Using Cyanobacteria and Prospect of Biofuel ... - ACS Publications

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Enhanced Biomass Recovery During Phycoremediation of Cr(VI) Using Cyanobacteria and Prospect of Biofuel Production Deepika Kushwaha,† Suman Saha,‡ and Susmita Dutta*,‡ †

Department of Earth and Environmental Studies, National Institute of Technology Durgapur, Durgapur, West Bengal 713209, India Department of Chemical Engineering, National Institute of Technology Durgapur, Durgapur, West Bengal 713209, India

‡

ABSTRACT: Utilization of cyanobacteria for remediation of pollutants and thereby large production of microalgae for sustainable biofuel production is a practicable option. In the present study, a cyanobacterial consortium of Oscillatoria subbrevis and Gloeocapsa atrata, collected from East Kolkata Wetland, a “Wetland of International Importance”, has been used for removal of Cr(VI) from simulated wastewater and the effect of Cr(VI) on biomass production was investigated. The Monod model has been used to depict growth kinetics of the cyanobacterial consortium in pure media. Maximum specific growth rate and saturation constant have been found to be 0.1562 day−1 and 0.024 g/L, respectively. The kinetic study on Cr(VI) removal shows that biomass and lipid production are more when the cyanobacterial consortium have been cultured in wastewater containing Cr(VI) than in pure media. The growth of the cyanobacterial consortium in relation to Cr(VI) removal as well as lipid production has been optimized using response surface methodology. Optimum metal removal has been achieved when initial Cr(VI) concentration, pH, inoculum size, and time are 11.08 ppm, 9.0, 0.39 g, and 9 days, respectively.

1. INTRODUCTION

Heavy metals are nonbiodegradable, have a recalcitrant nature, and can accumulate in different ecological systems. Biosorption and bioaccumulation of heavy metals have been recognized as a potential alternative to the conventional methods for treatment of contaminated wastewater.7 Biosorption is a metabolically independent mechanism of pollutant removal while bioaccumulation is a metabolically dependent technique. It is of great interest to use cyanobacterial strains for treatment of industrial wastewater containing heavy metals. Cyanobacterial biosorbents have been found to be significant because of their enhanced biomass production, comparatively less nutrient requirements, and usually nontoxic characteristics.8 The cell wall in conjunction with the external mucilaginous sheath consists of a number of ligands with various functional groups giving the sites for binding several metallic ions.8 Cyanobacteria have been proved as a potential biosorbent due to the presence of polysaccharides, proteins, or lipids on the surface of their cell walls.9 Furthermore, the presence of a negative charge on the cell wall of cyanobacteria makes them a strong contender for treatment of heavy metal laden wastewater.2 Chromium being the seventh most abundant element on the earth exists in two oxidation states, namely, trivalent chromium (Cr3+, Cr(OH)2+, etc.) and hexavalent chromium (HCrO4−, CrO42−, Cr2O72−, etc.).10 Cr(VI) is known to be more toxic than Cr(III) due to its high solubility and mobility.11 According to the World Health Organization (WHO), the maximum permissible limits for Cr(VI) and total chromium in potable water are 0.05 and 2 ppm, respectively.12 Chromium may be introduced to the water bodies through the

As the demand for energy has increased globally, consumption of fossil fuel has also been increased. Over 65% of the world’s electrical energy used today is generated by steam turbine generators burning fossil fuels as their source of energy. Excessive utilization of fossil fuels is not a practicable option for long-term issues, such as greenhouse gas emissions, climate change, fossil fuel depletion, and energy security.1 Thus, a renewable energy resource having lower environmental impact is required. Microalgae are one of the most vital natural sources that are presently getting lots of interest due to a number of reasons.2 Microalgae are efficient and play a dual role of treating industrial wastewater, predominantly for the removal of heavy metals and organic pollutants, and being essential for growth, lead to enhanced biomass and lipid production. Therefore, utilization of microalgae for remediation of pollutants and thereby large production of biomass for sustainable biofuel production, such as alcohol production through fermentation, producer gas generation through gasification, etc., is a practicable option. Concentrations of several heavy metals have been shown to be reduced by cultivation of microalgae.2 Biomass can be used for biofuel production whereas the lipid of microalgae is the only source of biodiesel. Thus, utilization of microalgae for wastewater treatment is beneficial from three perspectives. First, environmental pollution can be subsided; second, the usage of wastewater as nutrients offsets the environmental burdens associated with algal growth and thereby the net energy ratio (NER) will be increased,3 and third, the enhanced biomass or lipid can effectively be used for biofuel generation and, thus, direct toward reduction in the consumption of fossil fuel and emission of greenhouse gases. Though few works have been carried out in this area,2,4−6 no comprehensive study to show quantitatively the effect of pollutants on the biomass or lipid content of algal biomass has been reported to date. © XXXX American Chemical Society

Special Issue: Energy System Modeling and Optimization Conference 2013 Received: March 29, 2014 Revised: August 7, 2014 Accepted: September 11, 2014

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dx.doi.org/10.1021/ie501311c | Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

Industrial & Engineering Chemistry Research

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Collected strains were cultivated in the pond water for 7 days and then transferred in basal media. Chu-10 media (NaNO3· 4H2O: 0.232 g; K2HPO4: 0.01 g; MgSO4·7H2O: 0.025 g; Na2CO3: 0.02 g; Na2SiO3·5H2O: 0.044 g; ferric citrate: 3.5 mg; citric acid: 3.5 mg; distilled water: 1000 mL) was selected for the growth of algal strains. They were cultured at 2400 lux light intensity and at 20 ± 4 °C temperature. Collected strains have then been identified as the cyanobacterial consortium of Oscillatoria subbrevis and Gloeocapsa atrata from Botanical Survey of India, Ministry of Environment and Forests, Kolkata, India. 2.2. Characterization of Cyanobacterial Biomass. Scanning electron microscopy was done for topographical characterization of the test cyanobacterial consortium before and after Cr(VI) removal. The samples were prepared and brought into the SEM unit (HITACHI S-3000N, Japan) under vacuum. The photographs were taken at the required magnification at room temperature. The secondary electron image (SEI) was used as a detector. The working distance and acceleration voltage were maintained at 25 mm and 15 kV, respectively. 2.3. Batch Study of Growth. Cyanobacteria are nonmotile and photoautotrophic. They can be grown easily in laboratory conditions. For the preparation of the inoculum, cyanobacterial cells cultivated in Chu-10 media were centrifuged at 5000 rpm for 10 min (eltek, TC 8100 F, India). An appropriate amount (0.1 g) of inoculum was transferred to a 100 mL Erlenmeyer flask containing 50 mL of autoclaved Chu-10 media under aseptic conditions using a Biosafety cabinet. Strains were incubated for 16 days maintaining the conditions as mentioned in Section 2.1. Sample broth was collected after a 2 day interval and centrifuged at 5000 rpm for 10 min. Cyanobacterial mass obtained by centrifugation of sample broth was analyzed in terms of dry biomass and chlorophyll and lipid contents separately. The collected sample was kept at 60 °C in a hot air oven overnight to obtain dry biomass. Chlorophyll and lipid contents of sample were analyzed by using the Jeffrey and Humphrey method14 and Folch method,15 respectively. To study the effect of media pH on the growth of the cyanobacterial consortium, a set of 100 mL flasks containing 50 mL of autoclaved growth media inoculated with an equal amount of cyanobacterial consortium was used. The initial pH of the media was varied from 3−11 by using 1 N HCl and 1N NaOH. HCl (35%, AR grade) and NaOH flakes were supplied by MERCK, India. The experiment was conducted for 16 days, and samples were collected from the flask after a 2 day interval. Dry biomass and chlorophyll and lipid contents have been determined experimentally from each sample individually following the protocol as mentioned above. 2.4. Modeling of Growth Kinetics and Determination of Kinetic Parameters for Growth of Cyanobacterial Biomass in Pure Media. Macronutrients such as nitrogen and phosphorus and micronutrients such as iron and molybdenum are known to play a major role in regulating the metabolism and ultimately the growth of cyanobacteria.16 In the present investigation, nitrate ion (NO3−) was considered as the growth limiting substrate. NaNO3·4H2O, the sole source of nitrate ion (NO3−) in media, was varied during batch experimentation in the range of 0.05−0.6 g/L keeping other compositions constant as prescribed in the Chu-10 medium. The cyanobacterial consortium was grown in several flasks containing different amounts of NaNO3·4H2O. The volume of media in each flask was maintained at 50 mL. The maximum period of growth was 16

discharge of untreated or improperly treated wastewater coming from different industries such as textile, tanning, mining, electroplating, metallurgical, and fertilizer industries, etc. Though conventional chemical and physicochemical methods may be used for Cr(VI) removal from aqueous solution, these methods have several drawbacks like high cost of operation, requirement of high energy input or large quantities of chemical reagents, inefficiency at low metal concentration, i.e., below 100 ppm, and production of toxic sludge, etc. Therefore, research is now being done to search for a novel, environmentally friendly, low-cost remediation technique. In the present work, Cr(VI) has been chosen as the model pollutant and bioremediation of Cr(VI) from simulated wastewater using a cyanobacterial consortium has been studied. Furthermore, since cyanobacteria grow more in wastewater and the biomass can be considered as a prospective source for biofuel production, the potential of the living cyanobacterial consortium has been assessed in terms of its Cr(VI) removal efficacy and the enhancement of its biomass content for biofuel production. A thorough kinetic study has been performed by culturing a living cyanobacterial consortium of Oscillatoria subbrevis and Gloeocapsa atrata in a simulated solution of Cr(VI). The cyanobacterial biomass, collected from the bioreactor intermittently, has been analyzed in terms of dry biomass, chlorophyll, and lipid contents, and the solution has been analyzed for residual Cr(VI) concentration. As far as it is known, this is the first ever attempt to show quantitatively the effect of Cr(VI) on biomass as well as on lipid production from a cyanobacterial consortium. The growth of the cyanobacterial consortium in the pure media has been modeled using the Monod equation, and kinetic parameters have been determined. Furthermore, in the present study, response surface methodology has been employed to enumerate the effect of the different parameters, viz., initial concentration of Cr(VI), initial pH, inoculum size and time on the growth of the cyanobacterial consortium, and lipid production, and to optimize the removal of Cr(VI). Statistical modeling and optimization of Cr(VI) removal and lipid production using RSM is a novel approach.

2. MATERIALS AND METHODS All the experiments were repeated thrice, and the arithmetic mean value has been reported. All the chemicals used were of AR grade unless otherwise stated. 2.1. Collection and Cultivation of Test Alga. Fresh algal biomass was collected from East Kolkata Wetland (EKW), Kolkata, West Bengal, (Latitude: 20°25′ N to 22°35′ N; Longitude: 88°20′ E to 88°35′ E). EKW is a natural waste recycling and biodiversity rich region.13 In August 2002, the EKW area was included in the “List” maintained under the Ramsar Bureau established under Article 8 of the Ramsar Convention. According to the Ramsar Convention on wetlands, “this site is one of the rare examples of environmental protection and development management”, and thus, EKW has been considered as a “Wetland of International Importance”.13 EKW acts as a natural sewage treatment plant because of the diversity of phytoplanktons (dominated by cyanophyceae) and bacterial phyla. Tanneries, small scale industries dealing with the production of paints, electroplating, batteries, etc. are source of metals like chromium, copper, etc.13 Phytoplanktons found in this region are, therefore, highly resistant to different heavy metals that hold their wide application in bioremediation as well as commercial utilization. B



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days, and flasks were collected after a 2 day interval. The broth in the flask was analyzed for both dry biomass and residual substrate concentration. The substrate, NaNO3·4H2O, has been observed to be consumed during the exponential phase, and the residual concentration of substrate in the broth has been analyzed by the cadmium reduction method.17 The classical Monod equation was proposed to model growth kinetics of the present cyanobacterial consortium as follows: μ=

Cr(VI) was performed, and its effect on dry biomass and chlorophyll and lipid contents was assessed. 2.6. Optimization of Removal of Cr(VI) and Growth of Cyanobacterial Biomass. 2.6.1. Experimental Section. Response surface methodology was employed to optimize the removal of Cr(VI). Design Expert software 8.0.7.1 was used for such purpose. Initially, four parameters, viz., initial metal ion concentration, solution pH, inoculum size, and time were considered as independent variables whereas percentage removal of Cr(VI) and chlorophyll and lipid contents of dry biomass were dependent. The maximum (+1) and minimum level (−1) of four input parameters, viz., initial metal ion concentration, solution pH, inoculum size, and time, were, 25 and 10 ppm, 9 and 5, 0.39 and 0.16 g, and 9 and 4 days, respectively. The experiments were carried out as per the statistical design made by the software. Test cyanobacterial biomass was inoculated in the media containing Cr(VI) as pollutant taken in a 100 mL Erlenmeyer flask. The pH, amount of inoculum, and concentration of Cr(VI) were maintained according to the said design. The volume of wastewater was kept at 50 mL. After definite time intervals, the flasks were taken out and sample broths were analyzed for residual Cr(VI) concentration and chlorophyll and lipid contents separately. 2.6.2. Design of Experiments. Response surface methodology is a statistical method that uses experimental data obtained from specified experimental design to model and optimize any process in which response is affected by a number of variables.18,19 Primarily, this optimization is done by following three major steps, viz., performing the statistically designed experiments, estimating the coefficients in a mathematical model, and predicting the responses and examining the adequacy of the model.20 RSM helps to enumerate the relationships between output variables called responses (Y) and input variables called factors (Xi).19

μmax CA (K s + CA )

(1) −1

where μ = specific growth rate (day ), μmax = maximum specific growth rate (day−1), CA = limiting substrate (nitrate ion) concentration (g/L) at time t, and Ks = substrate saturation constant (g/L). The kinetic equations in the batch study during the exponential phase are

dC B = μC B dt

(2)

dC /dt dCA =− B dt YX/S

(3)

Initial conditions prevailing in the batch reactor were as follows: At t = 0,

CA = CA0 ,

C B = C B0

(3a)

where CA0 = initial substrate (nitrate ion) concentration (g/L), CB = biomass concentration at time t (g/L), CB0 = initial biomass concentration (g/L), and t = time (day). Maximum specific growth rate (μmax) and substrate saturation constant (Ks) were determined by nonlinear regression analysis using the experimental data. Yield coefficient (YX/S) was also determined. The values of the kinetic parameters obtained during the batch study are of utmost importance in the design of the continuous reactor, suitable for industrial operation. 2.5. Kinetic Study of Cr(VI) Removal Using Cyanobacterial Consortium. In the present study, Cr(VI) was selected as the model pollutant. The stock solution of Cr(VI) was made by dissolving 141.4 mg of K2Cr2O7 (MERCK, India) in 100 mL of distilled water (500 ppm). This stock solution was used for the preparation of test solutions by dilution. The kinetic study was done by varying two parameters, viz., initial Cr(VI) concentration and initial pH. 2.5.1. Initial Concentration of Cr(VI) as a Parameter. Initial concentration of Cr(VI) was varied in the range of 15−35 ppm at constant pH condition. The original media pH was found to be 9, and it was kept unaltered during the present investigation. The cyanobacterial biomass was grown in the 50 mL of simulated wastewater containing Cr(VI) for 16 days. Every 2 days, the flasks were taken and subjected to an analysis of residual Cr(VI) concentration at 540 nm using a spectrophotometer (Techcomp UV 2300 spectrophotometer). 1,5-Diphenyl carbazide (MERCK, India) in acid solution was used as complexing agent for Cr(VI).17 The sample broth was also analyzed for dry biomass and chlorophyll and lipid contents separately. 2.5.2. Media pH as a Parameter. 50 mL of simulated wastewater containing hexavalent chromium (10 ppm) was taken in several 100 mL Erlenmeyer flasks. The pH of the solution was varied to different pH values (3−11) using 1 N HCl and 1N NaOH. Flasks were inoculated following the protocol as mentioned earlier and kept for 16 days. Analysis of residual

Y = f (X1 , X 2 , X3 , ..., X n)

(4)

A standard RSM design called central composite design (CCD) was applied. Hameed et al. reported that “this method is suitable for fitting a quadratic surface and it helps to optimize the effective parameters with a minimum number of experiments, as well as to analyze the interaction between the parameters”.18 In general, the CCD comprises 2n factorial runs with 2n axial runs and nc central runs.18 The center points are used to assess the reproducibility of the data. Thus, for a removal process having four independent parameters, the total number of experiments required is N = 2n + 2n + nc = 24 + (2 × 4) + 6 = 30

(5)

The outcome of each experimental run was analyzed, and the response was correlated with four input factors through an empirical second degree polynomial equation as given by the following equation Y = β0 +

∑ βi Xi + ∑ βiiXi 2 + ∑ βijXiXj

(6)

where Y = predicted response, Xi and Xj = independent variables, β0 = constant coefficient, βi = linear coefficient, βii = quadratic coefficient, and βij = interaction coefficient. ANOVA was used to model the system represented by independent parameters and dependent output response and to optimize the system by estimating the statistical parameters. C



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3. RESULTS AND DISCUSSION 3.1. Batch Study of Growth. A growth study of the cyanobacterial consortium has been done to find out the growth pattern in terms of dry biomass and chlorophyll and lipid contents as shown in Figure 1a,b. Volume of media, inoculum

Figure 1. Growth study of cyanobacterial consortium in Chu-10 media: (a) dry biomass and chlorophyll and (b) lipid.

size, and media pH have been kept constant at 50 mL, 0.1 g, and 9.0, respectively. Figure 1a represents the growth in terms of both dry biomass and chlorophyll content. From Figure 1a, it is seen that a lag phase exists up to 4 days and the stationary phase starts after 14 days. Thus, to get an overall idea, experimentations have been continued up to 16 days. A similar growth pattern has been found in terms of lipid content as shown in Figure 1b. During the exponential phase, dry biomass and chlorophyll and lipid contents have been increased from 0.094 g/L, 0.225 g/L/g, and 0.027 g/g to 0.212 g/L, 0.368 g/L/g, and 0.056 g/g, respectively. Figure 2a−c reveals the effect of media pH (3−11) on the growth of the cyanobacterial consortium in terms of dry biomass and chlorophyll and lipid content, respectively. For all the cases, inoculum size and volume of media has been kept constant at 0.1 g and 50 mL, respectively. It is evident that pH of the media has a direct effect on the growth of cyanobacterial strains. The growth of the cyanobacterial consortium in terms of dry biomass and chlorophyll and lipid contents has been the lowest at pH 3 and varies from 0.108 to 0.214 g/L, 0.221 to 0.331 g/L/g, and 0.019 to 0.026 g/g, respectively, in a 16 day incubation period.

Figure 2. Effect of media pH on the growth of the cyanobacterial consortium: (a) dry biomass, (b) chlorophyll, and (c) lipid.

Maximum growth is observed at pH 9, i.e., original pH of the Chu-10 media. The growth of the cyanobacterial consortium in terms of dry biomass (Figure 2a) and chlorophyll (Figure 2b) and lipid (Figure 2c) contents has been found at the maximum of 0.258 g/L, 0.419 g/L/g, and 0.0655 g/g, respectively, at pH 9 after 14 days. Thus, it can be concluded from the result that alkaline pH (i.e., pH 9) of the media is favorable for the growth of the cyanobacterial biomass studied. Less growth is observed at media pH 11 which is in conformity with the observation made by Pedersen and Hansen.21 3.2. Characterization of Cyanobacterial Biomass. Figure 3a,b represents the scanning electron microscopy (SEM) images of native cyanobacterial biomass and Cr(VI) loaded cyanobacterial biomass, respectively. In both images, two types of structure have been seen. As identified earlier, the filamentous structure is D



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Figure 4. Concentration−time histories of dry biomass obtained experimentally during (a) the growth study of the cyanobacterial consortium with concentration of NaNO3·4H2O as a parameter. In all the cases, CB0 = 0.128 g/L and pH = 9. (b) Concentration−time histories of dry biomass during the exponential phase of the cyanobacterial consortium with concentration of NaNO3·4H2O as a parameter. Simulated data: lines; experimental data: points. In all the cases, CB0 = 0.128 g/L and pH = 9.

Figure 3. Scanning electron microscopy images of the cyanobacterial consortium: (a) native biomass and (b) Cr(VI) loaded biomass.

Oscillatoria subbrevis and the globular form represents Gloeocapsa atrata. Comparing Figure 3a,b, it is seen that in native cyanobacterial biomass the surface is smooth whereas after Cr(VI) treatment the surface becomes rough in both the cyanobacterial structures. Such roughness of the surface may be due to the biosorption of Cr(VI) over the surface that makes the surface coarser than its original form. It has also been seen that there has been very little or no change in the fraction of filamentous Oscillatoria subbrevis and globular Gloeocapsa atrata before and after chromium removal. It suggests that the presence of chromium does not make the medium selective toward any of the strains and the biological nature of the consortium remains fairly constant. Densities of the filaments and nodules also seem to be unaffected by the presence of chromium suggesting that the growth kinetics of the consortium remains unchanged in the presence of chromium in simulated wastewater. 3.3. Modeling of Growth Kinetics and Determination of Kinetic Parameters for Growth of Cyanobacterial Biomass in Pure Media. The growth of the cyanobacterial consortium has been studied in batch culture by varying the amount of NaNO3·4H2O in the range of 0.05−0.6 g/L. The experimental values of dry biomass obtained during the total experimentation period for different values of NaNO3·4H2O in pure media have been plotted in Figure 4a. The classical Monod equation is used to represent the growth of the cyanobacterial

consortium in pure media during exponential phase only. Maximum specific growth rate and saturation constant have been evaluated by nonlinear regression analysis using the experimental data obtained during the batch study. Their values are μmax = 0.1562 day−1 and Ks = 0.024 g/L. The yield coefficient has been found to be dependent on the ratio of initial biomass and substrate concentration. The expression of yield coefficient (YX/S) is as follows ⎛C ⎞ YX/S = 1.1679ln⎜ B0 ⎟ + 2.3749 ⎝ CA0 ⎠

(7)

The kinetic equations to represent the variation of biomass and substrate with time as given in eqs 2 and 3 are solved simultaneously using the Runge−Kutta fourth order method. The simulated data have been plotted in Figure 4b. From close observation of Figure 4b, it is seen that the simulated data match well with experimental data. Root mean square error (RMSE = (∑i N= 1(CB,expt − CB,simt)2/N)1/2) has been found to vary from 0.034 to 0.098 where, CB,expt, CB,simt, and N represent the experimental concentration of biomass (g/L), simulated E



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concentration of biomass (g/L) at any time t, and number of experimental points, respectively. 3.4. Kinetic Study of Cr(VI) Removal Using Cyanobacterial Consortium. 3.4.1. Initial Concentration of Cr(VI) as a Parameter. The kinetic study of Cr(VI) removal has been studied by culturing the cyanobacterial consortium in 50 mL of simulated wastewater containing various amounts of Cr(VI) (15−35 ppm) and keeping inoculum size and pH constant at 0.1 g and 9.0, respectively. The study reveals the high potential of the cyanobacterial consortium in removal of Cr(VI) from simulated wastewater. Figure 5a represents the variation of percentage

The declining nature of the percentage removal curve after 14 days may be due to initiation of the death phase of the cyanobacterial consortium. 3.4.2. Media pH as a Parameter. In Figure 5b, the percentage removal of Cr(VI) has been plotted against time at various media pH (3−11). For all the cases, initial Cr(VI) concentration, media volume, and inoculum size are kept constant at 10 ppm, 50 mL, and 0.1 g, respectively. From the figure, it is clear that the percentage removal of Cr(VI) is higher in basic media pH than acidic and maximum removal (70.3%) has been observed at pH 9.0 after 14 days treatment with the cyanobacterial consortium. This may be attributed to the favorable growth of cyanobacterial biomass in alkaline media pH (i.e., pH 9) as observed earlier (Section 3.1). Thus, the present cyanobacterial consortium can effectively be used to treat tannery effluent as it generally comes at alkaline pH. 3.5. Comparative Study of Growth of Cyanobacterial Biomass in Pure Media and in Wastewater Containing Cr(VI). Cyanobacteria produce more biomass vis-à-vis lipids under stressed conditions.2 To ascertain the present statement and to extract the advantage of it in terms of enhanced biofuel or biodiesel production, a comparative study has been performed in synthetic media as well as in simulated wastewater containing Cr(VI). Figure 6a,b compares the growth of the cyanobacterial consortium on the basis of dry biomass and lipid contents when they are cultured in pure media as well as in wastewater containing various amounts of Cr(VI). From Figure 6a,b, it is clear that in every case the growth of cyanobacterial biomass is favored in the presence of chromium ion than in pure media. The percentage increase in dry biomass or lipid content can be calculated by using the following equation percentage increase in dry biomass or lipid =

w1 − w2 × 100 w2 (8)

where w1 = dry biomass or lipid content when cultured in wastewater and w2 = dry biomass or lipid content when cultured in pure media. When one analyzes the sample broth taken at 16 days, it is seen that the percentage increase in dry biomass and lipid vary from 1.91% to 9.52% and from 18.18% to 45.46%, respectively, when initial Cr(VI) concentration in wastewater has been increased from 15 to 35 ppm. It will be a beneficial step when biofuel generation is concerned. Figure 7a represents the effect of pH on dry biomass content of the cyanobacterial consortium in pure media and simulated wastewater at initial pH of 5, 7, and 9, respectively, when the initial concentration of Cr(VI) is kept constant at 10 ppm. It is seen from the figures that in all the cases growth of the test cyanobacterial consortium is more in wastewater than in pure media. The percentage increase in dry biomass content has been varied from 3.51% to 7.5% when initial pH is changed from 5 to 9 after 16 days of treatment. Thus, it can be stated that cyanobacteria grows more under stressed conditions. Figure 7b represents the effect of pH on lipid content of cyanobacterial biomass. While the percentage increase in lipid content varies from 22.81% to 7.81%, for changing the initial pH in the range of 5−9 in a 16 day incubation period, the absolute magnitude of lipid production is seen to be at the maximum (0.073 g/g of dry biomass) at pH 9. Thus, the growth of the test cyanobacterial consortium can be suggested at the original media pH (i.e., at pH 9) for enhanced lipid production.

Figure 5. Kinetic study of Cr(VI) removal. (a) Percentage removal of Cr(VI) considering initial Cr(VI) concentration as a parameter. (b) Percentage removal of Cr(VI) considering media pH as a parameter.

removal of Cr(VI) with time considering initial Cr(VI) concentration as a parameter. An S-shaped growth curve has been found with all concentrations of Cr(VI). This represents the effective growth of cyanobacterial biomass in simulated wastewater. From Figure 5a, it is evident that the percentage removal of Cr(VI) in all the cases is almost same. After 14 days of growth, the percentage removal of Cr(VI) has been observed to vary from 69.9% to 71.5% when initial concentration of Cr(VI) varies from 15 to 35 ppm. Thus, it may be concluded that the percentage removal of Cr(VI) does not depend appreciably on the initial Cr(VI) concentration under the present range studied. F



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Figure 7. Comparative studies of (a) dry biomass and (b) lipid content in pure media and simulated wastewater considering pH as a parameter. pm: pure media; ww: wastewater. Figure 6. Comparative study in pure media and simulated wastewater considering initial Cr(VI) concentration as a parameter. (a) Dry biomass and (b) lipid.

R1 = +0.50 − 0.027 × A + 0.038 × B + 0.082 × C + 0.039 × D − 0.017 × A × B − 5.625 × 10−3 × A × C − 0.026 × A × D + 0.013 × B × C + 0.031 × B × D − 0.011 × C × D − 0.044 × A2

3.6. Optimization of Removal of Cr(VI) and Growth of Cyanobacterial Biomass. Response surface methodology has been employed to optimize Cr(VI) removal using the cyanobacterial consortium. Four parameters, viz., initial Cr(VI) concentration (A, ppm), media pH (B), inoculum size (C, g), and time of culture (D, day) have been considered as input variables. Three responses such as chlorophyll content (R1, g/L/g of dry biomass), lipid content (R2, g/g of dry biomass), and percentage removal of Cr(VI) (R3, %) are chosen to be optimized. The design of the experiment is given in Table 1, and the values of responses have been placed against the corresponding experimental condition in the same table. The regression analysis has been performed to fit the responses. As suggested by the software, no transformation has been required and quadratic process order has been selected to analyze the data for three responses. The final regression function for estimation of chlorophyll, lipid contents, and percentage removal of Cr(VI) in terms of coded factors are given below (eqs 9−11):

− 0.060 × B2 − 0.045 × C 2 − 0.045 × D2

(9)

R 2 = +0.053 − 2.667 × 10−3 × A + 3.833 × 10−3 × B + 8.250 × 10−3 × C + 3.833 × 10−3 × D − 1.750 × 10−3 × A × B − 6.250 × 10−4 × A × C − 2.500 × 10−3 × A × D + 1.250 × 10−3 × B × C + 3.125 × 10−3 × B × D − 1.000 × 10−3 × C × D − 4.417 × 10−3 × A2 − 6.042 × 10−3 × B2 − 4.542 × 10−3 × C 2 − 4.542 × 10−3 × D2

(10)

R3 = +64.96 − 1.14 × A + 2.36 × B + 10.00 × C + 10.87 × D − 0.40 × A × B − 0.96 × A × C − 3.20 × A × D + 0.22 × B × C − 0.24 × B × D − 3.60 × C × D − 2.92 × A2 − 3.78 × B2 − 3.70 × C 2 − 5.16 × D2

(11)

The three correlation coefficients, viz., R2, Radj2, and Rpred2 for three responses such as chlorophyll content (R1), lipid content G



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Table 1. Experimental Design for Optimization of Cr(VI) Removal run

initial Cr(VI) concentration (A, ppm)

pH (B)

inoculum size (C, g)

time (D, day)

chlorophyll (R1, g/L/g of dry biomass)

lipid (R2, g/g of dry biomass)

percentage removal (R3, %)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

10 32.5 10 2.5 17.5 25 10 17.5 17.5 25 10 17.5 25 17.5 25 17.5 10 10 17.5 10 17.5 17.5 17.5 25 17.5 25 10 25 25 17.5

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

0.39 0.27 0.39 0.27 0.27 0.16 0.39 0.27 0.5 0.16 0.39 0.27 0.16 0.27 0.39 0.27 0.16 0.16 0.27 0.16 0.27 0.27 0.05 0.39 0.27 0.16 0.16 0.39 0.39 0.27

4 6.5 9 6.5 6.5 9 9 6.5 6.5 4 4 6.5 4 6.5 9 1.5 4 4 6.5 9 6.5 11.5 6.5 4 6.5 9 9 4 9 6.5

0.38 0.26 0.32 0.38 0.5 0.31 0.6 0.5 0.55 0.19 0.31 0.33 0.2 0.5 0.3 0.23 0.19 0.2 0.5 0.37 0.5 0.4 0.08 0.35 0.18 0.19 0.29 0.34 0.37 0.5

0.041 0.029 0.035 0.041 0.053 0.034 0.063 0.053 0.058 0.022 0.034 0.036 0.023 0.053 0.033 0.026 0.022 0.023 0.053 0.04 0.053 0.043 0.011 0.038 0.021 0.022 0.031 0.037 0.04 0.053

56.15 41.92 65.91 60.96 64.96 55.2 70.55 64.96 71.65 35 46.5 52 32 64.96 60 13.95 20.45 26 64.96 57.63 64.96 71 25 54.5 44 48.85 54 58.51 63.76 64.96

Figure 8. Combined effect of initial concentration of Cr(VI) and time on the percentage removal of Cr(VI) using the cyanobacterial consortium at constant pH 7 and inoculum size of 0.27 g.

(R2), and percentage removal of Cr(VI) (R3) have been found to be 0.9497, 0.9027, and 0.7102; 0.9514, 0.9061, and 0.7203; 0.9483, 0.9001, and 0.7023, respectively. High values of correlation indices indicate good fitting of experimental data to the proposed simulated equation.

It has been found that quadratic effects of initial Cr(VI) concentration, media pH, inoculum size, and time have significant effect on chlorophyll and lipid as well as on Cr(VI) removal by the test cyanobacterial consortium. The interactive effects of initial Cr(VI) concentration and time, and media pH H



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Figure 9. Combined effect of inoculum size and time on percentage removal of Cr(VI) at constant pH 7 and initial Cr(VI) concentration of 17.5 ppm.

Figure 10. Combined effect of initial concentration of Cr(VI) and time on the lipid content at constant media pH 7 and inoculum size of 0.27 g.

and time have been found to be significant for both chlorophyll and lipid contents while interactive effects of initial Cr(VI) concentration and time, and inoculum size and culture time have been reported as significant during optimization of Cr(VI) removal. Figure 8 represents the three-dimensional response surface diagram of the combined effect of initial Cr(VI) concentration and time on the percentage removal of Cr(VI) using the cyanobacterial consortium at constant pH (B = 7) and inoculum size (C = 0.27 g). From the figure, it is evident that with an increase in culture time from 4 to 9 days, percentage removal increases from 44.06% to 72.09% and from 48.19% to 64.14% when initial Cr(VI) concentrations have been kept constant at 10 and 25 ppm, respectively. The maximum removal of 72.09% is achieved when 10 ppm of Cr(VI) solution has been cultured for 9 days at the above-mentioned conditions. It is quite obvious that, with an increase in culture time, percentage removal should increase.

Figure 9 shows the interactive effect of culture time and inoculum size at constant pH (B = 7) and initial concentration of Cr(VI) (A = 17.5 ppm). Figure 9 reveals that the percentage removal of Cr(VI) increases from 31.77% to 60.65% and from 58.76% to 73.39%, respectively, when culture time varies from 4 to 9 days at constant inoculum size of 0.16 and 0.39 g, respectively. Thus, it is evident that both the parameters have profound synergistic effect on Cr(VI) removal. Figure 10 represents the combined effect of initial Cr(VI) concentration and time on the amount of lipid content in cyanobacterial biomass at constant media pH (B = 7) and inoculum size (C = 0.27 g). The figure reveals that, with an increase in culture time from 4 to 9 days, lipid content increases from 0.0405 to 0.0532 g/g with 10 ppm initial Cr(VI) concentration and 0.041 to 0.0429 g/g with 25 ppm initial Cr(VI) concentration. The maximum lipid content (0.0532 g/g of dry biomass) has been achieved when the cyanobacterial consortium has been cultured in wastewater having 10 ppm initial Cr(VI) concentration for 9 days. I



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remediation as well as renewable energy source for biofuel production. However, this is a preliminary work involving a simulated solution of Cr(VI), and a comprehensive study with real industrial wastewater encompassing a detailed parametric study in a continuous reactor system is needed.

Figure 11 shows the combined effect of culture time and pH on the total lipid content in cyanobacterial biomass at constant

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Fax: 91-343-2547375. Tel: 91-343-2754082. Notes

The authors declare no competing financial interest.

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REFERENCES

(1) Subhadra, B. G. Sustainability of Algal Biofuel Production Using Integrated Renewable Energy Park (IREP) and Algal Biorefinery Approach. Energy Policy 2010, 38, 5892. (2) Rawat, I.; Kumar, R. R.; Mutanda, T.; Bux, F. Dual Role of Microalgae: Phycoremediation of Domestic Wastewater and Biomass Production for Sustainable Biofuels Production. Appl. Energy 2011, 88, 3411. (3) Sturm, B. S. M.; Lamer, S. L. An Energy Evaluation of Coupling Nutrient Removal from Wastewater with Algal Biomass Production. Appl. Energy 2011, 88, 3499. (4) Chinnasamy, S.; Bhatnagar, A.; Hunt, R. W.; Das, K. C. Microalgae Cultivation in a Wastewater Dominated by Carpet Mill Effluents for Biofuel Applications. Bioresour. Technol. 2010, 101, 3097. (5) Olguin, E. J. Dual Purpose Microalgae−Bacteria-Based Systems that Treat Wastewater and Produce Biodiesel and Chemical Products within a Biorefinery. Biotechnol. Adv. 2012, 30, 1031. (6) Chinnasamy, S.; Bhatnagar, A.; Claxton, R.; Das, K. C. Biomass and Bioenergy Production Potential of Microalgae Consortium in Open and Closed Bioreactors using Untreated Carpet Industry Effluent as Growth Medium. Bioresour. Technol. 2010, 101, 6751. (7) Brierley, J. A. Production and Application of a Bacillus-Based Product for Use in Metals Biosorption. In Biosorption of Heavy Metals; Volesky, B., Ed.; CRC Press: Boca Raton, FL, USA, 1990, pp 305−312. (8) Kiran, B.; Kaushik, A. Cyanobacterial Biosorption of Cr(VI): Application of Two Parameter and Bohart Adams Models for Batch and Column Studies. Chem. Eng. J. 2008, 144, 391. (9) Flouty, R.; Estephane, G. Bioaccumulation and Biosorption of Copper and Lead by a Unicellular Algae Chlamydomonas reinhardtii in Single and Binary Metal Systems: A Comparative Study. J. Environ. Manage. 2012, 111, 106. (10) Zhang, H.; Tang, Y.; Cai, D.; Liu, X.; Wang, X.; Huang, Q.; Yu, Z. Hexavalent Chromium Removal from Aqueous Solution by Algal Bloom Residue Derived Activated Carbon: Equlibrium and Kinetic Studies. J. Hazard. Mater. 2010, 181, 801. (11) Gomes, P. I. A.; Asaeda, T. Phycoremediation of Chromium (VI) by Nitella and Impact of Calcium Encrustation. J. Hazard. Mater. 2009, 166, 1332. (12) Baral, A.; Engelken, R. D. Chromium-Based Regulation and Greening in Metal Finishing Industries in the USA. Environ. Sci. Policy 2002, 5, 121. (13) Kundu, N.; Pal, M.; Saha, S.East Kolkata Wetlands: A Resource Recovery System through Productive Activities. In Proceedings of the Taal2007: The 12th World Lake Conference, Jaipur, Rajasthan, India, October 28 to November, 2, 2007; ILEC: Shiga, Japan, 2008; pp 868− 881. (14) Jeffrey, S. W.; Humphrey, G. New Spectrophotometric Equations for Determining Chlorophyll a, b, c1 and c2 in Higher Plants, Algae and Natural Phytoplankton. Biochem. Physiol. Pflanz. 1975, 167, 191. (15) Folch, J.; Lees, M.; Stanley, G. H. S. A Simple Method for the Isolation and Purification of Total Lipids from Animal Tissues. J. Biol. Chem. 1957, 226 (1), 497. (16) Carpenter, E. J. Physiology and Ecology of Marine Planktonic Oscillatoria (Trichodesmium). Mar. Biol. Lett. 1983, 4, 69.

Figure 11. Combined effect of time and media pH on the lipid content at constant inoculum size of 0.27 g and initial Cr(VI) concentration of 17.5 ppm.

inoculum size (C = 0.27 g) and initial Cr(VI) concentration (A = 17.5 ppm). From the figure, it is seen that, with an increase in culture time from 4 to 9 days, lipid content increases from 0.0381 to 0.0394 g/g at pH 5 and from 0.0394 to 0.0533 g/g at pH 9. Lipid content has also been seen to be increased with an increase in pH from 5 to 9. Finally, Design Expert Software has been used to optimize the removal of Cr(VI). The criteria have been set as follows: Initial concentration: “in range”; pH: equal to “9”; inoculum size: “maximize”; culture time: “maximize”; all the responses have been set to “maximize”. According to the software, the optimized condition obtained is as follows: initial Cr(VI) concentration: 11.08 ppm; pH: 9.00; inoculum size: 0.39 g; time: 9 days. The predicted removal of Cr(VI), chlorophyll content, and lipid content at the optimum condition are 74.66%, 0.57303 g/L/g of dry biomass, and 0.0604 g/g of dry biomass, respectively, with desirability of 0.979.

4. CONCLUSION Fuel shortage in the near future poses a serious challenge; hence, a renewable energy resource having less environmental effect is necessary. Application of microalgae for such a purpose is an effective step. In the present study, an efficient microalgal consortium has been isolated from a native source and identified as the cyanobacterial consortium of Oscillatoria subbrevis and Gloeocapsa atrata. It has been found suitable for the removal of Cr(VI) from simulated wastewater, and an enhanced biomass production has been observed when the cyanobacterial consortium has been cultured in simulated wastewater instead of in pure media. RSM is used to optimize the removal of Cr(VI). A kinetic study has been performed in pure media as well as in simulated wastewater. The cyanobacterial consortium removes 71.5% of Cr(VI) from simulated wastewater after 14 days of treatment with initial chromium concentration of 35 mg/L at pH 9. The maximum lipid production (0.081 g/g of dry biomass) has been found with an initial Cr(VI) concentration of 35 mg/L at pH 9 after 14 days of incubation. Thus, it can be stated that the cyanobacterial consortium of Oscillatoria subbrevis and Gloeocapsa atrata can be employed as an effective biomaterial for J



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