Evaluation of the effect of the feeding regime on the removal of metals and pathogens in microalgae–bacterial systems Open Access

Microalgae bacterial processes, such as those commonly used in high rate algal ponds (HRAPs), have shown to be, when compared to conventional treatments, a promising technology. This system has stood out because it is able to effectively and economically remove many types of pollutants, including metals and pathogens, the focus of this study. One of the main advantages of these systems is the potential to recover resources – water, energy, and nutrients – as they generate biomass as a product that can be used in the production of fuels, fertilizers, and biogas, promoting sustainability and enhancing the application of the circular economy (Muñoz & Guieysse 2006). Life-cycle assessment (LCA) studies show that HRAPs coupled with the production of biofertilizer or biogas, when compared to typical small-sized activated sludge system, is potentially of lower environmental impact for categories, such as climate change and fossil fuel consumption (Arashiro et al. 2018).

In HRAP reactors, in addition to other types of interactions, there is a symbiosis between microalgae and bacteria, which is a cooperative type of interaction among many other complex interactions, established between these types of microorganisms. The bacteria use O₂ to convert organic matter into CO₂, among others, while the microalgae consume this CO₂ and the nutrients present for photosynthesis, producing O₂ and biomass (Muñoz & Guieysse 2006). Thus, the process decreases energy costs and carbon footprint of wastewater treatment, while fixing nutrients in biomass (García et al. 2018).

Among the pollutants present in sewage, heavy metals represent a serious problem with a great impact on the environment and human health, due to their persistence, toxicity, and bioaccumulative effects in the food chain. Among possible effects are damage to the nervous system, cancer, and gastrointestinal disorders (Zeraatkar et al. 2016). The term ‘heavy metals’, however, is somewhat imprecise, and included in this group are trace elements, such as copper (Cu), manganese (Mn), nickel (Ni), and zinc (Zn), which are essential for many metabolic processes, but which can become harmful if the concentration exceeds certain limits (Duffus 2002).

Environmental pollution with metals typically originates from anthropogenic sources (Duffus 2002), and elements most frequently found in surface and groundwater are lead, mercury, chromium, arsenic, cadmium, zinc, copper, and nickel (Jácome-Pilco et al. 2009). Chemical and physico-chemical technologies may be used for the removal of metals from wastewater, but often these methods have specific limitations, such as high cost, generation of sludges (chemical precipitation), and secondary pollution (ion exchange), among others (Wang et al. 2019). Thus, interest exists in developing more economic and simple technologies capable of removing metals.

Pathogens, including a wide variety of bacteria, viruses, helminth eggs, and protozoa, are responsible for numerous diseases of oral–fecal transmission and represent a significant hazard associated with sewage, and one of the main functions of wastewater treatment is reducing this hazard (Curtis 2003). The ease and low cost of quantification of the Escherichia coli bacteria, as well as the reliability of this method, make this one of the main indicator organisms for the presence of fecal material from warm-blooded animals and pollution by wastewater, considered more specific than total and fecal coliforms (Liu et al. 2020).

In addition to the symbiotic biodegradation mentioned before, the removal of pollutants in microalgae–bacteria systems can occur through other mechanisms as well. Biosorption, including adsorption and absorption processes, is used by biomass to accumulate metal ions (Kumar et al. 2016), but metals can also be chelated by extracellular metabolites released by algae, or by precipitation (Muñoz & Guieysse 2006). In the case of pathogens, their deactivation and consequent disinfection can happen by photo-oxidation, the effect of constantly fluctuating environmental conditions such as pH and temperature, and as a result of the presence of bactericidal substances produced by microalgae (Chambonniere et al. 2021).

Although several researchers already obtained good results considering pathogen and metal removal in HRAPs (Saavedra et al. 2018; Ruas et al. 2020), for metals, few studies have been carried out in experiments with real wastewater and outdoor conditions. Among the operational conditions, it is already known that factors such as pH, temperature, and dissolved oxygen (DO) are crucial for the removal of these pollutants in these systems (Muñoz & Guieysse 2006; Couto et al. 2015). As the removal mechanisms are complex, involving many factors, conducting studies under real-life conditions is fundamental to optimize the treatment through these types of processes.

An important parameter that can influence the cost and quality of treatment in HRAPs is the feeding regime, with both continuous and semi-continuous cultivation being used in larger-scale applications (Lu et al. 2021). Although in batch systems, sometimes more concentrated biomass may be obtained, they are limited to bench-scale applications due to the periodic need to prepare new cultures at low volumes (Do et al. 2020). A semi-continuous feeding regime has the potential to increase productivity while reducing costs (Pereira et al. 2020), therefore potentially increasing the efficiency of pollutant removal. However, for both continuous and semi-continuous systems, results may depend on the feeding rate applied, as stability in the growth of algae cultures needs to be ensured to maintain the treatment capacity (Do et al. 2020). In this context, this work aimed to study the influence of the feeding regime – continuous or semi-continuous – on the removal of metals and pathogens (Escherichia coli) from primary domestic wastewater (PDW), using three HRAP-type reactors in parallel, of which one fed continuously, and the other two semi-continuously.

A microalgae culture (≈ 98% predominance of individuals of the gender Scenedesmus sp.) with 1.4 g L⁻¹ of total suspended solids (TSS), originating from an outdoors HRAP used for the treatment of domestic wastewater was used as inoculum. Scenedesmus sp. stands out as one of the most important microalgae genera that naturally predominate in HRAP treatment systems due to its fast growth and high resistance characteristics (Muñoz & Guieysse 2006). The reactors were also inoculated with a nitrifying–denitrifying activated sludge from a wastewater treatment plant (WWTP) treating domestic wastewater, with 4.2 gTSS L⁻¹. The system was fed with PDW collected from a municipal WWTP and stored at 4 °C in a cooled agitated storage tank (Implemis, Brazil). The average concentrations of the microbiological and physico-chemical properties of the influent are summarized in Table 1. The metals presented in Table 1 were all those detected by the spectrophotometer equipment (excluding the less relevant ones according to the criteria of toxicity and importance for recovery by biomass). The actual concentrations of these elements in the sewage were used, without any fortification.

Table 1

Physical–chemical and microbiological characterization of the PDW

Parameter .	Unit .	Concentration .
pH	–	8.0 ± 0.1
Chemical oxygen demand (COD)	mg O2 L−1	127 ± 11
TOC	mg C L−1	119 ± 9
IC	mg C L−1	53 ± 11
TN	mg N L−1	66 ± 15
Ammonium nitrogen (N-NH4+)	mg N- L−1	20 ± 5
Total phosphorus as P-PO43– (TP)	mg P- L−1	6.1 ± 0.4
C:N:P	–	28/14/1
C:N	–	2
Escherichia coli	MPN 100 mL−1	(2.5 ± 1.3) × 106
Cr	mg Cr L−1	0.03 ± 0
Cu	mg Cu L−1	0.02 ± 0.01
Fe	mg Fe L−1	0.58 ± 0.7
Mn	mg Mn L−1	0.03 ± 0.01
Mg	mg Mg L−1	4.66 ± 3.5
Na	mg Na L−1	24.58 ± 10.7
Zn	mg Zn L−1	0.05 ± 0.01

Parameter .	Unit .	Concentration .
pH	–	8.0 ± 0.1
Chemical oxygen demand (COD)	mg O2 L−1	127 ± 11
TOC	mg C L−1	119 ± 9
IC	mg C L−1	53 ± 11
TN	mg N L−1	66 ± 15
Ammonium nitrogen (N-NH4+)	mg N- L−1	20 ± 5
Total phosphorus as P-PO43– (TP)	mg P- L−1	6.1 ± 0.4
C:N:P	–	28/14/1
C:N	–	2
Escherichia coli	MPN 100 mL−1	(2.5 ± 1.3) × 106
Cr	mg Cr L−1	0.03 ± 0
Cu	mg Cu L−1	0.02 ± 0.01
Fe	mg Fe L−1	0.58 ± 0.7
Mn	mg Mn L−1	0.03 ± 0.01
Mg	mg Mg L−1	4.66 ± 3.5
Na	mg Na L−1	24.58 ± 10.7
Zn	mg Zn L−1	0.05 ± 0.01

MPN, most probable number.

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The experimental setup, a small pilot scale system, consisted of three outdoors reactors (HRAP₁, HRAP₂, and HRAP₃), of 20 L each, with 0.32 m² of illuminated area and 16 cm culture depth. Continuous agitation of the HRAPs was maintained by a submersible pump with a nominal flow rate of 650 L·h⁻¹ (Sarlo Better B650, Brazil), resulting in a recirculation velocity of 20 ± 2 cm s⁻¹ (Ruas et al. 2020). Hydraulic tests prior to the operation of the systems ensured that there were no dead zones or hydraulic short circuits throughout the entire extension of the reactors, including the inlet and outlet devices. The study was conducted at the Federal University of Mato Grosso do Sul (Campo Grande/MS, Brazil) for 36 days, at ≈ 29 °C.

To assess the influence of the feeding regime, reactor HRAP₁ was fed continuously, while HRAP₂ and HRAP₃ were fed in a semi-continuous regime. HRAP₂ was fed 12 h per day (between 09:00 and 21:00) while HRAP₃ was fed 0.1 h per day (between 09:00 and 09:06). Only for reactor HRAP3, in order to avoid short-circuiting, when applying the daily feed of influent, a waiting time of 5 min was applied, before the excess liquid was drained from the reactor. The same HRT of 7 days was applied to all three reactors.

Samples of feed, cultivation broth, and effluent were collected 3 days per week, at 09:10 (T1) and 16:00 (T2). Turbidity, pH, DO, temperature, and light intensity were determined in samples T1 and T2 of the culture broth. E. coli was also determined at both collection times from the feed and the effluent. T1 samples (feed and effluent) were also used to determine soluble concentrations of chemical oxygen demand (COD), total organic carbon (TOC), inorganic carbon (IC), total organic nitrogen (TN), ammonium nitrogen (N-NH₄⁺), nitrite nitrogen (N-⁠), nitrate nitrogen (N-⁠), total phosphorus as P- (TP), and metals. For these analyses of dissolved compounds, the samples were previously filtered with 0.45 μm glass fiber filters.

The applied semi-continuous feeding regime approximates the chemostat culture method (keeping the culture volume constant, adding culture medium at a constant rate), and therefore the systems reach a quasi-steady state (Boraas 1993). The steady state was determined based on graphical and numerical analysis of the physico-chemical parameters (pH, DO, TSS, etc.) and nutrient removals (P and N), being reached when the variation (dX = dt) of most monitored concentrations tended to zero (Ruas et al. 2022).

Analyses were performed according to Standard Methods (APHA 2017). Light intensity (photosynthetically active radiation – PAR), was determined using a PAR MQ-200 radiation meter (Apogee Instruments, USA). Concentrations of TOC, TC, IC, and TN were determined using a Vario TOC cube (Elementar, Germany) organic carbon analyzer. Turbidity, DO, and pH were measured using Hanna HI98703-01, Hanna HI2004-02, and Hanna HI2002-02 bench meters, respectively (Hanna Instruments, USA). N-NH₄⁺ was measured using an Orion Five Star (Thermo Scientific, USA) multiparameter analyzer with ammonia electrode. Anions (N-⁠, N-⁠, and P-⁠) were analyzed using a Dionex UltiMate ICS 1100 ion chromatograph with an IonPac AG19/AS19 column (Thermo Scientific, USA). Microalgae were identified through microscopic examination (Leica DM5500B, Germany).

For the determination of metal concentrations, samples were filtered using 0.7 μm MN GF1 glass fiber microfilters (Macherey-Nagel, Germany), acidified with HNO₃, and stored at 4 °C before analysis. Samples were digested in acid medium, according to method 3030F: nitric acid-hydrochloric acid digestion (APHA 2017), before analysis using a Varian SpectrAA 200 FS flame atomic absorption spectrophotometer (Varian, USA). Escherichia coli was determined using Colilert^® quantification kits (IDEXX Laboratories, USA), and the results were reported as E. coli most probable number (MPN) per 100 mL.

In both equations, C_inf and C_eff are influent and effluent concentrations (mg L⁻¹), respectively, V is the working volume of the reactor (L), and M is the dry weight of the culture biomass (g).

Statistical analyses were performed using version 3.2.2 of the R statistical software. The normality of all the data sets was checked using the Shapiro–Wilk test, and the comparison of means was conducted by analysis of variance (ANOVA) followed by the Tuckey hypothesis test, at a 95% confidence level. In the case of normal distribution, Pearson's Correlation was used to verify the influence of environmental parameters on the removals obtained. Otherwise, Spearman's rank correlation was used.

During the experiment, temperatures and evaporation losses for all three reactors were similar at ≈ 27 °C and ≈ 0.9 L m⁻² day⁻¹, respectively (Table 2). The average PAR (1,083 ± 490 μE m⁻² s⁻¹) was similar to the 1,087.3 ± 697.6 μE m⁻² s⁻¹ reported by Couto et al. (2015) for an experiment under outdoor conditions with a local climate characterized as tropical altitude.

With continuous feeding, the pH at T1 was 8.6 ± 0.5, while in the reactors with semi-continuous feeding, HRAP₂, and HRAP₃, the pH had similar values of 10.4 ± 0.1 and 10.1 ± 0.3, respectively, as shown in Table 2. At time T2, the pH values followed the same trend, with higher averages in the reactors operated in a semi-continuous feeding regime. Likewise, DO concentrations were also higher in HRAP₂ and HRAP₃, at 13.4 ± 1.3 mgO₂ L⁻¹ and 11.8 ± 1.6 mgO₂ L⁻¹, respectively, than in HRAP₁ (7.6 ± 1.3 mgO₂ L⁻¹ at T1) indicating a higher bacterial oxidation activity in this reactor overnight.

DO concentrations at T2 were lower for all three reactors. The results in HRAP₂ and HRAP₃ show a positive correlation between the DO and pH in these HRAPs, in line with the consideration that the increase in DO is related to the photosynthetic activity of the algae, which removes CO₂ from the culture medium, and consequently raising the pH (Dias et al. 2017). The observed variations in turbidity at times T1 and T2 are related to natural fluctuations in light intensity, where the photosynthetic apparatus tends to decrease after higher light intensities (T2) and also by the cessation of photosynthesis in periods of the low incidence of light (hours before T1) (Muñoz & Guieysse 2006).

Higher biomass productivities, of 21.9 ± 0.3 and 21.2 ± 0.1 mg L⁻¹ day⁻¹, respectively, were achieved in HRAP₂ and HRAP₃, as shown in Table 2. The areal productivity was 1.5, 3.6, and 3.3 g m² day for HRAP₁, HRAP₂, and HRAP₃, in that order. The C:N ratio of the primary sewage used (Table 1), although being close to that expected for this matrix (C:N ≈3:0), indicates carbon limitation, and this may have reduced the growth of biomass in the three conditions studied and consequently the treatment efficiencies (Couto et al. 2015; Ruas et al. 2020).

Pereira et al. (2020) obtained higher biomass productivities in experiments in continuous mode using anaerobic secondary effluent and growth of five microalgae strains, including Chlorella sp. and Scenedesmus sp., with a peak volumetric productivity of 283 mg L⁻¹ day⁻¹ at a dilution rate of 0.3 day⁻¹ for Chlorella sp. L06, which compared to other higher dilution rates, was more favorable because the biomass is in a constant state of exponential growth (steady state growth). Do et al. (2020) observed in an experiment in raceway ponds with a C. variabilis TH03-bacteria consortium in the semi-continuous mode that optimal replacement was achieved when replacing 80% of the culture volume by new sewage, reaching a stable biomass productivity of 66.2–1,189 mg L⁻¹ day⁻¹ where higher substitution rates impaired stable growth.

The final concentrations obtained in the reactors with a semi-continuous feeding regime (HRAP₂ and HRAP₃) were similar (without significant difference, p > 0.05), with the highest removals for Zn (48 ± 2 and 54 ± 5%) and Cu (44 ± 5 and 33 ± 1% respectively for each reactor). However, the removal efficiency was similar in HRAP₁ (without significant difference, p > 0.05), reaching results of up to 72 ± 2% for Fe. Jácome-Pilco et al. (2009) achieved greater removals of Cr(VI) by Scenedesmus incrassatulus in a continuous culture system using a split-cylinder internal-loop airlift photobioreactor with a removal efficiency of 43.5 ± 1.0% while in this study the removal efficiencies for this element were 33 ± 14, 38 ± 3 and 38 ± 1% for HRAP₁, HRAP₂, and HRAP₃, respectively. Wang et al. (2019) used a combined HRAP and submerged macrophyte pond (APMP), obtaining a greater removal efficiency for Cr with 75.8% and a lower removal efficiency for Zn, with 61.1%, using 5-day hydraulic retention time (HRT).

Few existing studies are using continuous and semi-continuous feeding in a system with microalgae in the removal of metals, the experiments in batch regimes prevailing (Lu et al. 2021). Assessing the biosorption of metals in a continuous system is advantageous considering that the applicability of large-scale batch systems is smaller, with continuous systems being more suitable for commercial applications (Kumar et al. 2016). Peña-Castro et al. (2004) observed a greater advantage in the continuous system compared to batch in the cultivation of microalgae Scenedesmus incrassatulus in artificial effluent in the presence of Cr(VI), Cd(II), and Cu(II), with a greater removal of Cr(IV) for being absorbed by energy-related processes and being better sequestered in actively growing cells, obtaining similar results of removal of this metal with an average reduction of 39%. Do et al. (2020) reported 56–100% removals of Cd, Hg, Pb, Fe, Cu, Mn, Zn, and Ni from domestic wastewater with an experiment in semi-continuous mode in a raceway pond, using a consortium of Chlorella variabilis TH03 and bacteria, therefore, results are greater than those obtained in this study for Cu and Zn and similar for the other metals.

In the biosorption process, the pH is one of the most important parameters, as it can affect both the availability of metal binding sites in the biomass and the solubility of metal ions, and the ideal pH range is 4–6 for better sorption of metal cations (Kumar et al. 2016). Considering the mean pH > 8 in the three HRAPs under study, which is related to the growing conditions of the algae, precipitation may have occurred and reduced the effectiveness of biosorption. The effect of pH on the uptake capacity may vary according to the species of microalgae used, as noted by Saavedra et al. (2018), whom, except for Chlorella vulgaris, reported greater removal efficiency of Mn and Zn at pH 5.5 for all species tested (89–92.1%), while a negligible pH effect was observed for Cu biosorption. Yang et al. (2015), reported lower bioavailability of Zn, Mn, Cd, and Cu at pH 10, while at pH 4–8, it was above 92% for adsorption by Chlorella minutissima UTEX2341.

Regarding the role of biomass, (García et al. (2018), in an experiment with algal-bacterial photobioreactors treating piggery wastewater, an average removal of 49% of Zn under conditions with higher biomass concentrations was observed, suggesting the mediation of this parameter in metal biosorption. However, the greater increase in biomass concentration under semi-continuous feeding conditions, of 0.23 ± 0.03 g L⁻¹ in HRAP₂ and 0.21 ± 0.01 g L⁻¹ in HRAP₃, compared to 0.13 ± 0.02 g L⁻¹ in HRAP₁, did not significantly affect the removal of the metals under study, including Zn, even though the increase in biomass should favor biosorption by providing a greater number of metal binding sites. The amount of biomass in the three conditions studied also seems not to have disfavored biosorption, considering that, except for Zn and Na, the association between metal removal and biomass concentration was positive, although with a very weak correlation.

The uptake capacities obtained in the three conditions studied were similar, except for some removal peaks in the condition of continuous feeding (HRAP₁) for the metals Cr, Zn, and Mn with 0.2, 0.3, and 0.2 mg g⁻¹, respectively (Figure 2). The highest biosorption peaks under semi-continuous feeding conditions were for the metals Cu with 0.1 mg g⁻¹ in HRAP₂ and Fe with 11 mg g⁻¹ for HRAP₃. According to the mean uptake capacity of the three studied conditions, it is observed that the biosorption was lower for Cu and Zn with means of 0.03 and 0.04 mg g⁻¹, respectively. In a real matrix, being a multimetallic solution, the competitiveness of ions must be considered. In this case, this may have been what happened to Cu and Zn: the presence of other cations reduced the biosorption of these ions due to competition for the same binding sites (Salam 2019). The greater biosorption capacity for Fe (11 mg g⁻¹) demonstrates the influence of the higher initial concentration of this metal on the sorption efficiency (Kumar et al. 2016).

Liu et al. (2020) observed in a study of pathogen removal in wastewater stabilization pond systems (WSPs), that the increase in pH to above 8.0 favored the inactivation of E. coli with good results, similar to those obtained in the three conditions studied here. However, Spearman's rank correlation coefficient for the results achieved at times T1 and T2 showed that there was a weak negative linear correlation between the pH and the removal efficiencies in the three reactors (ρ = −0.4241, p-value = 0.1016) and negligible correlation (ρ = −0.1436, p-value = 0.6096), respectively, indicating that the greatest removals occurred at lower pHs, but still in the alkaline range. The reduction related to the pH parameter is associated with the death of the bacterium when it is no longer able to acidify its own cytoplasm, being for this aspect a non-linear relationship because the limit will be when the homeostatic mechanism of this microorganism is overloaded and can occur at different levels of pH (Curtis 2003).

The increase in DO concentrations is related to photosynthesis performed by algae and the combination with sunlight conditions (UV irradiation, a.o.) causes the decrease of pathogenic organisms in ponds (Dias et al. 2017). However, at time T1, this parameter showed a weak negative linear correlation (Pearson's linear correlation test, p = 0.0952, ρ = −0.4314, r² = 0.1861) and at time T2 a negligible negative correlation (p = 0.5844, ρ = −1537, r² = 0.0236). The high DO concentration can be related to the increase in photo-oxidation, a disinfection mechanism in which the bacterial cell damage is caused by reactive oxygen species (ROS) that can be formed by many sensitizers in the presence of oxygen (Chambonniere et al. 2021). However, like in this study, Liu et al. (2016), also did not find a good correlation of this parameter with E. coli removal, indicating that disinfection induced by photo-oxidation is not only dependent on DO concentrations but is also influenced by other factors such as solar light intensity and pH.

The feeding regime can impact the pH and DO levels in an HRAP system, as a result of the volume of fresh effluent added, which may cause a marked decrease in pH due to nitrification and of the DO level due to an acceleration in bacterial oxidation processes (Pham et al. 2021). However, the pH and DO concentrations obtained in the HRAP2 and HRAP3 reactors rule out this possibility of nitrification with the decrease in the values of these two parameters. Do et al. (2020) observed in an experiment performed in semi-continuous mode with different percentages of replacement of the culture volume by new wastewater, that in substitutions of more than 90%, despite showing good biomass growth, the algal–bacteria culture experienced a long lag phase, weakening the health of this consortium and affecting the treatment capacity, this being a possibility for the results obtained in HRAP₃, in which feeding at 0.1 h day⁻¹ resulted in a greater dilution of the cultivation broth (around 14%) in a short time.

For the PAR parameter, Spearman's rank correlation coefficient was negligible at T1 but moderately positive at time T2 (Spearman's correlation coefficient ρ = 0.4493, p-value = 0.0928), indicating that sunlight-mediated inactivation was possibly an active mechanism in removing the pathogens. This mechanism may have occurred by direct absorption of solar UV-B or photo-oxidation (Dias et al. 2017). The action of pathogen removal mechanisms mediated by sunlight is affected by the attenuation of light in HRAPs due to algae growth, dependent therefore on the operational and environmental parameters and the composition of the influent. However, this negative impact is neutralized due to the constant recirculation and mixing of the culture broth in the reactor, allowing greater exposure of pathogens near the surface of the HRAP (Chambonniere et al. 2021).

The removal efficiencies of E. coli and metals were similar for both continuous and semi-continuous feeding regimens. For metals, considering the two feeding regimes tested, the highest removals were obtained for Fe (81 ± 2%) and Mn (83 ± 3%), while the lowest removals were for Cu (33 ± 11%) and Zn (25 ± 1%). The average pH < 8.0 indicates that precipitation may have been the main mechanism of removal of metals, in addition to biosorption. Concerning E. coli, the lowest removal was obtained in the reactor with a semi-continuous feed of 0.1 h⁻¹ day⁻¹, with an LRV of 1.8 ± 0.4 log₁₀ MPN 100 mL⁻¹, indicating that the high dilution in a short space of time may have negatively affected the treatment capacity. The sunlight-mediated inactivation was possibly a relevant mechanism in removing the pathogens in this experiment. The semi-continuous feeding regime was beneficial for increasing the biomass productivity, with growth rates of 21.9 ± 0.3 and 21.2 ± 0.1 mg L⁻¹ day⁻¹. In order to further quantify the advantages of the semi-continuous feeding regime in these systems, future studies with other pollutants will be carried out, combining the presented research with a study of other parameters, as well as an economic feasibility analysis.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.