Vol. 12 | No. 4 |2306 - 2310| October - December | 2019
ISSN: 0974-1496 | e-ISSN: 0976-0083 | CODEN: RJCABP
http://www.rasayanjournal.com
http://www.rasayanjournal.co.in
KINETICS OF Chlorella sp GROWTH MODELS IN REDUCING
CO2 EMISSIONS
1
Okik Hendriyanto Cahyonugroho1,*, Dwi Dipta Yuniawati1
and Euis Nurul Hidayah1
Department of Environmental Engineering, University of Pembangunan Nasional “Veteran”
Jawa Timur, 60294, Indonesia
*E-mail: okikhc@upnjatim.ac.id
ABSTRACT
CO2 emissions resulting from human activities are relatively higher concentrations that disrupt the equilibrium
system in the air and ultimately damage the environment and human well-being. One environmentally friendly
solution for CO2 gas removal is to use microalgae (Chlorella sp.). Chlorella sp. in photobioreactors has the ability to
biofixate CO2 gas. Chlorella sp. was chosen because of the most numerous in freshwater and seawater. The purpose
of this study was to determine the kinetic model of the effect of adding substrate concentrations and flow rate
variations on the growth and development rates of Chlorella sp. due to exposure to pure CO2 gas emissions. This
study uses pure CO2 gas with a flow rate of 0.02 L/min, 0.04 L/min, 0.06 L/min, 0.08 L/min, 0.1 L/min and a
substrate of 350 mg/L, 500 mg/L, 650 mg/L, 800 mg/L, 950 mg/L on a laboratory scale. The results showed that the
most optimum growth rate occurred at the addition of substrate concentrations of 800 mg/L with a flow rate of 0.08
L/min.
Keywords: CO2 Emission, Chlorella sp, Photobioreactors, Kinetic Models
© RAS YAN. All rights reserved
INTRODUCTION
The phenomenon of global warming is characterized by a gradual rise in the average temperature of the
earth. Temperature changes occur in the long run slowly, but over time will be felt and have a big effect.
Increased global warming due to air pollution by high CO2. Where carbon dioxide is a colorless gas found
in the atmosphere with amounts reaching 330 ppm and most comes from burning fossil fuels.1
Research began in the 90s in anticipation of increasing flue gas globally directed to find solutions, one of
which was carried out using cyanobacteria and microalgae biological activity because of its reliability in
fixing CO2 through photosynthesis reactions with the help of light energy.2 Microalgae-based CO2
fixation technology that has been widely developed is photobioreactor technology.3 Photosynthesis is
generally defined as the process of forming new chemical compounds using light energy consisting of
light and dark reactions. During the light reaction, the light energy is captured, whereas in the dark
reaction that is the energy used to capture CO2 from the air.
Microalgae is the most efficient plant in capturing, utilizing solar energy, and CO2 for photosynthesis
purposes.4 Microalgae are single-celled microscopic plants that can absorb CO2 in an effort to reduce
concentrations of CO2 in the air.5 Carbon dioxide through the process of photosynthesis with the help of
sunlight is converted into oxygen, so that the amount of carbon dioxide that enters the system will be
reduced when it exits the microalgae system. Green cells such as leaves that contain lots of chlorophyll
which are used by algae to capture light to synthesize carbon sourced from carbon dioxide (CO2).
Microalgae can fix CO2 (10 - 50) times more efficient compared to plants.6 Microalgae breeding to obtain
high cell density is carried out in microalgae biotechnology with optimal reactor designs and processes.7
Chlorella sp. including one group of green algae which have a structure similar to plants, one of which is
a cell wall composed of cellulose. In this study, Chlorella sp. used because it is able to fix CO2, rapid
growth rate, as well as the production of biomass produced, is very beneficial for life.8
Rasayan J. Chem., 12(4), 2306-2310(2019)
http://dx.doi.org/10.31788/RJC.2019.1245439
Vol. 12 | No. 4 |2306 - 2310| October - December | 2019
Microbial growth is characterized by an increase in microbial cells due to the availability of nutrients. In
the previous studies2, to predict the relationship between the growth of Chlorella Vulgaris Buitenzorgwith
the substrate in the media is using a general equation model, one of which is the Monod equation model.
Microbial growth can be measured by looking at the increase in biomass or the number of cells usually
following a certain growth pattern in the form of a sigmoid growth curve (monod model). In order to
investigate the mechanism of sorption and potential controlling steps such as mass transport, several
kinetic models were tested including the pseudo-first-order kinetic model, the Elovich model and the
pseudo-second-order kinetic model for a batch contact time process9, but the monod equation is simpler
and is commonly used with the relationship of growth rate and substrate concentration.10 Kinetic studies
are needed to describe the efficacy of biosorption. It is necessary to recognize the mechanism of
biosorption.11 Therefore this study was conducted to determine the removal of CO2 gas by microalgae
(Chlorella sp.) Using photobioreactor technology with the Monod equation model to determine the
optimal CO2 absorption in microalgae (Chlorella sp.).
EXPERIMENTAL
This research was to determine the kinetic model of the effect of adding substrate concentrations and flow
rate variations on the growth and development rates of Chlorella sp. due to exposure to pure CO2 gas
emissions. The reactor used is a closed container with a diameter of 12 cm and a height of 18 cm with a
volume of 2 liters, then the reactor is placed on a stacked 5 rack. The reactor that contains microalgae is
supplied with CO2 gas with a predetermined CO2 flow rate for approximately 8 hours.
The running process is carried out when the reactor is ready and running based on the algal life cycle. At
the time of running, algae are expected to be in a homogeneous condition. Sampling is conducted every
hour during the CO2 exposure process. After that, chlorophyll-a testing was done using a
spectrophotometer to determine the biomass of microalgae in the reactor. During the running process, the
reactor must be closed so that the reactor is not contaminated by external light or other foreign matter.
RESULTS AND DISCUSSION
Growth Rate (µ)
The specific growth rate values (µ) (day-1) is obtained in Table-1.
Table-1: Specific Growth Rate Values (day-1) on Variations in Substrate Concentration and Flow Rate
µ (day-1)
Flow Rate
Substrate Concentration (mg/L)
(L/min)
350
500
650
800
950
0.02
0.8231
0.5624
0.2984
0.8031
0.3682
0.04
0.8231
0.2181
0.4004
0.379
0.6918
0.06
0.0854
0.2181
0.4004
0.379
0.6918
0.08
0.1503
0.1919
0.711
0.8375
0.6041
0.1
0.7497
0.0598
0.5207
0.302
0.3896
The table above shows that the highest coefficient of the linear regression is at the variation of flow rate
0.08 L/min for substrate concentration800 mg/L, while the lowest coefficient value is at the variation of
flow rate 0.06 L/min for substrate concentration350 mg/L. Low µ values indicate slow microalgae
growth, but low coefficient values can be influenced by cell density and differences in observation time.12
Fluctuations in the curve can also be caused by the sampling time of each reactor so that the growth
phases are not well observed. At the addition of a large substrate concentration of 950 mg/L can not
produce a high growth rate, this can be due to the substrate concentration can be an inhibitor for
microorganisms.
Growth Yield / Y Growth
Yield coefficient (Y) is the ratio of the amount of biomass production and the amount of substrate
concentration used.13 By plotting the value of Xm (maximum biomass) with substrate concentration (So),
2307
KINETICS MODELLING OF Chlorella sp.
O.H. Cahyonugroho et. al.
Vol. 12 | No. 4 |2306 - 2310| October - December | 2019
the results of Growth Yield (Y) can be obtained (Fig.-1) by knowing the straight-line equation with the
formed slope line is the Y value as shown in Table-2.
Fig.-1: The plot of Maximum Biomass (Xm) and Substrate Concentration on Flow Rate Variation.
Table-2: Growth Yield Value (Y) on Each Flow Rate Variation
Growth
Flow Rate
Equation
Yield (Y)
(L/menit)
0.02
Xm = 0.0001So + 0.9775
0.0001
0.04
Xm = 0.0002So + 0.8203
0.0002
0.06
Xm = 0.0002So + 0.9108
0.0002
0.08
Xm = 0.0003So + 0.8778
0.0003
0.1
Xm = 0.00004So + 1.1995
0.00004
The results showed that the greater the CO2 flow rates (from 0.02 L/min to 0.08 L/min), there was an
increase in the value of growth yield (Y) which reached 0,0001 to 0,0003. This indicates that the time of
CO2 exposure of 0.08 L/min, there was a large conversion of new cells with an increase in chlorophyll-a
concentration in algae. However, at the highest flow rate of 0.1 L/min has a small Y coefficient value
which is 0.00004. This is due to the excessive concentration of gas which can be a barrier for algal
growth.
Yield values indicate the amount of organic material that is converted into new cells.14 The greater the
flow rate used, the smaller the coefficient of Y. A high Y value does not always indicate a better
concentration of degradability because there are other factors that control the kinetics of biodegradation,
including enzyme activity and initial substrate concentration11.
Saturation Constants (Ks) and Maximum Growth Rate (µmax)
Ks value indicates the substrate concentration which has saturated with the growth of microorganisms.
The value of Ks depends on the type of microorganisms and the type of substrate used. The maximum
growth rate (µmax) is the maximum value of the growth rate at the peak point in the exponential phase
2308
KINETICS MODELLING OF Chlorella sp.
O.H. Cahyonugroho et. al.
Vol. 12 | No. 4 |2306 - 2310| October - December | 2019
before entering the stationary phase. The values of µmax and Ks in each flow rate variation can be shown
in Table-3.
Table-3: The Values of µmax and Ks in Each Flow Rate Variation
Flow rate
Equation
µmax
Ks
(mg/L)
0.02
1/µ = -642.49 1/S + 3.1788
0.315
202.117
0.04
1/µ = -114.12 1/S + 2.6748
0.374
42.665
0.06
1/µ = 5554.7 1/S + 5.0881
0.197
1091.704
0.08
1/µ = 3280.6 1/S + 2.4831
0.403
1321.171
0.1
1/µ = 1604.1 1/S + 2.8718
0.348
856.983
Table 3 shows that the optimum of µmax coefficients and Ks coefficients found in the CO2 flow rate of
0.08 L/min, which are 0.403 and 1321.171. That is because the substrate is in maximum concentration
and the growth of microalgae will experience saturation. At a flow rate of 0.1 L/min, it can be seen that
the coefficient µmax and the Ks coefficient have decreased by 0.348 and 856.983. This shows that
microalgae are experiencing burnout and are in a phase of decay. The greater the coefficient values of
µmax and Ks indicate the concentration of the substrate will experience saturation of the growth of
microalgae. Ks shows the saturation of substrate concentration on biomass growth.15 However (ks) was
unaffected by ionic strength since the reaction is taking place between charged and uncharged species.16
Based on the specific growth kinetics coefficient (µ), Growth Yield (Y), saturation constant (Ks) and
maximum growth rate (µmax) show the consistency that the CO2flow rate of 0.08 mg/L shows the
optimal coefficient value in the growth of microalgae Chlorella sp the CO2 absorption process.
CONCLUSION
From the results of the research and discussion that has been described, it can be concluded that the time
of exposure to CO2 gas with each variation of CO2 flow rate and the addition of substrate concentrations
affect the growth of Chlorella sp. with different growth phases, but the provision of high concentrations
of CO2 exposure and high substrate concentrations can be a barrier to the growth of the algae. The most
optimum value of chlorophyll-a concentration occurs at the addition of a substrate concentration of 800
mg/L with a flow rate of 0.08 L/min. Basically, the kinetic model parameters show the increasing growth
rate of Chlorella sp. in removing CO2 gas. Optimum CO2 removal conditions are found at a flow rate of
0.08 L/min and substrate concentrations of 800 mg/L which have optimal coefficients of µ, Y, Ks, and
µmax as well.
ACKNOWLEDGMENT
The financial support provided to this research by Research and Community Service Centre of University
Pembangunan Nasional Veteran Jawa Timur(RCSC-UPN Veteran Jawa Timur), Indonesia (Contract No.
SPP/95/UN.63.8/LT/V/2019) is greatly appreciated.
REFERENCES
1. A. Wijanarko, H. Hermansyah, M. Gozan, and B. A. Witarto, Biotechnology and Bioprocess
Engineering Journal, 11(6), 484(2006), DOI: 10.1007/BF02932071
2. A. Wijanarko, Dianursanti, B. A. Witarto, and W. R. Soemantojo, Makara Journal of Technology,
8(2), 35(2004), DOI:10.7454/mst.v8i2.254
3. O. H. Cahyonugroho, S. N. Nindhita., International Journal of ChemTech Research, 11(10),
08(2018), DOI: 10.20902/IJCTR.2018.111002.
4. Kasrina, S. Irawati, and Wahyu, E., Exacta Journal, 10(1), 36(2012)
5. A. Mulyanto, Indonesian Hydrosfir Journal. 5(2), 13(2010)
6. B.
Wang,
C.
Q.
Lan,
M.
Horsman,
Biotechnol.
Adv.,
30(4),
904(2012)
DOI:10.1016/j.biotechadv.2012.01.019
7. M. J. G. V. Barbosa, Ph.D Thesis,Wageningen University, Wageningen, The NetherlandWithsummary in Dutch, (2003).
2309
KINETICS MODELLING OF Chlorella sp.
O.H. Cahyonugroho et. al.
Vol. 12 | No. 4 |2306 - 2310| October - December | 2019
8. N. Sopiah, M. Adi, and S. Sindi, Journal of Environmental Technology, 14(1), 01(2013).
DOI:10.29122/jtl.v14i1.1431.
9. C. Sumithra and S. Karthikeyan, Rasayan Journal of Chemistry, 7(2), 149(2014).
10. Margono, H. Sulistyo, and Sumardi, Technical Forum, pp. 65-71,(2001).
11. P. P. Kumar, Y. P. Kumar, and B. V. Rao, Rasayan Journal of Chemistry, 10(3), 1025(2017), DOI:
10.7324/RJC.2017.1031683
12. Fahria, Thesis, Department of Environmental Engineering, Faculty of Civil Engineering and
Planning, National Development University, Surabaya, (2012),
13. Metcalf and Eddy, Inc., (1979), Wastewater Engineering Treatment Disposal Reuse, Mc Graw Hill,
Inc., New York. pp. 234-246.
14. Wahyu, S. Istiyantyo, C. K. Andri and Silviana, In Proceedings of the National Seminar on Chemical
Engineering. Bandung, Indonesia, pp. 143-150 (2014).
15. D. W.Septiani, A.Slamet, and J. Hermana, Pomits Engineering Journal, 15(3), 20(2014)
16. Salem Et. Ashoor, Fatma M. Ashoor and Noori Y. Salman, Rasayan Journal of Chemistry, 6(1), 1
(2013).
[RJC-5439/2019]
2310
KINETICS MODELLING OF Chlorella sp.
O.H. Cahyonugroho et. al.
Keep reading this paper — and 50 million others — with a free Academia account
Used by leading Academics
Richard Smardon
SUNY: College of Environmental Science and Forestry
Shivaji Chaudhry
Indira Gandhi National Tribal University, Amarkantak , India
Prof. Raimonds Ernsteins
University of Latvia
Roger Saint-Fort
Mount Royal University
