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Microalgae harvesting from wastewater by pH modulation and flotation: Assessing and optimizing operational parameters
Journal of Environmental Management 254 (2020) 109825
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Journal of Environmental Management journal homepage: http://www.elsevier.com/locate/jenvman
Research article
Microalgae harvesting from wastewater by pH modulation and flotation: Assessing and optimizing operational parameters Luan de Souza Leite *, Priscila Ribeiro dos Santos, Luiz Antonio Daniel Department of Hydraulics and Sanitation, S~ ao Carlos School of Engineering, University of S~ ao Paulo, Av. Trabalhador S~ ao-Carlense, 400, 13566-59, S~ ao Carlos, S~ ao Paulo, Brazil
A R T I C L E I N F O
A B S T R A C T
Keywords: Chlorella sorokiniana dissolved air flotation pH-induced Wastewater
Microalgae harvesting is one of the major bottlenecks for the production of high-value microalgal products on a large scale, which encourages investigations of harvesting methods with better cost-benefits. Among these harvesting techniques, flotation stands out as a promising method, however it is still minimally explored when compared to the sedimentation method. In this study, the pH modulation followed by dissolved air flotation (DAF) was tested as a harvesting method for Chlorella sorokiniana cultivated in wastewater. The main aims of this study were to optimize the operational parameters of coagulation (pH, velocity gradient, and mixing time) and flotation (recirculation rate), check their reproducibility and resilience with the variability of wastewater characteristics, and evaluate the final wastewater quality after treatment using an optimized harvesting method. Parameter optimization was carried out using the one-factor-at-a-time method. The optimal parameters were a velocity gradient of 500 s 1, mixing time of 30 s, pH 12, and 20% of recirculation rate. High efficiencies were obtained for C. sorokiniana removal (96.5–97.9%), making it a successful process. Moreover, the photobioreactor effluent quality was also improved significantly after microalgae harvesting, with high nutrient removal (88.6–95.1% of total Kjeldahl nitrogen and 91.8–98.3% of total phosphorus) and organic matter removal (80.5–86.8% of chemical oxygen demand). The results showed the pH modulation and DAF as an effective process for wastewater treatment and biomass harvesting. This study also indicated the importance of opera tional optimization, not studied until now, in which the achieved results could be potentially applied as practical guidelines for microalgae harvesting on a large scale.
1. Introduction
pollutant removal (carbon, nitrogen, and phosphorus) from wastewater while producing biomass with a high economic value (Choi and Lee, 2015; Delgadillo-Mirquez et al., 2016; Leite et al., 2019b). A major cost reduction can be estimated when nutrients, water and carbon supply come from low-cost sources (Slade and Bauen, 2013). Microalgae cultivation followed by harvesting processes have been reported as being effective in tertiary wastewater treatment (Cassini et al., 2017; Elawwad et al., 2017; Nguyen et al., 2019a, Nguyen et al., 2019; Shchegolkova et al., 2018). The final quality of wastewater ensures its safe disposal, avoiding problems in aquatic environments such as eutrophication (Stutter et al., 2018). Different methods have been used for microalgae harvesting, which include mainly filtration, flotation, flocculation, and centrifugation (Kadir et al., 2018). Flotation stands out as a promising method, with high biomass recovery, low retention time, small footprint, high over flow rates, and the fact that it produces final biomass with 2–7% of solids
Microalgae is a sustainable source of bioproducts with high eco nomic value (e.g. lipids, carbohydrates, protein, carotenoids, and fatty acids), however the huge costs incurred by biomass cultivation and harvesting do not make it economically feasible on a large scale (Katiyar et al., 2017). These considerable expenses are associated with the dif ficulty in separating and recovering microalgae cells from the medium due to the low concentration of biomass (0.5–5.0 g L 1), small cell diameter (5–50 μm) and negative surface charge (Sukenik and Shelef, 1984). Using cost-effective harvesting methods may be an alternative way to achieve significant savings, once the biomass recovery implies about 20–60% of the total production costs (Molina Grima et al., 2003). Microalgae production coupled with wastewater treatment is a promising alternative to overcome the high costs incurred by cultivation processes (Ansari et al., 2019). Microalgae use can provide an efficient * Corresponding author. E-mail addresses: [email protected], [email protected] (L.S. Leite).
https://doi.org/10.1016/j.jenvman.2019.109825 Received 25 May 2019; Received in revised form 16 October 2019; Accepted 4 November 2019 Available online 13 November 2019 0301-4797/© 2019 Elsevier Ltd. All rights reserved.
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Journal of Environmental Management 254 (2020) 109825
0.65 m3 and hydraulic retention time of 3 days. Then, the anaerobically treated wastewater mixture was collected and used for microalgae growth. The characteristics of the treated wastewater mixture used in this research were 229.4 � 46.9 mg N⋅L 1 of total Kjeldahl nitrogen (TKN), 57.8 � 15.5 mg P⋅L 1 of total phosphorus, 422 � 92 mg L 1 of total suspended solids (TSS), and 558 � 100 mg O2⋅L 1 of chemical ox ygen demand (COD). The cultivation was carried out in three photobioreactors (PBR) with a capacity of 50 L in each one for 168 h. Batch cultivation was proceeded according to Leite et al. (2019b). The biomass concentration in the photobioreactor effluent (PBRE) was based on absorbance at 680 nm and dry weight (DW) measurements. DW was quantified according to Leite et al. (2019c). PBRE was also characterized by pH and alkalinity according to procedures described by APHA (2012).
(Brennan and Owende, 2010; Ndikubwimana et al., 2016). Among the several flotation types, dissolved air flotation (DAF) has been reported as an efficient microalgae harvesting process (Besson and Guiraud, 2013; Hosseini et al., 2016; Kwon et al., 2014; Leite et al., 2019c; Zhang et al., 2014). The DAF process is based on air bubble generation to promote the rising of microalgae flocs to the systemʼs surface, where solids are accumulated and removed, allowing water clarification (Laamanen et al., 2016a). DAF is also well-known as being an efficient process to improve wastewater quality, reducing chemical oxygen demand, sus pended solids, turbidity, phosphorus and emerging pathogenic pro tozoa, Giardia spp. cysts and Cryptosporidium spp. oocysts (Nardi et al., 2011; Reali et al., 2001; Santos and Daniel, 2017). Consequently, an improvement in wastewater quality is also expected after the harvesting process. Prior to the flotation process, coagulation must be performed by adding chemical compounds to the solution to destabilize the cells and form microalgae flocs (Edzwald, 2010). In this context, pH modulation to induce floc formation appears as an effective, non-toxic and fast so lution for microalgae harvesting. More specifically, the increase in pH medium leads to the chemical precipitation of calcium and/or magne sium salts, commonly found in wastewaters (Cole et al., 2016), which have a positive superficial charge (Vandamme et al., 2012). Then, pre cipitates may interact with negative microalgae cells by the charge neutralization mechanism and form microalgae-precipitate flocs (Bra nyikova et al., 2018; Lei et al., 2018). pH modulation associated with sedimentation has been studied as a harvesting method for many microalgae strains cultivated in culture medium (Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P�erez et al., 2017). However, microalgae harvesting using pH modula tion followed by flotation has been minimally explored. Besson and Guiraud (2013) studied Dunaliella salina harvesting from a prepared culture medium using high pH to induce flocculation and flotation subsequently. Despite the study conducted by Besson and Guiraud (2013), no other scientific investigation has been reported using this same method. Due to the lack of information in the literature, it is important to assess pH modulation-DAF as a harvesting technique for microalgae cultivated in wastewater. Furthermore, the influence of operational parameters on this method is unclear, which motivates the optimization of these parameters. According to Alwan (2013), optimization is a powerful tool to obtain operating conditions that maximize the perfor mance of the process. Moreover, determining the optimal parameters is fundamental to scale up the process and promote an efficient integration of microalgae harvesting on a large scale. In this work, the coagulation-DAF through pH modulation was tested as a harvesting method for Chlorella sorokiniana cultivated in waste water. This paper aims to: (1) optimize the operational parameters of coagulation (pH, gradient and mixing time) and flotation (recirculation rate), (2) check the reproducibility and resilience of the optimal pa rameters with the variability of wastewater characteristics, and (3) evaluate the final wastewater quality after treatment using the opti mized harvesting method.
2.2. Flotation system The lab-scale coagulation experiments followed by DAF were per formed to promote microalgae harvesting from PBRE. In general, DAF is preceded by coagulation and flocculation processes, however for the present study, the induced floc formation was achieved only by coagu lation through pH-modulation. The schematic representation of the batch DAF unit (Flotatest) used for flotation tests is shown in Fig. 1. The system comprises four acrylic cylindrical columns with a capacity of 2.3 L operating in parallel and connected with an air saturation chamber. In a Jar-test unit, the coag ulation process was carried out in rapid mixing between 2 L PBRE and NaOH. The appropriate quantity of NaOH (Qhemis, Brazil) was added to promote the pH requested. After the rapid mixing time, the sample was put on the flotatest column. Air-saturated water from the saturation chamber was injected at a suitable amount in the column bottom entrance. The tap water used in the saturation chamber was previously saturated with compressed air for 20 min under a controlled pressure of 500 kPa. The amount of air-saturated water used in the tests was related to the recirculation rates investigated. Due to the dilution promoted by using air-saturated water, the analysis obtained during this work were corrected by a correcting factor (CF) according to the recirculation rate (RR) applied to the flotation. The CF values (CF ¼ 1.10 for RR ¼ 10%, CF ¼ 1.15 for RR ¼ 15%, CF ¼ 1.20 for RR ¼ 20%) were calculated ac cording to Leite et al. (2019c). The flotation test effluent (FTE) was collected at 20 cm from the column bottom after 100 s from the beginning of the flotation operation, which corresponds to a flotation velocity of 12 cm min 1. After that, the FTE samples were characterized by absorbance at 680 nm and physicochemical parameters. 2.2.1. Operational parameter optimization The coagulation-flotation parameters for Chlorella sorokiniana har vesting through pH modulation were optimized using the one-factor-ata-time (OFAT) method (Oraeki et al., 2018). Using this method, the operational parameters were optimized individually varying one by one while the others were kept constant. The response variable was the microalgae harvesting efficiency, expressed in terms of absorbance removal at 680 nm. The major operational parameters involved in the process were optimized, which included pH, velocity gradient (GV) and mixing time (TM) for coagulation and recirculation rate (RR) for flotation. Due to this, the experimental procedure was divided into the following steps:
2. Materials and methods 2.1. Chlorella sorokiniana cultivation Freshwater microalgae Chlorella sorokiniana (C. sorokiniana) 211-8k were cultivated in a wastewater mixture previously treated by an upflow anaerobic sludge blanket (UASB). The raw wastewater mixture was prepared weekly using 400 L of piggery wastewater and 1200 L of municipal wastewater, from a swine ~o farm (Brotas, Brazil) and a full-scale wastewater treatment plant (Sa Carlos, Brazil), respectively. It was pumped and treated in a UASB reactor, 4 m long and 450 mm in diameter, operating with a volume of
(1) Selection of the best pH values. Different pH values were tested (from 8.6 to 13) using pre-chosen parameters (GV ¼ 500 s 1, TM ¼ 30 s, and RR ¼ 20%). The pH values which provided the best efficiencies (pH 12, 12.5, and 13) in microalgae removal were selected and used in the other steps. (2) Optimization of GV. Different GV values (250, 500, and 750 s 1) were tested using TM ¼ 30 s and RR ¼ 20%. 2
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Journal of Environmental Management 254 (2020) 109825
Fig. 1. Schematic representation of the batch DAF unit called Flotatest, proposed by Reali et al. (2001).
(3) Optimization of TM. Different TM values (10, 20, and 30 s) were tested using RR ¼ 20% and GV previously optimized in step 2. (4) Optimization of RR. Different RR values (10, 15, and 20%) were tested using GV and TM values defined in prior steps (Steps 2 and 3).
filtered in glassmicrofiber filters (poro size of 0.45 μm and diameter of 47 mm). Each analysis was performed in triplicate. 2.3. Zeta Potential Samples from the first stage of the optimization process were collected immediately after coagulation. The Zeta potential (ZP) mea surements were done using Zetasizer Nano-ZS (Malvern, UK) at 25 � C. Different pH values were evaluated (pH 8.6 to 13) and each condition was measured at least five times.
All harvesting tests were performed in triplicate. Significance of re sults and differences among flotation parameters tested were evaluated using a two-way ANOVA analysis and Tukey Test (p < 0.05). The sta tistical studies were performed on Minitab software (version 18.1, Minitab LLC., PA, USA). All experiments in this section were conducted using PBRE from one cultivation cycle to ensure the same conditions. The PBRE had 8.6 of pH, 0.42 mg CaCO3⋅L 1 of alkalinity and 0.6 g L 1 of C. sorokiniana biomass. Flotation efficiency (FE, %) to microalgae recovery was calculated by Eq. (1). Abi Abf FE ð%Þ ¼ x100 Abi
3. Results and discussion 3.1. Optimization of coagulation-flotation parameters 3.1.1. Optimization of pH modulation Different pH values (8.6–13) were tested with different VF (12–24 cm min 1) in terms of absorbance 680 nm removal, and the re sults are shown in Fig. 2. The test performed without pH increment (pH 8.6) showed the lowest FE (9.9%), while the highest FE (97.8%) was obtained at pH 13. Statistical analysis of the results showed a significant effect of pH modulation on FE (Tukey test, p < 0.05). The high pH induces the formation of inorganic salt precipitates in the wastewater (e.g. calcium phosphate, calcium carbonate, magnesium hydroxides, struvite, and calcite). These precipitates interact with the microalgae cells by the charge neutralization mechanism, which is responsible for the formation of microalgae-precipitates floc (Branyi kova et al., 2018; Lei et al., 2018). Due to this phenomenon, the appli cation of physical processes such as DAF for microalgae harvesting is possible. In order to evaluate the effect of the pH in the electrostatic in teractions, ZP measurements were done immediately after the coagu lation (Fig. 2). ZP remained negative in the whole pH range (pH 8.6 to 13) from 30.9 mV at pH 8.6 to 14.8 mV at pH 13. The upward trend
(1)
where Abi and Abf represent the absorbance values (at 680 nm) before and after the flotation, respectively. 2.2.2. Optimized process In order to evaluate the reproducibility of the optimized harvesting process (obtained from Section 2.2.1), coagulation-flotation tests were performed using PBRE from three different cultivation cycles (three weeks). This investigation was done to ensure the use of PBRE with a different quality and microalgae concentration. The PBRE and FTE quality were also assessed using physico-chemical analysis. The following parameters were determined according to APHA (2012): apparent color, COD, dissolved organic carbon (DOC), soluble COD (sCOD), TKN, total phosphorus (TP), true color, TSS, and turbidity. For DOC, sCOD, and true color analysis, the samples were previously 3
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condition, which occurs when a large amount of NaOH is added to induce the precipitation. This premise is in line with previous studies for calcium phosphate recovery by precipitation (Baya et al., 2013; Lei et al., 2017; Song et al., 2002). Despite the requirement of extreme alkaline pH to reach high FE, this does not impair the harvesting process proposed in this study. The vast majority of microalgal cells are still intact at pH 12 according to Van damme et al. (2012), presenting minimal damage to the bioproduct produced. Cell viability analysis also showed an advantage of pH mod ulation over the metal salt coagulants. Ummalyma et al. (2016) reported the presence of dead cells after flocculation using inorganic coagulants (aluminum sulfate and ferric chloride), differently from pH modulation at pH 12. Moreover, high pH has an advantage for wastewater treatment because it is effective in promoting the lysis of pathogenic indicator bacteria cells (Starliper and Watten, 2013). Considering the obtained results, the pH values of 12, 12.5, and 13, which reached the highest FE, were selected to optimize coagulationflotation parameters (GV, TM, and RR).
Fig. 2. Flotation efficiency (FE) of C. sorokiniana and Zeta Potential (ZP) at different pH values. Tests were carried out using GV ¼ 750 s 1, TM ¼ 30 s, and RR ¼ 20%. ZP measurements were carried out immediately after the coagula tion process.
3.1.2. Optimization of coagulation Microalgae are maintained in suspension in the culture medium due to their small size (5–50 μm) and negative surface charge, which makes the harvesting process difficult (Sukenik and Shelef, 1984). In order to have a satisfactory flotation process, the cells must be destabilized by a chemical addition which leads to the charge neutralization mechanism and hydrophobicity increment (Wiley et al., 2009; Laamanen et al., 2016b). The coagulation process was responsible for causing the destabili zation of microalgae and particles in the solution. In this process, the base was added to increase the pH causing floc formation through the charge neutralization mechanism, as discussed before. The interparticle collision promoted by velocity gradient (GV) and mixing time (TM) during coagulation have an impact on the mean diameter of the flocs (Aktas et al., 2013). As the floc size directly affects the flotation effi ciency (Ahmed and Jameson, 1985), it is crucial to investigate these parameters. The previous studies related to flocculation of algal cells by pH modulation did not consider the operating conditions of stirring (or coagulation) to promote floc formation. In general, the experiments were conducted in lab recipients, such as glass beakers, which were stirred in a determined velocity (in rpm unit) by a mechanical agitator or magnetic stirrer (Vandamme et al., 2012; Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P� erez et al., 2017). A more accurate ex amination of the coagulation process provides information about its influence on the efficiency of microalgae harvesting and may also enable a scale-up of the process. The influence of GV ranging from 250 to 750 s 1 on FE is shown in
of ZP values with pH increases indicates the neutralization of the surface charge of microalgae cells by the positive charged precipitates as the convergence of ZP values to zero indicate the action of the neutralization mechanism (Wu et al., 2012). It may explain the FE results obtained among the pH values tested in the coagulation-flotation tests. Higher pH values intensify the electrostatic interaction between microalgae and precipitates, expressed as ZP measurements. This interaction increases the floc formation, enabling microalgae flocs attached to air bubbles to rise to the systemʼs surface, consequently increasing the FE. For instance, the tests carried out at pH 10 presented FE of 59.6% and ZP of 25.9 mV, in contrast to those at pH 12.5 with FE of 96.7% and ZP of 15.4 mV. Besson and Guiraud (2013) studied Dunaliella salina harvesting using high-pH-induced flocculation followed by flotation. The authors found high FE (>90%) at high pH (11–12) in synthetic salt-marsh water me dium. Complementary analysis suggested the formation of magnesium hydroxide precipitates during the NaOH addition, which promoted the floc formation for subsequent flotation. Despite the study conducted by Besson and Guiraud (2013), previous studies using pH modulation for microalgae harvesting mainly focused on the flocculation-sedimentation method (Vandamme et al., 2012; Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P� erez et al., 2017). This fact makes it difficult to compare the present study with data from the literature, even with the charge neutralization mechanism also acting in the alkaline flocculation. Different optimal pH values (10–12) have been reported for micro algae harvesting using flocculation through pH-modulation in culture medium (Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P�erez et al., 2017). The diversity of results makes it clear that the process also depends on the chemical species in the medium, mainly the component concentrations of the precipitates. Differently from these studies, the tests of the present study were performed in wastewater, which makes the interaction of microalgae-precipitates more complex (Leite et al., 2019). This can be observed by the increment of the pH value required for microalgae flocculation carried out in wastewater. In this complicated matrix, the best efficiency (94%) was reached at pH 13 for Chlorella sp. recovery (Mennaa et al., 2019). The high pH required for microalgae cultivated in wastewater may be caused by the effluent composition. Furthermore, microalgae cells, solids and other materials present in the wastewater may interact with the precipitates, causing extra demands for them. It has been reported that negatively charged particles (e.g. protein and humic acid) can compete with the microalgae to bind with the precipitates, and this significantly affects the microalgae harvesting efficiency (Leite et al., 2019). Due to this, the process demands a highly supersaturated
Fig. 3. Flotation efficiency (FE) of C. sorokiniana using different velocity gra dients (GV) at pH 12, 12.5, and 13. Tests were performed using TM ¼ 30 s and RR ¼ 20%. 4
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Fig. 3. High variability of FE was experimentally obtained at pH 12 (76.2–91.1%) according to the Gv evaluated, in contrast to pH 12.5 (96.1–97.9%) and pH 13 (96.9–99.5%). Statistical analysis showed a significant effect of GV only at pH 12 (Tukey Test, p < 0.05). The highest efficiencies were achieved using GV ¼ 500 s 1 for the three pH values tested. Based on that, GV ¼ 500 s 1 was chosen as the optimum value. The influence of TM ranging from 10 to 30 s on FE is shown in Fig. 4. A high range of FE was experimentally obtained at pH 12 (79.5–91.1%) according to the TM evaluated, in contrast to pH 12.5 (95.8–97.9%) and pH 13 (97.6–99.5%). Statistical analysis showed a significant effect of TM only at pH 12 (Tukey test, p < 0.05). The highest efficiencies were achieved using TM ¼ 30 s for the three pH values tested. Based on that, TM ¼ 30 s was chosen as the optimum value. As mentioned before, the interparticle collision depends on opera tional parameters such as GV and TM during coagulation, influencing the mean diameter of the flocs and consequently the FE. The floc size can directly affect the flotation efficiency, which was checked by previous studies (Moruzzi and Reali, 2014; Zhang et al., 2014). Due to that, GV of 500 s 1 and TM of 30 s, indicated as optimal values, probably conducted to a more adequate floc size in the flotation process.
Fig. 5. Flotation efficiency (FE) of C. sorokiniana using different recirculation rates (RR) values at pH 12, 12.5, and 13. Tests were performed using GV ¼ 500 s 1 and TM ¼ 30 s.
microalgae harvesting through DAF in accordance with the data re ported by Zhang et al. (2014), who studied the effects of RR, floc size and bubble volume on Chlorella zofingiensi harvesting by DAF. Considering the optimal condition, the difference between the highest FE obtained was significant for the three pH values (Tukey test, p < 0.05). Besides the efficiency, the NaOH concentration used to reach the pH tested must be also considered to determine the optimal pH. In the tests, the NaOH concentration of 0.7, 2.6 and 6.4 g L 1 was used to modify the pH value to pH 12, 12.5, and 13, respectively. The difficulty in modifying the pH values of the samples is associated with the NaOH capacity, which can be observed by the titration curve of NaOH (Kahlert et al., 2016). In this curve, the pH modification is slow for pH values higher than pH 11, requiring a higher amount of base. This finding ex plains the high concentration of NaOH to reach pH 12.5 and 13. In this context, the pH 12 was considered the optimal value because the NaOH concentration was considerably lower than the other pH values (12.5 and 13) and also promoted efficient microalgae harvesting (FE ¼ 91.1%). Thus, the optimized parameters were GV ¼ 500 s 1, TM ¼ 30 s, pH 12, and RR ¼ 20%.
3.1.3. Optimization of flotation The DAF process occurs when the opportunity for collisions and consequent attachment among flocs and air micro-bubbles is provided. The floc-bubble aggregates must rise to the systemʼs surface, and then be removed to achieve water clarification. For bubble formation, air is dissolved into an amount of water by adding air under pressure in a saturation chamber. The saturated water is then forwarded to the flotation system under atmospheric pressure for the bubble release. The quantity of air bubbles is associated with the saturation pressure and the amount of saturated water used in the flotation tests. Moreover, the amount of saturated water must ensure the adequate bubble volume to reduce the bubble-floc density to less than that of the water, allowing the bubble-floc to reach the surface (Crossley and Valade, 2006; Edzwald, 2010). The amount of saturated water used in the flotation tests and its respective bubble volume is associated with the recirculation rate (RR). Due to the importance of this parameter to the DAF process, it was selected to be investigated. The influence of RR ranging from 10% to 20% on FE is shown in Fig. 5. A high range of FE was experimentally obtained at pH 12 (75.3–91.1%) according to the RR evaluated, in contrast to pH 12.5 (94.2–97.9) and pH 13 (97.0–99.5%). Statistical analysis showed a significant effect of RR only at pH 12 (Tukey Test, p < 0.05). The highest efficiencies were achieved using RR ¼ 20% for the three pH values tested. Based on that, RR ¼ 20% was chosen as the optimum value. The results for RR showed a strong influence of this parameter on
3.2. Optimized harvesting The quality of municipal and piggery wastewater used to feed the UASB reactor is subject to variations in each cultivation cycle. This oc curs because the wastewater characteristics (mainly municipal waste water) depend on weather conditions, daily patterns, and possible industrial wastewater discharge (Chys et al., 2018). Considering the use of UASB effluent as a culture medium for microalgae cultivation, it may affect the microalgae production and nutrient removal. In order to check the reproducibility and resilience of the optimized harvesting process throughout these wastewater quality variations, coagulation-flotation tests were carried out using PBRE from three different cultivation cy cles (each one occurring over a week). The FE obtained from these tests using the best three pH conditions (12, 12.5, and 13) are shown in Fig. 6. FE results proved that the opti mization process was successful, and efficiencies higher than 96% were obtained in all the PBRE tested. Furthermore, no significant differences in FE were found considering the pH values used (Tukey test, p < 0.05). An interesting point is that the efficiencies obtained are somewhat higher than those found during the optimization process. Moreover, the FE results found (96.5–97.9%) are higher than those reported in the literature using flotation for other microalgae strains and different types of culture medium. The FE varying from 81 to 95% is usually found in traditional methods of flotation based on bubble gen eration with different types of coagulants (e.g. natural polymers, metal salts, and surfactants) (Alkarawi et al., 2018; Kurniawati et al., 2014; Kwon et al., 2014; Laamanen et al., 2016a, 2016b; Xia et al., 2017;
Fig. 4. Flotation efficiency (FE) of C. sorokiniana using different mixing times (TM) at pH 12, 12.5, and 13. Tests were performed using GM ¼ 500 s 1 and RR ¼ 20%. 5
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concentration (Nguyen et al., 2019a); and illumination condition (fluorescent, sunlight) (Nguyen et al., 2019). Therefore, optimization of PBR operational conditions and harvesting methods for each type of wastewater is clearly needed. Some studies have been performed in order to investigate the application of microalgae cultivation in wastewater treatment followed by a harvesting method (Table 2). The presented studies differ in scale, operational conditions, harvesting method types, microalgae strains, wastewater type and consequently, influent concentrations in terms of N, P and COD. These different characteristics make the results diverge significantly and the data comparison difficult. However, the results (including from the present study) showed high and satisfactory efficient removals of pollutants (N, P, and COD) from the wastewater in general. Besides that, this study used initial COD and nutrient concentrations higher than those reported in the literature, suggesting the robustness of this kind of treatment (PBR followed by pH modulation and DAF) for highly polluted wastewaters. Moreover, the proposed combined treatment (PBR followed by pH modulation-DAF) can also be considered as a more compact system (with efficient removal of COD, TKN, and TP simultaneously) when compared to conventional treatments for particulate and dissolved organic matter, N and P removal from wastewaters. For example, ni trogen removal is usually conducted by two biological processes, nitri fication followed by denitrification, leading to the requirement of two separate reactors with the optimal conditions for each process (Zhang et al., 2007), and for phosphorus removal, additional treatment is needed, such as for physico-chemical methods (e.g. precipitation, sorption, and/or ion exchange processes), biological treatment (e.g. enhanced biological phosphorus removal), or a combination of both (Ndam et al., 2018). Some other factors may be disadvantageous for conventional treatments: physico-chemical methods imply in secondary contamination from the generated sludge, adding further concern for safe disposal; the nitrification/denitrification treatment converts most of the nitrogen to N2, impeding nutrient reuse, differently to what happens through microalgae cultivation (Christenson and Sims, 2011). Thus, these results indicate that the microalgae cultivation in PBR followed by the coagulation-DAF process configured an efficient process for wastewater treatment and biomass recovery. Considering future studies, a complete microbiological assessment of the harvesting process is recommended. However, high removal of pathogenic microorganism is expected. DAF has been reported as an effective wastewater treatment for pathogenic protozoa (Giardia spp. and Cryptosporidium spp.), E. coli and Total Coliform removal (Nardi et al., 2011; Santos and Daniel, 2017). In addition, high pH (10–12) has a high bactericidal effect, which promotes lysis of indicator bacteria cells (e.g, E. coli and total coliform) (Starliper and Watten, 2013). An evaluation of the disinfection treatment (e.g. ozone) in the FTE is also recommended to reach a better quality to reuse the effluent.
Fig. 6. Flotation efficiency (FE) of coagulation-flotation tests using three different photobioreactor effluents (PBRE). The tests were performed using the optimized parameters (GV ¼ 500 s 1, TM ¼ 30 s, and RR ¼ 20%).
Zhang et al., 2014). Therefore, great FE results were achieved, even using a complex matrix as wastewater. This fact indicates that pH-modulation followed by DAF has a great potential to be applied as a harvesting method, which has been scientifically untapped so far. The improvement of wastewater quality after the coagulationflotation tests using the optimized process was also analyzed (Table 1). The wastewater quality (FTE in relation to the PBRE) improved significantly (Tukey test, p < 0.05). High removals were ach ieved for physical parameters: 96.4–98.3% for turbidity, 91.3–97.2% for apparent color, 80.5–86.8% for COD and 94.3–99.1% for TSS. These results reflect the capacity of pH modulation-DAF to remove the par ticulate fraction, which includes wastewater solids and microalgae. On the other hand, sCOD, DOC and True color had low removal as expected. Average removals were 30.9–38.4% for sCOD, 13.2–17.7% for DOC, and 40.2–52.3% for True color. These parameters represent the dissolved or soluble part of the organic matter present in the wastewater and the low removal capacity of these fractions by the DAF is wellknown (Leite et al., 2019c; Santos and Daniel, 2017). The nutrient removal efficiencies were 88.6–95.1% for TKN and 91.8–98.3% for TP. These results are associated with the microalgal biomass removal as the nitrogen and phosphorus dissolved cannot be removed by DAF (Reali et al., 2001). Thus, nutrient removal from wastewater mainly depends on the cultivation parameters and nitrogen and phosphorus (N:P) ratio (Choi and Lee, 2015), which affects the nutrient uptake by microalgae, and consequently the nutrient removal by the pH modulation-flotation process. Other operating parameters may influence microalgae harvesting methods from wastewater and in the final effluent quality: coagulant type (organic, inorganic) combined with the pH (Cassini et al., 2017); hydraulic retention time in PBR (Elawwad et al., 2017); hydraulic retention time (Shchegolkova et al., 2018); initial microalgae
Table 1 Evaluation of photobioreactor effluent (PBRE) and flotation test effluent (FTE) quality. The tests were carried out over three weeks using the optimized parameters (GV ¼ 500 s 1, TM ¼ 30 s, pH 12, and RR ¼ 20%). Initial C. sorokiniana concentrations were 0.5, 0.6, and 0.8 g L 1 in the cultivation cycle 1, 2, and 3, respectively. Average removal is shown between parentheses. Cultivation cycle
Sample
Parameters Turbidity (NTU)
Apparent color (Pt–Co)
True color (Pt–Co)
TSS (mg⋅L 1)
COD (mg O2⋅L 1)
sCOD (mg O2⋅L 1)
DOC (mg⋅L
258 123 � 2 (52.3) 214 128 � 1 (40.2) 296 161 � 4 (45.6)
454 � 30 4�4 (99.1) 409 � 6 13 � 1 (96.8) 563 � 6 32 � 3 (94.3)
778 � 2 103 � 3 (86.8) 774 � 2 151 � 12 (80.5) 1000 � 3 193 � 2 (80.7)
136 � 1 94 � 3 (30.9) 211 � 1 130 � 3 (38.4) 289 � 1 192 � 9 (33.6)
35.9 � 0.2 30.6 � 0.3 (14.8) 48.6 � 0.1 40.0 � 0.7 (17.7) 62.2 � 0.2 54.0 � 1.2 (13.2)
1
PBRE FTE
175 3 � 0 (98.3)
4564 130 � 2 (97.2)
2
PBRE FTE
196 7 � 1 (96.4)
6740 586 � 9 (91.3)
3
PBRE FTE
284 9 � 2 (96.8)
10,430 817 � 5 (92.2)
6
1
)
TKN (mg N⋅L 1)
Total phosphorus (mg P⋅L 1)
42.8 � 0.8 2.1 � 2.0 (95.1) 37.6 � 1.1 4.3 � 1.0 (88.6) 99.8 � 1.4 11.0 � 0.5 (89.0)
35.3 � 1.5 0.6 � 0.0 (98.3) 38.3 � 1.2 1.8 � 0.6 (95.3) 71.0 � 1.6 5.8 � 0.5 (91.8)
L.S. Leite et al.
Journal of Environmental Management 254 (2020) 109825
Table 2 Microalgae cultivation combined with different methods for microalgae harvesting aiming at wastewater treatment and biomass recovery. Treatment process
Operation mode
Microalgae
Wastewater type
Wastewater influent concentration (mg⋅L 1)a
Removal (%)
Reference
Membrane photobioreactor microfiltration PBR and sedimentation
Continuous
Chlorella vulgaris
Synthetic
Batch
Chlorella sp.
Domestic
PO34 : 1.8 NH4: 4.0 TP: 9.8 TKN: 37.2 COD: 110
Praveen et al. (2016) Cassini et al. (2017)
PBR and sedimentation (lamellar settler)
Continuous
Scenedesmus, Spirulina, Ankistrodesmus, Closterium, and Anabaena
Domestic
TP: 2.6–5.8 NH4: 6.5–12.5 COD: 60-90
PBR and filtration
Batch
Domestic
PBR and auto-flocculation
Batch
Scenedesmus quadricauda and Chlorella sorokiniana Chlorella vulgaris
PBR and coagulation (pH modulation)-DAF
Batch
Chlorella sorokiniana
Domestic and piggery
PO34 : 2.5–24.2 NH4: 1.6–5.6 PO34 : 11.5 TN: 92.7 COD: 306 TP: 38-75 TKN: 183-300 COD: 450-670
PO34: 2 NH4: 84-97 TP: 85.7–90.6 TKN: 85.5–95.1 COD: 80-84 TP: 59.7–85.6 NH4: 63.1–90.2 COD: 44.6–67.3 PO34: 89-91 NH4: 34-48 PO34 : 79-95 TN: 72-83 COD: 81-88 TP : 92-98 TKN: 96-99 COD: 72-78
Seafood
Elawwad et al. (2017)
Shchegolkova et al. (2018) Nguyen et al., 2019 This study
Note: Nitrogen concentration was expressed as TKN (total Kjeldahl nitrogen), NH4 (ammonia) and TN (total nitrogen), and the phosphorus concentration was expressed as PO34 (ortophosphate) and TP (total phosphorus).
4. Conclusions
Ansari, F.A., Ravindran, B., Gupta, S.K., Nasr, M., Rawat, I., Bux, F., 2019. Technoeconomic estimation of wastewater phycoremediation and environmental benefits using Scenedesmus obliquus microalgae. J. Environ. Manag. 240, 293–302. https:// doi.org/10.1016/j.jenvman.2019.03.123. APHA, 2012. Standard Methods for Examination of Water and Wastewater, twentysecond ed. American Public Health Association, American Water Works Association, Water Environment Federation, Washington. Baya, D.T., Effebi, K.R., Tangou, T.T., Keffala, C., Vasel, J.L., 2013. Effect of hydroxyapatite, octacalcium phosphate and calcium phosphate on the autoflocculation of the microalgae in a high-rate algal pond. Environ. Technol. 34, 2407–2414. https://doi.org/10.1080/09593330.2013.770563. Besson, A., Guiraud, P., 2013. High-pH-induced flocculation-flotation of the hypersaline microalga Dunaliella salina. Bioresour. Technol. 147, 464–470. https://doi.org/ 10.1016/j.biortech.2013.08.053. Branyikova, I., Filipenska, M., Urbanova, K., Ruzicka, M.C., Pivokonsky, M., Branyik, T., 2018. Physicochemical approach to alkaline flocculation of Chlorella vulgaris induced by calcium phosphate precipitates. Colloids Surfaces B Biointerfaces 166, 54–60. https://doi.org/10.1016/j.colsurfb.2018.03.007. Brennan, L., Owende, P., 2010. Biofuels from microalgae-A review of technologies for production, processing, and extractions of biofuels and co-products. Renew. Sustain. Energy Rev. 14, 557–577. https://doi.org/10.1016/j.rser.2009.10.009. Cassini, S.T., Francisco, S.A., Wagner, P., Antunes, P., Oss, R.N., Keller, R., 2017. Harvesting microalgal biomass grown in anaerobic sewage treatment effluent by the coagulation-flocculation method : effect of pH. Braz. Arch. Biol. Technol. 60, 1–12. https://doi.org/10.1590/1678-4324-2017160174. Choi, H.J., Lee, S.M., 2015. Effect of the N/P ratio on biomass productivity and nutrient removal from municipal wastewater. Bioproc. Biosyst. Eng. 38, 761–766. https:// doi.org/10.1007/s00449-014-1317-z. Christenson, L., Sims, R., 2011. Production and harvesting of microalgae for wastewater treatment, biofuels, and bioproducts. Biotechnol. Adv. 29, 686–702. https://doi.org/ 10.1016/j.biotechadv.2011.05.015. Chys, M., Demeestere, K., Nopens, I., Audenaert, W.T.M., Van Hulle, S.W.H., 2018. Municipal wastewater effluent characterization and variability analysis in view of an ozone dose control strategy during tertiary treatment: the status in Belgium. Sci. Total Environ. 625, 1198–1207. https://doi.org/10.1016/j.scitotenv.2018.01.032. Cole, A.J., Neveux, N., Whelan, A., Morton, J., Vis, M., de Nys, R., Paul, N.A., 2016. Adding value to the treatment of municipal wastewater through the intensive production of freshwater macroalgae. Algal Res. 20, 100–109. https://doi.org/ 10.1016/j.algal.2016.09.026. Crossley, I.A., Valade, M.T., 2006. A review of the technological developments of dissolved air flotation. J. Water Supply Res. Technol. - Aqua 55, 479–491. https:// doi.org/10.2166/aqua.2006.057. Delgadillo-Mirquez, L., Lopes, F., Taidi, B., Pareau, D., 2016. Nitrogen and phosphate removal from wastewater with a mixed microalgae and bacteria culture. Biotechnol. Rep. 11, 18–26. https://doi.org/10.1016/j.btre.2016.04.003. Edzwald, J.K., 2010. Dissolved air flotation and me. Water Res. 44, 2077–2106. https:// doi.org/10.1016/j.watres.2009.12.040. Elawwad, A., Karam, A., Zaher, K., 2017. Using an algal photo-bioreactor as a polishing step for secondary treated wastewater. Pol. J. Environ. Stud. 26, 1493–1500. https:// doi.org/10.15244/pjoes/68426. Hosseini, M., Starvaggi, H.A., Ju, L.K., 2016. Additive-free harvesting of oleaginous phagotrophic microalga by oil and air flotation. Bioproc. Biosyst. Eng. 39, 1181–1190. https://doi.org/10.1007/s00449-016-1594-9.
The results showed the pH modulation and DAF as an effective process for microalgae harvesting from wastewater. Parameter optimi zation using the one-factor-at-a-time method was successful, in which high efficiencies were obtained for C. sorokiniana harvesting (96.5–97.9%). The optimal parameters were a velocity gradient of 500 s 1, mixing time of 30 s, pH 12, and 20% of recirculation rate. The method also showed robustness with the variation of photobiorreactor effluent quality. Moreover, wastewater quality improved significantly after microalgae harvesting, with high nutrient removal (88.6–95.1% of TKN, and 91.8–98.3% of Total phosphorus), and organic matter removal (80.5–86.8% of COD). This study also indicated the importance of operational optimization, and the results could be potentially applied as practical guidelines for microalgae harvesting on a large scale. Acknowledgements ~o Paulo Research Foundation This work was supported by the Sa (FAPESP) for research assistance [Proc. 2013/50351–4] and Master’s ~o Grant [Proc. 2017/14620–1]. The authors would like to thank SAAE Sa �cio de Loyola Farm. Carlos and the Santo Igna Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.jenvman.2019.109825. References Ahmed, N., Jameson, G.J., 1985. The effect of bubble size on the rate of flotation of fine particles. Int. J. Miner. Process. 14, 195–215. https://doi.org/10.1016/0301-7516 (85)90003-1. Aktas, T.S., Fujibayashi, M., Maruo, C., Nomura, M., Nishimura, O., 2013. Influence of velocity gradient and rapid mixing time on flocs formed by polysilica iron (PSI) and polyaluminum chloride (PACl). Desalin. Water Treat. 51, 4729–4735. https://doi. org/10.1080/19443994.2012.751883. Alkarawi, M.A.S., Caldwell, G.S., Lee, J.G.M., 2018. Continuous harvesting of microalgae biomass using foam flotation. Algal Res. 36, 125–138. https://doi.org/10.1016/j. algal.2018.10.018. Alwan, G.M., 2013. Simulation and optimization of a continuous biochemical reactor. J. Chem. Eng. Process Technol. 4, 1000142 https://doi.org/10.4172/21577048.1000142.
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Research article
Microalgae harvesting from wastewater by pH modulation and flotation: Assessing and optimizing operational parameters Luan de Souza Leite *, Priscila Ribeiro dos Santos, Luiz Antonio Daniel Department of Hydraulics and Sanitation, S~ ao Carlos School of Engineering, University of S~ ao Paulo, Av. Trabalhador S~ ao-Carlense, 400, 13566-59, S~ ao Carlos, S~ ao Paulo, Brazil
A R T I C L E I N F O
A B S T R A C T
Keywords: Chlorella sorokiniana dissolved air flotation pH-induced Wastewater
Microalgae harvesting is one of the major bottlenecks for the production of high-value microalgal products on a large scale, which encourages investigations of harvesting methods with better cost-benefits. Among these harvesting techniques, flotation stands out as a promising method, however it is still minimally explored when compared to the sedimentation method. In this study, the pH modulation followed by dissolved air flotation (DAF) was tested as a harvesting method for Chlorella sorokiniana cultivated in wastewater. The main aims of this study were to optimize the operational parameters of coagulation (pH, velocity gradient, and mixing time) and flotation (recirculation rate), check their reproducibility and resilience with the variability of wastewater characteristics, and evaluate the final wastewater quality after treatment using an optimized harvesting method. Parameter optimization was carried out using the one-factor-at-a-time method. The optimal parameters were a velocity gradient of 500 s 1, mixing time of 30 s, pH 12, and 20% of recirculation rate. High efficiencies were obtained for C. sorokiniana removal (96.5–97.9%), making it a successful process. Moreover, the photobioreactor effluent quality was also improved significantly after microalgae harvesting, with high nutrient removal (88.6–95.1% of total Kjeldahl nitrogen and 91.8–98.3% of total phosphorus) and organic matter removal (80.5–86.8% of chemical oxygen demand). The results showed the pH modulation and DAF as an effective process for wastewater treatment and biomass harvesting. This study also indicated the importance of opera tional optimization, not studied until now, in which the achieved results could be potentially applied as practical guidelines for microalgae harvesting on a large scale.
1. Introduction
pollutant removal (carbon, nitrogen, and phosphorus) from wastewater while producing biomass with a high economic value (Choi and Lee, 2015; Delgadillo-Mirquez et al., 2016; Leite et al., 2019b). A major cost reduction can be estimated when nutrients, water and carbon supply come from low-cost sources (Slade and Bauen, 2013). Microalgae cultivation followed by harvesting processes have been reported as being effective in tertiary wastewater treatment (Cassini et al., 2017; Elawwad et al., 2017; Nguyen et al., 2019a, Nguyen et al., 2019; Shchegolkova et al., 2018). The final quality of wastewater ensures its safe disposal, avoiding problems in aquatic environments such as eutrophication (Stutter et al., 2018). Different methods have been used for microalgae harvesting, which include mainly filtration, flotation, flocculation, and centrifugation (Kadir et al., 2018). Flotation stands out as a promising method, with high biomass recovery, low retention time, small footprint, high over flow rates, and the fact that it produces final biomass with 2–7% of solids
Microalgae is a sustainable source of bioproducts with high eco nomic value (e.g. lipids, carbohydrates, protein, carotenoids, and fatty acids), however the huge costs incurred by biomass cultivation and harvesting do not make it economically feasible on a large scale (Katiyar et al., 2017). These considerable expenses are associated with the dif ficulty in separating and recovering microalgae cells from the medium due to the low concentration of biomass (0.5–5.0 g L 1), small cell diameter (5–50 μm) and negative surface charge (Sukenik and Shelef, 1984). Using cost-effective harvesting methods may be an alternative way to achieve significant savings, once the biomass recovery implies about 20–60% of the total production costs (Molina Grima et al., 2003). Microalgae production coupled with wastewater treatment is a promising alternative to overcome the high costs incurred by cultivation processes (Ansari et al., 2019). Microalgae use can provide an efficient * Corresponding author. E-mail addresses: [email protected], [email protected] (L.S. Leite).
https://doi.org/10.1016/j.jenvman.2019.109825 Received 25 May 2019; Received in revised form 16 October 2019; Accepted 4 November 2019 Available online 13 November 2019 0301-4797/© 2019 Elsevier Ltd. All rights reserved.
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Journal of Environmental Management 254 (2020) 109825
0.65 m3 and hydraulic retention time of 3 days. Then, the anaerobically treated wastewater mixture was collected and used for microalgae growth. The characteristics of the treated wastewater mixture used in this research were 229.4 � 46.9 mg N⋅L 1 of total Kjeldahl nitrogen (TKN), 57.8 � 15.5 mg P⋅L 1 of total phosphorus, 422 � 92 mg L 1 of total suspended solids (TSS), and 558 � 100 mg O2⋅L 1 of chemical ox ygen demand (COD). The cultivation was carried out in three photobioreactors (PBR) with a capacity of 50 L in each one for 168 h. Batch cultivation was proceeded according to Leite et al. (2019b). The biomass concentration in the photobioreactor effluent (PBRE) was based on absorbance at 680 nm and dry weight (DW) measurements. DW was quantified according to Leite et al. (2019c). PBRE was also characterized by pH and alkalinity according to procedures described by APHA (2012).
(Brennan and Owende, 2010; Ndikubwimana et al., 2016). Among the several flotation types, dissolved air flotation (DAF) has been reported as an efficient microalgae harvesting process (Besson and Guiraud, 2013; Hosseini et al., 2016; Kwon et al., 2014; Leite et al., 2019c; Zhang et al., 2014). The DAF process is based on air bubble generation to promote the rising of microalgae flocs to the systemʼs surface, where solids are accumulated and removed, allowing water clarification (Laamanen et al., 2016a). DAF is also well-known as being an efficient process to improve wastewater quality, reducing chemical oxygen demand, sus pended solids, turbidity, phosphorus and emerging pathogenic pro tozoa, Giardia spp. cysts and Cryptosporidium spp. oocysts (Nardi et al., 2011; Reali et al., 2001; Santos and Daniel, 2017). Consequently, an improvement in wastewater quality is also expected after the harvesting process. Prior to the flotation process, coagulation must be performed by adding chemical compounds to the solution to destabilize the cells and form microalgae flocs (Edzwald, 2010). In this context, pH modulation to induce floc formation appears as an effective, non-toxic and fast so lution for microalgae harvesting. More specifically, the increase in pH medium leads to the chemical precipitation of calcium and/or magne sium salts, commonly found in wastewaters (Cole et al., 2016), which have a positive superficial charge (Vandamme et al., 2012). Then, pre cipitates may interact with negative microalgae cells by the charge neutralization mechanism and form microalgae-precipitate flocs (Bra nyikova et al., 2018; Lei et al., 2018). pH modulation associated with sedimentation has been studied as a harvesting method for many microalgae strains cultivated in culture medium (Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P�erez et al., 2017). However, microalgae harvesting using pH modula tion followed by flotation has been minimally explored. Besson and Guiraud (2013) studied Dunaliella salina harvesting from a prepared culture medium using high pH to induce flocculation and flotation subsequently. Despite the study conducted by Besson and Guiraud (2013), no other scientific investigation has been reported using this same method. Due to the lack of information in the literature, it is important to assess pH modulation-DAF as a harvesting technique for microalgae cultivated in wastewater. Furthermore, the influence of operational parameters on this method is unclear, which motivates the optimization of these parameters. According to Alwan (2013), optimization is a powerful tool to obtain operating conditions that maximize the perfor mance of the process. Moreover, determining the optimal parameters is fundamental to scale up the process and promote an efficient integration of microalgae harvesting on a large scale. In this work, the coagulation-DAF through pH modulation was tested as a harvesting method for Chlorella sorokiniana cultivated in waste water. This paper aims to: (1) optimize the operational parameters of coagulation (pH, gradient and mixing time) and flotation (recirculation rate), (2) check the reproducibility and resilience of the optimal pa rameters with the variability of wastewater characteristics, and (3) evaluate the final wastewater quality after treatment using the opti mized harvesting method.
2.2. Flotation system The lab-scale coagulation experiments followed by DAF were per formed to promote microalgae harvesting from PBRE. In general, DAF is preceded by coagulation and flocculation processes, however for the present study, the induced floc formation was achieved only by coagu lation through pH-modulation. The schematic representation of the batch DAF unit (Flotatest) used for flotation tests is shown in Fig. 1. The system comprises four acrylic cylindrical columns with a capacity of 2.3 L operating in parallel and connected with an air saturation chamber. In a Jar-test unit, the coag ulation process was carried out in rapid mixing between 2 L PBRE and NaOH. The appropriate quantity of NaOH (Qhemis, Brazil) was added to promote the pH requested. After the rapid mixing time, the sample was put on the flotatest column. Air-saturated water from the saturation chamber was injected at a suitable amount in the column bottom entrance. The tap water used in the saturation chamber was previously saturated with compressed air for 20 min under a controlled pressure of 500 kPa. The amount of air-saturated water used in the tests was related to the recirculation rates investigated. Due to the dilution promoted by using air-saturated water, the analysis obtained during this work were corrected by a correcting factor (CF) according to the recirculation rate (RR) applied to the flotation. The CF values (CF ¼ 1.10 for RR ¼ 10%, CF ¼ 1.15 for RR ¼ 15%, CF ¼ 1.20 for RR ¼ 20%) were calculated ac cording to Leite et al. (2019c). The flotation test effluent (FTE) was collected at 20 cm from the column bottom after 100 s from the beginning of the flotation operation, which corresponds to a flotation velocity of 12 cm min 1. After that, the FTE samples were characterized by absorbance at 680 nm and physicochemical parameters. 2.2.1. Operational parameter optimization The coagulation-flotation parameters for Chlorella sorokiniana har vesting through pH modulation were optimized using the one-factor-ata-time (OFAT) method (Oraeki et al., 2018). Using this method, the operational parameters were optimized individually varying one by one while the others were kept constant. The response variable was the microalgae harvesting efficiency, expressed in terms of absorbance removal at 680 nm. The major operational parameters involved in the process were optimized, which included pH, velocity gradient (GV) and mixing time (TM) for coagulation and recirculation rate (RR) for flotation. Due to this, the experimental procedure was divided into the following steps:
2. Materials and methods 2.1. Chlorella sorokiniana cultivation Freshwater microalgae Chlorella sorokiniana (C. sorokiniana) 211-8k were cultivated in a wastewater mixture previously treated by an upflow anaerobic sludge blanket (UASB). The raw wastewater mixture was prepared weekly using 400 L of piggery wastewater and 1200 L of municipal wastewater, from a swine ~o farm (Brotas, Brazil) and a full-scale wastewater treatment plant (Sa Carlos, Brazil), respectively. It was pumped and treated in a UASB reactor, 4 m long and 450 mm in diameter, operating with a volume of
(1) Selection of the best pH values. Different pH values were tested (from 8.6 to 13) using pre-chosen parameters (GV ¼ 500 s 1, TM ¼ 30 s, and RR ¼ 20%). The pH values which provided the best efficiencies (pH 12, 12.5, and 13) in microalgae removal were selected and used in the other steps. (2) Optimization of GV. Different GV values (250, 500, and 750 s 1) were tested using TM ¼ 30 s and RR ¼ 20%. 2
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Fig. 1. Schematic representation of the batch DAF unit called Flotatest, proposed by Reali et al. (2001).
(3) Optimization of TM. Different TM values (10, 20, and 30 s) were tested using RR ¼ 20% and GV previously optimized in step 2. (4) Optimization of RR. Different RR values (10, 15, and 20%) were tested using GV and TM values defined in prior steps (Steps 2 and 3).
filtered in glassmicrofiber filters (poro size of 0.45 μm and diameter of 47 mm). Each analysis was performed in triplicate. 2.3. Zeta Potential Samples from the first stage of the optimization process were collected immediately after coagulation. The Zeta potential (ZP) mea surements were done using Zetasizer Nano-ZS (Malvern, UK) at 25 � C. Different pH values were evaluated (pH 8.6 to 13) and each condition was measured at least five times.
All harvesting tests were performed in triplicate. Significance of re sults and differences among flotation parameters tested were evaluated using a two-way ANOVA analysis and Tukey Test (p < 0.05). The sta tistical studies were performed on Minitab software (version 18.1, Minitab LLC., PA, USA). All experiments in this section were conducted using PBRE from one cultivation cycle to ensure the same conditions. The PBRE had 8.6 of pH, 0.42 mg CaCO3⋅L 1 of alkalinity and 0.6 g L 1 of C. sorokiniana biomass. Flotation efficiency (FE, %) to microalgae recovery was calculated by Eq. (1). Abi Abf FE ð%Þ ¼ x100 Abi
3. Results and discussion 3.1. Optimization of coagulation-flotation parameters 3.1.1. Optimization of pH modulation Different pH values (8.6–13) were tested with different VF (12–24 cm min 1) in terms of absorbance 680 nm removal, and the re sults are shown in Fig. 2. The test performed without pH increment (pH 8.6) showed the lowest FE (9.9%), while the highest FE (97.8%) was obtained at pH 13. Statistical analysis of the results showed a significant effect of pH modulation on FE (Tukey test, p < 0.05). The high pH induces the formation of inorganic salt precipitates in the wastewater (e.g. calcium phosphate, calcium carbonate, magnesium hydroxides, struvite, and calcite). These precipitates interact with the microalgae cells by the charge neutralization mechanism, which is responsible for the formation of microalgae-precipitates floc (Branyi kova et al., 2018; Lei et al., 2018). Due to this phenomenon, the appli cation of physical processes such as DAF for microalgae harvesting is possible. In order to evaluate the effect of the pH in the electrostatic in teractions, ZP measurements were done immediately after the coagu lation (Fig. 2). ZP remained negative in the whole pH range (pH 8.6 to 13) from 30.9 mV at pH 8.6 to 14.8 mV at pH 13. The upward trend
(1)
where Abi and Abf represent the absorbance values (at 680 nm) before and after the flotation, respectively. 2.2.2. Optimized process In order to evaluate the reproducibility of the optimized harvesting process (obtained from Section 2.2.1), coagulation-flotation tests were performed using PBRE from three different cultivation cycles (three weeks). This investigation was done to ensure the use of PBRE with a different quality and microalgae concentration. The PBRE and FTE quality were also assessed using physico-chemical analysis. The following parameters were determined according to APHA (2012): apparent color, COD, dissolved organic carbon (DOC), soluble COD (sCOD), TKN, total phosphorus (TP), true color, TSS, and turbidity. For DOC, sCOD, and true color analysis, the samples were previously 3
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condition, which occurs when a large amount of NaOH is added to induce the precipitation. This premise is in line with previous studies for calcium phosphate recovery by precipitation (Baya et al., 2013; Lei et al., 2017; Song et al., 2002). Despite the requirement of extreme alkaline pH to reach high FE, this does not impair the harvesting process proposed in this study. The vast majority of microalgal cells are still intact at pH 12 according to Van damme et al. (2012), presenting minimal damage to the bioproduct produced. Cell viability analysis also showed an advantage of pH mod ulation over the metal salt coagulants. Ummalyma et al. (2016) reported the presence of dead cells after flocculation using inorganic coagulants (aluminum sulfate and ferric chloride), differently from pH modulation at pH 12. Moreover, high pH has an advantage for wastewater treatment because it is effective in promoting the lysis of pathogenic indicator bacteria cells (Starliper and Watten, 2013). Considering the obtained results, the pH values of 12, 12.5, and 13, which reached the highest FE, were selected to optimize coagulationflotation parameters (GV, TM, and RR).
Fig. 2. Flotation efficiency (FE) of C. sorokiniana and Zeta Potential (ZP) at different pH values. Tests were carried out using GV ¼ 750 s 1, TM ¼ 30 s, and RR ¼ 20%. ZP measurements were carried out immediately after the coagula tion process.
3.1.2. Optimization of coagulation Microalgae are maintained in suspension in the culture medium due to their small size (5–50 μm) and negative surface charge, which makes the harvesting process difficult (Sukenik and Shelef, 1984). In order to have a satisfactory flotation process, the cells must be destabilized by a chemical addition which leads to the charge neutralization mechanism and hydrophobicity increment (Wiley et al., 2009; Laamanen et al., 2016b). The coagulation process was responsible for causing the destabili zation of microalgae and particles in the solution. In this process, the base was added to increase the pH causing floc formation through the charge neutralization mechanism, as discussed before. The interparticle collision promoted by velocity gradient (GV) and mixing time (TM) during coagulation have an impact on the mean diameter of the flocs (Aktas et al., 2013). As the floc size directly affects the flotation effi ciency (Ahmed and Jameson, 1985), it is crucial to investigate these parameters. The previous studies related to flocculation of algal cells by pH modulation did not consider the operating conditions of stirring (or coagulation) to promote floc formation. In general, the experiments were conducted in lab recipients, such as glass beakers, which were stirred in a determined velocity (in rpm unit) by a mechanical agitator or magnetic stirrer (Vandamme et al., 2012; Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P� erez et al., 2017). A more accurate ex amination of the coagulation process provides information about its influence on the efficiency of microalgae harvesting and may also enable a scale-up of the process. The influence of GV ranging from 250 to 750 s 1 on FE is shown in
of ZP values with pH increases indicates the neutralization of the surface charge of microalgae cells by the positive charged precipitates as the convergence of ZP values to zero indicate the action of the neutralization mechanism (Wu et al., 2012). It may explain the FE results obtained among the pH values tested in the coagulation-flotation tests. Higher pH values intensify the electrostatic interaction between microalgae and precipitates, expressed as ZP measurements. This interaction increases the floc formation, enabling microalgae flocs attached to air bubbles to rise to the systemʼs surface, consequently increasing the FE. For instance, the tests carried out at pH 10 presented FE of 59.6% and ZP of 25.9 mV, in contrast to those at pH 12.5 with FE of 96.7% and ZP of 15.4 mV. Besson and Guiraud (2013) studied Dunaliella salina harvesting using high-pH-induced flocculation followed by flotation. The authors found high FE (>90%) at high pH (11–12) in synthetic salt-marsh water me dium. Complementary analysis suggested the formation of magnesium hydroxide precipitates during the NaOH addition, which promoted the floc formation for subsequent flotation. Despite the study conducted by Besson and Guiraud (2013), previous studies using pH modulation for microalgae harvesting mainly focused on the flocculation-sedimentation method (Vandamme et al., 2012; Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P� erez et al., 2017). This fact makes it difficult to compare the present study with data from the literature, even with the charge neutralization mechanism also acting in the alkaline flocculation. Different optimal pH values (10–12) have been reported for micro algae harvesting using flocculation through pH-modulation in culture medium (Wu et al., 2012; Rakesh et al., 2014; Ummalyma et al., 2016; P�erez et al., 2017). The diversity of results makes it clear that the process also depends on the chemical species in the medium, mainly the component concentrations of the precipitates. Differently from these studies, the tests of the present study were performed in wastewater, which makes the interaction of microalgae-precipitates more complex (Leite et al., 2019). This can be observed by the increment of the pH value required for microalgae flocculation carried out in wastewater. In this complicated matrix, the best efficiency (94%) was reached at pH 13 for Chlorella sp. recovery (Mennaa et al., 2019). The high pH required for microalgae cultivated in wastewater may be caused by the effluent composition. Furthermore, microalgae cells, solids and other materials present in the wastewater may interact with the precipitates, causing extra demands for them. It has been reported that negatively charged particles (e.g. protein and humic acid) can compete with the microalgae to bind with the precipitates, and this significantly affects the microalgae harvesting efficiency (Leite et al., 2019). Due to this, the process demands a highly supersaturated
Fig. 3. Flotation efficiency (FE) of C. sorokiniana using different velocity gra dients (GV) at pH 12, 12.5, and 13. Tests were performed using TM ¼ 30 s and RR ¼ 20%. 4
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Fig. 3. High variability of FE was experimentally obtained at pH 12 (76.2–91.1%) according to the Gv evaluated, in contrast to pH 12.5 (96.1–97.9%) and pH 13 (96.9–99.5%). Statistical analysis showed a significant effect of GV only at pH 12 (Tukey Test, p < 0.05). The highest efficiencies were achieved using GV ¼ 500 s 1 for the three pH values tested. Based on that, GV ¼ 500 s 1 was chosen as the optimum value. The influence of TM ranging from 10 to 30 s on FE is shown in Fig. 4. A high range of FE was experimentally obtained at pH 12 (79.5–91.1%) according to the TM evaluated, in contrast to pH 12.5 (95.8–97.9%) and pH 13 (97.6–99.5%). Statistical analysis showed a significant effect of TM only at pH 12 (Tukey test, p < 0.05). The highest efficiencies were achieved using TM ¼ 30 s for the three pH values tested. Based on that, TM ¼ 30 s was chosen as the optimum value. As mentioned before, the interparticle collision depends on opera tional parameters such as GV and TM during coagulation, influencing the mean diameter of the flocs and consequently the FE. The floc size can directly affect the flotation efficiency, which was checked by previous studies (Moruzzi and Reali, 2014; Zhang et al., 2014). Due to that, GV of 500 s 1 and TM of 30 s, indicated as optimal values, probably conducted to a more adequate floc size in the flotation process.
Fig. 5. Flotation efficiency (FE) of C. sorokiniana using different recirculation rates (RR) values at pH 12, 12.5, and 13. Tests were performed using GV ¼ 500 s 1 and TM ¼ 30 s.
microalgae harvesting through DAF in accordance with the data re ported by Zhang et al. (2014), who studied the effects of RR, floc size and bubble volume on Chlorella zofingiensi harvesting by DAF. Considering the optimal condition, the difference between the highest FE obtained was significant for the three pH values (Tukey test, p < 0.05). Besides the efficiency, the NaOH concentration used to reach the pH tested must be also considered to determine the optimal pH. In the tests, the NaOH concentration of 0.7, 2.6 and 6.4 g L 1 was used to modify the pH value to pH 12, 12.5, and 13, respectively. The difficulty in modifying the pH values of the samples is associated with the NaOH capacity, which can be observed by the titration curve of NaOH (Kahlert et al., 2016). In this curve, the pH modification is slow for pH values higher than pH 11, requiring a higher amount of base. This finding ex plains the high concentration of NaOH to reach pH 12.5 and 13. In this context, the pH 12 was considered the optimal value because the NaOH concentration was considerably lower than the other pH values (12.5 and 13) and also promoted efficient microalgae harvesting (FE ¼ 91.1%). Thus, the optimized parameters were GV ¼ 500 s 1, TM ¼ 30 s, pH 12, and RR ¼ 20%.
3.1.3. Optimization of flotation The DAF process occurs when the opportunity for collisions and consequent attachment among flocs and air micro-bubbles is provided. The floc-bubble aggregates must rise to the systemʼs surface, and then be removed to achieve water clarification. For bubble formation, air is dissolved into an amount of water by adding air under pressure in a saturation chamber. The saturated water is then forwarded to the flotation system under atmospheric pressure for the bubble release. The quantity of air bubbles is associated with the saturation pressure and the amount of saturated water used in the flotation tests. Moreover, the amount of saturated water must ensure the adequate bubble volume to reduce the bubble-floc density to less than that of the water, allowing the bubble-floc to reach the surface (Crossley and Valade, 2006; Edzwald, 2010). The amount of saturated water used in the flotation tests and its respective bubble volume is associated with the recirculation rate (RR). Due to the importance of this parameter to the DAF process, it was selected to be investigated. The influence of RR ranging from 10% to 20% on FE is shown in Fig. 5. A high range of FE was experimentally obtained at pH 12 (75.3–91.1%) according to the RR evaluated, in contrast to pH 12.5 (94.2–97.9) and pH 13 (97.0–99.5%). Statistical analysis showed a significant effect of RR only at pH 12 (Tukey Test, p < 0.05). The highest efficiencies were achieved using RR ¼ 20% for the three pH values tested. Based on that, RR ¼ 20% was chosen as the optimum value. The results for RR showed a strong influence of this parameter on
3.2. Optimized harvesting The quality of municipal and piggery wastewater used to feed the UASB reactor is subject to variations in each cultivation cycle. This oc curs because the wastewater characteristics (mainly municipal waste water) depend on weather conditions, daily patterns, and possible industrial wastewater discharge (Chys et al., 2018). Considering the use of UASB effluent as a culture medium for microalgae cultivation, it may affect the microalgae production and nutrient removal. In order to check the reproducibility and resilience of the optimized harvesting process throughout these wastewater quality variations, coagulation-flotation tests were carried out using PBRE from three different cultivation cy cles (each one occurring over a week). The FE obtained from these tests using the best three pH conditions (12, 12.5, and 13) are shown in Fig. 6. FE results proved that the opti mization process was successful, and efficiencies higher than 96% were obtained in all the PBRE tested. Furthermore, no significant differences in FE were found considering the pH values used (Tukey test, p < 0.05). An interesting point is that the efficiencies obtained are somewhat higher than those found during the optimization process. Moreover, the FE results found (96.5–97.9%) are higher than those reported in the literature using flotation for other microalgae strains and different types of culture medium. The FE varying from 81 to 95% is usually found in traditional methods of flotation based on bubble gen eration with different types of coagulants (e.g. natural polymers, metal salts, and surfactants) (Alkarawi et al., 2018; Kurniawati et al., 2014; Kwon et al., 2014; Laamanen et al., 2016a, 2016b; Xia et al., 2017;
Fig. 4. Flotation efficiency (FE) of C. sorokiniana using different mixing times (TM) at pH 12, 12.5, and 13. Tests were performed using GM ¼ 500 s 1 and RR ¼ 20%. 5
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concentration (Nguyen et al., 2019a); and illumination condition (fluorescent, sunlight) (Nguyen et al., 2019). Therefore, optimization of PBR operational conditions and harvesting methods for each type of wastewater is clearly needed. Some studies have been performed in order to investigate the application of microalgae cultivation in wastewater treatment followed by a harvesting method (Table 2). The presented studies differ in scale, operational conditions, harvesting method types, microalgae strains, wastewater type and consequently, influent concentrations in terms of N, P and COD. These different characteristics make the results diverge significantly and the data comparison difficult. However, the results (including from the present study) showed high and satisfactory efficient removals of pollutants (N, P, and COD) from the wastewater in general. Besides that, this study used initial COD and nutrient concentrations higher than those reported in the literature, suggesting the robustness of this kind of treatment (PBR followed by pH modulation and DAF) for highly polluted wastewaters. Moreover, the proposed combined treatment (PBR followed by pH modulation-DAF) can also be considered as a more compact system (with efficient removal of COD, TKN, and TP simultaneously) when compared to conventional treatments for particulate and dissolved organic matter, N and P removal from wastewaters. For example, ni trogen removal is usually conducted by two biological processes, nitri fication followed by denitrification, leading to the requirement of two separate reactors with the optimal conditions for each process (Zhang et al., 2007), and for phosphorus removal, additional treatment is needed, such as for physico-chemical methods (e.g. precipitation, sorption, and/or ion exchange processes), biological treatment (e.g. enhanced biological phosphorus removal), or a combination of both (Ndam et al., 2018). Some other factors may be disadvantageous for conventional treatments: physico-chemical methods imply in secondary contamination from the generated sludge, adding further concern for safe disposal; the nitrification/denitrification treatment converts most of the nitrogen to N2, impeding nutrient reuse, differently to what happens through microalgae cultivation (Christenson and Sims, 2011). Thus, these results indicate that the microalgae cultivation in PBR followed by the coagulation-DAF process configured an efficient process for wastewater treatment and biomass recovery. Considering future studies, a complete microbiological assessment of the harvesting process is recommended. However, high removal of pathogenic microorganism is expected. DAF has been reported as an effective wastewater treatment for pathogenic protozoa (Giardia spp. and Cryptosporidium spp.), E. coli and Total Coliform removal (Nardi et al., 2011; Santos and Daniel, 2017). In addition, high pH (10–12) has a high bactericidal effect, which promotes lysis of indicator bacteria cells (e.g, E. coli and total coliform) (Starliper and Watten, 2013). An evaluation of the disinfection treatment (e.g. ozone) in the FTE is also recommended to reach a better quality to reuse the effluent.
Fig. 6. Flotation efficiency (FE) of coagulation-flotation tests using three different photobioreactor effluents (PBRE). The tests were performed using the optimized parameters (GV ¼ 500 s 1, TM ¼ 30 s, and RR ¼ 20%).
Zhang et al., 2014). Therefore, great FE results were achieved, even using a complex matrix as wastewater. This fact indicates that pH-modulation followed by DAF has a great potential to be applied as a harvesting method, which has been scientifically untapped so far. The improvement of wastewater quality after the coagulationflotation tests using the optimized process was also analyzed (Table 1). The wastewater quality (FTE in relation to the PBRE) improved significantly (Tukey test, p < 0.05). High removals were ach ieved for physical parameters: 96.4–98.3% for turbidity, 91.3–97.2% for apparent color, 80.5–86.8% for COD and 94.3–99.1% for TSS. These results reflect the capacity of pH modulation-DAF to remove the par ticulate fraction, which includes wastewater solids and microalgae. On the other hand, sCOD, DOC and True color had low removal as expected. Average removals were 30.9–38.4% for sCOD, 13.2–17.7% for DOC, and 40.2–52.3% for True color. These parameters represent the dissolved or soluble part of the organic matter present in the wastewater and the low removal capacity of these fractions by the DAF is wellknown (Leite et al., 2019c; Santos and Daniel, 2017). The nutrient removal efficiencies were 88.6–95.1% for TKN and 91.8–98.3% for TP. These results are associated with the microalgal biomass removal as the nitrogen and phosphorus dissolved cannot be removed by DAF (Reali et al., 2001). Thus, nutrient removal from wastewater mainly depends on the cultivation parameters and nitrogen and phosphorus (N:P) ratio (Choi and Lee, 2015), which affects the nutrient uptake by microalgae, and consequently the nutrient removal by the pH modulation-flotation process. Other operating parameters may influence microalgae harvesting methods from wastewater and in the final effluent quality: coagulant type (organic, inorganic) combined with the pH (Cassini et al., 2017); hydraulic retention time in PBR (Elawwad et al., 2017); hydraulic retention time (Shchegolkova et al., 2018); initial microalgae
Table 1 Evaluation of photobioreactor effluent (PBRE) and flotation test effluent (FTE) quality. The tests were carried out over three weeks using the optimized parameters (GV ¼ 500 s 1, TM ¼ 30 s, pH 12, and RR ¼ 20%). Initial C. sorokiniana concentrations were 0.5, 0.6, and 0.8 g L 1 in the cultivation cycle 1, 2, and 3, respectively. Average removal is shown between parentheses. Cultivation cycle
Sample
Parameters Turbidity (NTU)
Apparent color (Pt–Co)
True color (Pt–Co)
TSS (mg⋅L 1)
COD (mg O2⋅L 1)
sCOD (mg O2⋅L 1)
DOC (mg⋅L
258 123 � 2 (52.3) 214 128 � 1 (40.2) 296 161 � 4 (45.6)
454 � 30 4�4 (99.1) 409 � 6 13 � 1 (96.8) 563 � 6 32 � 3 (94.3)
778 � 2 103 � 3 (86.8) 774 � 2 151 � 12 (80.5) 1000 � 3 193 � 2 (80.7)
136 � 1 94 � 3 (30.9) 211 � 1 130 � 3 (38.4) 289 � 1 192 � 9 (33.6)
35.9 � 0.2 30.6 � 0.3 (14.8) 48.6 � 0.1 40.0 � 0.7 (17.7) 62.2 � 0.2 54.0 � 1.2 (13.2)
1
PBRE FTE
175 3 � 0 (98.3)
4564 130 � 2 (97.2)
2
PBRE FTE
196 7 � 1 (96.4)
6740 586 � 9 (91.3)
3
PBRE FTE
284 9 � 2 (96.8)
10,430 817 � 5 (92.2)
6
1
)
TKN (mg N⋅L 1)
Total phosphorus (mg P⋅L 1)
42.8 � 0.8 2.1 � 2.0 (95.1) 37.6 � 1.1 4.3 � 1.0 (88.6) 99.8 � 1.4 11.0 � 0.5 (89.0)
35.3 � 1.5 0.6 � 0.0 (98.3) 38.3 � 1.2 1.8 � 0.6 (95.3) 71.0 � 1.6 5.8 � 0.5 (91.8)
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Table 2 Microalgae cultivation combined with different methods for microalgae harvesting aiming at wastewater treatment and biomass recovery. Treatment process
Operation mode
Microalgae
Wastewater type
Wastewater influent concentration (mg⋅L 1)a
Removal (%)
Reference
Membrane photobioreactor microfiltration PBR and sedimentation
Continuous
Chlorella vulgaris
Synthetic
Batch
Chlorella sp.
Domestic
PO34 : 1.8 NH4: 4.0 TP: 9.8 TKN: 37.2 COD: 110
Praveen et al. (2016) Cassini et al. (2017)
PBR and sedimentation (lamellar settler)
Continuous
Scenedesmus, Spirulina, Ankistrodesmus, Closterium, and Anabaena
Domestic
TP: 2.6–5.8 NH4: 6.5–12.5 COD: 60-90
PBR and filtration
Batch
Domestic
PBR and auto-flocculation
Batch
Scenedesmus quadricauda and Chlorella sorokiniana Chlorella vulgaris
PBR and coagulation (pH modulation)-DAF
Batch
Chlorella sorokiniana
Domestic and piggery
PO34 : 2.5–24.2 NH4: 1.6–5.6 PO34 : 11.5 TN: 92.7 COD: 306 TP: 38-75 TKN: 183-300 COD: 450-670
PO34: 2 NH4: 84-97 TP: 85.7–90.6 TKN: 85.5–95.1 COD: 80-84 TP: 59.7–85.6 NH4: 63.1–90.2 COD: 44.6–67.3 PO34: 89-91 NH4: 34-48 PO34 : 79-95 TN: 72-83 COD: 81-88 TP : 92-98 TKN: 96-99 COD: 72-78
Seafood
Elawwad et al. (2017)
Shchegolkova et al. (2018) Nguyen et al., 2019 This study
Note: Nitrogen concentration was expressed as TKN (total Kjeldahl nitrogen), NH4 (ammonia) and TN (total nitrogen), and the phosphorus concentration was expressed as PO34 (ortophosphate) and TP (total phosphorus).
4. Conclusions
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The results showed the pH modulation and DAF as an effective process for microalgae harvesting from wastewater. Parameter optimi zation using the one-factor-at-a-time method was successful, in which high efficiencies were obtained for C. sorokiniana harvesting (96.5–97.9%). The optimal parameters were a velocity gradient of 500 s 1, mixing time of 30 s, pH 12, and 20% of recirculation rate. The method also showed robustness with the variation of photobiorreactor effluent quality. Moreover, wastewater quality improved significantly after microalgae harvesting, with high nutrient removal (88.6–95.1% of TKN, and 91.8–98.3% of Total phosphorus), and organic matter removal (80.5–86.8% of COD). This study also indicated the importance of operational optimization, and the results could be potentially applied as practical guidelines for microalgae harvesting on a large scale. Acknowledgements ~o Paulo Research Foundation This work was supported by the Sa (FAPESP) for research assistance [Proc. 2013/50351–4] and Master’s ~o Grant [Proc. 2017/14620–1]. The authors would like to thank SAAE Sa �cio de Loyola Farm. Carlos and the Santo Igna Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.jenvman.2019.109825. References Ahmed, N., Jameson, G.J., 1985. The effect of bubble size on the rate of flotation of fine particles. Int. J. Miner. Process. 14, 195–215. https://doi.org/10.1016/0301-7516 (85)90003-1. Aktas, T.S., Fujibayashi, M., Maruo, C., Nomura, M., Nishimura, O., 2013. Influence of velocity gradient and rapid mixing time on flocs formed by polysilica iron (PSI) and polyaluminum chloride (PACl). Desalin. Water Treat. 51, 4729–4735. https://doi. org/10.1080/19443994.2012.751883. Alkarawi, M.A.S., Caldwell, G.S., Lee, J.G.M., 2018. Continuous harvesting of microalgae biomass using foam flotation. Algal Res. 36, 125–138. https://doi.org/10.1016/j. algal.2018.10.018. Alwan, G.M., 2013. Simulation and optimization of a continuous biochemical reactor. J. Chem. Eng. Process Technol. 4, 1000142 https://doi.org/10.4172/21577048.1000142.
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