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Article

CO2 Addition and Semicontinuous Feed Regime in Shaded HRAP—Pathogen Removal Performance

by
Graziele Ruas
1,2,3,*,
Sarah Farias Lacerda
1,
Maria Alice Nantes
1,
Mayara Leite Serejo
4,
Gustavo Henrique Ribeiro da Silva
3 and
Marc Árpad Boncz
1
1
Post-Graduate Programme of Environmental Technology, Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil
2
Campus Jardim, Federal Institute of Mato Grosso do Sul, Jardim 79240-000, MS, Brazil
3
School of Engineering, São Paulo State University (Unesp), Bauru 17033-360, SP, Brazil
4
Campus Aquidauana, Federal Institute of Mato Grosso do Sul, Aquidauana 79200-000, MS, Brazil
*
Author to whom correspondence should be addressed.
Water 2022, 14(24), 4047; https://doi.org/10.3390/w14244047
Submission received: 25 October 2022 / Revised: 29 November 2022 / Accepted: 8 December 2022 / Published: 12 December 2022
(This article belongs to the Special Issue Advances in Aerobic and Anaerobic Wastewater and Sludge Treatment and Recovery)
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Abstract

:
The influence of CO2 addition and feeding regime (continuous versus semicontinuous) on the removal of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus, Enterococcus faecalis, and Escherichia coli (E. coli) from three shaded high-rate algal ponds (HRAPs) treating raw sewage (RS) was studied. The three HRAPs were operated at an analogous hydraulic retention time (HRT) for 5 days and with shading of 50%. The CO2 addition and feeding regime had no statistically significant influence on the removal of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus sp., and Enterococcus faecalis, with 2.39–3.01, 2.07–2.31, 3.02–3.38, and 3.14–3.45 log units, respectively. However, the removal of E. coli decreased significantly with the feeding regime of 0.1 h d−1 and 2.23–3.29 log units. The productivity and the total suspended solids (TSS) removal efficiency were significantly improved with the semicontinuous feeding regime and CO2 addition. The highest productivity was obtained in the semicontinuous feeding regime, 5.93 g m2 d−1, while the TSS removal efficiency was similar between the semicontinuous feeding regime and CO2 addition (31–36%). The control of light intensity led to greater variability in the algal community, and was present in the three reactors, in different proportions, in the form of the microalgae Scenedesmus acutus, Scenedesmus obliquus, and Chlorella sp.

Graphical Abstract

1. Introduction

The concern with the efficiency of domestic effluent disinfection, for reuse or just final disposal, has grown in recent years, driven by the discovery of conventional sewage treatment plants (STP) as hot spots for the development and spread of multiresistant bacteria in the environment [1], even causing diseases outside the hospital environment and in healthy people [2]. The disinfection of sewage can be performed through chlorination, ozonization, UV radiation, and advanced oxidative processes, all of which depend on the performance of previous treatment steps, as the presence of organic matter and suspended solids decrease efficiency and can lead to the formation of toxic byproducts [3,4].
Given the limitations of traditional disinfection techniques, mostly due to the need for high-efficiency pretreatment and the potential generation of toxic byproducts, microalgae systems, especially HRAPs, have shown promise, as they are able to inactivate different types of pathogenic microorganisms with a high efficiency while removing nutrients, organic matter, heavy metals, and micropollutants from sewage [5,6,7,8,9].With the advantage that it can be applied in the treatment of raw and secondary sewage [7,10] and produced biomass, it can be used as an input in aquaculture, agriculture, and energy production (anaerobic digestion) [11,12,13].
The main factors acting in the removal of pathogens in microalgae–bacterial systems are pH, HRT, dissolved oxygen (DO), light intensity, and toxins or metabolites with antibiotic effects produced by algae [14], which act in a complex and interdependent way in the systems. Among these factors, what is most correlated directly with others is light intensity, as the process of indirect photooxidation is dependent on DO, pH, and the occurrence of photosensitizers, such as humic substances, pigments, dissolved organic matter, and flavins [14,15]. In addition, light intensity influences the microalgae community and the photosynthetic activity of the system. The control of the photosynthetic activity consequently alters DO and pH, and when it is too high, it can inhibit microalgae activity (photoinhibition), negatively impacting the productivity and efficiency of the system [16]. The control of solar radiation (light intensity) can be done through the use of shading blankets or the installation of reactors in the greenhouse [10,16,17]. Therefore, it is necessary to understand how shading (control of light intensity) influences the main indicator organisms to disinfect and treat the effluent simultaneously.
Other important parameters that directly influence the removal of pathogens and the efficiency of effluent treatment in HRAPs are the pH and feeding regime. CO2 addition helps to control the pH of the media and increase the availability of carbon to the microalgae, making the C/N ratio more favorable by improving the nitrogen removal capacity of the system, which has also been reported as a promoter factor of pathogen removal, specifically Pseudomonas aeruginosa [10]. The feeding regime (continuous and semicontinuous) and its impacts on HRAP efficiency are still poorly known, and were determined in the removal of surfactants and nutrients for the first time by Serejo et al. [18]. However, its effects on the removal of the indicator and pathogen microorganisms are not yet recognized, and this knowledge is essential in order to understand and enhance the disinfection process in microalgae–bacterial systems.
Therefore, the objective of this study was to evaluate the influence of CO2 addition and feed regime (continuous versus semicontinuous) on the removal of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus sp., Enterococcus faecalis, and Escherichia coli from raw sewage (RS) in shaded HRAPs.

2. Materials and Methods

2.1. Experimental Setup and Operation Conditions

The experiment consisted of three 21 L pilot outdoor HRAPs (R1, R2, and R3) with a 0.13 m2 illuminated surface area (78 cm long × 40.5 cm wide) and 16 cm culture depth. In the bottom of each HRAPs was a submerged pump with a nominal flow rate of 650 L h−1 (Sarlo Better B650, São Caetano do Sul, Brazil) to promote the complete mixing of the culture, which resulted in a liquid recirculation velocity of 20 ± 2 cm s−1. After leaving each HRAP, the mixed liquor was sent to a 1 L settler (S1, S2 and S3) operating at a hydraulic retention time (HRT) of ≈5.8 ± 0.1 h. The three reactors were covered with a screen, (Sombrite®-Equipesca®, Campinas, Brazil), with 50% shading (Figure 1).

2.2. Raw Sewage, Microorganisms, and Culture Conditions

Raw sewage (RS) was collected twice a week from the primary treatment tank of a STP in Campo Grande, MS (Brazil), and stored at 4 °C. Influent soluble concentrations of the chemical oxygen demand (COD), total organic carbon (TOC), inorganic carbon (IC), total organic nitrogen (TN), ammonium ion (N-NH4+), nitrite (N-NO2−), nitrate (N-NO3−), and phosphorus (P), as well as insoluble Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus, Enterococcus faecalis, Escherichia coli, pH, and TSS, are summarized in Table 1. A synthetic gas (SG) composed of CO2 (30%) and N2 (70%) (White Martins, Campo Grande, Brazil) was used as a source of CO2 in R1 and was added at a rate of 2.5 ± 0.4 mL min−1. In R2 and R3, no CO2 source was added. The reactors were inoculated with a 1.18 g TSS L−1 cultivation broth composed of microalgae and a denitrifying–nitrifying aerobic bacteria consortium collected from an outdoor HRAP treating sewage at the Effluents Laboratory (Federal University of Mato Grosso do Sul, Brazil). The main species recorded were Scenedesmus acutus (45%), Scenedesmus obliquus (45%), and Chlorella sp. (10%).

2.3. Continuous Experiment and Sampling

The three HRAPS were operated with similar HRTs and organic loading rates (Table 2), but R1 and R2 were fed with RS in continuous mode using a peristaltic pump (Watson Marlon 505U, Falmouth, UK), and R3 was fed semicontinuously for 0.1 h per day. CO2 was added only in R1 at a rate of 2.5 ± 0.4 mL CO2 min−1. To evaluate the influence of the feeding regime and CO2 addition on the removal efficiency (RE) of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus, Enterococcus sp., and Escherichia coli. With this purpose, three times a week, 300 mL liquid samples were withdrawn from the influent and the effluent (settler output, Figure 1) to determine the pathogens, TSS, and soluble COD, TOC, IC, TN, N-NH4+, NO2−, NO3−, and P (filtration through 0.45 μm glass fiber filters prior to analysis). Additionally, liquid samples (100 mL) were collected from the HRAPs to determine the concentrations of pathogens and TSS in the cultivation broth. The pH, HRT, dissolved oxygen (DO), light intensity, and ambient and cultivation broth temperatures were monitored daily. The evaporation rate was measured from the difference between the measured influent and effluent flows [18]. The experiment was carried out in the Effluents Laboratory of the Federal University of Mato Grosso do Sul (UFMS) in Campo Grande, MS (Brazil), for 26 days at a temperature of ≈24 °C.

2.4. Analytical Procedures

The TN, IC, and TOC were determined using a total organic carbon analyzer (Vario TOC Cube, Elementar, Langenselbold, Germany). The DO and temperature in the HRAPs were measured using a Jenway 9500 DO2 Oximeter (Jenway-Cole-Parmer, Cambridgeshire, UK). N-NH4+ was measured using an Orion Five Star multiparameter meter (Thermo Scientific, Bleiswijk, The Netherlands), while the pH was measured with a Hanna pH meter HI2211 (Hanna Instruments, Barueri, Brazil). NO2−, NO3−, and P-PO43− were analyzed using a Dionex UltiMate ICS 1100 ion chromatography system with an IonPac AG19/AS19 column (Thermo Scientific, Austin, TX, USA). Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus sp., and Enterococcus sp. were determined using the membrane filtration method with M-PA Agar Base—M1121, M-CP Agar Base M1354, Baird Parker Agar Base M043 (HIMEDIA, Mumbai, India), and Agar Base M-Enterococcus K25-610134 (KASVI, São José dos Pinhais, Brazil), respectively. E. coli was determined using Colilert® kits (IDEXX Laboratories, Westbrook, ME, USA). The identification of microalgae was conducted by microscopic examination (Olympus BX41, Miami, FL, USA) of samples fixed with 5% Lugol’s solution and stored at 4 °C prior to analysis, according to Sournia [19]. The light intensity (PAR—photosynthetically active radiation) was recorded using a Quantum meter MQ-200 (Apogee Instruments, Logan, UT, USA). All of the parameters were analyzed according to Standard Methods for the Examination of Water and Wastewater [20].

2.5. Statistical

The pathogen removal under the different test conditions performed was evaluated using an analysis of variance (ANOVA) with Fisher’s least significant difference (LSD) test using a 95% confidence level. The analyses were performed using Microsoft Excel® 2021 with Real Statistics Resource Pack software (Release 7.6) [21] and R® (R Core Team 2020).

3. Results and Discussion

3.1. Operation and Environmental Conditions

The temperature, evaporation losses, DO, and pH value were similar among the three reactors (Table 2); therefore, neither CO2 addition nor the feeding regime significantly influenced these operating parameters. The recorded temperature (≈21 °C) was adequate for the microorganisms and biological activity support [7]. The evaporation losses (5.21–6.79 L m−2 d−1) were significantly lower than those estimated by Guieysse et al. [22] for tropical climates (≈13 L m−2 d−1) and slightly lower than those found by Serejo et al. [23] and Ruas et al. [6], possibly due to the radiation control in our test. In all of the reactors, the shade indirectly induced the pH to neutrality (7.3) and the DO below the usual values for this type of system (8–10 mg O2 L−1) [6,23,24], but was enough to satisfy the oxidized demands of organic matter and NH4+ (>2 mg O2 L−1) [25].

3.2. Influence of Solar Radiation and CO2 Addition on Pathogen Removal Efficiency

The removal efficiency of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus sp., Enterococcus faecalis, and Escherichia coli in the reactor R1, R2, and R3 is described in Figure 2. The effect of the VBNC (viable nut non-culturable) state on Pseudomonas aeruginosa and Enterococcus faecalis removal was not measured.

3.2.1. Pseudomonas Aeruginosa

The removal efficiency of Pseudomonas aeruginosa was statistically equal (p = 0.05) in the three reactors, with values of 3.01 ± 1.15, 2.93 ± 1.66, and 2.39 ± 0.59 units log (Log-Re) in reactors R1, R2, and R3, respectively. These efficiencies were similar to those found by Ruas et al. [6], 3.4–3.8 log-Re, treating raw sewage in HRAPs, operated with a higher light intensity (≈725 μmol m−2 s−1) than in the present study (≈507 μmol m−2 s−1), an HRT of 5 and 7 days, and a microalgae population composed mostly of Scenedesmus sp. (>90%). The RE was higher, however, than that found by Ruas et al. [10], who recorded removals of ≈ 1.6 log-Re under conditions without CO2 addition and ≈2.5 log-Re under conditions with CO2 addition, in a 180-L HRAP operated inside a greenhouse with light intensity ranging between 139–172 μmol m−2 s−1. The microalgae population in the Ruas et al. [10] experiment was different in the two stages, with Chlorella sp. the predominant microalgae in stage I and Microspora sp. in stage II. The author pointed out this change in microalgal population, induced by CO2 addition, as the main factor responsible for increasing the removal of Pseudomonas aeruginosa by improving the efficiency of biomass removal in the settler, from 71 to 96%. However, in your study, despite the negative settler removal efficiencies in R2, the Pseudomonas aeruginosa log-Re were not affected, indicating that the removal of this microorganism is linked to the microalgal species present in the reactor and the toxins or antibiotic substances produced by these algae [26,27], as observed between our study and that of Ruas et al. [6], despite having different operating conditions, similar removals, and microalgal populations (Scenedesmus sp. > 90%).
The CO2 addition and light intensity also seemed to have no direct effect on the removal of Pseudomonas aeruginosa, as there was no statistically significant difference between conditions with and without CO2 addition in our study and in the study of Ruas et al. [6] and between different light intensities ranging between 507 and 725 μmol m−2 s−1.

3.2.2. Clostridium Perfringens

Clostridium perfringens is an anaerobic Gram-positive and endospore-forming bacterium found in human intestinal and animal feces and in aquatic environments contaminated with sewage and farming wastewater [28]. Its greater environmental and disinfection resistance have made it a valuable indicator of the presence of viruses and protozoan cysts [29,30]. Clostridium perfringens is adopted in the European Union as a mandatory indicator in the agricultural reuse of treated sewage [31], where removals ≥ 4 log units of this microorganism are needed. The Clostridium perfringens removal was 2.31 ± 1.05, 2.07 ± 1.01, and 1.82 ± 1.31 in reactors R1, R2, and R3, respectively. The removals were similar (p > 0.05), so neither the feeding regime nor the CO2 addition significantly influenced the removal of this pathogen. In previous studies, similar removals were found, between 2.2 and 2.6 log-Re, and it was observed that Clostridium perfringens removals were also not affected by CO2 addition [6]. Although the light intensity between our study and the study of Ruas et al. [6] was different, the removals were similar, with the microalgae Scenedesmus sp. being dominant in the reactors. Clostridium perfringens has a high resistance to wastewater and disinfection processes due to its spore forming ability in adverse environments [28], and it is resistant to chlorination, ozonation, UV radiation, and advanced oxidative processes [4,30,32,33]. In the experiments of Gutiérrez-Alfaro et al. [34] and García et al. [32], the Clostridium perfringens removals were only ≈0.1 and 1.1–1.3 log units, but unfortunately, the values of solar intensity and microalgal species present in the HRAP were not presented.
Therefore, the greater the radiation applied to the treatment systems, the faster the formation of spores, making the process of disinfection more difficult [35]. Then, in conditions with less radiation or controlled radiation, the removal of this bacteria could be more effective. The microalgae community can have a direct effect on the capacity to remove Clostridium perfringens and other pathogens in photobioreactors. Krustok et al. [36] determined that the use of lake water as an inoculum in photobioreactors increased the diversity of the algal and bacterial communities, which led to better biomass yields and better removal of nutrients and pathogens. The photobioreactors with lake water inoculum presented four times more species of microalgae, with a dominance of Scenedesmus obliquus, while in the reactor without the inoculum, the most abundant algae was Chlorella vulgaris, both of which were operated with constant temperature, photoperiod, and light intensity of ≈23 °C, 16:8 h (light:dark) and ≈135 μmol m−2 s−1. This phylogenetic abundance and functional structure, provided by the inoculum, led to greater removal of pathogens, increasing the removal of Clostridium perfringens, Escherichia coli, and Staphylococcus aureus by 3.5 times and the removal of Enterococcus faecalis and Pseudomonas aeruginosa by 2.5 times. Therefore, the effect of the microalgae present in the photobioreactors seems to be the main parameter for the removal of Clostridium perfringens, as different microalgae can produce biocomponents with bactericidal properties [27].

3.2.3. Staphylococcus sp.

The CO2 addition and feeding regime had no impact on Staphylococcus sp. removal, with similar removals of 3.38 ± 0.84, 3.28 ± 0.87, and 3.02 ± 1.62 log units in R1, R2, and R3, respectively. The removals we found were higher than those found by Garcia et al. [32], 1.2 log-Re, and Ruas et al. [6], 1.3–1.7 log-Re, despite the shading in our system, submitting the reactors to a light intensity twice as low as that recorded by Ruas et al. [6]. Nola et al. [37] determined that increasing the light intensity and concentration of dissolved biodegradable organic matter would improve the removal of Staphylococcus sp., but the light intensity tested was low (15 to 135 μmol m−2 s−1), smaller than the light intensity recorded in our experiment (≈507 μmol m−2 s−1), and there were no algae. This was not verified by comparing our results with those found by Ruas et al. [6], because an even higher light intensity resulted in lower removal.
Therefore, it seems that a neutral pH value (≈7.00) favors its removal because the removals were higher in our experiment (pH value between 7.27 and 7.46) than in Ruas et al. [6] (pH value between 7.8 and 9.5), and the OD concentrations may not significantly influence the removal of this microorganism. The effect of the microalgae activity in Staphylococcus sp. removal may be the most important mechanism for the inactivation of the pathogens, because the bactericidal effect of some micro- and macroalgae on this bacterium is already known [26,38]. Therefore, more studies with different inoculums and microalgal communities should be conducted to demonstrate the effects and potential for sewage disinfection.

3.2.4. Enterococcus sp.

Enterococcus sp. removal was 3.37 ± 0.52 log-Re in R1, 3.45 ± 0.30 log-Re in R2, and 3.14 ± 0.75 log-Re in R3, with statistically equal removal (p > 0.05). The CO2 addition and semicontinuous feed regime did not impact Enterococcus sp. removal. The log-Re in our experiment was higher than that reported by Ruas et al. [6], 2.6 log-Re (7-day HRT without CO2 addition) and 3.1 and 3.0 (5-day HRT—with and without CO2 addition, respectively), even though we operated with a half-light intensity. Lower Enterococcus sp. removal was recorded by Ruas el al. [10] (≈ 2.7 log-Re) in the two stages of operation in an HRAP of 180 L and 5-day HRT and by Awuah et al. [39] (≈2.0 log-Re) in an algae-based stabilization pond at 7-day HRT. Light intensity and pH value are the main factors identified as drivers of the removal of Enterococcus and fecal coliforms [39,40], with the pH value being the most influential in this process. As the removal rate of Enterococcus is higher at lower pH values and lower at pH values > 11, the survival rate of Enterococcus increases with higher pH values. The pH values of all reactors in our study were similar (≈7.3) and lower than the pH values reported by Ruas et al. [6]), which may explain why we obtained a higher log-Re and even lower light intensity. Other possible factors that may influence the removal of Enterococcus sp. are competitive for nutrients, predation, and algal toxins [41,42].

3.2.5. Escherichia coli

Escherichia coli is the most monitored bacteria in HRAP-type systems, as it is the main indicator of fecal contamination in drinking water and sewage. Escherichia coli-Re were 3.20 ± 0.77, 3.29 ± 0.45, and 2.23 ± 0.60 log units in reactors R1, R2, and R3, respectively (Figure 1). The log-Re values in R1 and R2 were significantly similar, so the addition of CO2 did not impact the removal mechanism of these bacteria. The feeding regime decreased the efficiency of the system in Escherichia coli-Re. In reactors R1 (≈1080 geometric mean MPN per 100 mL) and R2 (≈1050 geometric mean MPN per 100 mL), the final concentrations of E. coli in the treated sewage fell within the most stringent standards for sewage use in the agriculture irrigation of crops eaten as raw food, on sports fields, and in public parks (≤1000 geometric mean number per 100 mL) [43].
The main factors affecting Escherichia coli are visible light, pH, and OD [44]. As the pH value and OD were similar among the reactors, the higher concentration of TSS in R3 (Table 3) may have protected the Escherichia coli from photooxidation. The process, observed by Craggs et al. [45] in batch tests, determined that the higher the TSS concentration, the lower the Escherichia coli-Re. The removals found in R3 were similar to those found by Ruas et al. [10] (2.0 ± 0.50 log-Re) with pH values between 6.8 and 7.7 and a light intensity of ≈156 μmol m−2 s−1 and 5-day HRT, and Ruas et al. [6] operating a 21 L reactor with CO2 addition, 5-day HRT, pH value ≈ 7.8 and light intensity of ≈ 725 μmol m−2 s−1. However, lower removals were found by Posadas et al. [7], who obtained a minimum removal of 0.65 log-Re in 850 L HRAP with CO2 addition for pH control (pH = 7) and a maximum of 2.30 log-Re in the same reactor operated without CO2 addition, without pH control (pH = 8.3–8.5).

3.3. Organic Matter, Carbon, and Nutrient Removal Efficiencies

The COD, TOC, IC, and TC REs were similar in the three reactors (Table 3); consequently, CO2 addition and different feeding regimes did not significantly impact the efficiency of the reactors. The COD (63–65%) and TOC REs (31–38%) in reactors R1 and R2 were within the ranges normally found for raw domestic effluent treatment in continuous HRAP, where removals of 34–88% and 36–80% have already been found for COD and TOC, respectively [6,10,24]. In semicontinuous HRAP reactors, the reported COD and TOC removal values were 42–63% and 58–74%, respectively [23,46]. These values are close to those found in reactor R3 (COD-Re = 59.36 ± 15.68% and TOC-Re = 36.94 ± 24.19%) operated in a semicontinuous regime (0.1 h d−1). The efficiencies achieved ensured effluents with COD concentrations < 46 mg COD L−1, staying below the limit established by Directive 98/15/CEE [31]. Similar to the organic carbon removal, IC-Re was also similar in the three reactors (R1, R2, and R3, ≈67%) and within the removal values commonly found in HRAPs treating sewage with 5-day HRT (64–72%) [6,10]. Therefore, comparing the reactors operated under the same conditions but with a higher light intensity (not shaded) [6] with our study, it can be inferred that shading did not significantly affect organic and inorganic carbon removal.
The TN-Re in R1, R2, and R3 were 73.40 ± 3.15%, 67.28 ± 21.47%, and 59.67 ± 18.31%, respectively, releasing effluents with TN concentrations of 23–32 mg TN L−1, above the limit established by Directive 98/15/CEE [31]. This poor TN-Re can be attributed to the low C/N of the RS (2.8) (Table 1), which is insufficient for the optimal growth of the microalgal biomass (≈5.6) [47]. The low removal and operating conditions of the reactors (pH ≈ 7 and temperature ≈ 21 °C) prevented the removal of N-NH4+ by stripping and supported high nitrification rates in the cultivation broth [48]. The CO2 addition and semicontinuous feed regime also did not influence the TP-Res of the three reactors, where removals of ≈28.98%, ≈26.57% and ≈ 35.05% were recorded (Table 3) in R1, R2, and R3, respectively. These removals were smaller than those reported by Serejo et al., [23], ≈46% and ≈80%, treating sewage in continuous and semicontinuous reactors, respectively. Posadas et al. [7] found TP-Res of 40% operating with 3-day HRT and adding pure CO2 and 60% operating also with 3-day HRT, but adding CO2 from flue gas, both operating in stages with a light intensity similar to those recorded in our study. Similar to what occurs with TN-Res, the low C/N and carbon limitation may have limited P-PO43− removal in the reactors.

3.4. Productivity and Settleability of Biomass and Microalgae Population

The CO2 addition and feed regimen influenced the biomass productivity in the reactors, with recorded productivities of 3.94 ± 1.00 g m−2 d−1 in R1, 2.83 ± 0.51 g m−2 d−1 in R2 and 5.93 ± 2.0 in R3 g m−2 d−1. Therefore, the highest productivity was obtained with the semicontinuous feed regime (0.1 h d−1), followed by CO2 addition. These productivities were lower than the productivities commonly reported in pilot HRAPs (10–35 g m−2 d−1) [49]. However, they were closer to the productivity values recorded in the primary sewage in HRAPs operated with 5–7 days of HRT, light intensity between ≈156 μmol m−2 s−1 and ≈725 μmol m−2 s−1, ≈4.1 g m−2 d−1 and ≈2.0–3.2 g m−2 d−1 in the works of Ruas et al. [10] and Ruas et al. [6], respectively. The TSS concentrations at R1 (≈0.18 g TSS L−1) and R2 (≈0.13 g TSS L−1) were statistically similar (p > 0.05), while at R3, the TSS concentration was higher ≈0.29 g TSS L−1. The TSS concentrations in reactors R1 and R2 were similar to those obtained by Ruas et al. [10], ≈12 and 11 g TSS L−1, operating without and with CO2 addition, respectively, a 180 L HRAP with 5-day HRT and by Ruas et al. [6], ≈15 and 18 g TSS L−1, in continuously operating HRAPs, 21 L, with 5-day HRT and CO2 addition and 7-day HRT without CO2 addition, respectively. However, the TSS concentration of R3 was similar to that found by Serejo et al. [23], especially in the reactors operated in a semicontinuous feeding regime, reaching concentrations of 0.23 gTSS L−1 with a feeding regime of 12 h d−1 and 0.21 g TSS L−1 with a feeding regime of 0.1 h d−1. However, in all of the reactors, both productivity and TSS concentrations were significantly lower than the values found by Posadas et al. [7], 13–17 g m−2 d−1 and 32–49 g TSS L−1, respectively, which treated primary sewage in a continuous regime with pH control through CO2 addition. The low biomass rate production in our experiment may be a result of the low carbon and nutrient loads applied (Table 1) [24]. The removal efficiencies of TSS (Sed-Re) were 31.51 ± 25.48% in R1 and 36.49 ± 27.26% in R3 (Table 2), similar to those found by Ruas et al. [6] in a reactor with a 7-day HRT (≈32%) and by Serejo et al. [23] in an HRAP with semicontinuous feed (≈18%). R2 not only had a low biomass productivity rate, but also had a poor removal efficiency in the settler, achieving average removals of -52.38 ± 104.79%. Ruas et al. [6] also registered negative Sed-Re (%) in its reactor without CO2 addition and with 5-day HRT treating of primary sewage. The removal of microalgae by gravitational sedimentation occurs as a function of the inherent sedimentability of the microalgae population and is directly proportional to the TSS concentration [50]. The sedimentability can be improved with the addition of CO2, which promotes the flocculation/aggregation of microalgae [51], an evident effect between R1 and R2. Although the microalgal community was similar between R2 and R3, Sed-Re was extremely different, indicating that the semicontinuous feed regime can also improve the biomass flocculation/aggregation. The statistically similar pathogen removals between reactors R1 and R2, despite the low performance of R2 in Sed-Re, demonstrate that the process of pathogen removal by attachment to the microalgal floc and subsequent sedimentation is not relevant for the removal/desactivation process of the studied pathogens, as suggested by Ruas et al. [10].
The reactors showed different variations in the microalgae population (Scenedesmus acutus, Scenedesmus obliquus, and Chlorella sp.) (Figure 3) driven by different cultures and feeding conditions. Although Scenedesmus acutus was the most abundant microalgae at R1 (>50%) at the end of the test period, it had a representation of <5% at reactors R2 and R3. Additionally, Chlorella sp., present in the inoculum, was found only in R3 at the end of the experiment. Finally, Scenedesmus obliquus was present in all of the reactors, being more abundant in R2 (≈4%) and R3 (≈76%) and less abundant in R1 (≈45%). The control of light intensity led to greater variability in the algal community [16], a phenomenon observed in this study when compared to other studies with similar treatment and effluent conditions, which presented a single species of microalgae with more than 90% dominance [6,7].

4. Conclusions

The CO2 addition did not impact the removal of pathogens (Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus, Enterococcus faecalis, and Escherichia coli), but improved the productivity and sedimentability of the microalgal biomass, enhancing the C/N ratio of sewage and promoting the aggregation/flocculation of biomass (Reactor 1). However, the semicontinuous feed regime improved the biomass productivity and TSS concentration while reducing Escherichia coli removal. Finally, the 50% shading light intensity control did not affect Pseudomonas aeruginosa, Clostridium perfringens, and Enterococcus faecalis removal and even improved Staphylococcus sp. removal. Therefore, the control of light intensity in HRAPs can be a resource to prevent photoinhibition, control biomass composition, and improve community variability without sacrificing the disinfection efficiency of the HRAPs.

Author Contributions

Conceptualization, G.R. and M.L.S.; methodology, G.R., S.F.L. and M.L.S.; validation, M.L.S. and M.Á.B.; formal analysis, G.R. and S.F.L.; investigation, G.R., S.F.L. and M.A.N.; resources, G.H.R.d.S. and M.Á.B.; data curation, G.R. and M.L.S.; writing—original draft preparation, G.R.; writing—review and editing, G.R., S.F.L., M.L.S., G.H.R.d.S. and M.Á.B.; visualization, G.R. and M.L.S.; supervision, M.L.S. and M.Á.B.; project administration, M.Á.B.; funding acquisition, G.H.R.d.S. and M.Á.B. All authors have read and agreed to the published version of the manuscript.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq (Project number 429567/2016-2 and 308663/2021-7); Coordenação de Aperfeiçoamento de Pessoal de Nível Supe-rior—CAPES, for the PhD grant awarded to Graziele Ruas (88882.458517/2019-01 and sandwich period 88881.190564/2018-01).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors would like to acknowledge the support obtained from the following Brazilian institutions: Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq (Project number 429567/2016-2 and 308663/2021-7); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—CAPES, for the PhD grant awarded to Graziele Ruas (88882.458517/2019-01 and sandwich period 88881.190564/2018-01); Fundação de Amparo à Pesquisa do Estado de Minas Gerais—FAPEMIG; Instituto Nacional de Ciência e Tecnologia em Estações Sustentáveis de Tratamento de Esgoto—INCT ETEs Sustentáveis (INCT Sustainable Sewage Treatment Plants).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Rizzo, L.; Manaia, C.; Merlin, C.; Schwartz, T.; Dagot, C.; Ploy, M.C.; Michael, I.; Fatta-Kassinos, D. Urban Wastewater Treatment Plants as Hotspots for Antibiotic Resistant Bacteria and Genes Spread into the Environment: A Review. Sci. Total Environ. 2013, 447, 345–360. [Google Scholar] [CrossRef] [Green Version]
  2. Bassetti, M.; Nicco, E.; Mikulska, M. Why Is Community-Associated MRSA Spreading across the World and How Will It Change Clinical Practice? Int. J. Antimicrob. Agents 2009, 34, S15–S19. [Google Scholar] [CrossRef]
  3. Gómez-López, M.D.; Bayo, J.; García-Cascales, M.S.; Angosto, J.M. Decision Support in Disinfection Technologies for Treated Wastewater Reuse. J. Clean. Prod. 2009, 17, 1504–1511. [Google Scholar] [CrossRef]
  4. Gehr, R.; Wagner, M.; Veerasubramanian, P.; Payment, P. Disinfection Efficiency of Peracetic Acid, UV and Ozone after Enhanced Primary Treatment of Municipal Wastewater. Water Res. 2003, 37, 4573–4586. [Google Scholar] [CrossRef]
  5. Saúco, C.; Cano, R.; Marín, D.; Lara, E.; Rogalla, F.; Arbib, Z. Hybrid Wastewater Treatment System Based in a Combination of High Rate Algae Pond and Vertical Constructed Wetland System at Large Scale. J. Water Process Eng. 2021, 43, 102311. [Google Scholar] [CrossRef]
  6. Ruas, G.; Farias, S.L.; Scarcelli, P.G.; Serejo, M.L.; Boncz, M.A. The Effect of CO2 Addition and Hydraulic Retention Time on Pathogens Removal in HRAPs. Water Sci. Technol. 2020, 82, 1184–1192. [Google Scholar] [CrossRef]
  7. Posadas, E.; del Morales, M.M.; Gomez, C.; Acién, F.G.; Muñoz, R. Influence of PH and CO2 Source on the Performance of Microalgae-Based Secondary Domestic Wastewater Treatment in Outdoors Pilot Raceways. Chem. Eng. J. 2015, 265, 239–248. [Google Scholar] [CrossRef] [Green Version]
  8. Vassalle, L.; García-Galán, M.J.; Aquino, S.F.; de Afonso, R.J.C.F.; Ferrer, I.; Passos, F.; R Mota, C. Can High Rate Algal Ponds Be Used as Post-Treatment of UASB Reactors to Remove Micropollutants? Chemosphere 2020, 248, 125969. [Google Scholar] [CrossRef]
  9. Saavedra, R.; Muñoz, R.; Taboada, M.E.; Bolado, S. Influence of Organic Matter and CO2 Supply on Bioremediation of Heavy Metals by Chlorella Vulgaris and Scenedesmus Almeriensis in a Multimetallic Matrix. Ecotoxicol. Environ. Saf. 2019, 182, 109393. [Google Scholar] [CrossRef] [Green Version]
  10. Ruas, G.; Serejo, M.L.; Paulo, P.L.; Boncz, M.Á. Evaluation of Domestic Wastewater Treatment Using Microalgal-Bacterial Processes: Effect of CO2 Addition on Pathogen Removal. J. Appl. Phycol. 2018, 30, 921–929. [Google Scholar] [CrossRef]
  11. Spolaore, P.; Joannis-Cassan, C.; Duran, E.; Isambert, A. Commercial Applications of Microalgae. J. Biosci. Bioeng. 2006, 101, 87–96. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Talaiekhozani, A.; Rezania, S. Application of Photosynthetic Bacteria for Removal of Heavy Metals, Macro-Pollutants and Dye from Wastewater: A Review. J. Water Process Eng. 2017, 19, 312–321. [Google Scholar] [CrossRef]
  13. Ward, A.J.; Lewis, D.M.; Green, F.B. Anaerobic Digestion of Algae Biomass: A Review. Algal Res. 2014, 5, 204–214. [Google Scholar] [CrossRef]
  14. Davies-Colley, R.J.; Craggs, R.J.; Park, J.; Sukias, J.P.S.; Nagels, J.W.; Stott, R. Virus Removal in a Pilot-Scale “advanced” Pond System as Indicated by Somatic and F-RNA Bacteriophages. Water Sci. Technol. 2005, 51, 107–110. [Google Scholar] [CrossRef] [PubMed]
  15. Curtis, T.P.; Mara, D.D.; Silva, S.A. Influence of PH, Oxygen, and Humic Substances on Ability of Sunlight to Dammage Fecal-Coliforms in Waste Stabilisation Pond Water. Appl. Environ. Microbiol. 1992, 58, 1335–1343. [Google Scholar] [CrossRef] [Green Version]
  16. Assemany, P.P.; Calijuri, M.L.; Couto, E.d.A.d.; de Souza, M.H.B.; Silva, N.C.; da Santiago, A.F.; de Castro, J.S. Algae/Bacteria Consortium in High Rate Ponds: Influence of Solar Radiation on the Phytoplankton Community. Ecol. Eng. 2015, 77, 154–162. [Google Scholar] [CrossRef] [Green Version]
  17. Assemany, P.P.; Calijuri, M.L.; da Santiago, A.F.; Couto, E.d.A.d.; de Leite, M.O.; Bermudez Sierra, J.J. Effect of Solar Radiation on the Lipid Characterization of Biomass Cultivated in High-Rate Algal Ponds Using Domestic Sewage. Environ. Technol. 2014, 35, 2296–2305. [Google Scholar] [CrossRef]
  18. Serejo, M.L.; Posadas, E.; Boncz, M.A.; Blanco, S.; García-Encina, P.; Muñoz, R. Influence of Biogas Flow Rate on Biomass Composition during the Optimization of Biogas Upgrading in Microalgal-Bacterial Processes. Environ. Sci. Technol. 2015, 49, 3228–3236. [Google Scholar] [CrossRef]
  19. Sournia, A. Phytoplankton Manual; United Nations Educational, Scientific and Cultural Organization, Eds.; Muséum National d’Histoire Naturelle: Paris, France, 1978; ISBN 92-3-101572-9. [Google Scholar]
  20. APHA. Standard Methods for the Examination of Water, 22nd ed.; American Public Health Association, American Water Works Association, Water Environment Federation: Washington, DC, USA, 2012; ISBN 9780875530130. [Google Scholar]
  21. Zaiontz, C. The Data Analysis for This Paper Was Generated Using the Real Statistics Resource Pack Software (Release 7.6). 2020. Available online: www.real-statistics.com (accessed on 24 October 2022).
  22. Guieysse, B.; Béchet, Q.; Shilton, A. Variability and Uncertainty in Water Demand and Water Footprint Assessments of Fresh Algae Cultivation Based on Case Studies from Five Climatic Regions. Bioresour. Technol. 2013, 128, 317–323. [Google Scholar] [CrossRef]
  23. Serejo, M.L.; Farias, S.L.; Ruas, G.; Paulo, P.L.; Boncz, M.A. Surfactant Removal and Biomass Production in a Microalgal-Bacterial Process: Effect of Feeding Regime. Water Sci. Technol. 2020, 2, 1–10. [Google Scholar] [CrossRef]
  24. Posadas, E.; Muñoz, A.; García-González, M.-C.; Muñoz, R.; García-Encina, P.A. A Case Study of a Pilot High Rate Algal Pond for the Treatment of Fish Farm and Domestic Wastewaters. J. Chem. Technol. Biotechnol. 2014, 90, 1094–1101. [Google Scholar] [CrossRef]
  25. Metcalf & Eddy, I.; Burton, F.L.; Tchobanoglous, G.; Tsuchihashi, R.; Stensel, H.D. Wastewater Engineering: Treatment and Resource Recovery, 5th ed.; McGraw-Hill’s Education: New York, NY, USA, 2013. [Google Scholar]
  26. Syed, S.; Arasu, A.; Ponnuswamy, I. The Uses of Chlorella Vulgaris as Antimicrobial Agent and as a Diet: The Presence of Bio-Active Compounds Which Caters the Vitamins, Minerals in General. Int. J. Bio-Sci. Bio-Technol. 2015, 7, 185–190. [Google Scholar] [CrossRef]
  27. Maghembe, R.; Damian, D.; Makaranga, A.; Nyandoro, S.S.; Lyantagaye, S.L.; Kusari, S.; Hatti-Kaul, R. Omics for Bioprospecting and Drug Discovery from Bacteria and Microalgae. Antibiotics 2020, 9, 229. [Google Scholar] [CrossRef] [PubMed]
  28. Bitton, G. Wastewater Microbiology, 3rd ed.; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2005; Volume 53, ISBN 978-0-471-71791-1. [Google Scholar]
  29. Payment, P.; Franco, E. Clostridium Perfringens and Somatic Coliphages as Indicators of the Efficiency of Drinking Water Treatment for Viruses and Protozoan Cysts. Appl. Environ. Microbiol. 1993, 59, 2418–2424. [Google Scholar] [CrossRef] [Green Version]
  30. Venczel, L.V.; Arrowood, M.; Hurd, M.; Sobsey, M. Inactation of Cryptosporidium Parvum Oocyts and Clostridium Perfringens Spores by a Mixed-Oxidant Disinfectant and by Free Chlorine. Appl. Environ. Microbiol. 1997, 63, 1598–1601. [Google Scholar] [CrossRef] [Green Version]
  31. European Union. Directiva 98/15/CE de La Comisión de 27 de Febrero de 1998 Por La Que Se Modifica La Directiva 91/271/CEE Del Consejo En Relación Con Determinados Requisitos Establecidos En Su Anexo I; European Union: Maastricht, The Netherlands, 1998; pp. L67/29–L67/30. [Google Scholar]
  32. García, M.; Soto, F.; González, J.M.; Bécares, E. A Comparison of Bacterial Removal Efficiencies in Constructed Wetlands and Algae-Based Systems. Ecol. Eng. 2008, 32, 238–243. [Google Scholar] [CrossRef]
  33. Lanao, M.; Ormad, M.P.; Goñi, P.; Miguel, N.; Mosteo, R.; Ovelleiro, J.L. Inactivation of Clostridium Perfringens Spores and Vegetative Cells by Photolysis and TiO2 Photocatalysis with H2O2. Sol. Energy 2010, 84, 703–709. [Google Scholar] [CrossRef]
  34. Gutiérrez-alfaro, S.; Rueda-márquez, J.J.; Perales, J.A.; Manzano, M.A. Combining Sun-Based Technologies (Microalgae and Solar Disinfection) for Urban Wastewater Regeneration. Sci. Total Environ. 2018, 619–620, 1049–1057. [Google Scholar] [CrossRef]
  35. Bailey, E.S.; Casanova, L.M.; Sobsey, M.D. Effects of Environmental Storage Conditions on Survival of Indicator Organisms in a Blend of Surface Water and Dual Disinfected Reclaimed Water. J. Appl. Microbiol. 2019, 126, 985–994. [Google Scholar] [CrossRef]
  36. Krustok, I.; Truu, J.; Odlare, M.; Truu, M.; Ligi, T.; Tiirik, K.; Nehrenheim, E. Effect of Lake Water on Algal Biomass and Microbial Community Structure in Municipal Wastewater-Based Lab-Scale Photobioreactors. Appl. Microbiol. Biotechnol. 2015, 99, 6537–6549. [Google Scholar] [CrossRef]
  37. Nola, M.; Matchim, A.G.S.; Mobili, O.B.; Nougang, M.; Krier, F.; Chihib, N.E.; Hornez, J.P.; Njiné, T. Photoinactivation of Staphylococcus Aureus and Vibrio Parahaemolyticus in the Model Aquatic Microcosm: Effect of Light Intensity and Dissolved Biodegradable Organic Compound. Water Sci. Technol. 2010, 62, 1775–1783. [Google Scholar] [CrossRef] [PubMed]
  38. Sánchez-Saavedra, M.D.P.; Licea-Navarro, A.; Bernáldez-Sarabia, J. Evaluation of the Antibacterial Activity of Different Species of Phytoplankton. Rev. Biol. Mar. Oceanogr. 2010, 45, 531–536. [Google Scholar] [CrossRef]
  39. Awuah, E.; Lubberding, H.J.; Asante, K.; Gijzen, H.J. The Effect of PH on Enterococci Removal in Pistia-, Duckweed- and Algae-Based Stabilization Ponds for Domestic Wastewater Treatment. Water Sci. Technol. 2002, 45, 67–74. [Google Scholar] [CrossRef]
  40. Davies-Colley, R.; Donnison, A.M.; Speed, D.J. Sunlight Wavelengths Inactivating Faecal Indicator Microorganisms in Waste Stabilisation Ponds. Water Sci. Technol. 1997, 35, 219–225. [Google Scholar] [CrossRef]
  41. Wu, S.Y.; Klein, D.A. Starvation Effects on Escherichia Coli and Aquatic Bacterial Responses to Nutrient Addition and Secondary Warming Stresses. Appl. Environ. Microbiol. 1976, 31, 216–220. [Google Scholar] [CrossRef] [Green Version]
  42. Legendre, P.; Baleux, B.; Troussellier, M. Dynamics of Pollution-Indicator and Heterotrophic Bacteria in Sewage Treatment Lagoons. Appl. Environ. Microbiol. 1984, 48, 586–593. [Google Scholar] [CrossRef] [Green Version]
  43. World Health Organization; Regional Office for the Eastern Mediterranean. A Compendium of Drinking-Water Quality Standards in the Eastern Mediterranean Region; WHO: Geneve, Switzerland, 2006; p. 24. Available online: https://apps.who.int/iris/handle/10665/116514 (accessed on 24 October 2022).
  44. Ouali, A.; Jupsin, H.; Ghrabi, A.; Vasel, J.L. Removal Kinetic of Escherichia Coli and Enterococci in a Laboratory Pilot Scale Wastewater Maturation Pond. Water Sci. Technol. 2014, 69, 755–759. [Google Scholar] [CrossRef]
  45. Craggs, R.; Park, J.; Heubeck, S.; Sutherland, D. High Rate Algal Pond Systems for Low-Energy Wastewater Treatment, Nutrient Recovery and Energy Production. N. Z. J. Bot. 2014, 52, 60–73. [Google Scholar] [CrossRef]
  46. Kim, B.H.; Kang, Z.; Ramanan, R.; Choi, J.E.; Cho, D.H.; Oh, H.M.; Kim, H.S. Nutrient Removal and Biofuel Production in High Rate Algal Pond Using Real Municipal Wastewater. J. Microbiol. Biotechnol. 2014, 24, 1123–1132. [Google Scholar] [CrossRef] [Green Version]
  47. Borowitzka, M.A.; Borowitzka, L.J. Micro-Algal Biotechnology; Cambridge University Press: Cambridge, UK, 1988. [Google Scholar]
  48. Posadas, E.; García-Encina, P.-A.; Soltau, A.; Domínguez, A.; Díaz, I.; Muñoz, R. Carbon and Nutrient Removal from Centrates and Domestic Wastewater Using Algal-Bacterial Biofilm Bioreactors. Bioresour. Technol. 2013, 139, 50–58. [Google Scholar] [CrossRef]
  49. Hoffmann, J.P. Minireview Wastewater Treatment with Suspended and Nonsuspended Algae 1. J. Phycol. 1998, 763, 757–763. [Google Scholar] [CrossRef]
  50. Park, J.B.K.; Craggs, R.J.; Shilton, A.N. Recycling Algae to Improve Species Control and Harvest Efficiency from a High Rate Algal Pond. Water Res. 2011, 45, 6637–6649. [Google Scholar] [CrossRef] [PubMed]
  51. Park, J.B.K.; Craggs, R.J. Wastewater Treatment and Algal Production in High Rate Algal Ponds with Carbon Dioxide Addition. Water Sci. Technol. 2010, 61, 633–639. [Google Scholar] [CrossRef] [PubMed]
Water 14 04047 g001 550
Figure 1. Schematic diagrams of the three HRAPs (R1, R2, and R3) for the removal of pathogens and nutrients from primary domestic wastewater.
Figure 1. Schematic diagrams of the three HRAPs (R1, R2, and R3) for the removal of pathogens and nutrients from primary domestic wastewater.
Water 14 04047 g001
Water 14 04047 g002 550
Figure 2. Logarithmic removal of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus sp., Enterococcus faecalis, and Escherichia coli in R1, R2, and R3 during the operational stage. Results in average ± standard deviation. Values with the same letter (a, b, c, d, e, and f) are statistically equal (α = 0.05). The number of replicates performed was n = 20.
Figure 2. Logarithmic removal of Pseudomonas aeruginosa, Clostridium perfringens, Staphylococcus sp., Enterococcus faecalis, and Escherichia coli in R1, R2, and R3 during the operational stage. Results in average ± standard deviation. Values with the same letter (a, b, c, d, e, and f) are statistically equal (α = 0.05). The number of replicates performed was n = 20.
Water 14 04047 g002
Water 14 04047 g003 550
Figure 3. Variations of the microalgae population in the HRAPs (R1, R2, and R3) during the operational period. The microalgae population was monitored on day 0 (inoculum), day 15 (half of experiment), and day 26 (end of experiment).
Figure 3. Variations of the microalgae population in the HRAPs (R1, R2, and R3) during the operational period. The microalgae population was monitored on day 0 (inoculum), day 15 (half of experiment), and day 26 (end of experiment).
Water 14 04047 g003
Table
Table 1. Physical–chemical and biological characterization of RS during the experiment.
Table 1. Physical–chemical and biological characterization of RS during the experiment.
ParametersUnitRS
CODmg COD L−1127.45 ± 48.43
TOCmg C L−1127.50 ± 10.61
ICmg C L−160.00 ± 5.66
TNmg N L−145.00 ± 35.49
NH4+mg N-NH4+ L−121.43 ± 15.25
NO2−mg N-NO2−L−1ND
NO3−mg N-NO3−L−1ND
Pmg P-PO43− L−16.09 ± 0.45
C:N-2.8
C/N/P-1 July 2022
pH-7.78 ± 0.18
Pseudomonas aeruginosaCFU (100 mL)−1(3.46 ± 5.99) × 105
Clostridium perfringensCFU (100 mL)−1(3.46 ± 5.99) × 105
Staphylococcus sp.CFU (100 mL)−1(3.46 ± 5.99) × 105
Enterococcus faecalisCFU (100 mL)−1(3.46 ± 5.99) × 105
Escherichia coliMPN (100 mL)−1(3.46 ± 5.99) × 105
Notes: Variations and standard deviation. MPN: most probable number. CFU: colony-forming unit. ND: not detected.
Table
Table 2. Operational conditions, DO concentration, pH value, temperature, evaporation rate, productivity, and settleability in each HRAP (R1, R2, and R3) during the experiment.
Table 2. Operational conditions, DO concentration, pH value, temperature, evaporation rate, productivity, and settleability in each HRAP (R1, R2, and R3) during the experiment.
ParametersUnitR1R2R3
HRTd4.97 ± 0.344.88 ± 0.335.00 ± 0.00
OLRg COD m2 d−14.08 ± 0.304.07 ± 0.283.94 ± 0.00
Shading%505050
CO2 additionmL min−12.5 ± 0.4 --
Fed regimeh24240.1
pH 7.27 ± 0.797.46 ± 0.577.38 ± 1.07
DOmg O2 L−17.30 ± 1.077.12 ± 1.136.83 ± 1.22
Light Intensity **μmol m−2 s−1507.2 ± 278.2
Temperature°C21.59 ± 3.5621.65 ± 3.5721.73 ± 3.46
Evaporation rate L m−2 d−16.79 ± 7.085.21 ± 7.516.04 ± 6.85
Productivity g m−2 d−13.94 ± 1.00 *2.83 ± 0.51 *5.93 ± 2.0 *
TSSg L−10.18 ± 0.040.13 ± 0.020.29 ± 0.09 *
Sed-Re%31.51 ± 25.48−52.38 ± 104.79 *36.49 ± 27.26
Notes: -: without CO2 addition. *: The values in the same line are statistically different (α = 0.05). HRT: hydraulic retention time. OLR: organic load rate. pH: potential of hydrogen. DO: dissolved oxygen. TSS: total solid suspended. Sed-Re: removal efficiencies of TSS. The number of replicates performed was n = 52 for OD, pH, light intensity, temperature, evaporation rate, and TSS. **: hourly light intensity with 50% shading.
Table
Table 3. Removal efficiency (%) of COD, TOC, IC, TC, TN, and TP in reactors R1, R2, and R3.
Table 3. Removal efficiency (%) of COD, TOC, IC, TC, TN, and TP in reactors R1, R2, and R3.
Removal Efficiency (%)
HRAP COD-ReTOC-ReIC-ReTC-ReTN-ReTP-Re
R163.26 ± 8.2131.02 ± 31.9467.36 ± 10.6442.62 ± 25.2173.40 ± 3.1528.98 ± 7.29
R265.65 ± 12.5938.76 ± 17.4169.79 ± 10.4448.76 ± 14.7267.28 ± 21.4726.57 ± 11.92
R259.36 ± 15.6836.94 ± 24.1966.23 ± 11.9546.44 ± 20.5459.67 ± 18.3135.05 ± 14.13
Notes: The number of replicates performed was n = 12 for COD, TOC, IC, TC, NT, and TP.
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Ruas, G.; Lacerda, S.F.; Nantes, M.A.; Serejo, M.L.; da Silva, G.H.R.; Boncz, M.Á. CO2 Addition and Semicontinuous Feed Regime in Shaded HRAP—Pathogen Removal Performance. Water 2022, 14, 4047. https://doi.org/10.3390/w14244047

AMA Style

Ruas G, Lacerda SF, Nantes MA, Serejo ML, da Silva GHR, Boncz MÁ. CO2 Addition and Semicontinuous Feed Regime in Shaded HRAP—Pathogen Removal Performance. Water. 2022; 14(24):4047. https://doi.org/10.3390/w14244047

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Ruas, Graziele, Sarah Farias Lacerda, Maria Alice Nantes, Mayara Leite Serejo, Gustavo Henrique Ribeiro da Silva, and Marc Árpad Boncz. 2022. "CO2 Addition and Semicontinuous Feed Regime in Shaded HRAP—Pathogen Removal Performance" Water 14, no. 24: 4047. https://doi.org/10.3390/w14244047

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