UNIVERSITY OF SANTO TOMAS CHEMICAL ENGINEERING · UNIVERSITY OF SANTO TOMAS CHEMICAL ENGINEERING 1...

UNIVERSITY OF SANTO TOMAS CHEMICAL ENGINEERING 1

CHAPTER 1

INTRODUCTION

1.1 Background of the Study

Brine evaporation is the process of vaporizing the liquid in seawater in

order to produce a crystalline solid (Korovessis and Lekkas, 2009). This may be

induced either by using heat or through solar energy (Akridge, 2008). Table

salt is largely manufactured in solar salt ponds wherein seawater at 3.5%

salinity (w/v), undergoes a series of evaporator ponds where much of the

water it contained is removed naturally, yielding salt that is a primary necessity

of mankind (Oren, 2010). In solar salt ponds, a green microalgae was

discovered to survive in more saline solutions (Oren, 2011). This microalgae,

Dunaliella sp. changed the physical characteristics of the brine in ponds

changing its color to green (Mendoza et al., 2008). It was also discovered later

on that these Dunaliella species are a great source of beta-carotene, an

essential nutrient which promotes good eyesight, and glycerol, which can be

further converted into a source of energy as biodiesel (Ralefala, 2011).

Since it was observed that it had no significant impact to the quality of

salt produced, many salt manufacturers or salterns have cultivated this culture

into their ponds in lieu of other possibilities. However, most salterns with

these types of species occurring in their ponds have devised a way to improve


the evaporation rate of brine. This is through the use of benthonic

communities that are not invasive in the salt production process but can create

a harmonious food cycle with Dunaliella (Butinar et al., 2005).

So far, this innovation on increasing the evaporation rate using the

microalgae has not been introduced by salt manufacturers in the Philippines.

Other salterns in the United States and other countries have utilized different

types of Dunaliella strains that are capable of changing colors from green to

pink (Creswell, 2010). Through thorough studies on Dunaliella strains applied

in the Philippine environment, new opportunities for improving the salt

production and quality may arise.

1.2 Statement of the Problem

Relevant studies have proven that the incorporation of Dunaliella

tertiolecta culture improves the process of evaporation and the amount of

brine evaporated (Tafreshi and Shariati, 2008). Without sufficient knowledge

of the culture, propagation, and optimum environment it can survive with,

such innovative application could not be utilized to its fullest capacity. The

concern now is to quantify its impact to brine evaporation and arrive at the

optimum amounts of controllable factors necessary to achieve faster brine


evaporation and effective replenishment of the algae for other possible

applications.

1.3 Significance of the Study

Despite of the Philippines being an archipelagic country with plenty of

resources for salt manufacturing, its needs for industrial and household salt

could not be accommodated by domestic salt-making farms and companies.

This study intends to fill the information gap on brine evaporation with

Dunaliella tertiolecta cultures in order to produce higher yields of table salt

that would benefit Filipino consumers and businesses by minimizing

importation of salt from larger salt-producing countries. This study also

provides an alternative in the mass production of Dunaliella tertiolecta culture

that minimizes the risk of algal death due to crowding and overpopulation.

This would help lessen the waste of valuable resource and would allow salt

manufacturers to effectively utilize the said technology. The findings of this

study would be profitable to this study’s benefactor, Salinas Foods

Incorporated, as it allows the development of better techniques for brine

evaporation and utilization of algae for viable biodiesel applications.


1.4 Objectives

The main objectives of this thesis are to quantify the impact of

Dunaliella tertiolecta to the evaporation rate of brine and identify the optimal

conditions required for high evaporation and culture sustainability. In line with

this, the study also intends to accomplish the following specific objectives:

To determine the relationship of adjustable factors such as brine depth,

brine salinity and brine turbidity to the evaporation rate of brine.

To quantify how much the evaporation rate of brine would increase when

Dunaliella tertiolecta is incorporated in brine.

To identify the optimum parameters that would both yield the highest

evaporation rate of brine with Dunaliella tertiolecta and assure algal

biomass survivability.

1.5 Assumptions

A higher evaporation rate of brine can be produced when brine is

incorporated with the green microalgae, Dunaliella tertiolecta.

1.6 Scope and Limitations

The study deals with the quantification and optimization of the

evaporation rate of brine incorporated with Dunaliella tertiolecta through

solar evaporation. In the process of achieving this goal, the evaporation rate

of Dunaliella tertiolecta cultures with and without dilution will be studied. It


will also include behavior of turbidity with dilution and a chart from the results

will be utilized to determine succeeding turbidities. The study will also see the

effect of adding a layer of soil in the simulation ponds. This study therefore

would only be focusing on controllable factors namely brine depth, brine

salinity and brine turbidity. The effect of other environmental factors like

temperature, humidity, solar radiation, and wind speed on the evaporation

rate of brine are considered but not expounded upon.

1.7 Definition of Terms

• Algae

Single-celled plants that can range from microscopic to large. They have

chlorophyll and can manufacture food through photosynthesis.

Benthonic

A collection of organisms living on or in the body of water.

Brine

A heterogeneous mixture of salt and water.

Dunaliella species

A green microalgae that proliferate in salt ponds.


Evaporation

The process at which water in solution and liquid form is vaporized into

gaseous state.

Flocculation

The phenomenon at which suspended particles and colloids aggregate or form

together into lumps or floc.

Salinity

The measure of all dissolved salts in water. Can be measured in degree

Baumé (°Bé) or % NaCl (w/v)

Saltern

An area or place used for salt making.

Turbidity

The measure of relative clarity of a liquid. It is an optical characteristic of water

and is an expression of the amount of light that is scattered by material in the

water when a light is shined through the water sample.


CHAPTER 2

REVIEW OF RELATED LITERATURE

This chapter states the diverse literature and reported studies regarding

the research topic. This include an overview on salt ponds and salt production;

evaporation methods; factors affecting evaporation; physiology and culture of

Dunaliella tertiolecta; and climatic effects to evaporation of brine.

2.1 Salt ponds

The extensive use of sodium chloride as raw material in the chemical

industry have increased salt consumption worldwide, with annual figures reaching

200 million tons nowadays. One third of this is produced in solar saltworks

(Korevessis and Lekkas, 2009).

Along tropical and subtropical coasts worldwide, saltern systems are found

in which seawater is evaporated for the commercial production of common salt

(NaCl) and sometimes other salts as well. To obtain salt of high purity, such

salterns are designed to consist of a series of shallow ponds in which the seawater

is evaporated in stages, keeping the salinity of each pond within a narrow

range. Calcium carbonate (calcite, aragonite) and calcium sulfate (gypsum)

precipitate in the early stages of evaporation. Then sodium chloride (halite)

precipitates in crystallizer ponds with total dissolved salt concentration at


approximately 300 to 350 g/L. The remaining brines that contain high

concentrations of magnesium, potassium, chloride and sulfate are generally

returned to the sea (Oren, 2009).

Solar salterns contain rich and varied communities of phototrophic

microorganisms along the saltern gradient, and the photosynthetic primary

production by these communities largely determines the properties of the

saltern system. The study of phototrophic autotrophs that inhabit salterns is not

only of purely scientific interest: the benthic cyanobacterial mats that develop in

saltern ponds of intermediate salinity effectively seal the bottom of these ponds

and prevent leakage of brine; on the other hand, unicellular cyanobacteria in these

mats and in the brine itself sometimes produce massive amounts of

polysaccharide slime that unfavorably affects the salt production process (Oren

2009).

2.2 Processes of salt production

Modern solar saltworks consist of a system of shallow ponds (15-60 cm

deep) mainly connected in series. Their bottoms are natural and have the

appropriate clay composition that ensure low water permeability. Their operation

principle is basically concerned with the means by which brine is transferred and

salt is harvested, resulting from subsequent technological progress. (Korevessis &


Lekkas, 2009) Figure 2.1 shows the typical process flow of manufacturing salt and

it shows how salt is made from sea water.

Figure 2.1 Process Flow in Salt Making

On a global scale, a solar saltern is not a major ecosystem that contributes

to primary biological production. However, the highly diverse biological system of

salterns with evaporation and crystallizer ponds of different salinities, and often

with high densities of planktonic as well as benthic phototrophic microorganisms

makes salterns excellent model systems for the study of primary production under

a variety of conditions (Oren, 2009).


2.3 Physicochemical process of salt production

Physicochemical process of salt production is actually the process that

current solar salterns use to recover salt from seawater, although there have been

improvements and variations allowing for the production of some hundred to

some million tons of salt depending on the size of the area in use. According to

this process, the ponds are divided into two basic groups. The first group is called

evaporating ponds which is where seawater is concentrated up to saturation point

in terms of NaCl concentration. The bottom is natural without any intervention

and the concentration of contained brine covers the whole range from 3.8 °Be

(almost seawater) to 25.7°Be, corresponding to the last pond which feeds the

crystallizers continuously with the required saturated brine (nurse pond). They

cover almost 90% of the saltern production area since 90% of the water in

seawater to be concentrated up to the point of salt crystallization.

The second group is called crystallizers or pans. It consists of the ponds

where salt crystallizes via further evaporation of the brine up to 28-29 °Bé.

Crystallizers take up the remaining 10% of the production area. These ponds are

specially designed and have their bottom level concentrated aiming to facilitate

and optimize mechanical salt harvesting. A salinity vector is created throughout

the ponds of the saltern with simultaneous and continuous reduction of the


volume of seawater which initially entered the pond system (Korevessis and

Lekkas, 2009).

2.4 Biological process of solar salt production process

Despite rising salinity, life in the salt ponds do not stop. Seawater

organisms gradually disappear as they move from the hostile environment of

other organisms. Without the presence of these predators, these organisms

proliferate. Large populations are able to survive in areas with different

concentration levels because of their varying sensitivity to the ion composition of

the medium they inhabit.

Parallel with the physicochemical process, a chain of organisms is

developed in the evaporating ponds system, similar to those of naturally saline

or hyper saline coastal ecosystems, constituting the biological process of solar

salt production process. This process depends on the quality of seawater feed,

the prevailing conditions in the ponds such as brine temperature, depth, turbidity

and concentration, and the control of the physicochemical process during salt

production and the overall design of the salt works (Korevessis and Lekkas, 2009).

On the work of Korovessis and Lekkas (2008) about improving microbial

growth, the cultures were divided and distributed to other ponds to multiply.

Mother cultures were subdivided into two then these are subdivided it into four


cultures, to the point that the desired amount of cultures is achieved. Figure 2.2

shows the different stages of brine concentration.

Figure 2.2 Stages in Brine Concentration for Salt Production

2.5 Evaporation

Evaporation is the process at which a medium accumulates sufficient

latent and sensible energies that result to phase transformation from liquid to gas

(Naschon et al., 2011). Evaporation is the process by which water is converted

from its liquid form to its vapor form. This is how water is transferred from land

and water masses to the atmosphere. Evaporation from the ocean accounts for

80% of the water delivered as precipitation with the balance occurring on land,

inland waters, and plant surfaces. It plays a critical role in salt production and is

greatly affected by both of its intrinsic and extrinsic factors (Lensky et al., 2005).


2.6 Methods of Evaporation of brine solution

Salt production has often been described as a labor intensive endeavor

requiring and time consuming task (Sundaresan, Ponnuchammy, and Rahaman,

2006). The procedures used in making salt varied by geographic region and

resources locally available. The quantity desired by the local population may have

also influenced the choice of salt production methods (Akridge, 2008).

Numerous studies have focused on the techniques and archaeological

remnants of saltworks. Three distinct techniques for evaporating brine are

described. Solar evaporation, evaporation from boiling due to an externally

applied heat source and evaporation from boiling caused by hot immersed object

these techniques were used sometimes in combination, to achieve the desired

evaporation (Akridge, 2008).

2.6.1 Solar Evaporation

In salt production, a vessel or ponded area containing brine is

allowed to evaporate under prevailing environmental conditions. This

technique works best at low latitudes where sunlight duration and

intensity are highest and areas with low relative humidity and rainfall.

Solar evaporation becomes the default method when fuel resources are

scarce and boiling of brine is unfeasible. Historically, this technique was


common in coastal areas and continues to be a viable commercial process

worldwide. Solar evaporation could have been practiced at many inland

salines where brine concentrations tend to be high thus reducing total

evaporation time (Akridge, 2008). Solar evaporation of sea water to

produce brine is not only a physical process but also entail the organic

contribution of biological communities within the pond ecosystem

(Sundaresan et al., 2006).

2.6.2 Evaporation from an externally heated pan

This technique typically involves the suspension of a vessel over a

fire or emplacement of a vessel directly onto a bed of hot coals. Heat is

transferred through the base and walls of the vessel and warms the

interior fluid. The amount of heat transferred to the brine is governed by

the energy output of the fire and efficiency of heat transfer in a particular

brine boiling set-up (Akridge, 2008).


2.6.3 Evaporation using hot immersed objects

This evaporation scenario considers a hot object (e.g. stone) placed

inside a pan of brine. This method is believed to have been utilized for salt

production in eastern North America from about A.D. 1000-1400. Stone

boiling as a cooking technique probably began with the introduction of

pottery (Akridge, 2008).

2.7 Parameters that Affect the Evaporation of Brine

Natural brine is a commercially important source of industrial salt and

occurs underground, in salt lakes, or as seawater. There are several factors

affecting brine evaporation. Some of these factors are due to the location of the

system. The system may be placed on a location that is ecologically rich in different

species of living things interrelating with each other to form an environment. Even

in the system, microorganisms which give coloration to the brine can affect the

evaporation rate. Another factor is the climatic condition where summer yields

the highest evaporation rate of brine. Brine concentration is another factor where

the higher the concentration, the longer it takes to evaporate brine.


2.7.1 Salinity on the Evaporation of Brine

Salinity is the measure of all dissolvable salts in water quantified in

grams per liter of total dissolved solids (TDS) or in other measurements

such as degree Baumé (°Bé) which is based on the specific gravity of brine.

Salt is produced by solar evaporation and methods for concentrating brine,

salt solutions of around 3.5 g/L and above, have been established

throughout the years.

On a basis at which brine solution is evaporated and concentrated

to crystallization, salinity showed adverse effects on the evaporation rate

of water. Based on a study on hydrological bases as seen in Figure 2.3, the

evaporation factor as well the evaporation rate of water decreases

exponentially as the salinity increases (Leaney and Christen, 2000).

The second law of thermodynamics implies that an increase in ion

activity as a result of the presence of solute reduces the chemical potential

of a liquid solvent and also the rate of spontaneous transformation of the

liquid phase into the vapor phase (Kokya & Kokya, 2006).


Figure 2.3 Effect of salinity in the evaporation factor, F.

The reduction in evaporation rate for salinity levels, S (g/L) up to

320 g/L has been approximated using the following relationship where F is

the evaporation factor (Leaney and Christen, 2000):

F = 1.025 − 0.0246 ∙ 𝑒 (0.00879 ∙ S) (1)

This phenomenon may be brought about by the tendency of water

to become ionized with salts, improving its bonding properties and

elevating its boiling temperature. Approaching the solubility limit of salt in

water also impedes evaporation as the vapor-diffusion coefficient is

significantly decreased due to the mechanical clogging of the matrix by

precipitated salt (Naschon et al., 2011).


Another study showed the variability of evaporation with

increasing salinity. Dama-Fakir and Toerien (2009) included in their work

the results from an observation done by Kokya and Kokya (2006) on

evaporator pans in attempt to propose an evaporation measurement for

saltwater resources.

Table 2.1 Observed evaporation rate with of samples from various sources

containing different counts of Total Dissolved Solids (TDS)

As described in Table 2.1, a decreasing trend in the evaporation

rate may be generalized as the Total Dissolved Solids (TDS) of the system

increases. This combines both organic and inorganic substances contained

in the liquid in molecular, ionized and colloidal state (Sigler and Bauder,

2015).

2.7.2 Microalgae Halophiles on the Evaporation of Brine

Methods of improving the evaporation of saltwater utilized

different microbial communities which did not hinder the output in salt

Day Observed Evaporation (mm)

Fresh Water (TDS= 0.2 g/L)

Ocean Water (TDS= 40 g/L)

Semi-Saline Water

(TDS= 80 g/L)

Salt Water (TDS= 160 g/L)

Urmia Lake Water

(TDS= 350g/L)

1 6.5 6.0 5.2 4.7 3.1

2 7.6 7.1 6.0 5.0 4.0

3 7.2 6.8 5.4 4.1 3.4

4 7.2 6.9 6.0 4.8 3.9

5 6.5 6.1 5.8 5.5 4.4

6 7.5 7.0 6.3 5.2 4.5

7 6.3 5.9 5.1 4.0 3.1

8 8.0 7.4 6.3 5.8 3.2


production. Figure 2.4 shows examples of microorganism that can

withstand high saline concentration. The halophilic autotrophic

microalgae, Dunaliella tertiolecta, was first sighted in the saltern

evaporation ponds in Southern France and was named by the Romanian

Botanist Emanoil C. Teodoresco from the discoverer Michel Felix Dunal

(Oren, 2011).

Figure 2.4 Halophilic microorganisms that can be found in solar salterns

This unicellular green alga is responsible for most of the primary

production in hypersaline environments (Oren, 2005). Dunaliella

tertiolecta is one of the few species of microalgae which can be mass

cultured outdoors including semi-intensive systems in hypersaline lakes

due to its wide halotolerance range, it allows the culture to change the

color and turbidity of the brine solution it occupies. It has an organic


weight of 85 picograms per cell (Creswell, 2010), and has a saturation limit

of 8.6x106cells/mL in DeWalne’s medium (Venkatesan et. al. 2013). This

increase in turbidity is a quantifiable factor that offers viability of increased

absorbance of light compared to clear brine. D. tertiolecta synthesizes and

accumulates dark green pigments which elevate the brine’s absorbency of

solar energy (Zhiling and Guangyu, 2006).

Figure 2.5 Growth curve of Dunaliella salina and Dunaliella tertiolecta in

Dewalne’s medium

D. tertiolecta changes depending on external factors like high

salinity, light intensity, pH and nutrient intake (Tafreshi and Shariati, 2008).

Because D. tertiolecta provides coloration to the ponds, relevant


experimentation shows that cultures of D. tertiolecta results to increase in

temperature of ponds by 5-10°C. This increased temperature increases the

rate of evaporation and hence causes faster precipitation of the halite

crystal (Litchfield et al., 2009).

2.7.3 Physiology of Dunaliella tertiolecta Cells

Dunaliella tertiolecta is a genus of unicellular algae belonging to the

family Polyblepharidaceae. It has become a convenient model organism

for the study of salt adaptation in algae. The establishment of the concept

of organic compatible solutes to provide osmotic balance was largely

based on the study of Dunaliella specie. Moreover, the massive

accumulation of β-carotene by some strains under suitable growth

conditions has led to interesting biotechnological applications. It cells lack

a rigid cell wall and they reproduce by longitudinal division of the motile

cell or by fusion of two motile cells to form a zygote (Oren, 2005).

Teodoresco described two species: D. tertiolecta and D. viridis. D.

tertiolecta has somewhat larger cells, and under suitable conditions it

synthesizes massive amounts of carotenoid pigments, coloring the cells

brightly red (Oren, 2005) and green. D. tertiolecta shows important

intraspecific variability in the β-carotene levels. This feature of the D.

tertiolecta is probably closely related to its nature of extremophile which


favors the natural growth of this alga in isolated environments such as

solar saltworks and hypersaline lakes (Mendoza et al,. 2008).

Dunaliella tertiolecta is distinguished by its ability to survive in a

certain range of salt concentrations through accumulation of intracellular

glycerol. It is one of the few species of microalgae that tolerates high levels

of sunlight, and can survive in the Tibet-Qinghai Altiplano, where UV

radiation is very strong. It is identified that D. tertiolecta possesses both

types of photolyas, and the gene of (6-4) photolyase from D. tertiolecta

(Ds64PHR) is the first one found in unicellular organisms (Lv et al., 2008).

2.7.4 Cultivation of Dunaliella tertiolecta

Similar to plants, Dunaliella tertiolecta is a mixotrophic algae that

utilizes both organic carbon and sunlight for food. Kumar et al. (2015)

provided in his work the contribution of individual factors affecting the

biomass growth of D. tertiolecta cultures using the fertilizer NPK 10-26-26.

Individual contributions were enumerated as follows: sunlight (76.52%),

NPK (16.14%), NaCl (4.84%), Temperature (2.27%) and NaHCO (0.22%).

With a large impact on biomass and carotenoid production, sunlight

becomes essential to evaporation.


As D. tertiolecta proliferate in salt environments, salinities must be

maintained at a certain range for maximum biomass production. Based on

the study of Arun and Singh (2013), the maximum cell concentration of D.

tertiolecta cells grow best at 6% NaCl solutions. As illustrated in Figure 2.5,

increasing the concentration to 25% NaCl would significantly retard its

growth and halt it completely at 30% NaCl.

Figure 2.6 Growth curve of Dunaliella tertiolecta grown on different salt

concentrations. (Acquired from the Journal of the Marine Biological

Association of India Vol. 55, No.1, Jan-Jun 2013)

In order to attain an efficient bioreactor community, D. tertiolecta

cells must be cultivated on certain conditions in which algal growth is

optimum. Microalgal production requires large areas for sunlight capture.

As light does not penetrate more than a few centimeters through dense


algal culture, scale-up is based on surface area rather than volume (Scott

et al., 2010). For that reason, many different types of algal cultivation

systems have been developed. Some of the renowned methods of

microalgae culturing include the use of tanks, tubes, fermenters, open

ponds and many, grouped under the categories of open-air and closed

systems. There are several considerations as to which culture system to

use. Factors to be considered include: the biology of the alga, the cost of

land, labor, energy, water, nutrients, and climate if the culture is outdoors.

All very large commercial systems apply open-air system due to the

high cost needed in operating, maintaining and scaling-up of closed

systems. The advantage of closed systems however, allow the mass culture

of highly-selective microalgae by variation of the system’s environment.

They could be grown in closed systems photoautotrophically,

mixotrophically or heterotrophically.

Basically, the different closed methods implied categorize itself by

method of nutrient requirement in growth. Photoautothrophs like algae

and plants use sunlight for food, heterotrophs utilize organic carbon, and

mixotrophs are the combination of both (Stuart, 2013). Although the

implementation to such process noted varies depending on the culture

used, intensive labor and costs are conclusive in closed systems.


In solar salterns, bioreactors consist of a biodiversity of benthonic

communities that are capable of withstanding high salinities (Litchfield et

al., 2009). Dunaliella tertiolecta exist along with other microorganisms like

flagellates, archaea, halobacteria, and many which serve their purpose in

this small ecosystem.

In order to cultivate D. tertiolecta, the control of predator and

competitor species is required and since D. tertiolecta is capable of living

in high saline environments, most of its competitors cease to exist

increasing efficiency of growth attained when D. tertiolecta is cultured

with its optimal environment. It can be observed in Figure 2.7 that

microalgae such as D. tertiolecta, exist with bacteria and protozoa in great

amounts in a salinity range less than its predator, artemia or more

commonly known as brine shrimp.


Figure 2.7 Biodiversity that exists in varying salinities. (Dervied from Global

NEST Journal, Vol 11, No 1, p. 53, 2009)

The tolerance of each specie gives an analogous representation on

their purpose in a salt pond setting. With the purpose of improving the

production of salt, salterns utilizate such communities, produce salt for

industrial use (Korovessis and Lekkas, 2009).

2.8 Climatic Effects to the Evaporation of Brine

Evaporation is constituted by several factors explained generally by

simultaneous modes of heat and mass transfer. Difference in temperature and

bulk concentration acts as the driving force that facilitates vapor diffusion leading

to evaporation. When the temperature of water is increased, water molecules

gain more energy, moving faster and escaping at a faster rate. The higher the


temperature, the higher the rate of evaporation (Oroud, 2001). For brine, removal

of solvent produces a more concentrated yield and continually precipitates the

minerals as the number of water molecules per ion gradually decreases below a

certain minimum value.

A mass and energy balance that accounts all the affecting parameters

would be a viable method to arrive at a mathematical model for the evaporation

of brine with Dunaliella tertiolecta. According to Lensky et al. (2005), the energy

balance that accounts all identified parameters consist of: the net solar

radiation 𝑸𝑺𝑵, the net long-wave radiation 𝑸𝑳𝑾, the evaporative and conductive

heat flux, 𝑸𝑬 and 𝑸𝑪; the advected heat flux 𝑸𝑨𝑫; and the net heat flux 𝑸𝑵.

Figure 2.8 Energy Balance that accounts for all energy gains and losses.

(Acquired from the Water Resources Research, vol. 41, W12418, p. 5)

This yields an overall energy balance of:

𝑸𝑵 = 𝑸𝑺𝑵 − 𝑸𝑳𝑾 − 𝑸𝑬 − 𝑸𝑪 + 𝑸𝑨𝑫 (2)

since the mass balance of the system varies with the amount of water lost

due to evaporation, the growth and death of Dunaliella cells at constant initial

salinity or dissolved salt, a mass balance can be formulated where 𝒎𝒘 is the mass


of fresh water, 𝒎𝑫 is the mass of Dunaliella culture and 𝒎𝒔 is the mass of induced

dissolved salt.

𝒎𝒕 = 𝒎𝒘 + 𝒎𝑫 + 𝒎𝒔 (3)

2.8.1 Evaporation due to Net Radiation

Solar radiation aids in promoting evaporation by imparting energy

into the absorbing material. Radiation heat transfer utilizes all factors that

changes the temperature of the system through electromagnetic waves

and wavelengths ranging from 0.5 to 50 microns for visible light. Usually,

radiation is accounted by short-wave and long-wave frequencies. These

frequencies may come in directly to the system, while other frequencies

are contained inside the earth’s atmosphere due to greenhouse gases.

For very high temperature sources, such as solar radiation, relevant

wavelengths encompass the entire visible region (0.4 to 0.7 µm) and may

extend down to 0.2 µm in the ultraviolet (0.01- to 0.4-µm) portion of the

EM spectrum (Green and Perry, 2007). Given that radiation is a primary

contributor to the evaporation of brine, peak temperatures and solar

radiation recorded by weather observatories per time of day should be

taken into account in evaporation studies.


2.8.2 Evaporation due to Combined Convection and Advection

Besides radiation, evaporation due to the differences between the

bulk fluids of the system and the environment is affected by convection.

Several factors such as relative humidity and wind speed affect vapor

diffusion and evaporation. As the two bodies are in contact with each

other, simultaneous heat and mass transfer occur as water particles

suspend into the atmosphere in vapor form. However, evaporation are

greatly affected by size or the surface area it covers.

The ‘oasis’ or the clothesline effect denotes that larger bodies of

water tend to have lower evaporation rates than those smaller in size due

to the tendency of larger basins to develop their own microclimate

resulting in increased humidity above the basin and a reduction in

evaporation from the basin (Leaney and Christen, 2000).

Basin parameters which includes soil also has an impact in a general

reduction in hydraulic conductivity if fresh water is induced. However, the

addition of saline water to sodic soils causes the clay to flocculate resulting

in the hydraulic conductivity of the soil (Leaney and Christen, 2000). This

hydraulic conductivity defines the leakage or seepage of brine in salt ponds

going into underground reserves and aquifers.


CHAPTER 3

THE RESEARCH METHODS

The materials used in all experiments consist of industrial grade sodium

chloride (NaCl) crystals, tap water with an average total dissolved solids (TDS) of

105 ppm, 0.82 ppm residual chlorine, and pH ranging from 6 to 8. The microalgal

culture, Dunaliella tertiolecta, is utilized for all related experimentation which is

exclusively mass-cultured in Novaliches, Quezon City and Bolinao, Pangasinan by

Salinas Foods Incorporated. Culture samples were fertilized using fixed amounts

of NPK 14-14-14, and plastic-encapsulated fish remains. For turbidity testing, two

reference solution standards of 0 and 100 NTU were used to calibrate the PCE-

TUM 20 Turbidimeter.

3.1 Relationship of volume, salinity, and turbidity with the evaporation rate of

brine

Different parameters affect the evaporation rate of brine like brine salinity,

brine depth, and brine turbidity. Several environmental factors that also affect the

evaporation rate like temperature, humidity, wind speed and radiant energy,

could not be adjusted. Therefore, such parameters were only accounted to

provide viability for the amount of evaporation obtained from the experiments.


3.1.1 Relationship of salinity to the evaporation rate of brine

Different brine setups were simulated using 0.5-meter diameter

cylindrical white basins. In order to quantify the relative difference

between different control samples, five control samples of clear brine with

salinities of 3, 5, 7, 9, and 11 °Bé were prepared by mixing tap water and

table salt. Salinities of the samples were measured using the Glass

Salinometer HX-1035 and brine depth was measured in millimeters (mm)

using Orion plastic ruler on an hourly basis. The sampling ran from 10 A.M.

in the morning until 5 P.M. in the afternoon. The salt concentration range

was set from 3 °Bé to 11 °Bé since Creswell (2010) indicated that the

seawater saline concentration starts from 3.5% (w/v), approximately 3 °Bé,

and the maximum concentration was set to 11 °Bé, based on the study of

Arun and Singh (2013) stating that Dunaliella tertiolecta begins to die at 11

°Bé.


3.1.2 Relationship of volume to the evaporation rate of brine with

Dunaliella tertiolecta

Different brine setups with Dunaliella tertiolecta cultures were

prepared using five basins with salinities of 3, 5, 7, 9, and 11 °Bé by mixing

tap water, industrial grade salt and Dunaliella culture. All samples were set

to 10 L volumes to account for the demand of succeeding runs. Salinities

of the samples were measured using the Glass Salinometer HX-1035. Every

hour, both salinity and depth were monitored and brine depth was

measured in millimeters (mm) using Orion plastic ruler. The sampling ran

from 10 A.M. in the morning until 5 P.M. in the afternoon.

3.1.3 Relationship of the turbidity to the evaporation rate of brine

Brine turbidity is due to the presence of Dunaliella tertiolecta. This

greenish hue may be achieved at a certain turbidity range. For D.

tertiolecta, the range was set at 100 NTU to 400 NTU since 100 NTU or a

cell concentration of 1.3 X 106 cells/mL (Creswell, 2010) allows enough

microalgae to grow and resist death due to the given setup conditions.

Presence of other microorganisms may dominate the culture and consume

it once underpopulated (Stuart, 2013) thus justifies this value. For the

maximum turbidity, 400 NTU, was set based on the study of Venkatesen


et al. (2013) where the maximum cell concentration of Dunaliella

tertiolecta species lie on 8.6 X 106 cells/mL on the DeWalne’s medium.

However, its capacity may grow given the depth and the surface area of

the culture. And upon relevant observation, maximum turbidity attained

in culturing was found at 400 NTU.

3.1.4 Turbidity chart preparation

100 mL of culture from an assayed stock of Dunaliella tertiolecta at

7 °Bé and 400 NTU was placed in a 250 mL beaker. Two transparent 10 mL

vials were filled with the culture and were analyzed for turbidity using the

PCE-TUM20 Turbidimeter.

Figure 3.1 PCE-TUM20 Turbidimeter analyzing algae samples

The contents of one vial were returned to the stock, and 10 mL

water was added. The new culture was photographed using a 5 megapixel

(MP) phone camera to account for the color corresponding to the recorded


turbidity. This process was repeated until turbidity values became

constant at around 0 to 10 NTU. The photographs were arranged using

Adobe Photoshop CS6, where the corresponding colors of each were

extracted using the eyedropper tool. The colors were presented in a chart

labeled with their turbidities from 50 – 400 NTU.

3.1.5 Preparation of the brine with Dunaliella tertiolecta by continuous

reculturing

Cultures of different salinities and depth were formulated at

conditions where the biomass D. tertiolecta would grow best. Initially, 4

basins of D. tertiolecta culture were grown and monitored. The salinity,

brine depth, and turbidity of samples were recorded and the cultures were

exposed to sunlight and open air. The cultures were fed with 0.1 grams of

NPK 14-14-14 per 1 liter of culture in order to sustain the biomass and

improve algal growth.


Figure 3.2 NPK 14-14-14 fertilizer used in promoting culture growth

After two days, measurements were taken to account for the

difference in salinity, depth, and turbidity. After which, the cultures were

then diluted to 2 degree Baume lower with that of their previous salinity.

This was to ensure culture survivability wherein salinities must not go

below 3°Bé or rise higher than 14°Bé.

3.2 Impact of Dunaliella tertiolecta on the Evaporation Rate of Brine

The impact of the culture to the evaporation rate of brine was realized

using the same experimentation performed in 3.1. Different brine setups with

brine only, brine with Dunaliella tertiolecta, and brine with Dunaliella tertiolecta

and soil bedding were ran simultaneously and the respective parameters were

measured every hour.


3.3 Modeling and optimization of evaporation with Dunaliella-cultured brine

Modelling and optimization were completed using the Box-Behnken

Response Surface Method. This method has set the minimum number of trial runs

needed to randomize the experimentation procedure and produce optimization

data and scale-fit quadratic models. Design Expert 7 by Stat-Ease was utilized in

acquiring the necessary results. Three quantifiable parameters were set, namely

salinity, volume, and turbidity. With a saline range of 3-11°Bé, volume range of 10

– 20 L, and a turbidity range of 100 – 400 NTU, 17 randomized trial setups were

required in which the formulation of each setup was set by the program itself.

Once the setups were fixed to the desired system, they were exposed to

sunlight and open air conditions and were measured again after 24 hours.

Relevant data were taken and replicate trials were done to assess data reliability.

Data acquired from the three setups were interpreted through graphs

using Microsoft Excel 2013 by Microsoft Corporation. In order to create a

comparison between three different setups, the observed evaporation rate were

plotted against time for all categories presented in the experiment.

A response surface design was used in the development of the

experimental design. Specifically, a Box-Behnken design was used. Figure 3.1

shows the design parameters used in the optimization. Figure 3.2 shows the


generated experimental design. Both figures were obtained from Design Expert 7

(Trial Version) by Stat-Ease.

Table 3.1 Summary of experimental design parameters

Table 3.2 Final experimental design

Name Units -1 Level +1 Level

Salinity °Bé 3 11

Volume L 10 20

Turbidity NTU 100 400

Std. Run Salinity

(°Bé) Volume

(L) Turbidity

(NTU)

Actual Evaporation (mm/day)

7 1 3.00 15.00 400.00

10 2 7.00 20.00 100.00

14 3 7.00 15.00 250.00

5 4 3.00 15.00 100.00

2 5 11.00 10.00 250.00

8 6 11.00 15.00 400.00

16 7 7.00 15.00 250.00

4 8 11.00 20.00 250.00

13 9 7.00 15.00 250.00

12 10 7.00 20.00 400.00

1 11 3.00 10.00 250.00

17 12 7.00 15.00 250.00

11 13 7.00 10.00 400.00

6 14 11.00 15.00 100.00

15 15 7.00 15.00 250.00

3 16 3.00 20.00 250.00

9 17 7.00 10.00 100.00


The acquired data were analyzed as response, and the program ran specific

tests on fit, ANOVA, and model graphs using the Box-Behnken Response Surface

Design in Design Expert 7. Other factors which are uncontrollable like ambient

temperature, solar irradiation, wind speed, cloud cover and relative humidity

were monitored through online weather data from an observatory along

Kamuning St., Quezon City, which is near the test site. Controllable factors such as

amount of feed and dilution cycles were held constant to all trials.

Computations for brine volume were derived from the actual height of

brine when 1 L of brine was poured into the basin. As observed and measured, 1

L of brine corresponded to 4.7 mm in height. Thus, the formula used for converting

brine depth into volume for a 520.48 mm-diameter cylindrical basin was

𝑉 = 𝐻 ∗𝜋

4(520.482)

where V is the volume in liters, L or 𝑑𝑚3 , and H is the brine depth in

millimeters, mm. The amount of NPK 14-14-14 fertilizer placed per liter of culture

were also computed using the company’s heuristic data. For every liter of D.

tertiolecta culture, 0.1 g of powdered fertilizer should be dissolved into the culture

per week.


Along the whole period of the experiment, the amount of fertilizer

dissolved in the culture was divided into the number of dilution cycles done per

week. Thus, the amount of fertilizer dissolved in each dilution of the culture was

𝑀 =0.1

𝑛×

𝐻

4.7

where M is the mass of the culture in grams, H is the height of brine in

millimeters, and n is the number of dilutions done per week.


CHAPTER 4

RESULTS AND DISCUSSION

4.1 Relationship of volume, salinity, and turbidity to the evaporation rate of

brine

There are different parameters that affects the evaporation rate of brine

solution, since not all the parameters can be controlled such as the weather and

humidity, the researcher decided to use the parameters that are controllable

which are salinity, volume, and turbidity of the brine solution. In the experiment

each of these parameters were quantified in determining their relationship with

the evaporation rate of the brine solution.

4.1.1 Relationship of salinity to the evaporation rate of brine

Salinity is defined as the presence of salt in a solution and its

concentration affects the evaporation rate of water in a brine solution.

Since dissolved salts reduce the free energy of water molecules, water is

hindered from escaping as vapor to the surroundings. Salt concentration

range was set from 3 oBé to 11 oBé. This due to saltwater being available

at 3.5% (w/v) salinity or approximately 3 oBé. The maximum salinity was

set to 11 oBé since it is the salinity at which D. tertiolecta becomes

ineffective in multiplying (Arun and Singh, 2013). Table 4.1 shows a sample


data gathered to determine the relationship of salinity to the evaporation

rate of brine using height difference.

Table 4.1 Evaporation rates of brine in varying saline concentration

Brine Solution

Salinity, °Bé 3 7 11

Time Height, mm

10:15 AM 48 48 48

11:30 AM 48 46 47.5

12:45 PM 46.5 46 46

1:45 PM 45 44 44.5

2:45 PM 44 44 43

3:45 PM 44 43 42

4:45 PM 44 43 42

Graphing the figures, Figures 4.1 exhibits a linear decrease in height

with respect to time. For the three trials conducted, the 11 °Bé culture

attained the largest change in height compared to the other brine

solutions. The 3 °Bé culture gave the least difference in height with the

given time. The rates of 5, 7, and 9 °Bé setups showed congruency and

varied little with respect to their evaporation rate. In reference to the work

of Leaney and Christen (2000), the result of this experiment is coherent

with their conclusion that the evaporation factor decreases exponentially

with increasing salinity.


Figure 4.1 Evaporation of Normal Brine

Though it contradicts the generalization that more saline solutions

tend to evaporate slower than less saline ones, this experiment was

situated in a salinity range that ensures the survivability of the microalgae.

Thus, all samples within the range of 30-100 g/L salinity would have

decreased the evaporation factor by around 4-6%.

4.1.2 Relationship of volume to the evaporation rate of brine with

Dunaliella tertiolecta

Volume is directly proportional to the evaporation rate. Since this

relationship is already known and existing, the volume and the

evaporation rate with the addition of Dunaliella tertiolecta was compared.

43

44

45

46

47

48

49

50

51

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght,

mm

Time

EVAPORATION OF NORMAL BRINE

3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé


Table 4.2 shows a sample of the evaporation rate with respect to the

change in height for the setup brine solution and brine with D. tertiolecta

solution.

Table 4.2 Evaporation of brine with Dunaliella tertiolecta with respect to height Brine Solution Brine with Dunaliella tertiolecta

Salinity,°Bé 3 7 11 3 7 11

Time Height, mm Height, mm

10:15 AM 48 48 48 48 48 48

11:30 AM 48 46 47.5 48 48 48

12:45 PM 46.5 46 46 48 47 48

1:45 PM 45 44 44.5 48 44 47

2:45 PM 44 44 43 47 44 47

3:45 PM 44 43 42 46 42.5 47

4:45 PM 44 43 42 46 42.5 47

To support the claim that the evaporation rate of brine would increase if

Dunaliella tertiolecta culture was introduced, basins with Dunaliella tertiolecta

culture in varying saline concentrations provided data on how different the

evaporation rate is compared to regular brine. Figures 4.3 shows the height with

respect to time of brine solution with Dunaliella tertiolecta culture.


Figure 4.2 Height vs. Time for Brine with Dunaliella tertiolecta

Similar to Figure 4.1, Figure 4.2 shows a linear decline in height with

respect to time. Despite the similar trend, the final heights attained for Dunaliella

tertiolecta setups are significantly lower as compared to regular brine. The treated

results also show no difference between the final heights of 5 and 7 °Bé cultures.

In comparison, 3 °Bé gave the least change in height.

Table 4.3 Quantitative difference between regular brine and algae-cultured brine

Salinity (°Bè) Brine Only Brine with D. tertiolecta

Response Initial height (mm)

Final height (mm)

Initial height (mm)

Final height (mm)

3 50 45 50 46 Decrease

5 50 44.5 50 43 Increase

7 50 44 50 43 Increase

9 50 44 50 44 No change

11 50 43.5 50 44.5 Decrease

42

44

46

48

50

52

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght,

mm

Time

HEIGHT VS. TIME FOR BRINE WITHD. TERTIOLECTA

3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé


Quantifying the difference in evaporation between the brine and algae

cultured brine, Table 4.3 provides necessary proof of an increase in evaporation

rate of brine at 5 and 7 °Bé when D. tertiolecta cultures was incorporated in the

process. Cultures from 3, 9 and 11 °Bé however produced lower evaporation as

compared with regular brine. This may be justified by the hindrance of

evaporation due to the occurrence of slightly dying algae in the culture and

flocculation due to dust particles.

Figure 4.3 Discoloration and flocculation of D. tertiolecta cells

4.1.3 Relationship of the turbidity to the evaporation rate of brine

Since the Dunaliella tertiolecta gives the brine its turbidity, an increase in

the cell concentration increases the Turbidity of the solution. The cell

concentration was monitored to determine if on a two day interval there would

be a change in the evaporation rate of brine and to justify that the algae

concentration has an impact on the solution’s evaporation rate.


4.1.4 Turbidity chart preparation

The turbidity chart was created for an easier measurement of the turbidity

of brine through qualitative analysis or by just looking at the physical color of the

samples and through comparison the turbidity can already be determined. Figure

4.4 shows the effect of dilution to the turbidity of the solution. It was observed

that the turbidity decreased linearly with the dilution of the culture in 10 mL

increments.

Figure 4.4 Impact of dilution to the turbidity of D. tertiolecta culture

The behavior of turbidity in constant dilution appeared linear as presented

in the figure. However as the dilution of the culture progressed, the decrease in

the turbidity becomes lesser at concentrations below 60% v/v. These changes

observed allowed the discontinuation of dilution since the turbidity started to be

constant at mixtures below 30% v/v.

0

50

100

150

200

250

300

350

400

0 0.2 0.4 0.6 0.8 1

TUR

BID

ITY,

NTU

Biomass Concentration, (%v/v)

Effect of Turbidi ty on Biomass Concentrat ion

Trial 1

Trial 2

Trial 3

Trial 4


4.1.5 Creation of the turbidity chart

After arriving with such relationship, the diluted 100 mL mixtures were

photographed and were arranged by their respective measurements.

As seen in Figure 4.5, the photograph of the samples were arranged in

grids, and the color of each culture were obtained using the “eyedropper tool” of

the photo editing software, Adobe Photoshop Cs6®.

Figure 4.5 Creation of turbidity chart using Adobe Photoshop Cs6®

The color of D. tertiolecta cultures from 400 NTU to 50 NTU were arranged

and labeled with their respective measurements. The final chart is presented in

figure 4.6. The proceeding experiments utilized this chart as basis for the turbidity


of samples. Values below 50 NTU were not included due to their transparency

which compares to clear water.

Figure 4.6 Turbidity chart with respective measurements

4.1.6 Preparation of the brine with Dunaliella tertiolecta with dilution cycles

This part of the discussion focuses on the cell concentration of the

Dunaliella tertiolecta with continuous dilution. Height is monitored to determine

if the evaporation rate, which is directly connected to the volume of the solution,

varies with the growth rate of the D. tertiolecta. The following sample tables were

obtained from May 2 to May 27 2015 because the month of May is the best suited

to make the experiment since it is summer and rainfall is not evident.


Table 4.4 Salinity and height difference from May 2 to 4 Salinity (°Bé)

Difference Height (mm)

Difference Before After Before After

5 7 2 87 78 9

4 7 3 72 63 9

6 5 -1 73 61 12

6 9.5 3.5 67 55 12

Table 4.5 Salinity and height difference from May 4 to 6

Salinity (°Bé) Difference

Height (mm) Difference

Before After Before After

5 5 0 87 77 10

4 4 0 72 60 12

4.5 5 0.5 73 60 13

5 5 0 67 50 17

Table 4.6 Salinity and height difference from May 6 to 13

Salinity (°Bé) Difference

Height (mm) Difference

Before After Before After

5 8 3 87 60 27

4 6.5 2.5 70 50 20

5 7.5 2.5 99 75 24

5 7 2 92 64 28





4 7.5 3.5 65 41 24

4 7.5 3.5 80 54 26

4.5 7.5 3 82 69 13

5 8.5 3.5 93 56 37

4 9 5 73 44 29

5 9 4 68 41 27

4 7 3 72 37 35

4 9 5 68 37 31




5 5 0 66 60 6

5 4 -1 84 78 6

5 5 0 74 67 7

5 5 0 74 68 6

5 5 0 78 72 6

5 5 0 78 73 5

5 5 0 80 74 6

5 4 -1 76 69 7

Since the volume of the solution is directly proportional to the height, it

was the parameter monitored to determine if there is a larger change in

evaporation rate due to biomass growth through continuous dilution. Continuous

dilution is important not only for maintaining the salinity of the solution but also

necessary to provide ample space for biomass growth and restore the initial

heights of each basin.


Figure 4.7 Difference between the height For March 2-4 and 4-6

Figure 4.7 shows the data gathered from a two-day interval from March 2-

4 and 4-6 2015, which presents a distinct change from the two two-day interval.

This shows an increase in the evaporation rate given the increase in height

difference of the samples. The factor that instigated this phenomenon was the

increase in cell concentration since for the two-day interval the salinity of the

solution was made constant by dilution and that the temperature and radiant

energy was also assumed constant since there were no rainfall or any obstructions

observed based on reference weather observatories.

As an example, Sample 1 in the graph has a change in height from March

2-4 2015 of 9 mm while in the next two days (March 4-6 2015), the change was

already 10 mm same as with the other samples, the change was very noticeable

0

5

10

15

20

1 2 3 4

9 912 12

1012 13

17

Hei

ght

dif

fere

nce

, m

m

Sample number

Difference Between the Height For March 2-4 and 4-6

March 2-4 2015 march 4-6 2016


especially in Sample 4 where the evaporation rate increased 5 units from the

original.

Figure 4.8 Difference between the height for March 4-6 and March 6-13

Since the evaporation rate was noticeable from a two-day interval, it was

validated if the assumption that a longer period of evaporation would still

applicable and if the evaporation rate will still be high. This assumption was

relative to the study of Arun and Singh (2013) that cell growth starts to decrease

if the salinity is critical in terms of the culture of D. tertiolecta.

As presented in Figure 4.8 where March 4-6 was compared to March 6-13,

Sample 1 was set to 5 °Bé with an initial height of 87 mm. After two days, there

was no observed change in salinity however there was a 10 mm change in height

unlike for the seven-day interval, where the salinity increase to 8 °Bé and a 27 mm

0

5

10

15

20

25

30

1 2 3 4

1012 13

17

27

2024

28

Hei

ght

Dif

fere

nce

, m

m

Sample no.

Difference between the height for March 4-6 and March 6-13, 2015

march4-6 2015 march 6-13 2015


difference from the initial height of the solution. A slower evaporation rate was

observed for Sample number 2 as seen in the Figure 4.9. The difference of a two-

day interval from the 7-day interval was minimal. It can be due to the salinity of

the solution being at 4 °Bé where culture growth in a lower salinities was

disfavored. The evaporation rate therefore decreased as an effect of the low

culture growth of the solution.

Figure 4.9 Difference between the height for March 16 to 25 And March 25 to 27

To be able to confirm the assumption, another trial was conducted using 8

samples. This was conducted using a 9-day difference from March 16 to 25 and a

2 day difference of March 25 to 27. The salinity of each sample from March 16 to

25 was fixed to a lower salinity at 4 to 5 °Bé to prevent the death of the culture in

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8

2426

13

37

2927

3531

6 6 7 6 6 5 6 7

Hei

ght

Dif

fere

nce

, m

m

Sample no.

Difference between the height for March 16-25 And March 25-27 2015

march 16-25 2015 march 25-27 2015


the samples since it would be set for 9 days. The result showed that at 8 to 9 °Bé

the evaporation rate had started to slow down. This may be due to the salinity of

the solution wherein water molecules are being prevented by the salt molecules

to escape due to intermolecular forces.

4.1.7 Relative relationship of brine salinity, turbidity and volume

Using the Box-Behnken Response Surface Method, the relationship

between the used parameters was identified using the One Factor Interaction

view in Design Expert Trial Ver. 7.0.0. In Figure 4.10, the relationship of salinity

and volume can be observed.

Figure 4.10 One Factor Interaction between Volume and Salinity


It can be observed in Figure 4.10 that based on the experiment, salinity

did not have a significant implication on the volume of brine due to the parallel

orientation of curves. Upon extending the curved lines, there may be chances of

convergence which would explain the impact of salinity to volume. This finding

was similar to the interaction of salinity and turbidity. As seen in Figure 4.11,

salinity does have an impact on the turbidity of the solution as a possible converge

is anticipated when these curves are extended. This means salinity has a higher

impact to turbidity as compared to volume.

Figure 4.11 One Factor Interaction between Turbidity and Salinity


Figure 4.12 on the other hand, shows a clear diverge on the interaction

between volume and turbidity. This means that volume impacts turbidity greatly

and possibly creates an impact on the evaporation rate of cultured brine.

Figure 4.12 One Factor Interaction between Turbidity and Volume

4.2 Impact of Dunaliella tertiolecta on the evaporation rate of brine

The impact of Dunaliella tertiolecta on the evaporation rate of brine

solution can be verified or validated using the data on the changes in height and

salinity. Height and salinity can be used to validate the change in the evaporation

rate since height is directly proportional to the volume of water evaporated from

the brine solution, and an increase in the concentration of the brine solution

signifies that some of the solvent (water) has already vaporized to the


atmosphere. Shown in Table 4.9 and Table 4.10 the change in salinity and the

change in height respectively and both recorded on an hourly basis.

Table 4.9 Change of salinity due to evaporation of water from brine solution in an hourly basis

Brine Solution Brine with Dunaliella Brine with Dunaliella and Soil

Salinity(°Bé) 3 7 11 3 7 11 3 7 11

Time SALINITY (°Bé)

10:15 AM 3 7 11 3 7 11 3 7 11

11:30 AM 3 7.5 11 5 7 11 3.5 7.25 11

12:45 PM 3 7.5 11 5 7.5 11 3.5 7.5 11

1:45 PM 3 7.5 11 6 7.5 12 3.5 7.5 11.5

2:45 PM 3 7.5 11 6 8 12 3.5 8 12

3:45 PM 3 7.5 11 6 9 12.5 4 9 12.5

4:45 PM 3 7.5 11.5 7 10 12.5 4 9 12.5

Table 4.10 Decrease in height due to evaporation of water from brine solution in an hourly basis

Brine Solution Brine with Dunaliella Brine with Dunaliella and Soil

Salinity 3 7 11 3 7 11 3 7 11

Time HEIGHT

10:15 AM 48 48 48 48 48 48 48 48 48

11:30 AM 48 46 47.5 48 48 48 48 48 48

12:45 PM 46.5

46 46 48 47 48 48 48 47

1:45 PM 45 44 44.5 48 44 47 47 46 44

2:45 PM 44 44 43 47 44 47 46 43 44

3:45 PM 44 43 42 46 42.5 47 44 42 43

4:45 PM 44 43 42 46 42.5 47 43 41 40.5


One of the experiments performed focused on quantifying the evaporation

produced with different brine setups through hourly observation and

measurement. The setups were prepared in such a manner that it imitated actual

salt pond conditions. The difference in evaporation were quantified through

simulating the salt pond using a basin as experimental set-ups introduced with the

algae, Dunaliella tertiolecta, which serves as the potential promoter in increasing

the evaporation rate in salt ponds.

Evaporation of brine solution was observed and measured in 1-hour

intervals for almost 7 hours starting from 10 A.M. in the morning to 5 P.M. in the

afternoon. Three batches of 5 basins were prepared; brine solution only, brine

with Dunaliella tertiolecta, and brine with Dunaliella tertiolecta and soil. Having

fixed initial height for all the samples, the depth were measured with respect to

time. Three replicate trials were conducted on the different dates with good

weather conditions. These activities are illustrated in Figure 4.10.


Figure 4.10 Experimental setups and data gathering procedure

Trial 3, being the most precise, was presented. Figures 4.11 shows the height vs.

time of brine solution.

Figure 4.11 Evaporation Rate of Brine Solution

Figures 4.11 exhibits a linear decrease in height with respect to time. For

the three trials conducted, the 11 °Bé culture attained the largest change in height

43

44

45

46

47

48

49

50

51

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght,

mm

Time

HEIGHT VS. TIME FOR BRINE ONLY SOLUTION

3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé


compared to the other brine solutions. The 3 °Bé culture gave the least difference

in height with the given time. The rates of 5, 7, and 9 °Bé setups showed

congruency and varied little with respect to their evaporation rate. In reference

to the work of Leaney and Christen (2000), the result of this experiment is

coherent with their conclusion that the evaporation factor decreases

exponentially with increasing salinity. Though it contradicts the generalization

that more saline solutions tend to evaporate slower that less saline ones, this

experiment was situated in a salinity range that ensures the survivability of

microalgae. Thus, all samples within the range of 30-100 g/L salinity would have

decreased the evaporation factor by around 4-6%.

To support the claim that the evaporation rate of brine would increase if

Dunaliella tertiolecta culture was introduced, basins with Dunaliella tertiolecta

culture in varying saline concentrations provided data on how different the

evaporation rate is compared to regular brine. Figures 4.12 shows the height

with respect to time of brine solution with Dunaliella tertiolecta culture.


Figure 4.12 Height vs. Time for Brine with Dunaliella tertiolecta

Similar to Figure 4.11, Figure 4.12 shows a linear decline in height with

respect to time. Despite the similar trend, the final heights attained for Dunaliella

tertiolecta setups are significantly lower as compared to regular brine. The treated

results also show almost no difference between the final heights of 5 and 7 °Bé

cultures. In comparison, 3 °Bé gave the least change in height.

Table 4.11 Quantitative difference between regular brine and algae-cultured brine

Salinity (°Bè)

Brine Only Brine with D. tertiolecta Response

Initial height (mm)

Final height (mm)

Initial height (mm)

Final height (mm)

3 50 45 50 46 Decreased

5 50 44.5 50 43 Increased

7 50 44 50 43 Increased

9 50 44 50 44 No change

11 50 43.5 50 44.5 Decreased

42

44

46

48

50

52

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght,

mm

Time

HEIGHT VS. TIME FOR BRINE WITHD. TERTIOLECTA

3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé


Quantifying the difference in evaporation between the brine and algae

cultured brine, Table 4.11 provides necessary proof of an increase in evaporation

rate of brine at 5 and 7 °Bé when D. tertiolecta cultures was incorporated in the

process. Cultures from 3, 9 and 11 °Bé however produced lower evaporation as

compared with regular brine. This may be justified by the hindrance of

evaporation due to the occurrence of slightly dying algae in the culture and

flocculation due to dust particles like in the work of Saarani (2012) on flocculants.

Figure 4.13 Discoloration and flocculation of D. tertiolecta cells

Since the basins are white and very reflective, the impact of bed color was

considered. Soil was used in order to replicate actual salt ponds. On that regard,

the evaporation rate of D. tertiolecta samples with soil was assessed and Figure

4.14 shows the height of brine with Dunaliella tertiolecta and soil with respect to

time.


Figure 4.14 Height vs. Time for Brine with Dunaliella tertiolecta and soil

Figures 4.14 also shows a linear decline in height with respect to time. The

final change in height for brine with Dunaliella tertiolecta with soil for 5 and 7 °Bé

samples is greatest than all other experimental set-ups. For three trials of these

set-ups, 5 and 7 °Bé gave the lowest final height comparing to 3, 9 and 11 °Bé.

Table 4.12 Quantitative difference between algae-cultured brine and algae-cultured brine with soil

Salinity (°Bè)

Brine with D. tertiolecta Brine with D. tertiolecta and Soil

Percentage Increased

(%) Initial height (mm)

Final height (mm)

Initial height (mm)

Final height (mm)

3 50 46 50 47.5 -37.5

5 50 43 50 43 0

7 50 43 50 42 14.29

9 50 44 50 48 -66.67

11 50 44.5 50 48 -63.64

4142434445464748495051

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Heig

ht, m

m

Time

HEIGHT VS. TIME FOR BRINE WITH D. TERTIOLECTA WITH SOIL

3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé


Table 4.12 shows the comparison of final heights of both clusters. It can be

seen that there has been a 14.29% increase in the evaporation rate of cultures

with soil compared to regular algae cultures. As observed, samples follow a

distinct trend with regards to the evaporation rate. This somehow allows the

generalization that 5 and 7 °Bé produce the greatest evaporation rate for D.

tertiolecta cultures within the set salinity range, and the impact of soil is

considerable to evaporation.

Upon comparison of the three clusters, the impact of salinity in different

setups was actualized. Figures 4.15, 4.16, 4.17, 4.18 and 4.19 shows the data on

the behavior of these clusters in specific salinities.

Figure 4.15 Evaporation of different brine samples at 3 °Bé

44

45

46

47

48

49

50

51

9:36 10:48 12:00 13:12 14:24 15:36 16:48

Hei

ght,

mm

Time

EVAPORATION OF DIFFERENT BRINE SAMPLES AT 3°BÉ

Brine Only Brine with Dunaliella Brine with Dunaliell and Soil


At 3 °Bé, it can be observed that the regular brine samples produced the

largest evaporation rate as compared with the other clusters. And upon further

observation, there is a steady and linear decrease in normal brine samples than

with Dunaliella-incorporated samples.

This phenomenon can be explained by the work of Vo and Tran (2014)

where low saline solutions tend to produce higher evaporation rates due to lower

electrostatic forces. Upon the addition of the culture, additional interactions

between water molecules and cells tend to change the physiology of water,

making it more viscous and changing increasing its pH.


In comparison with the 3 °Bé clusters, 5 °Bé samples exhibit a more linear

behavior in terms of evaporation. Brine with Dunaliella and brine with Dunaliella

42434445464748495051

9:36 10:48 12:00 13:12 14:24 15:36 16:48

Hei

ght,

mm

Time

EVAPORATION OF DIFFERENT BRINE SAMPLES AT 5 °BÉ

Brine Only Brine with Dunaliella Brine with Dunaliella and Soil


and soil exhibited more evaporation than with regular brine. This behavior can

be related to the findings of Arun and Singh (2013) where the growth of biomass

is highest at 6% NaCl concentrations. Closely similar to this range, this allows the

best environment for biomass proliferation and thus, may account for the

increase in evaporation rate due to increasing turbidity due to cell growth. This

finding is congruent with cultures at 7°Bé.


As presented in Figure 4.17, there are slight differences between the

evaporation rates of each cluster. However, brine with Dunaliella and soil

exhibited a different behavior with regards to its decrease compared with normal

brine and brine with Dunaliella. Despite of such, it can be regarded that the

impact of turbidity significantly affects brine evaporation.

4142434445464748495051

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght,

mm

TIME




As seen in Figure 4.18 and 4.19 on brine clusters at 9 and 11 °Bé, it can be

generalized that the evaporation rate of clusters of normal brine and brine with

Dunaliella is higher compared to samples with soil. This may be due to the

apparent death of Dunaliella tertiolecta cultures as they tend to survive within a

certain salinity range.


43

44

45

46

47

48

49

50

51

9:36 10:48 12:00 13:12 14:24 15:36 16:48

Heu

ght,

mm

Time





As observed in Figure 4.19, clusters with Dunaliella tertiolecta cultures

have attained lower evaporation rates than compared with the normal brine. This

could be attested relative to the work of Vo and Tran (2014) which mentioned the

impact of algae death on the intermolecular activity of brine solutions.

4.3 Modeling and optimization of evaporation with Dunaliella-cultured brine

The process parameters utilized in the experiment were brine salinity (A),

volume (B) and turbidity (C). The data gathered were analyzed and treated using

Design-Expert® Version 7.0.0 Trial Version. This software was able to generate a

model in a form of a quadratic equation shown in Equation 4.1 that allows the

prediction of the evaporation rate of brine with D. tertiolecta using the values of

the process parameters aforementioned.

434445464748495051

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght,

mm

Time




𝐸 = +19.96146 + 2.13333𝐴 − 1.90167𝐵 − 0.089583𝐶 + 0.0000 𝐴𝐵

+ 4.16667𝐸 − 04𝐴𝐶 + 3.66667𝐸 − 03𝐵𝐶 − 0.15313𝐴2

+ 0.042000𝐵2 + 8.00000𝐸 − 05𝐶2 (Eq. 4.1)

Where E is the evaporation rate in mm/day, A is the salinity of brine in

degree Baumé (°Bé), B is the brine volume expressed in liters (L), and C is the

turbidity of brine in Nephelometric Turbidity Units (NTU).

To ensure the validity of the data gathered, a statistical analysis was

applied to test the differences among group means and their associated

procedures. Analysis of variance (ANOVA) checks whether the specific model

equation is statistically significant and is fit to represent the actual relationship

with response to factors. Upon data analysis, the fit summary derived from lack of

fit tests and model statistics suggested that the response surface quadratic model

is to be used. The ANOVA of such model is presented in Table 4.13.


Table 4.13 ANOVA for the Response Surface Quadratic Model on Evaporation

Source Sum of Squares

Degrees of Freedom

Mean Square

F-Value p-value

Model 100.67 9 11.19 5.07 0.0219 significant

A 1.12 1 1.12 0.51 0.4984

B 15.13 1 15.13 6.85 0.0345

C 12.50 1 12.50 5.66 0.0489

AB 0.000 1 0.000 0.000 1.0000

AC 0.25 1 0.25 0.11 0.7463

BC 30.25 1 30.27 13.71 0.0076

A2 25.27 1 25.27 11.45 0.0117

B2 4.64 1 4.64 2.10 0.1903

C2 13.64 1 13.64 6.18 0.0418 Residual 15.45 7 2.21

Lack of Fit 2.25 3 0.75 0.23 0.8732 Not significant

Results from this analysis states that the Model F-value of 5.07 implies

that the model is significant, allowing a 2.19% chance that a “Model F-value this

large could occur due to noise.

The values of p-value less than 0.05000 indicate that the model terms

used are significant. In this case, B, C, BC, A2, and C2 are significant model terms.

The “Lack of Fit” value of 0.23 implies that it is not significant relative to the pure

error. This means there is an 87.32% chance that the “Lack of fit” value exists due

to large noise and is desirable in order for the model to fit.

Table 4.14 Fit of Model Parameters in Design Space

R-Squared 0.8669

Adj R-Squared 0.6959

Pred R-Squared 0.5123

Adeq. Precision 9.983


R-squared value of 0.8669 shows how close the data are to the regression

line. The Predicted R-Squared value of 0.5123 is viable and is in reasonable

agreement with the “Adj R-Squared Value” of 0.6959. A ratio of greater than 4 is

desirable for the “Adeq. Precision” value as it measures the signal to noise ratio.

With a value of 9.983, this model can be used to navigate the design space.

In order to verify the precision and the validity of the model equation 4.1,

the calculated values using the equation are compared to the actual evaporation

rate values. Table 4.15 shows the percent difference between the actual and

predicted values of the evaporation rate.

Table 4.15 Numerical Differences of Actual and Predicted Evaporation Rate Values

Std. Run Salinity

(°Bé) Volume

(L) Turbidity

(NTU)

Actual Evaporation (mm/day)

Predicted Evaporation

Rate (mm/day)

Percent Difference

(%) 7 1 3.00 15.00 400.00 5 5.37505 6.98

10 2 7.00 20.00 100.00 6 5.624707 6.67

14 3 7.00 15.00 250.00 6 5.39978 11.12

5 4 3.00 15.00 100.00 3 3.374935 11.11

2 5 11.00 10.00 250.00 3 2.999419 0.02

8 6 11.00 15.00 400.00 7 6.624465 5.67

16 7 7.00 15.00 250.00 4 5.39978 25.92

4 8 11.00 20.00 250.00 5 5.749394 13.03

13 9 7.00 15.00 250.00 3 5.39978 44.44

12 10 7.00 20.00 400.00 14 13.62483 2.75

1 11 3.00 10.00 250.00 3 2.250005 33.33

17 12 7.00 15.00 250.00 7 5.39978 29.63

11 13 7.00 10.00 400.00 5 5.374848 6.97

6 14 11.00 15.00 100.00 4 3.624349 10.36

15 15 7.00 15.00 250.00 7 5.39978 29.63

3 16 3.00 20.00 250.00 5 4.99998 0.00

9 17 7.00 10.00 100.00 8 8.374737 4.47


Most predicted values are coherent with the actual experimental values.

Large percent differences ranging from 10-45% may be brought about by

uncontrollable environmental factors leading to indeterminate errors. Table 4.16

contains information of the “p-value” values of model terms in each trial.

Replicate trials proved the validity of this data as the “p-value” values of each

model term were relatively similar and coherent.

Table 4.16 p-Values of Model Terms in Replicate Tests Trial 1 Trial 2

Model 0.0291 0.0325

Salinity (A) 0.4984 0.4769

Volume (B) 0.0345 0.0407

Turbidity (C) 0.0489 0.0588

The impact of salinity, volume, and turbidity to the overall evaporation

rate can be represented in a three dimensional surface graph. Figure 4.20 shows

the trend in the evaporation rate with respect to volume and salinity when the

turbidity is set to 100 NTU.


Figure 4.20 3D Surface Plot of the Model Terms at 100 NTU cultures

It is observed that the highest evaporation rate can be achieved on 100

NTU cultures with salinities at 7 °Bé and 10 L culture volume. An evaporation rate

of 8.4 mm/day was achieved in a 100 NTU culture of D. tertiolecta at 7.11°Bé.

Upon increasing the turbidity to 250 NTU, it is observed in Figure 4.21 that

the peak of the contour shifted from low to high culture volumes. Regions with

higher evaporation rate lie from 5 to 9 °Bé, increasing with volumes from 15 to 20

L. This shift can be explained by most of the cultures in the experiment having

higher evaporation rates at higher volumes.



At an optimal value, the highest evaporation rate achieved on 250 NTU

cultures is at 7.31°Bé and 20 L culture volume. Upon increasing the turbidity of

the culture to 400 NTU, it is observed that the contour began to stretch in a plane-

like incline. The highest evaporation rate of 13.67 mm/day was achieved on a 400

NTU culture at 7.51°Bé and 20 L volume.



The effect of the set parameters in the evaporation rate of brine with D.

tertiolecta can be explained by figures 4.20, 4.21, and 4.22. Looking into the

impact of brine volume to the evaporation rate, it can be observed that a higher

volume leads to a higher evaporation rate. This is supported by its p-value of

0.0325 which can be derived from Table 4.13. In Figure 4.20, lower volumes at low

turbidity are desirable since they behave similarly with water. Liquids with smaller

volumes tend to evaporate faster given its smaller energy requirement for

vaporization. Oppositely in Figures 4.21 and 4.22, as the turbidity increased, a

higher culture volume is required to produce a higher evaporation rate.

Salinity and turbidity are both dependent on the brine volume. It shares

an inversely proportional relationship with salinity and a directly proportional

relationship with turbidity. As the volume of culture decreases, the culture


becomes more concentrated in salt. As for turbidity, experiments performed led

to the observation that deeper culture volumes are more turbid compared to

shallow ones. Higher culture volumes promote biomass growth which improves

the color of the culture. The darker the culture is, the more light is absorbed by

the culture. Thus, promote greater biomass production and faster evaporation

rates.

The effect of salinity to the evaporation rate is observed to be irrelevant.

Based on the p-value value of salinity in Table 4.13, and the following 3D surface

figures, the salinity for optimal evaporation lie at regions from 5 to 9 °Bé. Despite

of the large increase in turbidity, the optimal salinity only increased from 7.11 to

7.51 °Bé. This may be explained by the observation that cultures placed in low and

high salinities tend to die during the process due to its small salinity range. In that

accord, cultures with these salinities tend to clear out or become colored with

dead D. tertiolecta culture. This results to a lower evaporation rate as compared

to the optimal salinity range for the culture.


CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.1 Conclusions

With the intention of improving the evaporation rate of brine, Dunaliella

tertiolecta culture was incorporated in brine. Several methods applied helped

determine the relationship of the parameters to the evaporation rate, quantify

the amount of evaporation increased upon incorporation of the microalgae, and

identify the optimum amounts of parameters that would yield the highest

evaporation rate.

The parameters that had significant effect on the evaporation rate of brine

was brine volume (p=0.0345) and brine turbidity (p=.0489). Despite of the

importance of brine salinity (p=0.4954) as a factor, it only proved the optimal

salinity range where Dunaliella tertiolecta culture could be grown in order to

maximize the evaporation rate. Brine salinity was inversely proportional to the

evaporation rate. With the presence of the culture however, the salinity remained

in a specific range, making the culture a potential buffer for salinity. Brine turbidity

was directly proportional to the evaporation rate.


The findings of this paper showed a 16 to 27% increase in evaporation rate

in mm/day for Dunaliella tertiolecta brine systems compared to regular brine at

similar salinities and optimal conditions.

Optimal conditions for maximizing brine evaporation on brine-cultured

systems were found at 7.52 °Bé, 20 L, and 400 NTU at 97% desirability. The

evaporation rate can also be computed using the following equation:

𝑬 = +19.96146 + 2.13333𝐴 − 1.90167𝐵 − 0.089583𝐶 + 4.16667𝐸 − 04𝐴𝐶

+ 3.66667 × 10−3𝐵𝐶 − 0.15313𝐴2 + 0.042000𝐵2

+ 8.00000 × 10−5𝐶2

where E is the evaporation rate in mm/day, A is the salinity of brine in degree

Baumé (°Bé), B is the brine volume expressed in liters (L), and C is the turbidity of

brine in Nephelometric Turbidity Units (NTU). Thus, it can be generalized that a

higher volume and culture turbidity greatly improves the evaporation rate. Since

a biological entity is incorporated in the process, brine must be maintained at 7 to

7.5 °Bé to achieve maximum evaporation.


5.2 Recommendations

It is recommended to perform experiments in a longer time frame. This

would help understand the relationship of the considered parameters with the

evaporation rate. It is also recommended to do additional studies on the effect of

brine depth with the evaporation rate of brine with the culture since the effect of

depth can only be realized when seasonal changes occur.

It is also recommended use different types of fertilizers that would

effectively help improve microalgae growth. Dilution cycles should also be varied

due to changing weather, and alternative evaporation methods like aeration

should be tested.

It is suggested also to run optimization tests with varying dilution cycles in

order to observe the behavior of each parameter when the microalgae grows.

Experimentation with constant environmental conditions is also suggested in

order to determine which environmental factor greatly affects evaporation as a

whole.


BIBLIOGRAPHY

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Davis, J. (2000). Structure, function and management of the biological system for seasonal solar saltworks. Global Nest, the Int. J, Vol.2, No.3, pp 217-226

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Korovessis, N., & Lekkas, T. (2009). Solar Saltworks' wetland Function. Global Nest, 49-57.

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Lv., Qiao, Xiong, You, Cao, He, and Cao. (2008). Photoreactivation of (6-4)photolyase in Dunaliella Salina. College of Life Sciences, Sichuan University China. Doi: 10.1111/j.1574-6968.2008.01144.x

Mendoza, H., De La Jara, A., Freijanes, K., Carmona, L., Ramos, A.A., Duarte, V. d.S., Varela, J.C.S. (2008). Characterization of Dunaliella salina strains by flow cytometry: a new approach to select carotenoid hyperproducing strains. Electric Journal of Biotechnology Vol.11 No.4 ISSN: 0717-3458. Pontificia Universidad Catolica de Valparaiso-Chile

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APPENDIX

Appendix A: Raw data for three-clustered experiment on brine, brine with Dunaliella, and brine with Dunaliella and soil

Table A.1 Trial 1 for raw data for the three-clustered experiment

Table A.2 Change in Salinity for Trial 1

Time

Height

Brine Only Brine with Dunaliella tertiolecta

Brine with Dunaliella tertiolecta and Soil

Salinity 3 5 7 9 11 3 5 7 9 11 3 5 7 9 11

10:15 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48

11:30 48 46.5 46 46 46 48 48 47 47 47 48 46 48 48 48

12:45 46.5 45 46 46 46 48 47 47 47 47 48 45 47 48 48

13:45 45 45 44 45 44 46.5 45.5 46 45 44 48 43 43 48 48

14:45 44 44 44 44 43 46 45 44.5 44 44 47 42 43 48 47

15:45 44 44 43 43 42 46 43 43 43 43 46 41 41 47 47

16:45 44 44 43 43 42 45 42 42.5 42 42 46 41 41 46 47

Time

Change in Salinity



Salinity 3 5 7 9 11 3 5 7 9 11 3 5 7 9 11

10:15 3 5 7 9 11 3 5 7 9 11 3 5 7 9 11

11:30 3 5.5 7.5 9 11 3.5 5.5 7.25 9 11 5 6 7 9.25 11

12:45 3 6 7.5 9 11 3.5 6 7.5 9 11 5 6 7.5 10 11

13:45 3 6 7.5 9 11 3.5 6 7.5 9 11.5 6 7.5 7.5 11 12

14:45 3 6 7.5 9 11 3.5 6.5 8 10 12 6 7.5 8 11 12

15:45 3 6 7.5 9 11 4 7 9 9 12.5 6 8 9 11 13

16:45 3 6 7.5 9 11.5 4 7 9 10 12.5 7 8.5 10 12 12.5


Table A.3 Trial 2 for raw data for whole day experiment

Table A.4 Trial 3 for raw data for One day experiment

Time

Height



Salinity 3 5 7 9 11 3 5 7 9 11 3 5 7 9 11 10:10 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51

11:20 50 49.5 49 49 49 51 50.5 50 50 50 51 49 50 51 51

12:30 48.5 48 49 49 48 50 49 49 49 49 51 47 49 51 50

13:30 47.5 47 47 48 46.5 49 47.5 48 48 47.5 50 45 46 50.5 50

14:30 46.5 46 46 47 45 48.5 46 47 47.5 46.5 49 44 45 49 50

15:30 46 46 45 46 44.5 48 45 46 46 45 48.5 43 44 48 49

16:30 45.5 45 45 45 44.5 48 44 44.5 44.5 44.5 48 43 43.5 48 49

Time

Height



Salinity 3 5 7 9 11 3 5 7 9 11 3 5 7 9 11 9:55 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50

11:10 49.5 48.5 48.5 48 48 50 49 48.5 49 49 50 48.5 49 50 50

12:25 48 47.5 47 47 47 49 47.5 47 47.5 48 50 47 47.5 50 49

13:25 47 46.5 46 46.5 45.5 47.5 45.5 46 46.5 47 49 45.5 44 49 49

14:25 46 46 45 45 44.5 47 45 45.5 46 46 48 44 43 48.5 48

15:25 45 45 44 44 44 47 44.5 44 45 45 48 43 42.5 48 48

16:25 45 44.5 44 44 43.5 46 43 43 44 44.5 47.5 43 42 48 48


Figure A.1 Height vs. Time for Brine only for trial 1

Figure A.2 Height vs. Time for Brine with Dunaliella tertiolecta for trial 1

41

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(mm

)

Time

HEIGHT VS TIME FOR BRINE ONLY

3 Bé 5 Bé 7 Bé 9 Bé 11 Bé

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49

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght

(mm

)

Time

HEIGHT VS TIME FOR BRINE WITH D.

TERTIOLECTA



Figure A.3 Height vs. Time for Brine with Dunaliella tertiolecta and soil for trial 1


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)

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TERTIOLECTA WITH SOIL


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)

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Hei

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(mm

)

Time


TERTIOLECTA


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50

52

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght

(mm

)

Time







43

44

45

46

47

48

49

50

51

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght

(mm

)

Time


3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé

42434445464748495051

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght

(mm

)

Time


TERTIOLECTA

3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé



Table A.5 Percentage Difference for Brine only and Brine with Dunaliella tertiolecta for trial 1

Salinity (°Bè) Brine Only Brine with D. tertiolecta Response (%) Initial height Final height Initial height Final height

3 50 45 50 46 -25

5 50 44.5 50 43 50

7 50 44 50 43 10

9 50 44 50 44 20

11 50 43.5 50 44.5 0

Table A.6 Percentage Difference for Brine with Dunaliella tertiolecta and Brine with Dunaliella tertiolecta for trial 1

Salinity (°Bè) Brine with D. tertiolecta Brine with D. tertiolecta and Soil

Response (%)

Initial height Final height Initial height Final height

3 50 46 50 47.5 -33.3333

5 50 43 50 43 16.6667

7 50 43 50 42 27.2727

9 50 44 50 48 -66.6667

11 50 44.5 50 48 -83.333

4142434445464748495051

9 : 3 6 1 0 : 4 8 1 2 : 0 0 1 3 : 1 2 1 4 : 2 4 1 5 : 3 6 1 6 : 4 8

Hei

ght

(mm

)

Time



3 °Bé 5 °Bé 7 °Bé 9 °Bé 11 °Bé




3 50 45 50 46 -45.4545

5 50 44.5 50 43 16.6667

7 50 44 50 43 8.333

9 50 44 50 44 8.333

11 50 43.5 50 44.5 0



Response (%)


3 50 46 50 47.5 0

5 50 43 50 43 14.2857

7 50 43 50 42 15.3846

9 50 44 50 48 -53.8462

11 50 44.5 50 48 -69.2308



3 50 45 50 46 -20

5 50 44.5 50 43 27.27

7 50 44 50 43 16.67

9 50 44 50 44 0

11 50 43.5 50 44.5 -15.38



Response (%)


3 50 46 50 47.5 -37.5

5 50 43 50 43 0

7 50 43 50 42 14.29

9 50 44 50 48 -66.67

11 50 44.5 50 48 -63.64


Appendix B: Raw data for evaporation rate of brine with Dunaliella tertiolecta cultured with variable dilution cycles

Table B.1 Raw data for periodic dilution (March 2-4, 2015)

Salinity Difference

Height Difference

before after before after

5 7 2 87 78 9

4 7 3 72 63 9

6 5 -1 73 61 12

6 9.5 3.5 67 55 12


Salinity Difference

Height Difference


5 5 0 87 77 10

4 4 0 72 60 12

4.5 5 0.5 73 60 13

5 5 0 67 50 17


Salinity Difference

Height Difference


5 8 3 87 60 27

4 6.5 2.5 70 50 20

5 7.5 2.5 99 75 24

5 7 2 92 64 28


Table B.4 Raw data for periodic dilution (March 16-25, 2015) Salinity

Difference Height

Difference before after before after

4 7.5 3.5 65 41 24

4 7.5 3.5 80 54 26

4.5 7.5 3 82 69 13

5 8.5 3.5 93 56 37

4 9 5 73 44 29

5 9 4 68 41 27

4 7 3 72 37 35

4 9 5 68 37 31


Appendix C: Turbidity chart creation raw data Table C.1 Raw data of turbidity of samples with dilution of water

Turbidity (NTU)

Run # TRIAL 1 TRIAL 2 TRIAL 3 TRIAL 4

0 400 400 400 400

1 367 357 361 359

2 327 325 330 327.5

3 285 285 290 287.5

4 247 240 248 244

5 212 211 209 210

6 178 176 177 178

7 143 140 145 142.5

8 126 126 127 126.5

9 114 114 115 114.5

10 102 101 105 103

11 90 91 92 91.5

12 81 80 82 81

13 73 73 72 72.5

14 65 64 64 64

15 58 56 57 56.5

16 52 52 51 51.5

17 46.41 45.88 44.21 45.045

18 41.86 40.4 40.2 40.3

19 36.96 36.9 35.7 36.3

20 33.9 33.58 33.1 33.34

21 31.62 30.69 31.5 31.095

22 28.28 26.16 27.22 26.69


Appendix D: Raw data of Second Trial on the Optimization Experiment

Table D.1 Second Randomized test with Actual Response by Design Expert Trial 7.0.0

Std Run Block Factor 1 A:

Salinity °Bé

Factor 2 B:

Volume L

Factor 3 C:

Turbidity NTU

Response Evaporation/Day

mm

7 1 Block 1 3.000 15.00 400.00 4

10 2 Block 1 7.00 20.00 100.00 5

14 3 Block 1 7.00 15.00 250.00 5

5 4 Block 1 3.00 15.00 100.00 4

2 5 Block 1 11.00 10.00 250.00 3

8 6 Block 1 11.00 15.00 400.00 7

16 7 Block 1 7.00 15.00 250.00 6

4 8 Block 1 11.00 20.00 250.00 5

13 9 Block 1 7.00 15.00 250.00 3

12 10 Block 1 7.00 20.00 400.00 13

1 11 Block 1 3.00 10.00 250.00 3

17 12 Block 1 7.00 15.00 250.00 7

11 13 Block 1 7.00 10.00 400.00 5

6 14 Block 1 11.00 15.00 100.00 4

15 15 Block 1 7.00 15.00 250.00 7

3 16 Block 1 3.00 20.00 250.00 5

9 17 Block 1 7.00 10.00 100.00 7

Table D.2 Selection of Type of Fit by Design Expert Trial 7.0.0

Sequential Model Sum of Squares Test


df Mean Square

F Value

p-value Prob > F

Mean vs Total

508.76 1 508.76

Linear vs Mean

23.75 3 7.92 1.50 0.2603

2FI vs Linear 27.25 3 9.08 2.20 0.1507

Quadratic vs 2FI

27.29 3 9.10 4.56 0.0450 Suggested

Cubic vs Quadratic

2.75 3 0.92 0.33 0.8071 Aliased


Table D.3 Analysis of variance table

Analysis of variance table [Partial sum of squares-Type III]


df Mean Square

F value P-value Prob>F

Model 78.29 9 8.70 4.36 0.0325 significant

A-Salinity 1.12 1 1.12 0.56 0.4769

B-Volume 12.50 1 12.50 6.27 0.0407

C-Turbidity

10.13 1 10.13 5.08 0.0588

AB 0.000 1 0.0000 0.0000 1.0000

AC 2.25 1 2.25 1.13 0.3233

BC 25.00 1 25.00 12.54 0.0094

A2 19.92 1 19.92 9.99 0.0159

B2 1.39 1 1.39 0.70 0.4309

C2 7.39 1 7.39 3.71 0.0955

Residual 13.95 7 1.99

Lack of Fit 2.75 3 0.92 0.33 0.8071 Not significant

Pure Error

11.20 4 2.8

Cor Total 92.24 16


Appendix E: Sample online weather data from Manila Observatory



Appendix F: Conversion of Nephelometric Units to Cell Density

Table F.1 Turbidity (NTU) to mg/L relationship

Std # 1 2 3 4 5

NTU 20 75 250 450 750

mg/L 40 100 420 1250 3300

Figure F.1 Organic wt. of Dunaliella tertiolecta: 85 𝑝𝑔/𝑐𝑒𝑙𝑙 (Creswell, 2010)

(𝑇𝑢𝑟𝑏𝑖𝑑𝑖𝑡𝑦)𝑚𝑔

𝐿×

𝑐𝑒𝑙𝑙

85 𝑝𝑔 ×

1000000000𝑝𝑔

1𝑚𝑔

𝐿

1000 𝑚𝐿×

1

106 = 𝑐𝑒𝑙𝑙𝑠 × 106/𝑚𝐿

Table G2. NTU conversion to Cells x 106/mL

NTU 50 55 60 65 70 80 90 100 110

Cells x 106/mL

0.76 0.8 0.85 0.9 1.0 1.1 1.2 1.3 1.5

NTU 130 140 180 210 250 280 330 360 400

Cells x 106/mL

1.8 2.0 3.0 3.8 5.1 6.2 8.3 9.7 11.8

y = 0.0056x2 + 0.1592x + 42.489R² = 0.9999

0

500

1000

1500

2000

2500

3000

3500

0 100 200 300 400 500 600 700 800

Regression curve for turbidity (NTU) to mg/L


Appendix G: Timetable for research


Appendix H: Identification of Costs and Budgetary Requirements

Materials

Quantity

Cost Per Piece (Php)

Cost Of Total (Php)

Basin 15 220 3300

Beaker 1 @ 1L 580 580

1 @ 250mL

120 120

Thermometer 1 Borrowed -

Salinometer 1 Borrowed -

pH meter 1 Borrowed -

Turbidimeter 1 Borrowed -

Soil Supplied by Salinas

Water Supplied by Salinas

Table Salt (Industrial grade)

25 23/pack 575

Dunaliella tertiolecta cuture

Supplied by Salinas

Swire feed (NPK 14-14-14)

1 1500/sack 1500

Total Cost 6075

Remarks

All research costs were covered by

Salinas Foods Incorporated


Curriculum Vitae

Kenneth Saniano Caraig, a 5th year

student from the University of Santo Tomas with

a program, Bachelor of Science in Chemical

Engineering, was born on August 5 1994. He was

the youngest son of Estelita Saniano and Ismael

Caraig. His only brother, Jhon Fritz Kevin Saniano

Caraig, is currently studying Medicine. They live in

#322 brgy. Tibig Lipa City Batangas. He was a high school graduate from De La Salle

Lipa in 2011 where he got his loyalty award. He was currently studying at UST on

his last term as a fifth year student. His stay in college made him a more confident

person. He joined organizations such as the UST Chemical Engineering Society

where he was a staff in the Performing Arts Recreations Committee, he is also a

member of the Pax Romana in UST. Aside from that, He is also the current vice

president of their section, which made him a more responsible person.


Alyssa Alicaway Rivera is a 5th year

engineering student major in B.S. Chemical

Engineering at University of Santo Tomas. She

graduated valedictorian at Bernardo College

Children’s Camp in her primary level and awarded

as one of the 13 outstanding students out of 400

graduates in her secondary level. To further excel

herself academically, she also engage in different organizations that will nurture

her current knowledge about her program she’s taking like Chemical Engineering

Society (ChES) and Philippine Institute of Chemical Engineers (PICHE). She also

involves in extracurricular activities to learn from people and experience, and to

discover more about herself. She is a varsity player of table tennis in high school.

She also become part of different organizations related to dancing like Engineering

Dance Troupe, Chemical Engineering Dance Crew. These organization helps her to

develop her multi-tasking skills and time management. She’s also part of UST Red

Cross Youth Council-Eng’g Unit as Junior Officer. She is a competent,

compassionate, and committed future Thomasian Chemical Engineer. She is eager

to learn and she is willing to impart her knowledge. Hardworking and dedication

are some of the values she can confidently proud of.


Jericho Bolok Zacarias is a 5th year

Chemical Engineering Student at the University

of Santo Tomas that had taken his secondary

education in Bacoor, Cavite, which is near his

hometown. Currently, he is taking up a course

on Bachelor of Science in Chemical Engineering

in the University of Santo Tomas, Espana,

Manila and is expected to finish on the School Year 2016. His aim is to develop a

skill in approaching different Engineering problems and be able to cope to new

challenges preented by novel problems and complications. He was a member of

the Chemical Engineering Society Public Relations Committee for 2 consecutive

years to present, and was awarded with recognitions in the said organization. He

also participated in various seminars with regards to food, polymerns, medicine,

and nanotechnology industries in view of acquisation of greater knowledge of the

various industires of Chemical Engineering. He is currently undertaking in an

undergraduate thesis program which is duly sponsored by Salinas Foods

Incorporated that aims to quantify evaporation difference of Dunaliella-cultured

brine to the regular brine.

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