A cost-effective strategy for marine microalgae

Separation and Purification Technology 147 (2015) 156–165

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Separation and Purification Technology journal homepage: www.elsevier.com/locate/seppur

A cost-effective strategy for marine microalgae separation by electro-coagulation–flotation process aimed at bio-crude oil production: Optimization and evaluation study Abooali Golzary a,b,⇑, Sajad Imanian a, Mohammad Ali Abdoli a, Abbasali Khodadadi c, Abdolreza Karbassi a a b c

Department of Environmental Engineering, Graduate Faculty of Environment, University of Tehran, P.O. Box 14155-6135, Tehran, Iran Department of Environmental Science and Technology, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan Department of Chemical Engineering, College of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran

a r t i c l e

i n f o

Article history: Received 2 February 2015 Received in revised form 27 March 2015 Accepted 6 April 2015 Available online 16 April 2015 Keywords: Microalgae separation Electrocoagulation–flotation process Chemical coagulation Response Surface Methodology Biocrude oil

a b s t r a c t Microalgae as the third generation of biomass sources for biofuel production has a promising future, but its economic challenges have not been resolved yet. One of the major challenges in order to practical implementation of biofuel production is separation of microalgae from culture medium, since this step devotes a significant part of the energy and time consumption. Although various methods have been reported for harvesting, electro-coagulation–flotation (EC) method was preferred due to the simplicity and capability of process scale up. In this study, the effect of three parameters, i.e., initial pH, electric current density and duration on microalgae separation efficiency and operating costs, as the response variables, was investigated by applying ‘‘Response Surface Methodology’’ (RSM) technique. It was revealed that duration was the most effective parameter on the microalgae separation efficiency, as well as the operational costs, wherein high efficiency was resulted in long duration. On the other hand, the high amount of electric current density caused to high coagulation, flotation rates, and also high power consumption. Although the pH of solution had a little impact on operating cost compared to the duration and current density, the natural condition, pH = 6, was recommended. In optimal point; current density = 1.6 mA/cm2 for 17.65 min, deprived of demanding to adjust pH, the microalgae separation efficiency was obtained 96.8%. Since the EC is a substitute for CC (chemical coagulation), its performance was evaluated on microalgae separation efficiency. The results demonstrated that the optimal coagulant concentration and pH was 450 mg/l and 8 respectively. At the optimal conditions, microalgae separation efficiency was resulted in 85%. Consequently, due to less sensitivity to pH changes, more flexibility and lower cost, the EC was introduced as a more efficient technology than CC Technology. All of these benefits recommend this method as the promising technique of microalgae harvesting in large-scale. Ó 2015 Elsevier B.V. All rights reserved.

1. Introduction Energy security, renewability, and climate change concerns have led to the world is looking for alternatives for current energy resources. Undoubtedly, reducing the environmental problems by replacement of fossil fuels and petroleum products with renewable resources is inevitable [1]. Several types of renewable energy resources such as solar energy, geothermal energy, hydro and ocean power, wind energy and biomass have been introduced, but biomass resources have numerous advantages such as ⇑ Corresponding author at: Department of Environmental Engineering, Graduate Faculty of Environment, University of Tehran, P.O. Box 14155-6135, Tehran, Iran. Tel.: +98 9124723148; fax: +98 21 66407719. E-mail address: [email protected] (A. Golzary). http://dx.doi.org/10.1016/j.seppur.2015.04.011 1383-5866/Ó 2015 Elsevier B.V. All rights reserved.

diversity of sources and accessible methods of biomass conversion to product with extensive applications [2,3]. As an important case, biomass resources were utilized to produce biofuels, especially biodiesel and bioethanol. Biofuels can be categorized into three generations based on resource type: first, second and third generation biofuels. 1st Generation biofuel is produced from food crops (sugar, starch, oil), such as palm, rapeseed, soy, beets and cereals (corn, wheat, etc.). 2nd Generation: the biofuel carbon is derived from cellulose, hemicellulose, lignin or pectin. For example, this may include agriculture, forestry wastes or residues and 3rd Generation: the biofuel carbon is derived from an aquatic autotrophic organism (e.g. Algae). Microalgae as the third generation source of biofuels have greater advantages such as simple structures, fast growth rate and high oil content, It Does not compete with food crops, does not require to agricultural or forestry

A. Golzary et al. / Separation and Purification Technology 147 (2015) 156–165

residues and coverts the atmosphere carbon dioxide to clean oxygen naturally, it is enable to growth in non-agricultural and nonarable seasons and lands, has the growth potential for changing weather conditions, production of more fuel as well as less water requirement compared to other oil crops [4–6]. Nevertheless, there are some limitations that made it difficult to commercialize. One of the major limitations is the separation of microalgae from cultivation media, which required high costs and energy due to the dilute nature of the microalgae in the growth media. The size of microalgae cells is typically in the micrometer range, which forms a stable colloidal suspension resulted from negatively charged cellular surface [7]. Several studies have shown that polymeric flocculants were ineffectual in separation of high salinity marine microalgae, because of its anionic nature [8–10]. One of the methods used for separation of the soluble and colloidal material in the aquatic medium is electrochemical or electrical coagulation. Electrocoagulation (EC) is a simple technology, which applies metal electrodes (usually made of iron or aluminum) and small amount of electricity demanded for the enhancement of performance [11]. This process has been used to remove a variety of contaminants and elements such as lead [12], copper [12–14], cadmium [12], chromium [13], nickel [13], arsenic [15,16], fluoride [17], mercury [18], manganese [19], cobalt [19], colloidal materials, COD [20], from water and wastewater, Also the electrocoagulation has been applied for treatment of some wastewater such as metalworking industry [13], bakery industry [21], production of tissue, textiles, manufacture of dyes [14] and restaurant wastewater [15]. Algal removal by EC for drinking water treatment purposes is also studied [22,23]. Nevertheless, application of EC in microalgae separation for bio-crude oil production is rarely evaluated. Chemical coagulation is one of the traditions and efficient methods for separation of colloidal materials from aqueous medium. Chemical coagulation (CC) usually puts into practice after the precipitation step. Precipitation occurs at increasing pH. Usually, the pH of water and wastewater rise by adding lime or soda. Coagulation takes place through the addition of coagulants such as iron chloride (FeCl3) or alum (Al2(SO4)3) to the medium [14]. Electro-coagulation (EC) is a technology that offers an attractive alternative to conventional coagulation. In EC, coagulant ions are produced in situ as anode electrode dissolves. Although the Flocs produced in EC and CC process are similar, the flocs, which are produced in (EC) process have less water, are larger and more stable [24,25]. Several chemical reactions that occurred at the EC reactor are explained as follows [26,14,21,27] In these reactions, M represents the metal, which was used as the electrode and n is the corresponding metal ion capacity. In this study, aluminum was used as an anode and cathode, where n = 3. Reactions that occurred at the anode were as follows: MðsÞ ! Mnþ ðaqÞ þ ne

ðReaction1Þ

2H2 OðlÞ ! 4HþðaqÞ þ O2ðgÞ þ 4e

ðReaction2Þ

Reactions that occur at the cathode are as follows: Mnþ ðaqÞ þ ne ! MðsÞ

ðReaction3Þ

2H2 OðlÞ þ 2e ! 2H2ðgÞ þ 2ðOHÞ

ðReaction4Þ

The following reaction occurs in solution:

M

nþ

þ

þ nH2 O ! MðOHÞnðsÞ # þ3H

above reactions, could react with each other and form mononuclear 4þ as Al(OH)2+, AlðOHÞþ 2 and Al2 ðOHÞ2 , also polymeric species such as 4þ 4þ 5þ 7þ Al6 ðOHÞ3þ 15 , Al7 ðOHÞ17 , Al8 ðOHÞ20 , Al13 ðOHÞ34 and Al13 O4 ðOHÞ24 . All of the species at the beginning of the reaction are in the form of AlðOHÞ3ðSÞ and at the end will be in the form of Aln ðOHÞ3nðSÞ

[21,26,27]. The formation of each of these species was dependent on media pH [21,28]. AlðOHÞ3ðSÞ could remove all types of impurities from the aqueous medium, because of its large surface that was a highly strong and efficient absorbent [26]. In this study, ‘‘Response Surface Methodology’’ (RSM) was applied to optimize the EC process and related to experimental design, was carried out by central composite design (CCD). Response Surface Methodology is a collection of mathematical and statistical methods, are used for modeling and analysis of processes, which affected by several variables [29] In such situations, we are usually interested in the optimization of the defined phenomenon [21,30]. If Y is the investigated phenomenon and xis are the affecting factor to Y, then Y will be a function of xis or:

Y ¼ f ðx1 ; x2 ; . . . ; xi Þ þ e

Reactions (4) and (2) occurs during the electrolysis of water. As a result, oxygen and hydrogen are released at the anode and the cathode, respectively. Coagulant ions are produced by anode dissolution in Reaction (1). Ions Al3+ and OH, which were produced in the

ð1Þ

In the above equation, Y is the response, xis are independent variables and e is the error observed in the response. The surface made by f(x1, x2, . . ., xi) is called ‘‘response surface’’ [31]. First, the optimization of the EC process for separation of microalgae from water is investigated. Then, as EC is known as the substitution for the CC, the CC performance in separation of microalgae is also evaluated. 2. Materials and methods 2.1. Experimental set-up and procedure Marine microalgae Chlorella sp. (PTCC 6010) was provided from Iranian Research Organization for Science and Technology (IROST). At first it was cultivated in four, 1 L laboratory scale aerated glass bubble column photobioreactors (PBRs) and then transferred to four, 10 L Plexiglas bubble column PBRs to supply the required microalgae. Chlorella sp. was grown in Rodik medium with the following composition per liter: 0.300 g NaNO3, 0.08 g K2HPO4, 0.02 g KH2PO4, 0.02 g NaCl, 0.047 g CaCl2, 0.02 g MgSO47H2O, 0.1 mg ZnSO47H2O, 1.5 mg MnSO4H2O, 0.08 mg CuSO45H2O, 0.3 mg H3BO3, 0.3 mg (NH4)6Mo7O244H2O, 17 mg FeCl36H2O, 0.2 mg Co(NO3)2H2O, 7.5 mg EDTA. The salinity of culturing environment was adjusted to 33 g/L, which was similar to the Persian Gulf seawater condition. Aeration for all 4 flasks was performed by a 50 L/min air pump (BOYU ACQ-003) which was split through a 4-port manifold with stainless steel needle valve for individual air flow control. For each needle valve, 100 cm of 0.48 cm I.D. tubing was attached with air diffuser. The lights, submersible fluorescent lamp (60 cm and 12 W), were positioned inside the PBR’s at the center, and the light intensity was measured at the surface of the vessels. After six days of culturing, the biomass growth was measured as total suspended solids (TSS). For this purpose, the samples taken were quantified by measuring the absorbance at 550 nm with a spectrophotometer (GBC-Model 911). These values were converted to TSS using a calibration curve correlating the culture absorbance to the dry weight of Chlorella sp. (g/L) (Eq. (2)).

W ðReaction5Þ

157

gr micro algae ¼ 0:49 OD L

ð2Þ

Apparatus used for EC was including reactor, DC current supply, and a magnetic stirrer. Open cube-shaped Plexiglas reactor with dimensions 16 * 12 * 8 cm and with a useful volume of 1280 cm3 were employed as the reactor. Required parts for pilot montage designed with Corel DRAW X6 v.16 software and cut by laser cutting

158


machine. Blade-shaped aluminum electrodes with useful dimensions 2 * 40 * 80 mm was cut from commercial aluminum sheets. To supply required electric current, DC current production source (DAZHENG PS-305D) with a production capacity of 0–5 A in 0– 30 V was used. In order to better mixing during the reaction, the reactor was put on a magnetic stirrer (Alpha stirrer, made in Iran). In each experiment, four electrodes connected to the power supply with parallel arrangement were used. The distances between the electrodes in all experiments were constant and were considered equal to 1 cm (Fig. 1). For each experiment, 1280 cc of medium (algae and water mixture) was poured into the reactor. Each experiment began to provide current electricity and turning on the magnetic stirrer and finished after a reaction time by cutting out electricity and stopping mixing. After the experiment, 30 min settling time were given to the reactor till coagulated algae came to the surface and were separated from the water. Temperature and pH of the wastewater at the beginning and the end of each experiment were measured using a pH meter (AZ Instruments) and a thermometer. Meanwhile, the cell voltage at the beginning, the end and two points during each experiment were recorded. To adjust the pH, the appropriate values of 0.5 N NaOH solution (Merck, Germany) and 5 N of HCl (Merck, Germany) were used. Before beginning each experiment, the electrodes were washed with water and dish soap and then placed inside solution of water and acid for 24 h to ensure that all impurities are separated. In order to evaluate the performance of CC for algae separation, jar test was performed. In these experiments, the aluminum sulfate-18-hydrate (Merck, Germany) was used as a coagulant. For each run of experiments, the amount of 500 ml water and algae mixture was poured into each jar. After adjusting the pH with NaOH and HCl solutions, coagulant will be added. The resulting mixture was stirred for 1 min at high speed (100 rpm). Subsequently the mixture was stirred at lower speeds on 30 rpm for 15 min. When the stirring process finished, 30 min were given to the mixture to be settled. 2.2. Analytical methods The electric current density (CD), the intensity of current through the electrode surface, was defined as in Eq. (3) [18].

CD ¼ I=A

ð3Þ

In the above equation, I and A represent current (A) and effective electrode surface (cm2) which was equal to 0.128 cm2. In order to

find the microalgae separation efficiency, concentration of samples was measured at the beginning and the end of each experiment and the separation percent was determined according to the following equation:

Separation percent ¼

C0 C1 100 C0

ð4Þ

where C0 and C1 are correspond to algae concentrations before and after testing, in each sample respectively. In all experiments in this study, C0 was 0.82 mg/l. The amounts of electrode consumption were calculated according to the Faraday’s equation in electrochemistry. In accordance with this law, the electric current intensity was directly related to the dissolved electrode mass. Faraday’s law states that [13,32,33]:

W¼

ItM nF

ðFaraday’s lawÞ

ð5Þ

In this relation, F is the Faraday constant (F = 96,487 104 C/Mol), M, the molecular weight of a given metal in grams per mole, n the number of electrons exchanged in the electrode surface (aluminum equal to 3), I the intensity of the electric current in ampere, t reaction time in seconds, and W donates dissolved electrode mass per gram respectively. Electrical energy consumption was calculated by using Eq. (6). According to Eq. (6), the electrical energy consumption was directly related to the electric current density and reaction time [13,33].

E¼

Z

t

IUðtÞdt ¼ I

0

Z

t

UðtÞdt

ð6Þ

0

where E is the electric energy consumed in W/h, I is electric current intensity in amperes, and t is reaction time in hours, and U is the cell voltage in volts. To integrate Eq. (6), the mean approximation was used which means we assume U is constant over the Dt time intervals. Operating costs include the energy and electrode consumption costs and is calculated by Eq. (7).

C T ¼ E cE þ W cW

ð7Þ

In the above equation, CT is processed operating costs in USD. W and E are defined as Eqs. (5) and (6) respectively. cE and cW represent, respectively, the unit price of electricity (equivalent to 0.000625 USD/kW h in Iran in 2014) and the price of aluminum (equivalent to 1.875 USD/kg in Iran in 2014). 2.3. Experimental design To optimize the EC process, Response Surface Methodology, associated with CCD for design of experiments, was applied. In this study, the effect of three parameters including initial pH, electric current density (CD) and time (t) on algae separation efficiency from aqueous solution has been investigated. Upper and lower limits for each variable according to the experimental observations

Table 1 The investigated parameters range.

a ¼

ðupper level þ lower levelÞ a ðupper level lower levelÞ 2

Name

Fig. 1. Schematic diagram of the electrocoagulation system (1. DC power source, 2. Plexiglas container, 3. Magnetic bar, 4. Aluminum electrodes, 5. Magnetic stirrer).

pH CD t

Unit

Lower level

Upper level

a

+a

mA/cm2 min

6 10 5

8.4 20 12

5.18 6.59 2.61

9.21 23.41 14.39

159


and the results of other studies [13,17,15,34,14,18,12] are defined in Table 1. According to the three parameters (pH, CD and t), a value was considered 1.68 [35]. Table 2 presented the results of experimental design derived from CCD, algae separation efficiency, energy and electrode consumption and operating cost values in each experiment. In Table 2, factorial points have been achieved by a full factorial design. In the full factorial design, 2k tests were performed (k was the number of factors affecting the process) [31,36]. According to three factors (initial pH, time and CD), 8 factorial points were achieved. The central point will be repeated 5 times. In RSM, the relation between the investigated phenomenon and affecting factors was assumed to be followed by a polynomial equation [37]. A second-order model was defined in Eq. (8) [30,17].

Y ¼ b0 þ

n n n1 X n X X X bi X i þ bii X 2i þ bij X i X j i¼1

i¼1

Table 3 Statistical data relating to the choice of model for microalgae separation efficiency.

Linear 2FI Quadratic Cubic

Sequential p-value

Lack of fit p-value

R2

0.0002 0.045 0.004 0.843

0.0041 0.0089 0.0733 0.0105

0.632494 0.751287 0.909643 0.877143

Suggested

Table 4 Statistical data relating to the choice of model for operational costs.

Linear 2FI Quadratic Cubic

Sequential p-value

Lack of fit p-value

R2