12
International Journal of Applied Environmental Sciences ISSN 0973-6077 Volume 13, Number 1 (2018), pp. 27-38 © Research India Publications http://www.ripublication.com Modelling Interaction of CO 2 Concentration and the Biomass Algae Due to Reduction of Anthropogenic Carbon Based on Predator-Prey Model Ruly Budiono 1 , Hafizan Juahir 2 , Mustafa Mamat 3 , Sukono 4 , Mohamad Nurzaman 5 1,5 Department of Biology, Faculty of Mathematics and Natural Sciences Universitas Padjadjaran, Bandung, Indonesia, 45363 2 East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin, Tembila Campus, 2200 Besut, Terengganu, Malaysia 3 Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin Tembila Campus, 2200 Besut, Terengganu, Malaysia 4 Department of Mathematics, Faculty of Mathematics and Natural Sciences Universitas Padjadjaran, Bandung, Indonesia, 45363 Abstract The energy consumption produces 75% of Carbon Dioxide to the antropogenic emission in the atmosphere. It causes a greatest impact in Climate change during a recent century. These major factors lead not only scientist, but also people all over the world to take into account in reducing the carbon emission. One of the safest and sustainable ways to reduce the concentration of anthropogenic carbon is to add a role of a biomass converter. Here, we modeled the carbon consumption for the biomass production of phytoplankton Nanochloropis oculata in a controlled fine-scale environment into simple

International Journal of Applied Environmental … Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman mathematical formulation based on predator and prey (lotka-Volterra)

Embed Size (px)

Citation preview

International Journal of Applied Environmental Sciences

ISSN 0973-6077 Volume 13, Number 1 (2018), pp. 27-38

© Research India Publications

http://www.ripublication.com

Modelling Interaction of CO2 Concentration and the

Biomass Algae Due to Reduction of Anthropogenic

Carbon Based on Predator-Prey Model

Ruly Budiono1, Hafizan Juahir2, Mustafa Mamat3,

Sukono4, Mohamad Nurzaman5

1,5Department of Biology, Faculty of Mathematics and Natural Sciences Universitas Padjadjaran, Bandung, Indonesia, 45363

2East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin,

Tembila Campus, 2200 Besut, Terengganu, Malaysia 3Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin

Tembila Campus, 2200 Besut, Terengganu, Malaysia 4Department of Mathematics, Faculty of Mathematics and Natural Sciences

Universitas Padjadjaran, Bandung, Indonesia, 45363

Abstract

The energy consumption produces 75% of Carbon Dioxide to the antropogenic

emission in the atmosphere. It causes a greatest impact in Climate change

during a recent century. These major factors lead not only scientist, but also

people all over the world to take into account in reducing the carbon emission.

One of the safest and sustainable ways to reduce the concentration of

anthropogenic carbon is to add a role of a biomass converter. Here, we

modeled the carbon consumption for the biomass production of phytoplankton

Nanochloropis oculata in a controlled fine-scale environment into simple

28 Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman

mathematical formulation based on predator and prey (lotka-Volterra) model.

We set him density of the biomass as ‘predator’ and the concentration of

carbon as ‘prey’. In the simulation result, the predator and prey model is fitted

with the data. The model is validated with the experimental data which will be

used for the provisional purposes that is to see the behavior of the

phytoplankton in reducing carbon in atmosphere. However, this is a

preliminary study that can be developed for further research.

Keywords: CO2 concentration, biomass energy, Nanochloropis oculata, predator and prey, mathematical modeling

INTRODUCTION

This research is intended to support the agreement reached in the climate change

conference in Paris, November 2015 (Paris Agreement) by 165 participating

countries. Where Indonesia is committed to reducing as soon as possible carbon

dioxide (CO2) emissions by 29% by 2030, or 41% reduction in carbon gas assisted by

developed countries in terms of limiting the average rise in global warming

temperature of 2̊ C and taking efforts to limit it to temperature average 1.5̊ C. With the

discovery of low-level plant species that quickly absorb / reduce carbon dioxide

emissions (CO2) waste so that carbon dioxide (CO2) wastes can be converted into

useful compounds in the plant body, which are renewable bioenergy / biofuel

feedstocks, food livestock, medicines, green economy-based oxygen producers [5].

The rapid absorption of carbon dioxide (CO2) emissions can support global warming

global warming. In the process of photosynthesis, the interaction of light, nutrients,

acidity (Ph), salinity, temperature and water can influence the growth rate of plants in

low levels so that the formation of compounds in plants maximum and carbon dioxide

(CO2) can be absorbed maximum. This supports the reduction of CO2 emissions can

be done transparently to support the carbon trading accounting system [4; 5].

One way to avoid and overcome the increase of carbon dioxide emissions is the

existence of an effort capable of fixation of carbon dioxide emission gas in the

atmosphere, using phytoplankton [1; 6]. Naturally green plants require (CO2) in the

air for photosynthesis. In addition to high levels of plants some types of

phytoplankton living in the sea and on land can also perform photosynthesis. Its great

potential as a raw material for renewable and renewable energy, phytoplankton may

also play a role in reducing atmospheric gas (CO2) emissions [10; 7].

Nannochloropsis sp. is a phytoplankton of a group of green algae. The cells are

ball-shaped with greenish color, small in diameter 2-8 μm [16; 17]. According to

Modelling Interaction of CO2 Concentration and the Biomass Algae Due… 29

Minillo et al. [11], mentions that the highest growth of Nannochloropsis sp. occurred

at pH 6.2-9.8. The pH range for growth of green phytoplankton is 7-9 .

In this research, test observations were performed to increase the production of cell

biomass Nannochloropsis oculata, by giving several concentrations of carbon dioxide

and different light intensity settings which can be judged most effective in its growth.

It is expected that this type of Nannochloropsis oculata can absorb and utilize carbon

dioxide effectively to increase the abundance of microalgae cell biomass, so as to

reduce carbon emissions in the atmosphere. With the application of photo bioreactor

technology and the use of different lights that are considered effective in supplying

media and culturing microalgae in the absorption of carbohydrate (CO2) gas both

during the day and night.

METHODOLOGY

Nanochloropsis oculata

Microalgae are the most primitive plant organisms that are resistant to

microorganisms, and live in all areas of sound, both fresh and marine. Microalgae are

classified as plants because they have chlorophyll and have a high-level cell network

[2]. The heat of nutrients that can be developed as a source of biodiesel feedstock

[10].

One type of microalga that can utilize carbon dioxide through photosynthesis is

marine microalgae namely Nannochloropsis sp. Described by Hernandes-Mireles et

al. [6] and Trevisan [15], that In addition to utilize CO2 from the atmosphere,

Nannochloropsis sp. is very important for humanity life. Nannochloropsis sp. can be

utilized to produce different types of biofuels or biofuels. Also explained by

Klinthong et al. [10], Nannochloropsis sp. has a high fat content that has the potential

to produce biofuel as an effort to handle the crisis of oil scarcity. In addition

Nannochloropsis sp. can become bioremediation. Bioremediation is the Restoration of

the environmental conditions of heavy metal pollution exploited by living creatures.

Nannochloropsis oculata is one type of marine microalgae that has an important role

in increasing the temperature of carbon dioxide CO2 exhaust gas [16]. Carbon dioxide

is capable of accelerating the growth of cell biomass content from Nannochloropsis

oculata. Using various types of light sources can be more effective in the

photosynthesis process of Nannochloropsis oculata because it corresponds to the

amount of energy that the microalgae can accept for its growth process [12; 14].

30 Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman

Experimental Study

The study was conducted in three stages consisting of: preparation stage including

Walne's medium manufacturing process, second stage including biomass harvesting

process, and lastly the calculation of carbon dioxide absorption absorbed by

Microalga Nannochloropsis oculata. Provision of fertilizer is done during cultivation.

Walne fertilizer is very beneficial for the growth of Nannochloropsis sp because

walne fertilizer contains vitamin B12 and B1 as well as trace elements with

composition ZnCl2, CaCl2, (NH4) 6, CuSO4 [13].

This test is done for 1 year. All tests are performed by repetition of 3 (three) times. The

treatment in this research is giving of Walne and vitamin fertilizer media. Walne doses

are used based on trials that have been done BBPBAP Jepara and the dose is commonly

used for culture Nannochloropsis sp. in the Natural Feed Division, Center for Brackish

water Aquaculture Development, Jepara

Data Analysis

The research method used a randomized block design (RAK) with four variables of

CO2 flow treatment i.e. CO2 15G / M / 1JAM / 3x, CO2 30G / M / 1JAM / 3x, CO2

60G / M / 1JAM / 3x and three treatment 4 intensity of fluorescent lamp lamp (TL)

9000 LUX, 7000 LUX, 3000 LUX and Indirect Sunlight. The growth and cell

biomass test of Nannochloropsis oculata using the Walne breeding nutritional

medium. Carbohydrate content was analyzed by luff schoorli method, fat with

soxhlex method, protein with Kjeldahl and Lowry method. Calculation of cell

abundance using Haemocytometre count method was followed by calculation of

specific growth rate miu μ [9]. The data obtained will be analyzed by statistical test,

with ANOVA test with 5% error rate. Thus, it can be known that the inhibition of

carbon dioxide (CO2) with various treatment of light source to growth.

Nannochloropsis oculata culture is conducted on a laboratory scale. During the

culturing process, N. oculata is highly dependent on the availability of temperature,

aeration, pH, nutrient formulas, light intensity, and carbon dioxide. With culture

media pH ranging from 8-9, with optimum pH 8.5-9. The intensity of light (lux) used

at 3000lux and 9000lux was performed on a 24 hour light treatment [10; 16].

Growth Test and Cell Biomass on Nannochloropsis oculata with Walne medium

Nannochloropsis oculata seeds as much as 1L with cell density of 1 x 106 cells / ml

cultured on culture container volume 2 L. Then given medium as culture growth with

Modelling Interaction of CO2 Concentration and the Biomass Algae Due… 31

medium Walne. The observation of the abundance of microalgae cells from each

study jar was done every day. The calculation of cell abundance using

Haemocytometer and microscope is observed for 24 hours once [2].

The content of dissolved carbon dioxide in water can be calculated using titration

method by Boyd in 1988. The calculation of abundance of microalga cells In addition

to calculating the abundance of microalgae cells, also calculated the specific growth

rate μ [9].

0

0ln(ln

TTNN

t

t

. (1)

Calculation of growth of phytoplankton cell Nannochloropsis oculata. N is density of

cell. C is constant improved neubauer (5.104)

CNND

2

)( 21 . (2)

Test Value Concentration of dissolved carbon dioxide Cell biomass in

Nannochloropsis oculata with medium Walne

Carbon concentration dissolved is calculated using following formula of Boyd in 1982.

VlpNm

2CO . (3)

Where m is the tittrant volume of NaOH, p is molarity of CO2, V and l is water

volume. N is constant (0.0227). While the biomass density are calculated using

following formula

)me(cultureolu

)drymass(Biomass

lgr

. (4)

The analysis was statistically performed by the ANOVA and Duncan test. ANOVA

(Analysis of Variance) test was conducted to determine the real effect of treatment on

the variables studied [9].

RESULT AND DISCUSSION

Nannochloropsis oculata culture is done on a laboratory scale. During the culturing

process, N. oculata relies heavily on the availability of temperature, aeration, pH,

nutrient formulas, light intensity, and carbon dioxide. With culture media pH ranging

32 Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman

from 8-9, with optimum pH 8.5-9. The intensity of light (lux) used at 3000 lux and

9000 lux was performed on a 24 hour light treatment.

By applying 15% CO2 concentration with CO2 gas flow rate (0.0199 g / l / m) at 180

buble / hour and 35% carbon dioxide injection with CO2 gas flow rate (0.0599 g / l /

l), speed 480 buble / hour, it is applied nutrition formula Walne every 2 days once as

much as 1 ml. Growth of nannochloropsis oculata performed for 21 days has

increased, with the number of cells abundance in each treatment has different values.

On the 3rd day until the 11th day, there is a steady increase with the condition of

almost balanced growth value, this phase is called lag phase. The lag phase is

characterized by an insignificant increase in density.

Figure 1. 15% CO2 concentration a gas flow rate (0.0199 g / l / m) at 180 buble / hour

and 35% carbon dioxide injection with CO2 gas flow rate (0.0599 g / l / l) speed 480

buble / hour. Performed nutrition formula Walne every 2 days once as much as 1 ml.

1.43

2.00

2.552.76

3.32

4.80

6.02 5.995.83

6.02

1.26

1.651.85

2.05

2.64

4.19

5.024.87

5.074.82

1.65 1.76

2.18 2.18

2.97

3.75

4.294.02

5.02 4.98

1.351.56

1.76 1.88

2.95

3.61

4.153.88

5.01 5.02

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

3th 5th 7th 9th 11th 13th 15th 17th 19th 21th

Average Growth Rate of Nannochloropsis oculata (million cells)

9000 lux (treatment) 3000 lux (treatment)

9000 lux (control) 3000 lux (control)

Modelling Interaction of CO2 Concentration and the Biomass Algae Due… 33

CO2 absorption by the Phytoplankton

Figure 2. CO2 Absorption by the phytoplankton for every light intensity

Based on the graph above, the concentration of dissolved carbon dioxide is directly

proportional to the cell biomass productivity. This means that the higher the

absorption of carbon dioxide the greater the rate of biomass productivity. And the

lower the uptake of carbon dioxide, the lower the biomass productivity. for best

growth occurs at carbon dioxide concentration 35% CO2 / 2kg CO2 with light

intensity 9000 lux in 1 l / minute yielded percentage of optimal absorbed CO2 that is

equal to 0,73245 g / l, and for treatment with concentration of 15% CO2 / 2kg CO2

with light intensity 3000 lux, that is equal to 0,5327 g / l. Meanwhile, for the

treatment of light intensity control 3000 lux and 9000 lux 0% CO2, no soluble carbon

dioxide uptake analysis was done with 0% CO2 percentage.

The results of Nannochloropsis oculata's ability to absorb carbon dioxide tend to be

good, compared with previous research, Okryreza et al. (2013), percentage of carbon

dioxide uptake in some fioplanktons, namely Chlorella vulgaris (0.551 g / l),

Chlamydomonas sp. (0.052 g / l), and Spirulina sp. of (0.891 g / l). It is known that

the highest percentage of carbon dioxide absorption (CO2) is Spirulina sp. which is

able to absorb carbon dioxide (CO2) optimally. This is possible, because Spirulina sp.

is a type of blue-green pigment algae that has better adaptability than Chlorella

vulgaris, Chlamdomonas sp. as well as Nannochloropsis oculata which is a green

0.73245

0.46611

0 0

0.98667

0.8

0.453330.4

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4

(g/l

)

Intensitas Cahaya (lux)

Relation between dissolved carbon and biomass production

Titrasi

Biomassa

Linear(Titrasi)

Linear(Biomassa)

34 Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman

pigmented algae. Based on these results, not the same as the results of research that

has been done by Klinthong et al. [10].

Effect of Light Intensity on Biomass Production Growth

Based on the results obtained from this study, increased production of biomass growth

occurs in the exponential phase. In the exponential phase occurs cell division up to

two-fold, so that from the optimal growth results, it can be known that the number of

biomass N. oculata is increasing. The highest biomass increase occurred in the final

exponential phase, i.e.on the 15th day at the treatment of 9000 lux 35% CO2 / 2kg

CO2 with an increase of 0.9867 g / l.

Figure 3. Biomass production in Exponential Phase

Meanwhile, for the lowest biomass increase occurred in the final exponential phase,

i.e. on the 15th day on the control treatment 3000 lux 0% CO2. By giving

concentration of optimal lux intensity, it is effective for the absorption process of

carbon dioxide as to increase growth rate and production of cell biomass

Nannochloropsis oculata. In accordance with the results obtained by Hirata et al.,

(1996) which mentions that the higher the intensity of light given the higher growth

rate of phytoplankton cells are consistent as well as to the maximum point.

Modelling the Experimental Data

Here, the Nanochloropis oculata has been experimented as the ‘Predator’ of the ‘Prey’

Carbon (CO2) Concentration to produce the biomass energy. The in vitro data of the

Modelling Interaction of CO2 Concentration and the Biomass Algae Due… 35

experiment is used for built a mathematical model based on Lotka-Volterra in 1926

[15]. In this work we propose a model to predict the increase of biomass density due

to CO2 concentration, considering the plant-atmospheric carbon interaction. Basically

we first obtain an experiment data considering the grows of the Nanochloropis oculata with controlled light density and evaporation. This data is then to be used for

built the mathematical model based on modification of Lotka-Volterra predator-prey

model. This research is to draws a provision of the interaction between the biomass

plant and the anthropogenic carbon in the atmosphere, with the equations is:

aCvNdtdC

. (5)

),( TLfNAeCdtdN

. (6)

We consider the carbon concentration as prey, while the biomass density is predator.

The carbon concentration (mg/l) is denoted by C which depends on adduction rate a (mg/days). The vegetal biomass distribution v is proportional to the density of

produced phytoplankton N (ppm). A (t) is the parameter related to the in vitro treatment such as the light density L and the temperature T. The T0 is room

temperature:

TT

bLTTLA0126

),(

. (7)

The sampled experimental data for 25 days is presented below (controlled light

density of 9000 Lux at room temperature (250).

Figure 4. The experimental data vs the predicted model

36 Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman

Based on the results obtained from the simulation, the proposed model may represent

the results of a carbon conversion experiment into biomass with plankton media. Can

be seen in experimental data of carbon concentration, the fit simulation model is near

perfect. On the other hand, biomass density simulation faces little problem in

emulating experimental data. This occurs because the biomass experimental data is

slightly anomalous in the modeling. There may be several in vitro factors during the

chemical treatment, in the experimental sample. However, in this real case it is within

reasonable limits.. More result can be seen in full paper

CONCLUSION

Based on the result of research, it can be concluded that: The higher concentration of

carbon dioxide and the intensity of light (lux) given the higher the rate of growth and

production of cell biomass Nannochloropsis oculata. Carbon dioxide concentration

35% CO2 / 2kg CO2 and light intensity 9000 lux effective in accelerating cell growth

rate of 6,025.000 cell / ml and increase cell biomass production rate of

Nannochloropsis oculata equal to (0,9867 g / l) with absorbance value equal to (1, 23

Abs). With the concentration of dissolved carbon dioxide (0.735 g / l). The

mathematical model has been proposed to the experimental data of CO2 by the

phytoplankton. The result shows that the model is well fitted for the first 21 days of

data. However, we need more data to validate the model in term of building a robust

model prediction.

ACKNOWLEDGEMENTS

We acknowledge to the Rector, Director of DRPMI, and Dean of FMIPA, Universitas

Padjadjaran, which has a grant program of the Riset Fundamental Unpad which

supports to increase research activities and publications to researchers at the

Universitas Padjadjaran.

REFERENCES

[1] Ali, A.M.A.S., Vignesh, S., Boomapriya, B., and Prasanya, D., 2016,

Feasibility Study on Carbon Sequestration Using Algae, International Research Journal of Engineering and Technology (IRJET), Volume: 03 Issue:

06 | June-2016. www.irjet.net.

[2] Aslam, A. and Mughal, T.A., 2016, A Review on Microalgae to Achieve

Maximal Carbon Dioxide (CO2) Mitigation from Industrial Flue Gases,

Modelling Interaction of CO2 Concentration and the Biomass Algae Due… 37

International Journal of Research in Advent Technology, Vol.4, Issue 9,

September 2016, E-ISSN: 2321-9637. Available online at www.ijrat.org

[3] Berge, T., Daugbjerg, N., and Hansen, P.J., 2012, Isolation and

cultivation of Microalgae Select for Low Growth Rate and Tolerance

to High pH, Harmful Algae, 20 (2012), 101 – 110. ww w.els evier.c o m/lo cat

e/hal.

[4] Cheng, W-H. and Chou, M-S., 2016, Optimization of Gas-Water Absorption

Equilibrium of Carbon Dioxide for Algae Liquors: Selection of Alkaline

Buffering Chemicals, Hindawi Publishing Corporation, International Journal of Photoenergy, Volume 2016, Article ID 2562638, 5 pages.

http://dx.doi.org/10.1155/2016/2562638.

[5] Erbach, G., 2016, The Paris Agreement A New Framework for Global Climate

Action. EPRS | European Parliamentary Research Service., PE 573.910.

[6] Gaikwad, R.W., Gudadhe, M.D., and Bhagat, S.L., 2016, Carbon Dioxide

Capture, Tolerance and Sequestration Using Microalgae A Review,

International Journal Of Pharmaceutical, Chemical And Biological Sciences

(IJPCBS) 2016, 6(3), 345-349. www.ijpcbs.com

[7] Hallegraeff, G.M. 2010, Ocean Climate Change, Phytoplankton Community

Responses, and Harmful Algal Blooms: A Formidable Predictive Challenge, J. Phycol. 46, 220–235 (2010), @2010 Phycological Society of America. DOI:

10.1111/j.1529-8817.2010.00815.x

[8] Hernandez-Mireles, I., van der Stel, R., and Goetheer, E., 2014, New

Methodologies for Integrating Algae with CO2 Capture, Energy Procedia

63 ( 2014 ) 7954 – 7958.

[9] Ibrahima, M., Skaugenb, G., and Ertesvåg, I.S., 2014, Modelling CO2 –Water

Thermodynamics Using SPUNG Equation of State (EoS) concept with

Various Reference Fluids, Energy Procedia 51 ( 2014 ) 353 – 362. Available

online at www.sciencedirect.com

[10] Klinthong, W., Yang, Y-H., Huang, C-H., and Tan, C-S., 2015, A Review:

Microalgae and Their Applications in CO2 Capture and Renewable Energy,

Aerosol and Air Quality Research, 15: 712–742, 2015. Copyright © Taiwan

Association for Aerosol Research, ISSN: 1680-8584 print / 2071-1409 online.

doi: 10.4209/aaqr.2014.11.0299

[11] Minillo, A., Godoy, H.C., and Fonseca, G.G., 2013, Growth Performance of

Microalgae Exposed to CO2, Journal of Clean Energy Technologies, Vol. 1,

38 Ruly Budiono, Hafizan Juahir, Mustafa Mamat, Sukono, Mohamad Nurzaman

No. 2, April 2013. DOI: 10.7763/JOCET.2013.V1.26

[12] Salih, F.M., 2011, Microalgae Tolerance to High Concentrations of Carbon

Dioxide: A Review, Journal of Environmental Protection, 2011, 2, 648-654.

doi:10.4236/jep.2011.25074 Published Online July 2011

(http://www.scirp.org/journal/jep).

[13] Sharmila,K., Ramya,S., and Ponnusami, B.A., 2014, Carbon sequestration

using microalgae-a Review, International Journal of ChemTech Research,

CODEN (USA): IJCRGG, ISSN : 0974-4290, Vol.6, No.9, pp 4128-4133,

September 2014.

[14] Singh, S.P. and Singh, P., 2014, Effect of CO2 Concentration on Algal

Growth: A Review, Renewable and Sustainable Energy Reviews, 38 (2014)

172–179. www.elsevier.com/locate/rser.

[15] Trevisan, L.A., 2008, Prey-Predator Modeling Of CO2 Atmospheric

Concentration, Working Paper, Departamento de Matemática e Estatística,

Universidade Estadual de Ponta Grossa, Avenida Carlos Cavalcante 4748.

[16] Van Wagenen, J., Miller, T.W., Hobbs, S., Hook, P., Crowe, B., and

Huesemann, M., 2012, Effects of Light and Temperature on Fatty Acid

Production in Nannochloropsis Salina, Energies 2012, 5, 731-740;

doi:10.3390/en5030731.

[17] Zhang, X., 2015, Microalgae Removal of CO2 from Flue Gas, IEA Clean Coal

Centre, April 2015, ISBN: 978–92–9029–572-3.