmotic stress imposed by desiccation and antifreeze compounds which are thought to act as cryoprotectants. 1. 1. 3.5 Cyanobacteria in urban environments We have looked at the ability of cyanobacteria to dwell in almost every imaginable natural habitat, from the various water bodies to the water starved deserts and from the thermal springs to the interior of rocks in cryogenic surroundings. However, there is one particular environment that is receiving increasing attenti on of late and that is the urban metropolises of the world. The beginning of the Nineteenth century marked the first recorded growth of microalgae and cyanobacteria on walls, masonry and other man made materials (such as concrete, asphalt, glass and metal)

PAGE 20

20 Since the surfaces of urban buildings provide the maximum area for the growth of cyanobacteria, one can argue that the trials faced by the microbes can be surmised by investigating what factors the surfaces are exposed to, though it is not entirely unlik ely to find some microbial growth in underground systems. The surfaces of most urban buildings are exposed to full sunlight incident on that particular location thereby subject to high irradiance, high exposure to UV rays and possibly extreme dehydration. In addition to these, urban environments are characterized by high level of pollutants (gases such as CO, SO 2 and NO x hydrocarbons, ozone apart from aerosols, dust and heavy metals) which contributes to negative growth conditions for cyanobacteria (Rindi, 2 007) Broadly speaking the knowledge available about the diversity and ecology of these microbial communities is still in its infant stage mainly because most studies focus on the biodeterioration caused by these organisms on man made surfaces rather than t heir biology. Very little or nothing is known about the dispersal patterns of these organisms in such environments. Even though some study has been carried out concerning the distribution of some species and assemblages, more is needed as this aspect of cy anobacterial populations in urban settings depends on an intricate interaction of various factors and properties like (Rindi, 2007) : Climate (temperature, light intensity, precipitation, wind, pollutants) Surface e ffects (chemistry, porosity, water holding capacity) Proximity of adjacent surfaces Internal properties of the wall or surface

PAGE 21

21 1. 2 Emissions and Fossil Fuels 1. 2.1 A Little Bit of History As early as late 19 th century, people were debating about the effect of emissions into the atmosphere by hum ans and some were even brave enough to suggest that fossil fuel usage will cause a degradation of the atmosphere and thereby in turn the climate. In the late 1890s American scientist Samuel Langley decided to measure the surface temperature of the moon by measuring the infrared radiation emanating from it. The angle of the Moon in the sky when a scientist took a measurement determined how much CO2 and water vapor the Moon's radiation had to pass through to reach the Earth's surface, resulting in weaker meas urements when the Moon was low in the sky. This result was unsurprising given that scientists had known about infrared radiation absorption for decades. A Swedish scientist, Svante Arrhenius, used Langley's observations of increased infrared absorption whe re Moon rays pass through the atmosphere at a low angle, encountering more carbon dioxide (CO2), to estimate an atmospheric cooling effect from a future decrease of CO2. He realized that the cooler atmosphere would hold less water vapor (another greenhouse gas) and calculated the additional cooling effect. He also realized the cooling would increase snow and ice cover at high latitudes, making the planet reflect more sunlight and thus further cool down. Overall Arrhenius calculated that cutting CO2 in half would suffice to produce an ice age. He further calculated that a doubling of atmospheric CO2 would give a total warming of 5 6 degrees Celsius. Another scientist during the same time had been quantifying the natural sources of CO2 emissions for the purpos e of understanding the carbon cycle and discovered

PAGE 22

22 that the industrial CO2 emissions (mainly from coal burning) was comparable to that from natural sources back in that time. Arrhenius observed this data and saw that human emissions of CO2 was going to cau se warming. However since the rate of CO2 production was relatively low back in 1896, he thought that it would take thousands of years for the warming to actually register on the global scale and even thought that it might be beneficial to humanity. The ea rly part of the 20 th century was spent mainly disputing and recalculating what Arrhenius had done and the whole world subsumed into a larger debate as to whether the atmospheric changes had caused the Ice ages. Various other theories were suggested but non e fared better. In 1938, a British engineer called Guy Callender set presented evidence that both temperature and the CO2 level in the atmosphere had been rising over the past half century, and he argued that newer spec troscopic measurements showed that the gas was effective in absorbing infrared in the atmosphere. Nevertheless, most scientific opinion continued to dispute, sometimes even ignore the theory. There was a period of increasing concern during the 50s and 60s about the harmfulness of greenhouse gases and its effects on climate change. By the end of the 1960s, aerosol pollution had become a serious local problem in many cities, and some scientists began to consider whether the cooling effect of particulate poll ution could affect global temperatures. Scientists were unsure whether the cooling effect of particulate pollution or warming effect of greenhouse gas emissions would predominate, but regardless, began to suspect that human emissions could be disruptive to climate

PAGE 23

23 on strengthened when the first evidence of warming due to the continuous use of fossil fuels began to surface in the 1970s thanks to considerable improvements in scientif ic data collection. By 1975 the evidence pointing to w arming had accumulated so much that a three dimensional Global Climate Model was made possible by Manabe and Wetherald. This model predicted a 2 degree C increase in temperature worldwide when the CO2 concentration was doubled. Many more models began to sp ring up and not one could say that the temperature will remain same if CO2 concentration was increased. By the early 1990s committees were being formed and scientists were beginning to get involved in political decisions regarding curbing Carbon Dioxide le vels in the atmosphere. Fast forwarding to the present day, it would be an understatement if we were to say that global warming has become one of the major environmental issues. Further research work on global warming and its effects is being added to the already burgeoning collection every day, and then some more. The question that arises most is how do we reduce the emission of greenhouse gases and more importantly how do we diminish the ones that are already present in the atmosphere. 1. 2.2 Emissions and its effects Ever since Arrhenius calculated that increasing carbon dioxide concentrations deterioration of the atmosphere. The negative implications of emissions in general are felt all over the world (Smith et al ., 2000) Loss of sea ice, particularly in the Arctic regions Decreasing snow packs in mountains, more profound in the western mountain ranges of North America

PAGE 24

24 Frequent, longer and more intense heat waves in cities that are currently experiencing them Increased risk of inland flash floods in parts of Europe Reduction of crop productivity in Southern Europe Severe decrease of freshwater availability in Asia and increase in deaths related to diseases from floods and drough ts in some regions The other side to the story is that it is not a secret that the source of energy that has been keeping us going in every sense for the past one and a half centuries is extremely limited, as opposed to what was previously thought. The id ea that fossil fuels will one day run out has been with us ever since the day it was used but with continued exploration of new reserves, growing installed production capacity and increasing equipment efficiencies, the possibility of facing that reality wa s being pushed further and further away. 1. 2.3 End of an Era Mankind has been using fossil fuels for ages now. Ever since the discovery of coal in 13 th century, we have been utilizing fossil fuels to improve our quality of life in all aspects imaginable. Primitive uses of coal were for cooking and providing heat. At present, coal is the major energy source that powers almost every home in the United States. It is safe to say then that our society is still dependent on fossil fuels. Not unt il recently has t here been a firm interest in renewable sources of energy. Given that fossil and cleaner sources of energy would have been the norm by now. There is a reason behind the apparent la te coming of renewables. Fossil fuels provide us with immense

PAGE 25

25 convenience. Oil proved to be so versatile and useful that the thought of it being non renewable did not matter. At least un til now. There is increasing evidence (Hook and Tang, 2012) that the w orld will reach a terminal decline, no matter how many new reserves we discover (Behrens et al ., 2011) Figure 1 3 Plot showing the relative time left for complete exhaustion of fossil fuels (Photo courtesy of Shafiee and Topal, 2009) The United Kingdom Energy Research Council predict that this will happen before 2020. It is estimated that even with the most conservative use of our fossil fuels, they will be able to last us only for 43 years in the case of oil, 148 years in the case of coal and 61 years in the case of natural gas (Shafiee and Topal, 2009) Contrary to popular belief, renewable sources of energy are not new and we have been fiddling with them as long back as the 17 th century. Over time, the one aspect of renewable energy sources that has seen tremendous improvement is the efficiency of energy production from any source. In the modern day, of all the renewable sources being used, one type occupies a fai r share of the usage charts, biomass.

PAGE 26

26 Figure 1 4 Total Energy Consumption with split up of Renewable Sources as of 2010 (Photo courtesy of Hook and Tang, 2012) Biomass production involves using garbage or other renewable resources such as corn or other vegetation to generate electricity. When garbage decomposes, the methane produced is captured in pipes and later burned to produce electricity. Vegetation and wood can be burned directly to generate energy, like fossil fuels, or processed to form alcohols Brazil has one of the largest renewable energy programs in the world, involving production of ethanol fuel from sugar cane, and ethanol now provides 18% of t he country's automotive fuel. Ethanol fuel is also widely available in the USA. The burnout of ou r current resources is a serious problem even without considering other factors like urbanization, increase in population, modernization, developing economies, consumerism and numerous others. The U.N. projects that world population will increase 41 percen t by 2050, with nearly all of this growth in developing countries (Behrens et al ., 2011) This surge in human numbers threatens to offset any savings in resource use from improved efficiency, as well as any gains in

PAGE 27

27 reducing per capita consumption. Develop ed countries like the USA (Behrens et al ., 2011) have their share of problems too. Consider this: The United States, with less than 5 % of the global population, uses about a burning up nearly 25 % of the coal, The U.S has more private cars than licensed drivers, and gas guzzling sport utility vehicles were among the best selling vehicles. New houses in the U.S. were 38 % bigger in 2002 than in 1975, despite having fewer people per household on average The need for newer technologies and newer energy sources that can successfully replace fossil fuels is higher than ever before. In more recent times, Energy Security is a term that is coming to the fore whenever there is any discussion on fossil or renewable fuels. Energy security is the constant availability and supply of affordable energy f or consumers and industry. Ris ks to energy security include disruptions to the supply of imported fossil fuels, limited ava ilability of f uel, and energy price spikes. All these factors drive the search for new technologies that can implement some processes which can produce energy from cleaner sources. 1. 3 E nter Cyanobacteria There has been no dearth of research and implement ation of plant based biofuels to date. Corn, rapeseed, linseed, sugarcane, palm oil, soybeans, sunflowers, cottonseed, jatropha and countless other crops have been used in producing bioethanol, biodiesel or biomethanol in the United States through differen t treatment processes, with corn being the crop most used primarily due to its abundance. However the disadvantages of using land based crops for producing renewable energy far outweighs the advantages (Parmar et al ., 2011) :

PAGE 28

28 Deforestation: Cultivating crop s require huge expanses of arable land leading to cutting down of trees, resulting in adding to greenhouse gas emissions, which is extremely undesirable Water Usage: The water demands of some crops used for biofuel production puts unsustainable pressure on local water resources Food Security: The use of food stocks like corn and soybeans for bioethanol production will result in their price increasing due their increased demand Use of Fertilizers: No crop is grown these days without fertilizers. The Nitrogen fertilizers in use today are a known source of Nitrous Oxide, a greenhouse gas that destroys ozone Monoculture: As demand for corn based bioethanol increases, more corn will have to be cultivated. If new land is unavailable, farmers will resort to growing corn alone and will not rotate crops which deprives the soil of nutrients The other option apart from land based crops in producing biofuels is using plant derived lignocellulose from agricultural and agro industrial resources such as wood chips, corn sto ver, sugarcane, bagasse and rice and wheat straw. These are a potentially vast source of renewable energy production that is not linked to food crops and also have the added advantage that most are considered waste in their respective manufacturing process es, therefore not limited in supply. At the moment the primary challenge is to find an economically viable method of converting the lignocellulosic material into simple sugars that can be degraded by microorganisms to produce fuel. A lot of research is bei ng focused on this aspect and it is a long term goal. Photosynthetic microorganisms like cyanobacteria and microalgae have the potential to be used as feed stocks for biofuel production because: The high growth rate of these microorganisms makes it possibl e to satisfy the massive demand on biofuels using limited land resources without causing potential biomass deficit. Microalgal or Cyanobacterial cultivation consumes less water than land crops.

PAGE 29

29 The tolerance of these microorganisms to high CO2 content in g as streams allows high efficiency CO2 mitigation. Nitrous oxide release could be minimized when photosynthetic cyanobacteria are used for biofuel production. Cyanobacterial harvest and farming could be potentially more cost effective than conventional farm ing. 1. 3.1 Polysaccharide Production As is the case with the strain under study in this work, many cyanobacteria have the ability to produce exocellular polysaccharide, purposes of which range from nutrient storage to, as in case of hypersaline or desert microorganisms, protection from desiccation. A widely accepted theory is that exocellular polysaccharide production is, directly or indirectly, related to environmental constraints imposed on the microorganism. In most cases the polysaccharide serves as a boundary between the cell and its immediate surroundings. Figure 1 5 is a nice example. Figure 1 5 A Nomarski contrast photomicrograph of a sheathed Chroococcus sp. (1000x) (Photo courtesy of Fattom and Shilo, 1984 )

PAGE 30

30 Being more specific one could argue that the layer of polysaccharide provide protection against, apart from desiccation, antibiotics, antibodies, predatory protozoans, surfactants etc. In extending this theory, some scientists suggest that since light is the one and only source of energy for these microorganisms, some cyanobacteria use the secretion of polysaccharides to maximize the availability of light (by flocculating solid particles and clearing the surrounding water column) resulting in higher rates of growth, a direct consequence of i ncreased light utilization and nutrient uptake (Fattom and Shilo, 1984). Other suggested uses of the polysaccharide are nitrogenase protection and a sort of adhesive. The main conclusion we can arrive at from studies of cyanobacterial exocellular polysacch aride is that it can fulfill various roles, depending on trying to understand if the exocellular polysaccharide produced by Synechococcus sp. BG0011 can, in some w ay, fulfill the role of an energy source. 1.3.2 Scope of Work Frankly cyanobacteria provide us with an exc iting opportunity to tackle the problem that has confounded society for a long time. Their unique properties and potential serve as a good platform t o begin the long process of damage limitation. This work examines the advances that can be made in making the use of biofuels a reality using polysaccharide producing algae. It focuses on formulating a model that takes the first steps in describing the pro cess of growing a n algal species and producing polysaccharide in a laboratory scale.

PAGE 31

31 CHAPTER 2 MATERIALS AND METHODS 2.1 Synechococcus BG0011 The cyanobacterial strain that was used in this project is a polymer producing strain of unicellular cyanobacte ria that was isolated from a coastal lagoon in Florida (Phlips et al ., 1989) The three most important characteristics of this algal strain that set it apart are: (1) it can fix its own nitrogen ( 2) it produces a highly viscous polymer that can be used to generate biomethane without separation or bioethanol after separation from culture broth (3) it can grow in a wide range of environmental factors like salinity and temperature (Phlips et al ., 1989 ) The fact that it can fix its own nitrogen from the atmosphere makes the use of nitrogen supplements unnecessary. Furthermore, unlike other cyanobacteria that require considerable amounts of freshwater on a comparatively higher scale, Synechococcus BG001 1 has been reported to grow with relatively high rates in conditions of varying salinity (Phlips et al ., 1989) This enables us to use lesser quantities of limited freshwater resources and maybe even some saline media that might have otherwise been unsuita ble for cyanobacterial growth. This type of tolerance to thermal changes and ability to grow in such conditions make this strain unique and provides us the perfect platform to explore the possibility of developing a clean source of energy. 2.2 Process Desc ription The algal strain was cultivated in a closed photobioreactor with aeration and active in situ sterilization. Aeration was provided by sparging atmospheric air at the rate of 0.5 L/min through each of the reactors The air was passed through filters prior to

PAGE 32

32 entering the reactors to remove any airborne contaminants. The air being sparged serves two purposes: (1) provides nitrogen and carbon dioxide which are essential for growth (2) creates turbulence inside the reactors resulting in a satisfactory de gree of mixing. The air exiting the photobioreactors is sent into a flask to account for some back pressure in the system before being let out into the atmosphere. 2.2.1 Stages of growth The whole process was split into two distinct growth periods: Batch Growth Phase: This begins once the reactors are inoculated and continues till the 18 th day, depending on the amount of growth observed during that period, and ends with dilution of reactor contents Semi Continuous Phase: This growth phase begins with the d ilution of the reactor contents and is maintained for as long as the run itself The two phases of growth have different sampling regimes and dilution rates as explained later. The main reason for carrying out the experiment in such a fashion is the loss of reactor contents, primarily water, through evaporation and entrainment. This causes the volume to drop and concentrates the biomass present in the reactors. Furthermore, a loss of reactor contents translates into a loss of vital nutrients for the cyanobac teria which might deter its growth, hence the addition of new growth medium and water during the semi continuous phase. 2.2.2 Reactor s etup A mechani cal 1.5 Amp pump was used to pass air through the system. To prevent any throttling of the pump, and thereb y consequent heating up, the bulk of the air from the outlet of the pump was purged and the active line was fed into a reservoir. A reservoir was used to negate the unwanted effects of using a mechanical pump, more specifically the infrequent variations in pressure and errors in measuring flow therein.

PAGE 33

33 The air from the reservoir entered a Humidifier, which does exactly what its name suggests. The Humidifier is a sealed flask having one inlet and two outlets containing autoclaved water. The main function of the Humidifier is to increase moisture content of process air thereby decreasing water loss in the reactors due to evaporation. One of the initial designs had the air exiting the Humidifier passing through a set of flowmeters and filters before being let i nto the reactors. However, this resulted in some rare cases of water buildup inside the flowmeters. To prevent this, a column of glass tubes with varying cross sectional area is used to catch any excess water present in the process air before being fed thr ough the flowmeters. As mentioned before, the air is filtered using 0.45 m filters to remove any sorts of contaminants This happens just before the air enters the reactors. The reactors are a set of four Erinmeyer bottles with a total volume of 250 ml an d a working volume of 200 ml. Three of the bottles are inoculated with the algal strain while the fourth is used a control to gauge the level of contamination, if any, in the system. All reactors are fitted with porous, fused ceramic spargers in the inlet tube which creates the aeration. The ceramic spargers are cylindrical with a diameter of 0.875 in and an average pore size of 60 m. The air, on exiting the reactors, is sent to an exit flask containing a solution of pH 12 made by dissolving Potassium Hyd roxide in distilled water The level of solution inside the flask provides the system with some backpressure preventing small gusts of outside air entering the system, in case the pressure inside drops momentarily due to the infrequent variations in pumpin g. The high pH maintained in the exit flask also serves to sterilize the system, preventing growth of unwanted bacteria.

PAGE 34

34 Figure 2 1. Picture showing one of the reactors and the control Additionally, the Humidifier and the exit flask are housed in a blac k box with a UV light of 350 nm wavelength to further the sterilization efforts and eliminate chances of contamination. All the tubing used in the system is general purpose food grade Norprene tube with an inner diameter of 3.2 mm made from polypropylene b ased material with USP mineral oil. The components of the system that come in contact with the process air or culture broth were autoclaved at 121 degrees C at 20 psi for a total of 30 minutes excluding cooldown period. Three of the reactors were inoculate d at the start of each run with 1 ml of exponentially growing cultures. Temperature inside the gro wth chamber was maintained at 28 30 degrees C.

PAGE 35

35 The irradiance for algal growth was provided by two whit e fluorescent light bulbs with a power rating of 20W ea ch The light unit was attached to a timer that was set to a 13/11 light/dark cycle ensuring the light was on for 13 hours and off for 11. This was done to mimic the light conditions in the natural growth habitat of the algae. 2.3 Sampling Each photobiore actor is fitted with a sampling port that remains pinched at all times except during sampling. Sampling was accomplished using sterilized needle syringes with the needles snipped off. The syringe was inserted into the sampling port when needed only. Sampli ng was done in 24 hour intervals beginning with the time of inoculation. During the batch phase of the experiment, sampling volume was kept at 1.5 ml per reactor. During the semi continuous phase, 5 ml of sample per reactor was withdrawn. The samples after analysis were stored in Eppendorf tubes in a freezer that was maintained at 4 degrees C. Dilution of the reactor contents was also done with another sterilized syringe through the sampling port. Care was taken to ensure: (1) proper mixing was observed be fore sampling, making sure the unmixed culture broth in the sampling tube is pushed back in and (2) sampling was done before dilution if the experiment was in the semi continuous phase. The optical density of the withdrawn samples was measured using a Milt on Roy Spectronic 401 spectrophotometer at a wavelength of 540nm. 1 ml of sample was vortexed and placed inside the spectrophotometer to obtain the measurement. It should be noted that vortexing significantly affects the final measurement displayed by the spectrophotometer. It was observed that different times and speeds of vortexing caused the spectrophotometer to display ambiguous readings for the same sample. So each

PAGE 36

36 sample was vortexed for 3 seconds at a speed setting of 4 before measuring its optical d ensity. 2.4 Modeling The model used to describe the experimental system was coded using Visual Basic for Applications (VBA) in Microsoft Excel. VBA was chosen to write the code because of the simple user interface, ease of learning and its interchangeabili ty with Microsoft Excel where all our data lies. As with all models, a set of assumptions were made right at the beginning. These are: Growth kinetics follows the Monod s kinetics characterized by the Monod s parameters maximum specific growth rate and h alf saturation constant Changes in volume of reactor content does not affect the end result Dilution of reactor contents happens instantaneously Transfer rates of all components except CO2 namely Oxygen, Phosphorus and Nitrogen, are either negligible or of no consequence There is no significant change in pH of the system Salinity of reactor contents is always kept constant throughout the runtime Each reactor is completely mixed with the optical density measurements considered as indicative of the entire r eactor contents at that period of time Light, though essential for growth, is not considered to affect the cell density. In other words, no cell shading occurs. 2.4.1 Characteristic equations The physical system under study comprised of two important proc esses with respect to modeling purposes : the growth of microorganisms and the transfer of carbon dioxide from gas phase to liquid phase. The equations describing these processes are described here. All symbols are defined in Appendix C.

PAGE 37

37 The growth of the a mathematical model for prediction of growth rate of a microorganism having a structure similar to Michaelis kinetics is given by the expression The mass transfer of carbon dioxide to culture broth depends on the mass transfer coefficient and is governed by the expression These two equations are solved simultaneously in the model using explicit first order Euler numerical integration technique. 2.4.2 Model Objectives The model should successfully be able to predict the o ccurrence and time of growth characteristics such as exponential growth phase and stationary phase It should estimate vital growth parameters like specific growth rate and half saturation constant by curve fitting with observed experimental data The model should also yield itself to a primitive One Factor at a Time (OFAT) sensitivity analysis

PAGE 38

38 CHAPTER 3 RESULTS The experimental studies on growth was carried out in terms of batches, running from Batch 1 through 5. Batch 1 was the first attempt in the newl y built reactor setup drawbacks. The loss of reactor contents was evident and there was flooding of flowmeters due to oversaturated air passing through them. The col umns previously mentioned were added after Batch 1. Batch 1 was also entirely run in Batch phase. The second run proved to be more successful in terms of dat a recovery and provided us with the fastest growth characteristics. Dilution of reactor contents wa s introduced in Batch 2 making it the first batch to operate in semi continuous phase. Batch 3 was not pursued beyond the first 3 days due to startup problems. Batch 4 was operated for a total of 19 days and was stopped due to precipitation issues in the m edia used in that particular run. Batch 5 proved to be the most consistent in terms of growth and data collection and was operated for a total of 52 days with distinct batch and semi continuous modes of operation. The dilution was carried out on the 18 th d ay after inoculation. Due to its numerous data points and consistency, the model uses the data accumulated from this batch for its validation. The primary parameters considered in the model for curve fitting was the maximum specific growth rate, mass trans fer coefficient, dilution ratios, half saturation constant and the biomass yield coefficient on substrate. The model was also used to

PAGE 39

39 study the effects of inlet substrate concentration and mass tran sfer coefficient (kla) at first. Figure 3 1. Experiment al data used in optimization of model The plot above (Figure 3 1) shows us the values obtained from experimental runs that helped in optimization of the model. This graph belongs to the run Batch 5. 3.1 Model Output ith initial guesstimates based on literature values and observed growth in the laboratory. The culture conditions were taken into account as well. Dilution factors were set at values that were experienced during actual dilution of reactor contents.

PAGE 40

40 Figur e 3 2. First run with estimates for parameter values. The dots represent the experimental curve which is what we are aiming at. The black plot is the model output for biomass growth in terms of absorbance measurements. Yellow line corresponds to the subst rate consumption rate. expected. Before the second run, the model output was used to calculate the error in the system and consequently the Sum of Squares Error (SSE) This was then minimized using the four parameters specific growth rate, half saturation constant, mass transfer coefficient and the yield of biomass from substrate. These were manipulated by the Microsoft Excel Solver to arrive at the least possible value for SSE. The second run produced results that were much closer to actual observations.

PAGE 41

41 Figure 3 3. Second run of model with minimization of error resulting in a good fit with experimental observations. As can be seen, the model now predicts a better growth curve that seems to fit reasonably well with our observations. Again the only parameters changed were the four previously discussed. The dilution factors were still kept the same. This output predicts a final absorbance reading of 1.2 (540nm) that transla tes to a final cell density of 0.45 g/L. The Solver, however, came up with an unusually high value of the yield coefficient to make fit the curve. This is not acceptable as the yield coefficient depends only on the stoichiometry. Hence, using stoichiometri c calculations a yield coefficient of 4.67 grams of carbon dioxide per absorbance was used in the third run to make the fit more realistic. Also the second dilution factor, r2, was included in the optimization.

PAGE 42

42 Figure 3 4. Third model run with Ysx = 4.6 7 From Figure 3 4, it can be seen that the error in the second part of the growth phase, namely the semi continuous phase is higher than before. The reason for this is that the error was split between exponential and semi continuous growth phases as includ ing both in the optimization for this run did not return any feasible solution. Hence, only the error in exponential phase of growth was minimized. To obtain a better fit overall, the parameter values produced by curve fitting was input into the model code and the final plot generated by the model showed a decent fit for both phases of growth. This is shown in Figure 3 5 below.

PAGE 43

43 Figure 3 5. M odel generated plot showing growth and substrate concentration predictions with parameter values obtained by optimi zation 3.2 Comparison of Strain Characteristics To get a better idea of the results obtained from this work, a rudimentary comparison between various algal strains was carried out with emphasis on the specific gro wth rate of the microorganisms. Even thoug h one could argue that some of the growth studies performed on the cyanobacteria used in the comparison were not geared towards increasing their growth rate, we shall assume, for purposes of simplification, that the noted values of specific growth rate wer e the maximum values of the said cyanobacteria. We can see from Table 3 1 that the maximum specific growth rate of Synechococcus BG0011 is significantly lower than most, with a strain from the same genus showing a value of 0.85 days 1 as compared to 0.56 d ays 1 of BG0011

PAGE 44

44 Table 3 1. Comparison of strain chara c ter istics Strains max (days 1 ) Doubling Time (days) Source Aphanizomenon gracile 0.85 0.81 Chi yong et al (2003) Anabaena minderi 0.71 0.97 Chi yong et al (2003) Anabaenopsis NE1 0.90 0.77 Chi y ong et al (2003) Microcystis aeruginosa 0.65 1.06 Moisander et al (2002) Nodularia FL2f 0.40 1.73 Moisander et al (2002) Synechococcus Elongatus 0.85 0.81 Gonzalo Barreiro et al (2004)

PAGE 45

45 CHAPTER 4 DISCUSSIONS 4.1 Model Performance The studies carr ied out in the laboratory were attempted to be defined by a set of equations in the form of a mathematical model. The model that has been presented here is a basic black box model with some telling assumptions to simplify the process. This is in no way a c omplete model as this growth study of Synechococcus BG 0011 is a complex process with numerous parameters and factors that all have a significant impression on the final results, be it biomass growth or polysaccharide production. The model has been found in general to agree with exper imental observations. The exponential growth phase was well predicted by the model with accurate dilution continuous phase of growth as one of the opti mization runs returned a non feasible solution coupled with a very high value of the yield coefficient. However, the model did generate a reasonable fit for the semi continuous phase with the optimized parameter values. The reason for this ambiguity could be the negligence of the effect of volume change during dilution, which is more prominent in the semi continuous phase. The final set of parameter values obtained from the model are: max = 0.56 days 1 Ks = 1.69*10 5 g/L. mass transfer coe 1 and the yield coefficient Ysx = 4.67 grams carbon dioxide per absorbance at 540nm. 4.2 Future Work The model described in this work is a simple non linear model that attempts to begin the characterization of the growth of Synecho coccus BG 0011. There have been

PAGE 46

46 some global assumptions made right from the start that help in quantifying our process and also in estimation of the parameters. Whenever any assumption is made there is always going to be a drawback associated with it. The theoretical assumption as clearly decrease in the reactor content volume concentrates the culture broth. This assumption could be mitigated in future models by using a program structure that accounts for the volume change and its effects. Additionally, the possibility of growth of the algae with two substrates, dissolved carbon dioxide and dissolved n itrogen, can be explored in subsequent work. The curve shown for carbon dioxide consumption in this work is purely model generated and it could be validated in future using appropriate experimental data. Finally, since we are most interested in the product ion of polysaccharide from this algae, a model incorporating the quantification of polysaccharide production and effects on it due to changes in environmental conditions can be looked into.

PAGE 47

47 APPENDIX A MODEL CODE The Visual Basic code is presented here. S ub SubstrateLimiting() c1 = Range("N4") 'od c2 = Range("N6") 'mol/L t = 0 Dt = 0.00001 tfinal = 52 'days 'miu = Range("N5") alpha = Range("N7") '1/days kla ks = Range("N8") 'od mumax = Range("N9") '1/days Ysx = Range("N10") 'g/g pt = 1 'atm h = 0.67 'L .atm/mol yc2 = 0.0004 'mole fraction tsc = 18 irow = 7 'beginning print row 'Dilution factors

PAGE 48

48 r1 = Range("N2") r2 = Range("N1") c2sol = (pt yc2) / h Do 'dilutions If Abs(t tsc) < 0.000001 Then c1 = c1 r1 c2 = c2 r1 End If If t > tsc + 0.5 And Abs(t Int(t + 0.000001)) < 0.000001 Then c1 = c1 r2 c2 = c2 r2 End If 'rates dc1dt = mumax c2 c1 / (ks + c2) dc2dt = 1 / Ysx mumax c2 c1 / (ks + c2) + alpha (c2sol c2) c1 = c1 + Dt dc1dt c2 = c2 + Dt dc2dt t = t + Dt If Abs(t Int(t + 0.000001)) < 0.000001 Then 'MsgBox (dc1dt)

PAGE 49

49 Cells(irow, 4) = c1 Cells(irow, 5) = c2 'Cells(irow, 8) = t irow = irow + 1 End If Loop While t < tfinal End Sub

PAGE 50

50 LIST OF REFERENCES Albertano P (2012) C yanobacterial biofilms in monuments and caves Ecology of Cyanobacteria II: 317 343 Benson E, Harding K, Day JG (2007) A l gae at extreme low temperatures. Cellular Origin, Life in Extreme Habitats and A strobiology Volume 11 : 365 383 Behrens CE, R atner M, Glover C (2011) U.S. fossil fuel resources: terminology, reporting, and summary Congressional Research Service C hi yong A M yung hwan P S eung hyun J H ee sik K K am yong J Hee mock O (2003) Growth i nhibition of cyanobacteria by ultrasonic radi ation: l a boratory and enclosure studies. Environ. Sci. Technol. 37 : 3031 3037 Fattom A, Shil o M. (1984) Phormidium J 1 biofl occulant: production and acti vity. Arch. Microbiol. 139, 421 426 F lechtner VR (2007) N orth american desert microbiotic soil crust communities Cellular Origin, Life in Ex treme Habitats and Astrobiology Volume 11: 537 551 Gonzalez Barreiro O, Rioboo C, Cid A, Herrero C (2004) Atrazine i nduced c hlorosis in Synechococcus elongatus. Cells Arc h. Environ. Contam. Toxicol. 46: 301 307 H aselkorn R ( 04/2009 ) Cyanobacteria Current Biology: CB ISSN 0960 9822 Volume 19 Issue 7 : R277 R278 Hoo k M Li J Johansson K Snowden S (2012) G rowth rates of global energy systems and future outlooks Natural Resources Research : 23 41 Hook M, Tang X (2012) Depletion of fossil fuels and anthropogenic climate change a r eview Energy Policy : 797 Hu C Gao K, Whitton BA (2012) S emi arid regions and deserts Ecology of Cyanobacteria II: 345 369 Moisander PH, McClinton E, Paerl HW (2002) Salinity effects on growth, p hotosynthet ic parameters, and nitrogenase a ctivity in estuarine planktonic c yanobacteria Microbial Ecology 43: 432 442 Parmar A, Singh NK, Pandey A, Gnansounou E, Madamwar D (2011) Cyanobacteria and microalgae: a positive prospect for biofuel s Bioresource T echnology Volume 102 Issue 22 : 10163 10172 Phlips EJ Zeman C, Hansen P (1989) Growth, photosynthesis, nitrogen fixat ion and carbohydrate production by a unicellular cyanobacterium, Synechococcus sp. (Cyanophyta) Journal of Applied Phyc ology: 137 145

PAGE 51

51 Quesada A, Vincent WF (2012) C yanobacteria in the cryosphere: snow, i ce and extreme cold Ecology in Cyanobacteria II: 387 399 Rindi F (2007) Diversity distribution and ecology o f green algae and cyanobacteria i n urban habitats Cellular Origin, Life in Extreme Habitats and Astrobiology Volume 11: 619 638 Seckbach J, Oren A (2007) O xygenic photosynthetic microorganisms in extreme environments: possibilities and limitations Cellular Origin, Life in Ex treme Habitats and Astrobiology Volu me 11 : 811 Shafiee S, Topal E (2009) When will fossil fuel reserves be diminished? Energy Policy: 181 189 Singh SM, Elster J (2007), C yanobacteria in antarctic lake environments: a mini review Cellular Origin: Life in Ex treme Habitats and Astrobiology V olume 11 : 303 320 Smith Sj Wigley TML Nakice novic N Raper SCB (2000) C limate implications of greenhouse gas emissions scenarios Technological Forecasting & Social Change : 195 204 Vernona C, Thompson E Cornella S (2010) Carbon dioxide emissio n scena rios: limitations of the fossil fuel resource Procedia Environmental Sciences Volume 6 : 206 215 Vincent WF, Quesada A (2012) C yanobacteria in high latitude lakes, rivers and seas Ecology in Cyanobacteria II: 371 385 Ward D M Castenholz RW, Miller SR (2 012) C yanobacteria in geothermal habitats E cology of cyanobacteria II: Their Diversity in Space and Time : 752 Whitton BA, Potts M (2012) Introduction to the c yanobacteria Ecology of Cyanobacteria II : 1 13

PAGE 52

52 BIOGRAPHICAL SKETCH RAGHAVENDRAN MURALI The a uthor, Raghavendran Murali, was born in the southern metropolitan city of Chennai in Tamil Nadu, India. He did his schooling in Padma Seshadri Bala Bhavan Senior Secondary School in his National Institute of Technology, Durgapur where he discovered his passion for the unlimited possibilities of Chemical Engineering. He also loves football, or soccer as its otherwise known, and loves playing the sport whenever he finds time.