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Article

Investigation of the Phycoremediation Potential of Freshwater Green Algae Golenkinia radiata for Municipal Wastewater

Department of Sea and Freshwater Science & Technology, Ege University Faculty of Fisheries, 35100 Izmir, Turkey
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Author to whom correspondence should be addressed.
Sustainability 2022, 14(23), 15705; https://doi.org/10.3390/su142315705
Submission received: 12 October 2022 / Revised: 16 November 2022 / Accepted: 22 November 2022 / Published: 25 November 2022
(This article belongs to the Special Issue Pollution and Toxicology of Aquatic Ecosystems)

Abstract

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Recent developments in the removal of pollutants from wastewater show that phycoremediation to wastewater treatment and reuse wastewater may provide sustainable biosolutions. This work investigated the performance of the green microalgae Golenkinia radiata Chodat 1984 (Chlorophyceae) in terms of N, P, and COD removal at different treatment stages of municipal wastewater, reusability of remediated wastewater and wastewater-based biomass production. Water samples were taken from different wastewater units (presettling basin effluent, active sludge basin effluent, and discharge channel) of a municipal wastewater treatment plant (İzmir, Turkey). In the 7-day experiments, Chl-a, Chl-b, DO, pH, and T (°C) were also measured alongside the pollutant analyses. The results in Chl-a (1803 ± 75.9 µg L−1) and biomass yield (7.66 ± 0.05 g L−1) in the primary effluent (P) were quite impressive. Additionally, the results showed that the correlation between the increase in Chl-a and the residual concentrations of pollutants was remarkable. NH4-N, NO3-N, NO2-N, PO4-P, and COD treatment efficiencies were in the ranges of (74.6–83.0%), (15.35–70.4%), (0.00–47.22%), (80.67–86.27%), and (77.22–87.53%), respectively. The final concentrations of pollutants (E) were found to comply with EU legislation. The results also reveal that green microalgae G. radiata may be a strong candidate for microalgae-based wastewater treatment.

1. Introduction

Globally, most marine and freshwater aquatic systems are primarily polluted by domestic and industrial wastewater (WW). Due to rapid population growth, urbanization and industrialization, environmental pollution problems have become more severe and affected ecosystem services [1]. Research estimates suggest that global municipal wastewater (MWW) production is predicted to reach 51 percent by 2050, compared with current levels [2]. Although it is claimed that 80% of global wastewater discharged into the aqua system is insufficiently treated, a recent study showed that about half of global wastewater is treated [3] rather than the previous estimate of 20% [4]. Despite this promising finding, especially in countries with limited water resources, given that problems such as global climate change and drought will continue, there remain significant concerns about issues such as the sustainability of water resources and access to clean water resources. Sustainability of water resources can only be possible with technologies with a zero-waste approach, in addition to approaches such as reducing the cost of wastewater treatment plants (WWTPs) and transitioning to systems that require less energy.
The conventional treatment system used in wastewater treatment (WWT) consists of physical, chemical, and biological treatment. Although these systems are used together or separately depending on pollutant types, contamination level, and the volume to be treated, they are insufficient in many cases. In addition, even if domestic and industrial wastewaters comply with discharge standards, they may affect aquatic organisms negatively such as through toxicity or inhibition effects, even after treatment, due to varying waste loads [5]. The other alternative, advanced wastewater treatment, has disadvantages, such as being a costly and high-energy-requiring process. Today, environmentally friendly technologies are highly promoted and increasingly widespread to alleviate or reduce environmental pollution. One such ecological and environmentally friendly technology is the phycoremediation process, which promises biotechnology-oriented WWT, and the number of microalgae-based WWT systems is increasing more and more [6]. Phycoremediation is defined as using microalgae (or, more rarely, macroalgae) to remove or bioconvert pollutants from foods and wastewater [7]. Phycoremediation systems, where wastewater is used as a resource, not as ‘waste’, could be the key to achieving high-performance treatment. Using microalgae in WWT may contribute to the WWT thanks to its cost-effectiveness, low energy necessity, beneficial biomass production, reduction in sludge formation, success in removing heavy metals, etc. [8]. On the other hand, there are still uncertainties about the varying concentrations of pollutant content of wastewater, difficulties in optimizing the system, and whether the convenient microalgae species is selected, even though a great number of studies have focused on microalgal wastewater treatment in recent years.
One of the four most important classes of microalgae, in terms of abundance, is green algae (Chlorophyceae) [9,10]. Members of the class Chlorophyceae are widely used in wastewater treatment due to their high removal efficiencies for pollutants and potential feedstock for bioenergy production or other high-value-added products [11]. Because Chlorophyceae members offer many options for microalgae-based applications, this study focuses on a native species belonging to this class. However, studies so far have focused on traditional Chlorophyceae genera such as Chlorella, Scenedesmus, and Chlamydomonas [12], and the number of known best-performance microalgae species is still very limited. For this reason, the first of the main steps toward goals such as identifying the best microalgae-based wastewater treatment, biofuel production, or valuable metabolite extraction is to discover up-and-coming novel microalgae species. The Golenkinia genus, belonging to the Chlorophyceae class, remains a mystery for microalgal technology, apart from a few reports. Almost all published research on the genus Golenkinia has addressed the subjects of its systematics and nutrient supply [13,14,15], sexual reproduction [16], and lipid, sugar, and carotenoid production [17,18,19]. Very few studies were conducted on its potential of culturing in wastewater [20,21]. In one of these previous studies the possibility of using textile wastewater for Golenkinia radiata culture was investigated, but the pollutant removal performance of the species has yet to be studied [20]. In another previous study of Golenkinia sp, one of the limited studies on growth performance in wastewater, the biocomposition and potential of Golenkinia sp for wastewater treatment was investigated in BG11 medium and campus sewage [21]. Although municipal wastewater (MWW) and sewage are sometimes used in the same sense, they are not the same. MWW is a mixture of domestic and industrial wastewater and precipitation water and has a rather complex structure compared with sewage. On the other hand, the term “sewage” describes wastewater from various domestic sources, and sewage is considered a subset of wastewater. While previous research on this genus was conducted in sewage, this study used MWW. As far as we know, this is the first research on green microalgae Golenkinia radiata Chodat 1984 (Chlorophyceae, Chlorophyta) in municipal or any wastewater treatment.
The main target of the research was determining and comparing the growth and treatment performances of native G. radiata in MWW. Primary, secondary, and discharge WW were used in the study to investigate possible places to be deployed for microalgal bioremediation processes that could be employed at WWTP with a practical setup. Additionally, the study aimed to research novel candidate species for use in phycoremediation systems, and to investigate the reuse possibility of obtained final water.

2. Materials and Methods

2.1. Microalgae Culture

Native green microalgae Golenkinia radiata Chodat 1984 were isolated from the Bornova Stream, İzmir-Turkey, according to the standard method [22]. The stream flows through the center of the city and was heavily polluted by industrial and domestic inputs [7,23]. Drinking water was prepared for G. radiata culture by first filtering (0.2 µ cartridge filter, Merck, Darmstadt, Germany) and then sterilizing (1 atm, 121 °C, 15 min). BG11 [24] enrichment medium was used for the strain; the medium composition is presented in Table S1. The monographic and descriptive studies belonging to different scientists explained in Ref.S1 were utilized to identify microalgae samples and were checked and verified by the expert on the subject at Katip Çelebi Uni. (Izmir). A microscope (Olympus BX53) was used for the identification and photography of the species. The strain was incubated and acclimated in photoperiod L:D = 24:0, at 24 ± 0.5 °C, at 100 μmol m−2 s−1 light intensity. The light intensity was measured with Quantum Instruments Photometer1 and was kept constant throughout the experiments. An air-pump with an airflow rate of about 400 mL min−1 was used for aeration. Then, the microalgae were acclimatized in a 5 L volume of wastewaters (filtered and sterilized) before being used in the experiments.

2.2. Experimental Design

The MWW was collected from a large municipal wastewater treatment plant (MWWTP) in İzmir City. The WW samples taken from different points of the treatment plant, consisting of primary settling effluent (P), secondary sedimentation effluent (S), and final effluent (E), were promptly brought to the EÜ Fisheries Faculty Basic Sciences Department Ecotechnology laboratory. Then, WW samples were filtered (0.2 µ cartridge filter, Merck, Darmstadt, Germany), sterilized (1 atm–121 °C, 20 min), and kept at a low temperature (+4 °C) after analyzing their characteristics [7]. The raw MWW characteristics and the discharge criteria are given in Table S2, and the experimental setup of the study is shown in Figure 1.
The primary settling effluent (P), secondary sedimentation effluent (S), and final effluent (E) samples and control groups (C) (BG11 medium) were put into 1.5 L batch reactors respectively, and G. radiata were added. Each experimental group was performed in triplicate. The strain in the exponential growth phase (4–5 days old) was collected by centrifugation (4000× g), and inoculated into the WWs. The amount of initial Chl-a was adjusted to contain approximately 55 ± 5 µg Chla L−1 in each trial group. Chlorophyll-a and Chlorophyll-b concentrations of the cultures of G. radiata were measured daily during the trial period as in vivo Chl-a and Chl-b fluorescence using a fluorometer (AquaFluor, Turner Designs, San Jose, CA, USA). Temperature and dissolved oxygen (DO) were measured using a WTW Oxi 330 dissolved oxygen meter; pH was measured using the Orion SA 729 pH meter. The analysis of pollutants was performed by modifying the method proposed by [7,25]. A sampling of 25 mL from each culture was taken daily to be used in pollutant analyses for each trial. After centrifugation at 6000× g (10 min), the samples were filtered (Whatman® nylon MF.-p.sz.0.45 µm, Merck, Darmstadt, Germany). NO3-N, NO2-N, NH4-N, PO4-P, and COD analyses of the filtered samples were performed by using reagent tests (Merck) according to the Merck Spectroquant Multy© Standard Methods Manual, as described in the previous study [7].

2.3. Equations and Statistics

The exponential growth rates (µ, day−1) based on Chl-a and Chl-b were calculated using the following expression:
μ = log 2 ( Chl x / Chl i ) t x t i
Chli: the Chl-a at ti, µg L−1; Chlx: Chl-a at tx, µg L−1; ti and tx: start and end of the growth were determined. The following equation was used for Chl production (PChl);
P ( chl ) = Chl t t Chl t i t t t i
Chlti: Chl-a concentration at time ti; Chltt: Chl-a concentration at time tt.
The removal efficiency R(%) of NH4-N, NO3-N, NO2-N, PO4-P, and total inorganic nitrogen (TN = NH4-N + NO3-N+ NO2-N) was calculated for three WW as follows:
R ( % ) = P 0 P t P 0 × 100
P0 (at the to) and Pt (at the tt) symbolize the residual concentration of pollutants (mean + SD).
The method explained previously was used to determine the biomass DW (g L−1) [26]. 50 mL microalgae suspension was collected, and microalgae suspensions (V) were sampled daily and filtered (0.45 μm Whatman GF/C 47 mm glass fiber) after being predried (105 °C, 24 h) (W1, g). The filters containing algae were also dried to obtain a constant weight (W2) and the weight of deionized water (W0) was accepted as a blank. The dry weight (DW, g L−1) and biomass productivity (BP, g L−1 day−1) were calculated using the following equations (T: the trial period):
DW = W 2 W 1 W 0 V
BP = DW T
Significant differences were determined for each parameter (mean ± SD) itself (µ, Chl-a, and Chl-b, DW, BP, P, and R%) with a one-way variance analysis (Fisher’s LSD-ANOVA). Chl-a and TP, TN, COD parameter relationships, Chl = f (TP, TN, COD), were reproduced using LLS using the approach of the previous work [7]. Before analysis, the Chl data were transformed (log10) to provide the homogeneity of their variances. The effects of categorical variables TN, TP and COD on these relationships were examined using a multivariate general linear model (GLM) with Statgraphics software (VR-16.1.11, Statgraphics Technologies, Inc., The Plains, VA, USA).

3. Results and Discussions

3.1. Growth Performance

Golenkinia is a genus with very interesting features. It contains rare species, 10 species belonging to this genus have been described, sexual reproduction is still controversial, and it is postulated that it is one of the relatively few single-celled oogamous green algae [19]. All of the few existing studies related to Golenkinia genus focused on its physiological and morphological characteristics, pigment synthesis, sexual behavior, and nutrition mode [14,16,19,27,28,29,30]. Golenkinia radiata, a member of Chloroccales, is a cosmopolite species living in freshwaters [20]. It is a unicellular microalga with several spines of 10–30 µm in diameter, and several fine spines of 60–65 µm in length (Figure 2). This was the first study on Golenkinia radiata on MWWT performance, and growth performances based on Chl and pollutant removal efficiency of native G. radiata strain in different MWW types were investigated. Within the scope of this study, the growth performances of the species in WW were examined based on main pigments (Chl-a, -b) and dry weight. However, the changes that may occur in cell sizes during the growth of the species in WW may need to be examined in detail in the future. The measurement of in vivo Chl fluorescence was used as a determiner of the exponential growth rate and Chl-based productivity (P) of the species [7,31,32]. The maxChl quotas, Chl-a and -b basis µ, pigment production (P, Chl-a), and biomass production (DW) of G. radiata are summarized in Table 1. Figure 3a,b presents Chl-a and Chl-b performance of G. radiata in different WW. Typical Chl-a and Chl-b-based growth graphs, consisting of both duration lag phase and exponential growth phase, were obtained for three WW and C medium (Figure 3a,b). Native green microalgae G. radiata exhibited a similar growth pattern in all WW and C groups. The same 4-day lag phase observed in all trials suggested that G. radiata required a longer adaptation duration to WW. However, the duration of the lag phase observed for all cultures in different WW was the same, including C medium. A very recent study has reported that the reason for the 1-day short lag phase in WW may be due to the fact that microalgae strains have adapted to MWW during 4 generations [7]. Another study mentioned a lag phase time of 10 days in the culture of laboratory strains with no applicated MWW conditioning [33]. This study was carried out with the first culture after the isolation of native G. radiata without any WW adaptation period, and the development of the species continued for up to 7 days regardless of the WW type. In light of the results obtained, it can be said that natural G. radiata has a high adaptation ability for all types of MWW, because the type of WW, its load, which species is used, and the growth strategy of the species at varying concentrations can affect the duration of the lag phase. Similarly, a 5-day adaptation duration in G. radiata growth has been reported in sterile and non-sterile textile WW [20]. This was an important criterion for evaluating the growth performances of G. radiata in MWW with different WW characterizations. While the native microalgae grown in all WW types had a similar growth trend to the C trial in the first 4 days, the highest Chl-a quota of G. radiata was obtained from the primary effluent trial with 1803.00 ± 75.92 µg L−1. The max-Chl quota reached by the strain in the trial groups was obtained as BG11<E<S<P, respectively. Statistically, the species had similar results in S and E. In contrast, the max- exponential Chl-a occurred in P, and the Chl-a of control groups was remarkably lower than the other group. The Chl-b started increasing from day 1 in all trials; after day 4, it differed depending on the WW type (p < 0.05), similar to the Chl-a-based growth curve (Figure 3c). While the highest Chl-b quota of the native microalgae was obtained from the P (primary effluent) trial with 649.2 ± 28.2 µg L−1, the maximum exponential Chl-b quota that the strain could reach was obtained from the P, S, E, and C trials, respectively. Chl a:b ratios for all trial groups increased versus decreasing N concentration over the trial period. The increase in chlorophyll (Chl) a:b ratio can be attributed to a higher degradation of Chl-b during nitrogen deficiency in the culture medium as a way to recycle the nitrogen pool [34,35]. The proportional increase in Chl-a and Chl-b may be an indicator of the chlorophyll cycle [36] that interconverts chlorophyll a and chlorophyll b. Similarly, growth rates based on Chl-a and -b can be expected to be parallel/proportional, and at the same time, the result can be considered confirmation for growth rates based on Chl-a. Therefore, the growth rate based on Chl-b was also calculated. The growth rate ratios (µ Chl-a/µ Chl-b) (Table 1) were consistent with both the differences in Chl a:b ratios in the trial groups and amongst the trial groups.
G. radiata reached its maximum growth rate in primary WW (C:N:P–40.5:10.7:1) (Table 1). The growth rates obtained in S, E, and C trials were similar in E and S WW, and higher than in the BG11 medium (Figure 3c). The quota of Chl-a and Chl-b of G. radiata in the exponential phase obtained from the C medium was the lowest quota in this study. On the other hand, the 7-day maximum quota of Chl-a and Chl-b in the C medium were similar to the previous research, reported as 406.9 ± 145.4 µg L−1 and 210 ± 58.8 µg L−1, respectively [20]. Ultimately, G. radiata showed excessive growth in primary effluents and its Chl-a, -b, and daily Chl productivity (P) was significantly higher than other trial groups (Table 1). It reached 8.3-fold Chl-a and 7.7-fold Chl-b of concentration compared with the BG11 (C) trial at the end of the exponential phase. Moreover, its daily biomass productivity (BP) was 12-fold more than in the C trial. Even though our previous study conducted in textile WW had given a pioneer signal [20], this enormous growth ability in MWW of native green microalgae G. radiata had hitherto been unexplored.
The organic C, N, and P concentrations in WW may significantly influence the growth rate. On the other hand, besides pollutant concentrations, their molar proportions in the medium may influence growth rates [33]. The C:N:P molar ratio for marine phytoplankton is accepted at 106/16/1 (Redfield ratio), whereas in the case of freshwater species, nitrogen and phosphorus molar proportion is accepted ranging from 8:1 to 45:1, and this is an exception rather than a rule determined via the species-specific cellular quota [33]. Moreover, the optimum ratio for C:N:P could not be well described for the microalgae- based treatment of MWW. For this reason, the link between C:N:P ratios in WW and the growth rates were also investigated. The results showed apparent differences in the initial C:N:P ratios of P, S, and E culture medium and C medium (Table 1). While the growth rate of G. radiata was almost the same in E and S effluents, the C medium result was significantly lower than in both of those trials (Figure 3c). In a previous study, the highest growth rates of monocultures of two green microalgae (Chlorella vulgaris-0.61 day−1 and Neochloris oleoabundans-0.35 day−1) were reportedly attained in pretreated effluent which had a C:N:P ratio of 24/5/1. The considerably high growth rate of G. radiata (1.687 ± 0.04 day−1) in this study was obtained in primary effluent which had a C:N:P ratio of 40.5/10.7/1 (Table 1). The specific growth rate of G. radiata is higher than the growth rates of both microalgae. However, the C:N:P ratio of WW used in this study is higher than in the previous study given above.
The ratio of N:P is also essential in the macronutrient requirements for algal growth. The optimal ratio of N:P for both nutrient removal and biomass yield in MWW purification was reported to range between 5–30 according to the environmental parameters in the medium [37]. Indeed, a previous study has found that while C. vulgaris exhibited a higher growth rate in municipal effluent which had a low N:P (0.36/1) ratio, the rate was lower in trials which had a high ratio of N:P (53/1) [38]. Although the N:P ratios of E WW and C medium were quite similar in the current study, the growth rates of G. radiata were significantly different, contrary to expectations. Interestingly, the growth rate of the species in E WW was quite close to that obtained from S, suggesting that it may be associated with the concentration of organic carbon in both WW. As a matter of fact, the ratios of organic carbon in S and E WW were very close to each other, confirming this. This result may also indicate that G. radiata can achieve mixotrophic growth.
The results of this study demonstrated a remarkable linkage between the pollutant removal ratios and the increase in Chl amounts (Table 1). On the other hand, the growth rate of G. radiata in the exponential growth phase in primary WW was significantly higher than in other trials. The specific growth rates ranged from 0.547 ± 0.03 to 1.687 ± 004 d−1 (Figure 3c). A previous study focusing on Golenkinia aff brevispicula-FAUBA-3 indicated that the species reached the specific growth rate of 0.78 d−1 at the exponential growth phase 6-days [39]. G. radiata exhibited a higher growth rate in all WW trials than in the previous study. However, the growth rate was lower in the BG11 medium (Table 1).
Wastewater-fed microalgae biomass production is becoming increasingly crucial in line with sustainability goals. However, the culture conditions in algal biomass production are an essential determinant of the amount of biomass to be obtained, as well as parameters such as the selected species, and WW type and content. For example, one of the limited previous studies on a strain belonging to the genus Golenkinia showed that the strain reached approximately 9-fold higher biomass productivity in a semi-batch-culture than in a batch-culture system [39]. It has also been reported that the species reached 1.04 ± 0.7 g L−1 of biomass dry weight (for eight days) with a growth rate of 0.78 d−1 (in Jaworski’s Medium) in the batch-culture system without any adaptation process [39]. MWW is an alternative that can be easily used to obtain microalgae biomass with its rich nutrient content, but biomass yield depends on the specific growth performance of the species. In this study, the biomass yield (DW) of G. radiata increased in parallel with the increase in nutrient concentration in MWW. The DWs obtained from the P, S, E, and C batch-experimental groups were 7.66 ± 0.05, 7.50 ± 0.05, 6.50 ± 0.09 and 2.33 ± 0.0 g L−1 (Table 1), respectively, and these values were relatively high. In a previous study, the algal biomass DW of N. oleoabundans was reported as 0.50, 1.44, and 1.11 g L−1 for MWW in different stages (primary, secondary and centrate), respectively [33]. Another study reported that N. oleoabundans, after a 96 h cultivation period in secondary WW, reached algal biomass of 0.68 g L−1 DW [40]. Another study reported that C. vulgaris achieved a 0.948 day−1 growth rate in WW at an N:P ratio of 0.36:1, and a 0.343 day−1 at 53:1 [40]. Reyimu and Özçimen, 2017 [41] reported that the maximum dry weight (1.285 g L−1) of N. oculata was provided at a mixing ratio of 75% (v/v) MWW. Differences between the biomass yield results from other studies and results of the current study may be due to differences in species-specific characteristics in initial concentrations of inoculated microalgae at the start of experiments, or nutrient levels in the medium [33]. Because microalgae can regulate their biomass volumes according to the amount of nutrient uptake from the environment, low biomass (DW) can be achieved when nutrient levels in WW are low [33,42]. The biomass results of this study showed that the G. radiata strain cultured in MWW has great potential for wastewater-based biomass production.

3.2. Nutrient Removal

The initial contaminant load of MWWs and C medium were ranked as P, C, S, and E (Table 2). The results of the native G. radiata in the removal performance of N and P, and COD showed that green microalgae grown in batch-culture mode had a high ability in bioremediation of MWWT (Figure 4). The R-Squared indicated that the models f(TN, TP, COD) explained a range of 88.33–95.79% of the variations of Chl-a biomass of G. radiata (p < 0.0245–p < 0.0005) (Table 1). As G. radiata had already adapted to the variable environmental conditions in the natural environment, it provided comparable results in terms of performance. Members of the same systematic microalgae group have similar characteristics, so it may be necessary to compare species belonging to the same group for a more accurate assessment of the new candidate microalgae performance in the WWT process, as they may show similar characteristics in similar WW. The native G. radiata used in this study demonstrated high performance in the removal of N (-NH4, -NO3, -NO2), P (-PO4), and COD and gave results comparable to other conventional Chlorophyceae species used in similar wastewater (Table 3). The highest removal efficiencies of G. radiata were obtained in secondary effluent (S) with 76.40% in TN removal, in primary effluent (P) with 86.27% in TP removal, and in C medium with 87.53% in COD removal, respectively.
The changes in temperature, pH, conductivity, DO, and salinity observed in the 3-repeat trials for seven days are given in Figure S1a–e. In the trials inoculated with G. radiata species, the DO value increased as soon as the trials started. After the second day, a steady state continued until the end of the fifth day, and then showed an increasing trend again. At the end of the sixth day, a decrease was observed in the C, S, and E trials, while the highest DO value was reached on the seventh day in the primary effluent (P) trial (approximately 9.9 mg/L) (Figure S1b). DO values were similar in all groups throughout the experiment (Figure S1b) and coincided with a similarly sharp increase in chl, which is a proxy of the increase in photosynthetic activity (Figure 3a,b). DO values decreased to 8.26–8.56 mg/L on day 2 for all trials. Subsequently, with the increase of Chl-a and Chl-b, up to 9.86–10.22 mg/L was recovered. As a general trend, an increasing pattern was observed in E, S, and C experimental groups and the highest DO value was reached on the sixth day in these experimental groups. After day 3 there was an increase in pH in all batch-system cultures, while the temperature was relatively stable throughout the trials (Figure S1a).
The pH trend of the trials was quite similar in the P, S, and E experimental groups, with pH hovering around 9.0 and increasing slightly toward the end of the trial period (Figure S1a). The pH increase was likely due to the photosynthetic activity of microalgae [43]. The highest measured pH value was obtained from the C trial, at 9.26. When the initial pH of the experimental groups was compared, a low pH level was recorded in the C group. The temperature, conductivity, and salinity values of the experimental groups remained relatively stable during the trial period, and between the WW groups, in terms of temperature, conductivity and salinity, no significant differences were found (p > 0.05) (Figure S1c–f).

3.2.1. Nitrogen Removal

Nitrogen is an essential macronutrient that regulates the metabolism and, consequently, the development of microalgae and their biochemical content. Generally, most microalgae prefer NH4-N requiring low energy for cellular supply, although cellular uptake can be affected by a variety of nitrogen from sources such as NO3-N, NO2-N, and rarely urea [7,44,45]. All G. radiata cultures showed quite satisfactory results in removing ammonium from MWW (Figure 5a–d). The per cent NH4–N removal rates for P, S, E WW, and C medium, treated with G. radiata, were 83.01%, 82.85%, 74.6% and 77.99%, respectively (Table 3). However, NH4–N removal efficiencies of microalgae species can be highly variable depending on both species-specific features and the initial concentration of NH4-N. A previous study showed that Chlorella sp achieved a reduction in nitrogen (83% N as NH4+) in MWW [46], while another study indicated that the mean TN removal coverage ranged from 72% to 83% [31]. Figure 5a–d show that during the exponential growth phase of G. radiata, NH4–N concentrations continued to decrease throughout the trial period. A previous study reported that the time required for C. vulgaris to remove nitrogen was 15 days [33]. The DO concentration did not stay below 8.4 mg L−1 confirming the observed algae growth (Figure S1b).
The most complex form of nitrogen uptake by microalgal organisms is nitrate. In the nitrate uptake mechanism, energy (NADH) is needed for the active transport of nitrate and its reduction to nitrite by the reductase enzyme [47]. It has been mentioned in general knowledge that algal microorganisms prefer nitrate uptake when ammonium and/or urea are at concentrations below the saturation limit. Although environmental conditions force microalgae to use different forms of nitrogen, the nutritional strategy they develop for optimal growth depends entirely on species-specific characteristics. The obtained results indicated that G. radiata was less effective than expected in nitrate and nitrite removal. This may also be why the concentrations of NH4-N in all WW used in the trials needed to be higher to encourage the species to use nitrite and nitrate in all WW. This situation is related to the fact that although most of the microalgae can use various N-forms such as NO3-N, NO2-N, and urea, their first preference is NH4-N as it requires less energy for cellular uptake [42,45]. Thus, while in all WW types remediated with G. radiata, the amount of residual NH4-N and NO3-N decreased significantly over experimental time in all trials, no significant decrease was observed in the NO2-N concentrations (Figure 5). Because the experiments were carried out under sterile conditions, it is clear that this result is related to the nitrogen affinity of the microalgae. The NH4-N reduction of G. radiata cultures exhibited an exponential reduction pattern (Figure 5). These were inversely matched with increases in Chl-a quota and biomass of Chl-based algal cells (Figure 3a,b). As a result, G. radiata had an affinity for NH4-N as a nitrogen source, and its first choice for nitrogen source was NH4-N.
Table 3. Pollutant removal performances of some microalgae species in different WW. “—”: not measured, NR: no removal occurred in WW, RT: Retention time (d), MWW: Municipal wastewater, and TN: NH4-N + NO2-N + NO3-N.
Table 3. Pollutant removal performances of some microalgae species in different WW. “—”: not measured, NR: no removal occurred in WW, RT: Retention time (d), MWW: Municipal wastewater, and TN: NH4-N + NO2-N + NO3-N.
MicroalgaeRemoval Efficiency (R%)RT (d)Type of WastewaterRef
NH4-NNO2-NNO3-NTNPO4-PCOD
Golenkinia radiata83.01 ± 3.26NR63.15 ± 3.4575.80 ± 2.6486.27 ± 2.7177.22 ± 0.837Primary municipal wastewaterThis study
82.85 ± 2.85NR68.29 ± 3.3776.40 ± 2.0881.01 ± 1.2683.33 ± 1.99Secondary municipal wastewater
74.60 ± 7.2747.22 ± 8.3370.41 ± 0.7372.40 ± 1.5280.67 ± 4.1686.84 ± 2.51Effluent municipal wastewater
77.99 ± 5.74NR15.35 ± 2.8517.80 ± 1.2479.13 ± 4.6687.53 ± 0.02BG-11
Golenkinia sp. SDEC-16 >9996.748.878Campus sewage[21]
22.4>99 BG-11
Chlorella vulgaris 84.095.033.7913Urban wastewater[48]
Scenedesmus obliquus 95.0926.86
Chlorella ellipsoidea SDEC11 36.0>99.0 8Campus sewage[49]
Chlorella sp. 94100 14 [50]
Chlorella sp.277 9286 9MWW[51]
Chlorella sp. 8980.990.0814Concentrated MWW[52]
82 68.083. 10MWW[44]
68.483.250.9Raw sewage
68.590.656.5Primary MWW
82.885.683Centrate MWW
Chlorella vulgaris60.7 9.960.234.840.128Primary MWW[33]
70.9 22.255.911.549.1Secondary MWW
64.123.1 33.625.861.1Centrate MWW
Chlorella vulgaris and Chlorella protothecoides 73.174.46029MWW[53]
Chlorella sorokiniana UTEX 1230 and Lemna minor 88.091.099.07MWW[54]
Scenedesmus sp 79.057.084.0 MWW[55]
Scenedesmus sp.80.099.086.0 66.0 20Domestic wastewater[56]
Chlorella sp. YG01 84.184.182.3 14Secondary MWW[57]
Chlorella sp. YG02 68.2 99.0

3.2.2. Phosphorus Removal

Phosphorus is found in major cell metabolites of microalgae and is crucial in microalgal development as it is used in many biochemical processes [58,59]. Microalgae, which can provide phosphorus directly from water, cause a pH increase in WW with the use of CO2 through photosynthesis, allowing phosphate to precipitate in WW [60]. In addition, the presence of cations (Ca, Mg, etc.) in MWW helps to remove phosphate by settling [54,55]. Although some studies demonstrated that polyphosphate and phosphite are bioavailable to microalgae such as cyanobacteria [61,62], inorganic phosphate (including Pi, PO4−3, HPO4−2 and H2PO4) is considered to be the most preferred P-form by microalgae [42,63]. Moreover, if the amount of ortho-PO4 in WW is inadequate, microalgae may transform organic-PO4 to ortho-PO4 and use it [33,64]. In this study, G. radiata eliminated 79.13–86.27% of PO4-P under autotrophic mode (24 h light: 0 h dark) in the batch experiments. PO4-P reduction models in the WW samples were close to each other, but the difference between the experimental groups in terms of daily removal performance was remarkably evident from the beginning of the test period (p < 0.05) (Figure 6a).
The highest removal ratio was observed at 86.27% using G. radiata in primary effluent (P), followed by S, E, and C experimental groups with rates of 81.01%, 80.67%, and 79.13%, respectively. The removals of PO4-P in MWW from G. radiata gave satisfactory results comparable to some other studies using WW with similar characteristics (Table 3).

3.2.3. COD Removal

Chemical oxygen demand is another important subject for WW purification and an indicator of organic loading in WW. Still, microalgae-based COD removal has been investigated much less than nitrogen or phosphorus [7]. Some microalgae can make use of organic substances and inorganic nutrients like nitrogen and phosphorus. However, the degradability of organic matter depends on the type of organic forms and species-specific features of the microalgae species used [65]. In previous studies in similar WW types, the COD removal performances of microalgae were highly variable (40–99%) [21,33,54]. Moreover, as there is no previous study with Golenkinia radiata species, the performance of the species was compared with that of the strain of G. olenkinia sp. and other microalgae species (Table 3). Microalgae are known as photosynthetic autotrophic organisms, but some, thanks to their species-specific features, can grow in a heterotrophic and/or mixotrophic mode [7,66]. Results of previous investigations have shown that the COD reduction ratio in both heterotrophic and mixotrophic modes was higher than in the autotrophic mode [54,67]. An early study showed that G. minutissima has the ability to grow in both autotrophic and heterotrophic conditions; it has been reported that acetate inhibited chlorophyll synthesis in the dark, even at low concentrations, and produced high chlorophyll in each photoperiod (light or dark) in the presence of glucose and other carbohydrates [14,27]. Although this study was conducted under autotrophic conditions (24 L: 0 D cycle), G. radiata removed COD 77.22%, 83.33%, 86.84%, and 87.53% from primary effluent (P), secondary effluent (S), effluent (E), and C trial respectively (Figure 6b). COD removal ratios were no different among S, E, and C experimental groups (except P) (Figure 4), but residual concentrations of COD were significantly different for each group (Table 4). Nie et al., 2018 [21] reported that Golenkinia s232 strain reduced a campus sewage COD from 235.96 mgL−1 to 120.64 mgL−1 on day 8 with a removal efficiency of 48.87% [21]. Our results for all experimental groups were considerably higher than the previous study on the genus Golenkinia, while comparable to other microalgae species (Table 3). The COD removal results show that G. radiata can meet the desired COD removal and final WW quality in MWW, its retention times can be adjusted to meet expectations, and it can be integrated into any desired treatment steps. The performance of G. radiata in COD removal under phototrophic conditions also may indicate that important responses may be obtained from future studies of this species under mixotrophic conditions. This result may be due to the growth strategy developed by the microalgae as a result of the high growth rate and self-shading as a result of intensive biomass production.

3.3. Reuse Potential of Final Effluent

Although it is essential today, the reuse of WW is not yet widespread enough due to requiring high capital investment. Cyprus (90%) and Malta (60%) reuse the majority of their WW [68], while WW reuse rates in the Middle East and North Africa and Western Europe, Turkey, Israel, and China are estimated to be approximately 15%, 16%, 1%, 13%, and 13%, respectively [3,7]. In this context, treating WW with microalgae may provide promising opportunities for WW reuse. As a matter of fact, a recent study reported that the final effluent obtained from N. veneta complied with the EU directive (Class: B, C, and D), the Turkey legislation (Class: A and B), and USEPA suggestion (Class: B) [7]. The final effluent characteristic obtained from discharge WW (E) by using G. radiata was found to comply with both legislation compared with the recommended limit values in EU Directives (91/271) [69] and Turkish legislation [70] (Table 4). When the results were evaluated in terms of WW reuse in irrigation, the final pollutant concentrations from the discharge WW (obtained from trial E) were lower than all limit values in the local [71], EU [72], and USEPA [73] directives. The results provided from the treatment of MWW with G. radiata show that the final effluent can be used for watering according to EU directives (Class: B, C, D), national legislation (Class: A), and USEPA (Class: B).
Table 4. Final concentrations of COD, TN, and TP (mean ± SD) at different MWW stages in the batch system with the native microalgae, and comparison with EU and USEPA legislation limit values.
Table 4. Final concentrations of COD, TN, and TP (mean ± SD) at different MWW stages in the batch system with the native microalgae, and comparison with EU and USEPA legislation limit values.
Parameters
(mg L−1)
Final ConcentrationWW Discharge CriteriaWW Reuse for Irrigation
PSEEU Directive
91/271
[69]
Turkey
2004/25687
[70]
Turkey
2010/27527 b
[71]
EU COM (2018) 337
[72]
USEPA (2012)
[73]
COD78.3 ± 2.8848.33 ± 5.724.33 ± 2.5125<100 ˂30 c (B)
<20 d (A)
25 (B, C, D) c
10 (A) d
30 c
10 d
TP1.16 ± 0.01.50 ± 0.00.96 ± 0.01 or 2 a<1 --
TN22.1 ± 2.6414.47 ± 2.0811.38 ± 0.5210-15 a<12 --
a Changing according to the agglomeration size; b It has been set for BOD5 [7,54], c suitable for non-food crops, and d suitable for food crops. Symbols A, B, C, and D represent water classes for reuse in irrigation.

4. Conclusions

The current study presented the removal performance of N, P, and COD of the native green microalgae Golenkinia radiata Chodat 1984 (Chlorophyceae, Chlorophyta) and its growth performance in municipal wastewater. The results showed a remarkable correlation between the increase in Chl-a and the residual concentrations of pollutants. The performance of the native green microalgae in removing COD, N, and P over seven days under phototrophic conditions (24:0) was remarkable. Additionally, the results in Chl-a (1803 ± 75.9 µg L−1) and biomass yield (7.66 ± 0.05 g L−1) in the primary effluent (P) were quite impressive. The final effluent result of the microalgae in the effluent trial (E) fulfilled the limit values of EU 91/271 and EU COM(2018) 337. We may have a strong candidate for wastewater treatment and wastewater-based biomass production based on the results obtained.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su142315705/s1, Ref. S1. Sample processing and identification of microalgae. References [74,75,76,77,78,79,80,81,82,83,84,85] are cited in the supplementary materials. Table S1. The composition of enrichment medium BG11. Table S2. The wastewater characteristic of Cigli Municipal Wastewater Treatment Plant and discharge criteria of effluent. Table S3. Multiple Linear Regression for in vivo Chla of the trials where is the residual TN, TP, and COD concentration-independent variables. Correlation matrix built using Pearson correlation coefficient for (a) primary ww, (b) secondary ww, (c) effluent, and (d) BG11. The upper diagonal matrix represents p values at 95% confidence interval and the lower diagonal matrix represents the Pearson’s correlation coefficient (r). Figure S1. Fluctuations of pH, DO, conductivity, salinity, and temperature in the batch phycoremediation systems.

Author Contributions

Conceptual approach-methodology, G.S.-A.; lab experiments, G.S.-A. and K.S.; writing, G.S.-A. and K.S.; review editing, G.S.-A.; visualization, G.S.-A. and K.S.; project administration, G.S.-A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Ege University Scientific Research Project Fund, Turkey. SRPs Funds number: SUF-14-010, Turkey.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data can be supplied by the corresponding author upon plausible demand.

Acknowledgments

Thanks to Hasim Somek for supporting in species identification.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Experimental setup.
Figure 1. Experimental setup.
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Figure 2. Microscopic images of Golenkinia radiata at different stages during the trials. (a) a vegetative cell, (b) stationary phase of cell, (c1,c2) new cells in the mother-cell wall, (d1,d2) hemizoospore liberation, and (e) released hemizoospores. Scale bar 10 μm.
Figure 2. Microscopic images of Golenkinia radiata at different stages during the trials. (a) a vegetative cell, (b) stationary phase of cell, (c1,c2) new cells in the mother-cell wall, (d1,d2) hemizoospore liberation, and (e) released hemizoospores. Scale bar 10 μm.
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Figure 3. In vivo Chl-a (a) and Chl-b (b) based logarithmic growth, Chl and DW (biomass) productivity (c) and growth rates of G. radiata (d) in batch experiments in primary effluent (P), secondary effluent (S), and final effluent (E). A significant difference is illustrated by a different sign (a, b, c) (p < 0.05), and units are mgL−1 d−1 for Chl-a, b, g L−1 d−1 for DW.
Figure 3. In vivo Chl-a (a) and Chl-b (b) based logarithmic growth, Chl and DW (biomass) productivity (c) and growth rates of G. radiata (d) in batch experiments in primary effluent (P), secondary effluent (S), and final effluent (E). A significant difference is illustrated by a different sign (a, b, c) (p < 0.05), and units are mgL−1 d−1 for Chl-a, b, g L−1 d−1 for DW.
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Figure 4. TN, TP, and COD removal performance of G. radiata in primary effluent (P), secondary effluent (S), final effluent (E), and, C medium. A box with a different symbol (a, b, c) on it represents a significant difference (p < 0.05).
Figure 4. TN, TP, and COD removal performance of G. radiata in primary effluent (P), secondary effluent (S), final effluent (E), and, C medium. A box with a different symbol (a, b, c) on it represents a significant difference (p < 0.05).
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Figure 5. The concentrations of nitrogen forms, and TN% removal ratios of G. radiata culture in primary effluent (P) (a), secondary effluent (S) (b), effluent (E) (c), and BG11 medium (C) (d). The error bars represent the SD around each box and point.
Figure 5. The concentrations of nitrogen forms, and TN% removal ratios of G. radiata culture in primary effluent (P) (a), secondary effluent (S) (b), effluent (E) (c), and BG11 medium (C) (d). The error bars represent the SD around each box and point.
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Figure 6. The decrease in the pollutant concentrations. TP (PO4-P) (a) and COD (b) in primary effluent (P), secondary effluent (S), final effluent (E), and BG11 (C). The error bars symbolize the standard deviation (SD) on each point.
Figure 6. The decrease in the pollutant concentrations. TP (PO4-P) (a) and COD (b) in primary effluent (P), secondary effluent (S), final effluent (E), and BG11 (C). The error bars symbolize the standard deviation (SD) on each point.
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Table 1. Performance of G. radiata in different WW; the intercourse amongst Chl performance and the final pollutant concentrations of TN (TN = NO2 + NO3 + NH4), TP (TP = PO4), and COD in MWW. The intercourse amongst Chl (y: Chl-a) and the pollutant concentrations (TN, TP, COD (x: abc: TN, TP, COD)) in P, S, E, and C. * Correlation matrix is shown in Table S3.
Table 1. Performance of G. radiata in different WW; the intercourse amongst Chl performance and the final pollutant concentrations of TN (TN = NO2 + NO3 + NH4), TP (TP = PO4), and COD in MWW. The intercourse amongst Chl (y: Chl-a) and the pollutant concentrations (TN, TP, COD (x: abc: TN, TP, COD)) in P, S, E, and C. * Correlation matrix is shown in Table S3.
Chl a Quota, µg L−1Chl b Quota, µg L−1µ, day−1
Chl a
µ, day−1
Chl b
µChl aChl bDW (g L−1)BP
(g L−1 d−1)
P(Chl)
(µg L−1 d−1)
C:N:PN:Px,yFitted Model EquationrR2p
P1803 ± 75.9649.2 ± 28.21.687 ± 0.041.552 ± 0.021.097.66 ± 0.051.02 ± 0.120.25 ± 0.0040.5:10.8:110.8:1(abc)log10 (Chla) = 3.268 − 0.2787 × TP − 0.001 × COD + 0.0143 × TN*92.0870.0102
S434.3 ± 22.1179.1 ± 6.060.939 ± 0.020.91 ± 0.031.037.5 ± 0.090.83 ± 0.190.05 ± 0.0036.7:6.5:1.9.0:1(abc)log10 (Chla) = 2.94 + 0.00036 × COD + 0.00084 × TN − 0.164 × TP*92.5290.0005
E444.6 ± 14.1139.6 ± 10.90.917 ± 0.010.731 ± 0.031.256.50 ± 0.050.58 ± 0.090.06 ± 0.0037:8.9:18.9:1(abc)log10 (Chla) = 1.121 + 0.0685 x TN − 0.334 × TP − 0.008 × COD*88.3320.0245
C218.2 ± 13.184.69 ± 3.330.547 ± 0.030.479 ± 0.011.142.33 ± 0.020.085 ± 0.060.02 ± 0.0022.8:8.4:18.4:1.(abc)log10 (Chla) =1.8024 + 0.0254 × TN − 0.5562 × TP − 0.0002 × COD*95.7880.0033
Table 2. Initial physicochemical features of municipal WW (primary WW: P, secondary WW: S, discharge WW: E, and, BG11 culture medium: C) (initial concentrations after sterilization).
Table 2. Initial physicochemical features of municipal WW (primary WW: P, secondary WW: S, discharge WW: E, and, BG11 culture medium: C) (initial concentrations after sterilization).
ParameterWastewater for Microalgae Cultivation
PSEC
pH9.4 ± 0.09.1 ± 0.09.0 ± 0.068.7 ± 0.06
T °C24.1 ± 0.024.1 ± 0.024.1 ± 0.024.1 ± 0.5
D.O (mg L−1)8.3 ± 0.08.8 ± 0.08.7 ± 0.08.8 ± 0.03
NO2-N (µg L−1)40 ± 0.0110 ± 0.090 ± 0.053.30 ± 5.77
NO3-N (mg L−1)38.3 ± 4.526.2 ± 1.3723.7 ± 0.57138 ± 5.77
NH4-N (mg L−1)53 ± 0.035 ± 0.021 ± 1.739 ± 2.64
PO4-P (mg L−1)8.5 ± 0.07.9 ± 0.05 ± 0.016.7 ± 0.25
COD (mg L−1)344 ± 0.0290 ± 0.0185 ± 0.0402 ± 0.00
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Sisman-Aydin, G.; Simsek, K. Investigation of the Phycoremediation Potential of Freshwater Green Algae Golenkinia radiata for Municipal Wastewater. Sustainability 2022, 14, 15705. https://doi.org/10.3390/su142315705

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Sisman-Aydin G, Simsek K. Investigation of the Phycoremediation Potential of Freshwater Green Algae Golenkinia radiata for Municipal Wastewater. Sustainability. 2022; 14(23):15705. https://doi.org/10.3390/su142315705

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Sisman-Aydin, Goknur, and Kemal Simsek. 2022. "Investigation of the Phycoremediation Potential of Freshwater Green Algae Golenkinia radiata for Municipal Wastewater" Sustainability 14, no. 23: 15705. https://doi.org/10.3390/su142315705

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