Bioremediation of Swine Wastewater and Biofuel Potential by using Chlorella vulgaris, Chlamydomonas reinhardtii, and Chlamydomonas debaryana

Corrected version: Hasan R, Zhang B, Wang L, Shahbazi A (2014) Bioremediation of Swine Wastewater and Biofuel Potential by using Chlorella vulgaris, Chlamydomonas reinhardtii, and Chlamydomonas debaryana. Journal of Petroleum & Environmental Biotechnology, 5:175. DOI: 10.13140/2.1.3348.4168 Due to the disagreement between the authors and the publisher, the paper published by the OMICS Group contains some printing errors. Please use this corrected version.


Introduction
Nowadays, it is truism to recognize that the pollution problem is a major concern of the society. Environmental laws are given general applicability and their enforcement has been gradually stricter [1]. The strategic importance of fresh water and air is universally recognized more than ever before. Issues concerning sustainable water management and air pollution can be found almost in every agenda all over the world.
There are few things invented which can be used to mitigate both water and air pollution.
Microalgal technology is one of them which can be used to reduce these crises as it ensures sustainable management of both air and water.
Microalgae are a diverse group of prokaryotic and eukaryotic photosynthetic microorganisms, typically found in freshwater and marine systems [2]. Algae are essential to global carbon, nitrogen and sulfur cycling. Approximately 45% of photosynthetic carbon assimilation is achieved by algae [3]. In addition, microalgae are considered as a promising feedstock for biofuel production. The oil yield of some algal stains is 1,000-4,000 gallons of oil/acre/yr whereas soybeans and other oil crops can generate 48 gallons of oil/acre/yr approximately. As an energy crop, microalgae do not compete with grain crops for limited arable lands because they may grow in water.
Bioremediation of wastewater using algal strains such as Chlorella and Dunaliella, spans over 75 years [3]. Algae bioremediation was applied for a range of purposes, some of which are used for the removal of coliform bacteria, reduction of chemical and biochemical oxygen demand (COD, BOD), removal of N and/or P, and also for the removal of heavy metals [1]. A number of microalgal strains including Ourococcus multisporus, Nitzschia cf. pusilla, Chlamydomonas mexicana, Scenedesmus obliquus, Chlorella vulgaris, Chlorella zofingiensis, and Micractinium reisseri had been used to treat municipal wastewater treatment effluents, livestock wastewater, agro-industrial wastewater and industrial wastewater [4][5][6]. Growing algae requires the consideration of three primary nutrients: carbon, nitrogen, and phosphorus. Micronutrients required in traceable amounts include silica, calcium, magnesium, potassium, iron, manganese, sulfur, zinc, copper, and cobalt, although the supply of these essential micronutrients rarely limits algal growth when wastewater is used. Therefore, the ultimate objective of this research is to optimize the growth conditions and determine growth kinetics of selected microalgal strains to assimilate nutrients in wastewater for swine wastewater treatment and bioenergy production. The growth characteristics and composition of microalgae are known to significantly depend on the cultivation conditions, such as light intensity, photoperiod, temperature, CO 2 flow rate, nutrient composition, etc [7]. In order to optimize the growth and lipid content of microalgae, it is required to combine all growth parameters in a systemic way so that the efficiency of an algal growth system can be maximized. In this study, the effects of cultivation temperature, light intensity, and nutrient removal on microalgae growth were observed.

Materials and Method
Microalgae strains and pre-culture conditions

Culture of microalgae with swine wastewater
Swine wastewater was collected from a swine growing facility at the NC A&T farm, and used as the substrate to cultivate microalgae. Pretreatment of swine wastewater was carried out by sedimentation and filtration with a Whatman quantitative filter paper (8 μm pore) to remove large, non-soluble particulate solids. After filtration the wastewater was autoclaved for 15 min at 121°C.
In order to investigate the effect of environmental factors on microalgae growth, a AlgaeTron Multi-Cultivator MC 1000 photobioreactor (Brno, Czech Republic) was used.
It consists of eight 100 ml tubular bioreactors. The temperature of the bioreactors is controlled centrally, and each bioreactor is independently illuminated by an array of white LEDs. Air is bubbled through each tube at the flow rate of 100 ml/min.
The autoclaved wastewater was used accordingly as medium for algal cultivation.
Subsequently, 72 ml of swine wastewater and 8 ml of seed microalgae suspension were introduced into each photobioreactor. In all cases, microalgae were cultured in the swine wastewater for 15 days varying light intensity (300, 600 and 900 μmol m -2 s -1 ) and temperature (20, 25 and 30°C ). The experimental designs are shown in Table 1. All experiments and analyses were performed in triplicate or duplicate.

Nutrients analysis
After 15-day cultivation, microalgal cells from each photobioreactor were collected and centrifuged at 4000 × G and 20°C for 15 min. Supernatants from the centrifuge were separated to check the nutrient removal from the wastewater.
Supernatants were filtered using a 0.45 mm nylon membrane filter. Then, the filtrates were appropriately diluted and analyzed for COD, ammonia nitrogen and total phosphorus according to the Lamotte Smart 3 colorimeter manual.
Nutrient removal ratio was defined as following:

Determination of microalgae growth
Microalgae growth was monitored by measuring the optical density at 680 nm every other day. A correlation between the optical density of microalgae at 680 nm and the cell number was determined by using a Guava easyCyte HT 5 Flow cytometer (Billerica, Massachusetts) and Spectrophotometer.
The specific growth rate μ in the exponential phase of algal growth was calculated by using equation (2) [8]: where, N 1 and N 2 are defined as the cell number concentration (cell/ml) at time t 1 and t 2 , respectively. The time required to duplicate the cell number: division rate (k), was calculated according to the equation (3):

Lipid extraction
A modified Christie method [9] was applied to quantify the amount of total lipid content. Approximately 0.1-0.2 g dried microalgae were weighed into clean screw-top glass tubes and 5 ml of a 2:1 chloroform-methanol (v/v) mixture was added. The tubes were incubated at 65 °C for 1 hr. Then the mixture was centrifuged at 4000 × G for 10 min, after which the supernatant was collected, and the leftover was re-extracted following the same procedures until the supernatant became colorless. All supernatants were pooled, and then evaporated by blowing nitrogen gas through the tube. The lipid was gravimetrically quantified.

Fatty acid methyl ester (FAME) content analysis
Extracted algal lipids (~20 mg) were weighed into clean, 20 ml screw-top glass tubes, to which 4 ml fresh solution of a mixture of methanol, concentrated sulfuric acid, and chloroform (1.7:0.3:2.0 v/v/v) was added. The tubes were closed tightly with Teflon tape to avoid leakage, and then weighed. For transesterification, tubes were placed inside a heating block at temperatures of 90°C and heated for 60 min. On completion of the reaction, the tubes were cooled down to room temperature and weighed again to dismiss leaking samples. Then, 1 ml distilled water was added into the mixture, and the mixture was thoroughly vortexed for 1 min. After the formation of two phases, the lower phase containing FAME was transferred to a 1.5 ml GC vial. Samples were stored in the freezer (-20°C) until GC-MS analysis [10].
Chemical compositions of the liquid products were identified using a GC-MS (Agilent 7890A gas chromatography with a HP-5MS capillary column /5975c mass spectrometer). The GC was programmed at 60°C for 4 min and then increased at 7 10 °C/min to 280 °C, and finally held with an isothermal for 5 min. The injector temperature was 250°C, and the injection size was 1 μl. The flow rate of the carrier gas (helium) was 1 ml/min. The ion source temperature was 230°C for the mass selective detector. The compounds were identified by comparison with the NIST Mass Spectral Database [11].

Elemental and compositional analysis of microalgae
A Perkin-Elmer 2400 Series II CHNS/O elemental analyzer (Waltham, Massachusetts) was used to analyze the elemental compositions of microalgal biomass.
The protein content of microalgae was determined by Dumas method [12]. The moisture content of the biomass was determined by the method of LAP #001, which is the laboratory analytical procedures (LAPs) developed by the National Renewable Energy Laboratory [13,14]. The ash content of the biomass was determined by the method of LAP #005 [15].

Statistical Analysis
The statistical significance of the cultivation temperature and light intensity on the algal cell density was assessed using ANOVA F-test. The experimental data measured under each condition were pooled together. The significance test was done for each factor using one-way ANOVA. The null hypothesis is that the population means measured at different levels of the experimental factor are all equal. The alternative is that they are not all equal, or the factor is significant. The statistical significance level cut-off was chosen as P = 0.05.

Microalgae growth
During the preliminary tests of four commercial microalgae strains, it's found that  Table 1.

The effect of temperature
The temperature range of 20-30°C was chosen, because it is easy to achieve in North Carolina. It was found that the optimal growth temperatures for two strains are different. A cultivation temperature of 25 o C gave the highest specific growth rates for C.
vulgaris. The highest specific growth rates and division rates were found to be 1.336 day -1 and 1.928 day -1 , respectively, which were obtained at 25°C and 600 μmol m -2 s -1 . At 20°C the specific growth rates and division rates obtained were 1.287-1.317 day -1 and 1.856-1.9 day -1 , respectively. The lowest growth rates of 1.199-1.214 day -1 were found at 30°C.
For C. reinhardtii, the highest specific growth rate and division rate were found to be 1.286 day -1 and 1.854 day -1 , respectively, which were obtained at 20°C and 300 μmol m -2 s -1 . At 25°C the specific growth rates and division rates obtained were 1.173-1.272 day -1 and 1.692-1.839 day -1 , respectively. The lowest growth rates of 1.141-1.184 day -1 were found at 30°C and 25°C/900 μmol m -2 s -1 .

The effect of light intensity
The reason for the selection of light intensities of 300-900 μmol m -2 s -1 is the same as the temperature selection. Moreover, the light intensities of 600 μmol m -2 s -1 and 900 μmol m -2 s -1 were used to study the effect of photoinhibition on microalgae growth. When the light intensity was increased from 300 μmol m -2 s -1 to 600 or 900 μmol m -2 s -1 , the growth patterns in lag phases were quite similar, and C. vulgaris had higher growth rate than C. reinhardtii. When the microalgae cultivation was conducted at 25°C or 30°C , the growth patterns of these two microalgal strains showed the similar trends.
Both the growth curves ( Fig. 1) and the specific growth rates (Table 1) show that a higher light intensity led to a significantly reduced growth rate. The lowest growth rates of both species were found at the highest light intensity of 900 μmol m -2 s -1 and 25°C.

Statistical Analysis
The P-values for the cultivation temperature and light intensity were 0.0375 and 0.530, respectively. If a statistical significance level cut-off is chosen as P = 0.05, it is concluded that the cultivation temperature was a significant factor, while the light intensity was not significant at a level of P < 0.05.

Removal of COD, ammonia nitrogen, and total phosphorus from swine wastewater
In this study, the autoclaved wastewater was used as medium for algal cultivation.
To provide the mass transfer and CO 2 , air is bubbled through each bioreactor at the flow rate of 100 ml/min during the 15-day culture. Table 2 summarizes the contents of COD, ammonia nitrogen, and total phosphorus in the swine wastewater before and after autoclave, and after 15-day air bubbling. By bubbling air through the wastewater, almost all nutrient contents were reduced. In order to calculate the nutrient removal rate, the data of the autoclaved wastewater bubbled with air was used as the reference.
The results indicated that the removal efficiency of nutrients is a function of microalgae growth (Table 3). For both microalgal species, the cultivation conditions for the highest growth rates also resulted in the highest nutrient removal efficiencies. The highest removal efficiencies of ammonia nitrogen, COD, and total phosphorus for C. vulgaris were 92.5%, 58.9% and 74.3%, respectively, which was achieved at the temperature of 25°C and light intensity of 600 μmol m -2 s -1 . For C. reinhardtii, the highest removal efficiencies of ammonia nitrogen, COD, and total phosphorus were 89.2%, 46.0% and 48.8%, respectively, which was achieved at the temperature of 20°C and light intensity of 300 μmol m -2 s -1 . C. vulgaris often had higher growth rate and removed more nutrients than C. reinhardtii under the same cultivation conditions.

C. debaryana AT 24 is a North Carolina native green microalgal species
(unpublished data), which served as a benchmark for the bioremediation ability of the native algal strains. Three strains were cultivated at 25°C and light intensity of 300 μmol m -2 s -1 . The results of elemental and composition analysis are listed in Table 4. The protein contents in all microalgal species are significantly high, representing 60-72 % of total dry weight. The ash contents are between 7.9-11.3% of total dry weight. The final biomass yields were 1.25 g/L, 0.86 g/L and 0.73 g/L for C. vulgaris, C. debaryana and C. reinhardtii, respectively. C. debaryana was able to remove 88.1% ammonia nitrogen, 53.6% total phosphorus, and around 47% COD from the swine wastewater. C. vulgaris gave the highest removal efficiency among three strains, and C. debaryana showed better performance than C. reinhardtii.

Lipid extraction and characterization
Lipids of microalgae were extracted and characterized according to the methods described in the Materials and Method section. Lipid contents from C. vulgaris, C. reinhardtii and C. debaryana are approximately 15.2%, 21.7%, and 19.7% of the total cell dry weight, respectively.
A GC/MS analysis of microalgal oils is presented in Table 5. Hexadecanoic Acid (C16) and three C18 fatty acids (Linoleic, Linolenic, and Octadecanoic acid) were found in all three microalgal oils. Moreover, the microalgal oil from C. debaryana also contains C12, C14, C15 and C17 fatty acids.

Discussion
Microalgal technology may combine bioremediation of swine wastewater and biofuel production in a more effective and sustainable way. However, the swine wastewater contains high doses of nutrients, which limited the growth of all microalgal species tested in this study.
As indicated by the statistical analysis, the effect of the light intensity on the algal cell density was not significant, but different microalgae species response to the light intensity differently. When the light intensity increased from 600 to 900 μmol m -2 s -1 , the growth rate of C reinhardtii decreased much more than that of C. vulgaris, which may indicate that C. reinhardtii is more sensitive to photoinhibition.
C. debaryana AT 24 was isolated from the lagoon at a NC A&T's farm. As a native green microalgal species, C. debaryana may have a competitive advantage under the local geographical, climatic and ecological conditions. Application of native microalgal species will also reduce the risk of invasive algae species. In addition, a variety of fatty acids was detected in the microalgal oil from C. debaryana. These medium-chain-length fatty acids are good sources for the production of bio-jet fuel.

Conclusion
This study describes a systemic optimization of microalgae growth for bioremediation of swine wastewater and the potential for biofuel production. It's found that Scenedesmus dimorphus and Neochloris oleoabundans were unable to grow on the swine wastewater. The optimal culture conditions for Chlorella vulgaris and Chlamydomonas reinhardtii were found to be (600 μ mol m -2 s -1 and 25°C ) and (300 μ mol m -2 s -1 and 20°C ), respectively. The growth kinetics was determined using optical density (OD) method and flow cytometry. Under the optimal culture conditions, the highest specific growth rates were found to be 1.336 day -1 and 1.286 day -1 for C. vulgaris and C. reinhardtii, respectively. Three microalgal strains of C. vulgaris, C. debaryana AT 24 and C. reinhardtii were able to effectively treat swine wastewater, and the relationships between microalgae growth and the removal efficiency of nutrients were established. The final biomass yields and lipid contents were 1.25 g/L and 15.2% (of the total cell dry weight), 0.86 g/L and 19.7%, and 0.73 g/L and 21.7% for C. vulgaris, C. debaryana and C. reinhardtii, respectively. The potentials of using these microalgal biomass for biodiesel production were also addressed.