OPTIMIZATION OF BIOMASS PRODUCTIVITY AND CARBON DIOXIDE FIXATION ABILITY BY FRESHWATER MICROALGAE SCENEDESMUS BAJACALIFORNICUS BBKLP-07, A STEP TOWARDS SUSTAINABLE DEVELOPMENT

Microalgae carbon dioxide (CO2) sequestration has been recognized as a promising technology in the arena of sustainable development to mitigate CO2. The objective of the present study was to optimize the culture conditions for freshwater microalgae Scenedesmus bajacalifornicus BBKLP07. Response surface methodology (RSM) was used to analyze biomass productivity (R1) and CO2 fixation (R2) of microalgae Scenedesmus bajacalifornicus BBKLP-07 cultivated on media containing varying concentrations of CO2, nitrate and phosphate at different pH conditions. The predicted second-order quadratic model for response variables was significant (p < 0.01). Additionally, predicted R-squared values 0.7111 (R1), 0.8616 (R2) of quadratic model indicated the satisfactory fit of the model. On the basis of statistical analysis of results, CO2 concentration (15%), sodium nitrate (1.75 g/l/day), Di potassium hydrogen phosphate (0.06 g/l/day) and pH 7 i.e. C15N1.75P0.06H7, was found to be the best combination for maximum biomass productivity (0.93 g/l/day) and highest carbon dioxide fixation rate (0.13 g/l/day).


INTRODUCTION
Global warming has been reached to an alarming level due to the change in global environment. Industries related to natural gas processing, steel manufacturing, electricity generation, cement, iron and combustion of municipal solid waste are the chief contributors of atmospheric CO 2 because of their dependence on carbon sources like natural gas, coal, and oil (Inventory of U.S greenhouse gas emissions and sinks : 1990-2008). Increasing concentrations of gasses will increase the average surface temperature of the Earth by up to 6 o C during the 21 st century (IPCC-Fourth assessment report 2007). In the year 2004 global electricity consumption was observed to be 131,000 GW h (EIA -International Energy Annual 2004); roughly around 86% of energy derived from fossil fuels which released approximately 29,000,000,000 tons of CO 2 to the environment (Raupach et al. 2007). Gigantic use of fossil fuels has increased the atmospheric CO 2 concentration to 385-395 ppm during the 2008 (NOAA. Earth system research laboratory; 2007); and even if CO 2 emissions are somehow instantaneously halved, CO 2 concentration would still ascent upto 540 ppm, approximately twice pre-industrial level, within next 30-40 years. Microalgae have been distinguished as one of the most potential sustainable biomass reserves due to their carbon neutrality toward natural environment and easy cultivation (Amaro et al. 2011). Microalgae dominate conventional crops in having higher carbon dioxide uptake rate, higher growth rate and lipid content and smaller land usage. However, the use of microalgae for biofuel production is still not economically feasible. This is principally attributed to the energy and cost constraints coupled with the cultivation and harvesting of microalgal cells (Barros. 2015). However, physicochemical surface properties of microalgal cells play a significant role in influencing both cultivation and harvesting of microalgae (Ozkan and Berberoglu 2013). Several species of microalgae have been examined under CO 2 concentrations of over 15%. For example, Euglena gracilis could grow under 5-45 % concentration of CO 2 and the optimum growth was observed with 5% CO 2 concentration (Nakano. 1996). Chlorococcum littorale has been studied under 60% CO 2 using the stepwise adaptation technique (Kodama. 1994). Another high CO 2 tolerant Chlorella sp. could grow successfully under 10% CO 2 conditions (Hirata.1996a;1996b) and it was also reported that the same species can be grown under 40% CO 2 conditions (Hanagata.1992). Furthermore, Maeda (1995) reported that a strain of Chlorella sp. T-1 can be grown under 100% CO 2 , even though the highest growth rate was observed under a 10% concentration. Scenedesmus sp. could grow under 80% CO 2 conditions but 10-20% CO 2 concentration was optimum (Hanagata. 1992). Cyanidium caldarium (Seckbach. 1971) and some other species of Cyanidium can grow in pure CO 2 (Graham and Wilcox 2000).
In previous study, Scenendesmus bajacaliforncus BBKLP-07 strain had been isolated from freshwater ponds of Bagalkot district, which is a highly CO 2 tolerant (Patil and Kaliwal 2016). The present investigation was focused on optimizing the culture conditions such as CO 2 concentration, nitrate, phosphate concentrations and pH. For this purpose, a mathematical model response surface methodology (RSM) was adopted. Central Composite Design (CCD)/ RSM explores the relationships between several explanatory variables (CO 2 , nitrate, phosphate and pH) and one or more response variables (Biomass productivity-R1 and CO 2 fixation rate-R2). RSM not only optimizes the process but also reduces cost and time required for experimentation by reducing the number of trials to be performed in laboratory. Additionally, RSM identifies optimal conditions of several variables in single set of experimental combination. Because of these advantages, RSM has been utilized in many ways for optimization of various parameters.

Microorganism
Scenedesmus bajacalifornicus BBKLP-07 was isolated from freshwater ponds of Bagalkot District, Karnataka, India through repeated streak plate method on BG-11 medium at pH 7.1 (Patil and Kaliwal. 2016). The cells have a parietal chloroplast with a single pyrenoid, and walls are unornamented with knobby cell apices at the ends. Purity was checked through microscopic observation at regular intervals and pure cultures were maintained at 27 ± 3 o C temperature and 40 µmol/m 2 /sec light intensity in culture room.

Response Surface Methodology (RSM)
Optimization of CO 2 , nitrate, phosphate and pH levels for different response variables, such as biomass productivity (R1), CO 2 fixation rate (R2) was done using statistical approach. For this, experiments were designed using Response Surface Methodology in Design expert version 10.0.4.0 (Statease Inc., Minneapolis, USA, trial version) and estimated the coefficients of a quadratic model using Box-Behnken design type. RSM was categorized in two models. First order model investigates linear relationship of response with its two independent variables and second order model, investigates a curvature on the response surface due to two or more than two variables (Kirana. 2016). An impressive feature of RSM is the designing of experiments with minimum number of combinations. The principle of response surface is based on the selection and identification of points having significant effect on responses. A full factorial approach is required to construct a model that can interact with and between 'n' number of variables and for analysis of all possible combinations. Factorial experiment is an approach in which combined effect of designed variables under various combinations can be studied by designing the variables simultaneously. Lower and upper limits of each of the variable were defined, as every variable is defined only at lower and upper boundary (i. e. two levels), then experimental design is known as 2 N full factorial. 2 N factorial design augmented with center(η 0 ), factorial (F) and axial points (star points, represented as A). Factorial points (F) represents a variance in optimal design for first order model whereas center point presents information concerning presence of curvature in the system. If curvature is present in the system, the axial points are included for the competent assessment of pure quadratic model and these points remain equidistant from each other providing rotatability to the model. In the present investigation, each factor was designed with 3 coded levels ( 1, 0, +1) as given in Table 1. The number of experiments in CCD can be calculated as: Equation (1) where, n = number of experiments, F = Factorial points, A = star points and η 0 = center point.
In the present study 29 experiments were performed as designed through Deign Expert version 10 (trial version) to study the effect of varying CO 2 concentration (%), nitrate (NaNO 3 ), phosphate (K 2 HPO 4 ), pH levels and various combinations of input variables provided by software are designated with suitable codes as presented in Table 2. Scenedesmus bajacalifornicus BBKLP-07 was cultivated in 100 ml autoclaved BG-11 media with modified levels of nitrate and phosphate in 250 ml conical flasks and the initial inoculum cell concentration was maintained as 2 x 10 7 cells/ml. Cultures were cultivated in shaker at 100 rpm speed and 34 µmol/m 2 /sec light intensity with 24hr photoperiod for 15 days.
The CO 2 optimization studies were carried out using the protocol given by Vidyashankar. (2013). For CO 2 optimization carbon dioxide from a pressurized cylinder was mixed with air pumped by a vacuum pump. Gases were mixed in a tee container, and then, the concentration of carbon dioxide in the introduced gas was calibrated using a Model 410i carbon dioxide gas analyzer Thermo Scientific (measurement range of 0 to 25 vol%). The gas was then introduced into the culture medium at a constant aeration rate of 0.26 vvm (volume gas per volume culture per min).

Determination of biomass productivity
Maximum biomass productivity (P max , g/l/day) was estimated from Eq. (2), where X t was the biomass concentration (g/l) at the termination of the cultivation period (t x ) and X 0 the initial biomass concentration (g/l) at t 0 (day) (Mariana. 2013).
Where C C was the carbon content of microalgal cells (% w/w), analysed by using a LECO CHNS-932 Elemental Analyser (USA), P max was the maximum biomass productivity (g/l/day), M CO2 was the molar mass of CO 2 (g/mol) and M C was the molar mass of carbon (g/mol).

Preparation of sample for Fourier transform infrared spectroscopy (FTIR)
50 ml of microalgal sample from optimized culture conditions was subjected to centrifugation at 3000 rpm for 10 min. The pellet was washed with double distilled water to eliminate any residue due to nutrient medium and was again pelletized by centrifugation (3000 rpm, 10 min). Samples was frozen overnight and freeze dried at 55 o C. From the harvested and dried biomass, approximately 2-3 mg of sample was mixed with potassium bromide (KBr) and subjected to a pressure of about 8 × 106 Pa to obtain clear disc of 13 mm diameter, 1 mm thickness and examined using FTIR spectrometer (Bruker Optics TENSOR 27). Spectrum was developed with a DTGS detector over a wavelength of mid-IR region (4000 to 500 cm 1 ). Empty ATR plate was practiced for background single beam spectra and the result was analyzed using OPUS control software.

Statistical analysis
All the experiments were carried out in accordance with set of conditions offered through Design Expert 10 (Table 2).
Noteworthy differences were determined by using examination of variance (ANOVA). Second order quadratic model was used to estimate the effect of CO 2 concentration, nitrate, phosphate levels and pH on response variables through following equation: Ri=0+c 1 A+c 2 B+c 3 C+c 4 D+c 12 AB+c 13 AC+c 14 AD+c 23 BC+c 24 BD +c 34 CD+c 11 A 2 +c 22 B 2 +c 33 C 2 +c 44 D 2 Equation (4) where Ri is Response variable; A, B, C and D are Independent variables i.e. CO 2 , nitrate, phosphate and pH, respectively; c 0 is intercept term; c 1 , c 2 , c 3 and c 4 are linear terms; c 11, c 22 , c 33 and c 44 are quadratic terms; c 12 c 13 c 14 c 23 c 24 and c 34 are interaction terms.

Central composite design / Response study
Observed and predicted values of CO 2 fixation rate and biomass productivity are presented in Table 3. To study the surface response for biomass productivity and CO 2 fixation rate by CCD, a quadratic model was studied with factors A, B, C, D, AB, BC, AC, AD, BD, CD, A 2 , B 2 , C 2 , D 2 and intercept, which were analyzed as a function of the model (Table 4). Where A, B, C, and D represent CO 2 nitrate, phosphate and pH level, respectively. The quadratic model predicted for the response variable R1 (biomass productivity) and R2 (CO 2 fixation rate) were found statistically valid. ANOVA was utilized for assessment of factual noteworthiness of every quadratic model. Reaction factors were examined utilizing coefficients. p-Value was utilized to concentrate the coefficient relationship with its separate error. smaller p-value proposes the bigger estimation of coefficient when contrasted with error; along these lines, guaranteeing the non-understanding of observed data and the null hypothesis.
The concluding quadratic equation for the response variable was established where positive sign before coefficient indicates a synergistic effect of a factor towards response and negative sign suggests an antagonistic effect. The quadratic model predicted for biomass productivity (R1) and CO 2 fixation rate (R2) using significant coefficients is given as:  (6) Factual importance was checked by Analysis of variance (ANOVA) and Analysis of variable factors (f test) for the recommended model and affirmed as significant with low pvalues (P value <0.0001 for both biomass productivity and CO 2 fixation rate), showing the high certainty level. Importance of the model was affirmed by linearity between normal probability graphs i.e. the predicted value is in great concurrence with observed value (Fig 2 A and B). The predicted values of response demonstrated sensible concurrence with experimental values in this manner uncovering the centrality of model for every response variable. Three dimensional graphs mirror the impact of fluctuating concentrations of CO 2 and nitrate (A), CO 2 and phosphate (B), pH and CO 2 (C), and nitrate and phosphate (D) on biomass productivity (R1) and CO 2 fixation rate R2 (Fig 3 and 4) individually. Most elevated biomass productivity (0.93 g/l/day) and CO2 fixation rate (0.13 g/l/day) were found at C 15 N 1.75 P 0.06 H 7 . Hence, this condition (i.e. C 15 N 1.75 P 0.06 H 7 ) is viewed as ideal for high biomass productivity and CO 2 fixation rate.

Effect of nutritional parameters on biomass productivity (R1) and CO 2 fixation rate (R2)
The present investigation reveals that the predicted values of response showed reasonable agreement with experimental values thus revealing the significance of model for each response variable. The effect of varying CO 2 concentration, nitrate, phosphate and pH levels on response variables i.e biomass productivity (R1) and CO 2 fixation rate (R2) is depicted in the perturbation graphs (Fig 1). The optimum response variable values for Biomass productivity as well as CO 2 fixation rate were 15% CO 2 , 1.75g/l nitrate, 0.06 g/l phosphate and pH 7. The maximum biomass productivity (0.93 g/l/day) and CO 2 fixation rate (0.13 g/l/day) were obtained with the above-mentioned variables. The predicted and observed response at optimal condition (C 15 N 1.75 P 0.06 H 7 ) were tabulated in table 5.

CO 2 concentration
The CO 2 concentration played a very important role on growth parameters of microalgae isolates. It was observed that the 15% CO 2 concentration was found to be optimum for the culturing of microalgae Scenedesmus bajacalifornicus BBKLP-07. The highest biomass productivity and maximum CO 2 fixation rate were 0.93 g/l/day and 0.13 ± 0.002 g/l/day at 15% CO 2 concentration respectively at pH 7. The minimum biomass productivity and lowest CO 2 fixation rate were 0.35 g/l/day and 0.01 ± 0.002 g/l/day at 5% CO 2 concentration respectively at pH 5. As the concentration of CO 2 increases in the media, the biomass productivity as well as CO 2 fixation rate is elevated up to 15% CO 2 and further increase in the CO 2 concentration lead to decrease in biomass productivity as well as CO 2 fixation rate.

Nitrate and phosphate
Studies showed that the effect of nitrate and phosphate on biomass productivity and CO 2 fixation is insignificant. Even though the optimal conditions for the microalgal growth were C 15 N 1.75 P 0.06 H 7 , nitrate has very little effect on biomass productivity. Biomass productivity was found to be maximum at nitrate concentrate N 1.75 (0.93 g/l/day) at 15% CO 2 ,whereas the biomass productivity was found to be 0.6 g/l/day at C 15 N 0.5 P 0.06 H 5 levels and 0.42 g/l/day at C 15 N 3 P 0.06 H 5 levels. CO 2 fixation was not affected by nitrate concentration. Similarly, phosphate doesn't appear to have any effect on biomass productivity as well as CO 2 fixation.

pH
The pH has a very significant effect on biomass productivity and CO 2 fixation. At low pH 5, biomass productivity and CO 2 fixation rate were very minimum in all the studied experimental conditions whereas at high pH 9, biomass productivity and CO 2 fixation rate were moderately increased. Maximum biomass productivity and CO 2 fixation rate were found to be 0.93 g/l/day and 0.13 g/l/day at pH 7.
The results indicate that pH 7 was optimum for the growth for microalgae Scenedesmus bajacalifornicus BBKLP-07.

FTIR analysis
Recognizable proof depends on examination of the groups of the recorded FTIR spectra with those of a reference literature. The FTIR transmittance of the Scenedesmus bajacalifornicus BBKLP-07. algal species uncovers the proximity of -OH, -COOH, NH 2 , and CO groups in the natural compound; aliphatic compounds: (500-800 cm -1 ), phenols and alcoholic compounds (1000-1500 cm -1 ), carboxyl compounds (1500-1700 cm -1 ), hydroxyl compounds (3200-3,450 cm -1 ). The band at 3410 cm -1 is expected to the O-H stretching vibration. The frail bands focused at 2925 and 2847 cm -1 are because of the nearness of asymmetric C-H stretching vibration.
Three unique groups were seen in the region of 1735, 1646, and 1455 cm -1 , which reveals the nearness of esters in the microalgae.

Central composite design / Response surface methodology
In statistics, RSM investigates the associations between quite a few illustrative variables and at least one response variables. The primary thought of RSM is to utilize a sequence of designed experiments to get an optimal response. RSM uses a second-degree polynomial model to perform the optimization. The experimental variables and responses were selected according to Box-Behnken design type (Box and Behnken 1960). Each independent variable is placed at one of three equally spaced values, usually coded as 1, 0, +1. The design is sufficient to fit a quadratic model, that is, one containing squared terms, products of two factors, linear terms and an intercept.
In the present four illustrative variables i.e CO 2 concentration (A), nitrate (B), phosphate (C) and pH (D) were used for the optimization of two responses i.e biomass productivity (R1) and CO 2 fixation rate (R2). The optimized conditions were found to be 15% (A), 1.75 g/l (B), 0.06 g/l (C) and 7 (D) and the maximum responses observed were 0.93 g/l/day (R1) and 0.13 g/l/day (R2). Similar studied have been performed by Kim . (2012) where they have optimized the culture conditions for biomass productivity of three different microalgae Chlorella sp., Dunaliella salina DCCBC2 and Dunaliella sp., and estimated the optimal growth conditions for Chlorella sp.
(initial pH 7.2, ammonium 17 mM, phosphate 1.2 mM), D. salina DCCBC2 (initial pH 8.0, nitrate 3.3 mM, phosphate 0.0375 mM) and Dunaliella sp. (initial pH 8.0, nitrate 3.7 mM, phosphate 0.17 mM). The biomass productivities were 0.28, 0.54 and 0.30 g dry cell wt /l and the CO 2 fixation rates were 42.8, 90.9 and 45.5 mg/l/day respectively. RSM have been also  used for the optimization of lipid and biomass productivity of Oocystis sp. IM-04, where the variable parameters studied were temperature, nitrate and phosphate levels (Kirana. 2016;Satapute. 2012). The highest lipid productivity (7.0 mg/l/day) and biomass productivity (47.8 mg/l/day) were reported for the optimized culture conditions of sodium nitrate (750 mg/l), Di potassium hydrogen phosphate (0 mg/l) at 30 o C temperature. Statistical methods such as RSM has been used to standardize the production process of a special substance by optimization of operational factors with respect algal species (Berges. 2002).

CO 2 concentration
The CO 2 concentration assumed an imperative part on growth parameter of microalgae S. bajacalifornicus BBKLP-07. The microalgae detach S. bajacalifornicus BBKLP-07 demonstrated an extensive variety of CO 2 resilience capacity. It was examined that the 15% CO 2 conentration was observed to be ideal for the growth of microalgae S. bajacalifornicus BBKLP-07. The biomass productivity and CO 2 fixation were at peak at 15% CO 2 fixation. The greatest rates of biomass productivity and CO 2 fixation rate were 0.93 g/l/day and 0.13 g/l/day respectively. Fifteen percent CO 2 was basic for microalgal growth; Riebesell. (1993) has expressed that when CO 2 is underneath a critical concentration, algal growth gets to be distinctly constrained. This critical concentration not just relies on upon the rate of CO 2 supply and CO 2 affinity but also on cell size, growth rate, and conceivable nearness of extracellular carbonic anhydrase. Comparative outcomes were seen in case the of Scenedesmus obtusus, in which the microalgae demonstrated a maximum biomass productivity was observed at 15% CO 2 concentration and no noteworthy distinction in the biomass productivity was observed. However, critical concentrations of CO 2 for CO 2 fixation and biomass productivity were different for different microalgae species. The Chlorella sp. and Scenedesmus sp., isolated from a coalfired thermoelectric power plant exhibited maximum biomass productivity at 6 and 12% CO 2 respectively (Morais and Costa 2007); it is because of the fact that they require higher CO 2 concentration to fulfill their carbon demands (Burkhardt. 1999). Yang and Gao (2003) reported three species having contrasting cell shape and size i.e Chlormadinones reinhardtii and Chlorella pyrenoidosa with circular cell shape and S. obliquus with spindle shape having varying demands of CO 2 concentration to saturate the growth. The enhancement of growth rate with increased CO 2 is probably related to lower energy consumption. Lee. (1998) recommended hoisting the underlying cell density as an option way to deal with increment the tolerance against high levels of CO 2 and lessen the long adjustment time period.

Nitrate and phosphate
Nitrate and phosphate have a very insignificant effect on the biomass productivity as well as on CO 2 fixation rate of Scenedesmus bajacalifornicus BBKLP-07. However, phosphorous is known to have a significant role in cellular metabolic processes of microalgae. Several reports suggest that high concentration of phosphate and nitrate affects the biomass production in Scenedesmus dimorphus KMITL (Ruangsomboon. 2013, Mandal andMallick 2009). Thus, the present study indicates that the effect of nitrate and phosphate on biomass productivity and on CO 2 fixation rate of microalgae Scenedesmus bajacalifornicus BBKLP-07 is insignificant.

pH
The role of pH on biomass productivity and CO 2 fixation is highly significant. In the present study pH 7 is observed to be optimum for the microalgal growth and CO 2 fixation, deviation in pH from 7 demonstrated adverse effect on S. bajacalifornicus BBKLP-07 biomass productivity and CO 2 fixation rate. The maximum biomass productivity and CO 2 fixation rate were 0.93 g/l/day and 0.13 g/l/day. However similar studies have been reported where Chlorella sp., have exhibited optimum growth conditions at pH 7.2, Dunaliella salina DCCBC2 and Dunaliella sp., have been exhibited maximum gowth at pH 8. The CO2 fixation rates of Chlorella sp., D. salina DCCBC2 and Dunaliella sp. were 42.8, 90.9 and 45.5 mg/l/day, respectively (Kim. 2012). The studies on C. reinhardtii showed that pH of 7.5 is optimum for microalgal growth however, excess CO 2 inhibited algae growth due to a significant decrease in pH (Kong. 2010). Contradictory reports suggest that biomass production by Scenedesmus obliquus and Chlorella vulgaris in laboratory cultures was significantly affected by the pH at which the cultures were preserved. Carbon fixation experiments exhibited that pH values in the range of 8 to 9 were important for influencing the free CO 2 concentrations in the medium (Azova 1982).

FTIR analysis
Fourier transform infrared (FTIR) spectroscopy is a novel method for monitoring carbon allocation in microalgae. This form of vibration spectroscopy can be used to collect midinfrared absorbance spectra from air dried, intact microalgal samples. When applied to whole organisms the resulting spectrum reflects the biochemical complexity of the cells, with absorbance bands from lipids, nucleic acids, carbohydrates and proteins. The FTIR transmittance of the Scenedesmus bajacalifornicus BBKLP-07. algal species reveals the nearness of -OH, -COOH, NH 2 , and CO groups in the microalgae; aliphatic compounds: (500-800 cm -1 ), phenols and alcoholic compounds (1000-1500 cm -1 ), carboxyl compounds (1500-1700 cm -1 ), hydroxyl compounds (3200-3,450 cm -1 ). The band at 3410 cm -1 is expected to the O-H stretching vibration. The frail bands focused at 2925 and 2847 cm -1 are because of the nearness of asymmetric C-H stretching vibration. Three unique groups were seen in the region of 1735, 1646, and 1455 cm -1 , which reveals the nearness of esters in the microalgae.

CONCLUSIONS
CO 2 , nitrate, phosphate and pH have their individual and independent effect on biomass as well as on CO 2 fixation ability of Scenedesmus bajacalifornicus BBKLP-07. Utilization of RSM based CCD approach for determination of optimum growth levels proved to be an efficient and effective method. It is concluded that predicted values by quadratic model lies in close proximity with experimental values. Thus, for high CO 2 fixation and biomass productivity, process conditions optimized through CCD i.e. C 15 N 1.75 P 0.06 H 7 for Scenedesmus bajacalifornicus BBKLP-07 are more suitable as compared normal BG-11 media. Since, optimal quantity of biomass was achieved at pH 7, therefore deflection in pH is not a prudent approach related to biomass production. Exploitation of such optimized system for bioprocess engineering will not only result in high CO 2 sequestration but also will lead to high biomass in Scenedesmus bajacalifornicus BBKLP-07. Still further research is required to study and explore the impact of pilot scale studies in open/closed environment on the efficiency of this species in terms of CO 2 fixation and biomass productivity.

Conflict of interest
Authors do not have any conflict of interest related to the manuscript.

Ethical approval
This article does not contain any studies related to animals and human participants.