In order to have an efficient operation, sequencing batch reactors (SBR) must support granular biomass with high conversion rates, settling properties, and be able to deal with the inherent variability of the composition of real wastewaters. In this study, the effect of the influent composition and the specific organic loading rate (Bx) on the granulation process was evaluated in two SBRs, fed with greywater (GW) and a synthetic medium (SM). The feeding with SM led to the formation of compact granular biomass, with a sludge volume index (SVI) of 22.4 mL g−1, and a zone settling velocity (ZSV) of 13.1 m h−1. In contrast, feeding with GW induced the formation of filamentous granules, with lower settling properties (SVI = 165 mL g−1 and ZSV = 10 m h−1), when the system was operated at high Bx (4.4 kg COD kg VSS−1 d−1). However, the reduction of the average Bx to 2 kg COD kg VSS−1 d−1 induced an improvement in the morphology and properties of the granules (SVI = 98 mL g−1 and ZSV = 13 m h−1). Furthermore, the kinetic analysis indicated that granules cultivated with SM were formed by fast growing microorganisms with a high cell yield, whereas those cultivated in GW presented a much lower cell yield.

INTRODUCTION

Greywater (GW) is the fraction of domestic wastewater composed of bathroom (shower and hand basin), laundry and kitchen discharges. Since this effluent does not contain faeces, urine and toilet paper, it is less polluted than municipal wastewater and its reuse has been considered as an attractive option to reduce the domestic water demand (Eriksson et al. 2002). However, GW composition is dependent on household activities, source and water availability (Morel & Diener 2006), so in many cases may present high concentrations of soluble and suspended organic matter as well as fats, detergents, synthetic chemicals and pathogens (Travis et al. 2010). Therefore, its reclamation for non-potable uses needs an efficient, robust and decentralized treatment capable of dealing with this inherent variability.

To date, several biological technologies have been applied for GW treatment, including constructed wetlands (Hyun et al. 2015), membrane bioreactors (Lamine et al. 2012), upflow anaerobic sludge blanket (UASB) reactors, and aerobic sequencing batch reactors (SBR) (Hernández Leal et al. 2010). Among these, SBR systems are advantageous due to the possibility of carrying out the removal of substrates in a single unit, with a small footprint due to the absence of secondary clarifiers (Arrojo et al. 2004). Furthermore, within the operation of the SBR it is possible to form an aerobic granular biomass, which presents a series of different qualities such as a high biomass concentration, high settling velocities and low sludge volume index (SVI), alongside the ability to resist toxins and high organic loading rates (Adav et al. 2008). All these particular characteristics may result in the operation of a compact system with high conversion rates, short hydraulic retention times, and the ability to support the inherent changes in the composition of GW.

The mechanisms leading to granulation of aerobic biomass and the variables involved in the process have been widely studied using a variety of media. These range from synthetic media with highly biodegradable carbon sources such as glucose, acetate, phenol and ethanol (Val del Río et al. 2012), to real wastewaters from different industrial sources such as dairy (Arrojo et al. 2004; Schwarzenbeck et al. 2005), brewery (Wang et al. 2007), as well as domestic wastewaters (De Kreuk & van Loosdrecht 2006). For most of these cases, the growth of compact granular biomass with an SVI lower than 70 mL g−1 and settling velocities higher than 20 m h−1 was observed. However, it has been underlined that the influent composition can greatly affect the granulation process, having an effect on the definition of the morphology, microbial structure and physical properties of the aerobic granules (Schwarzenbeck et al. 2005; De Kreuk & van Loosdrecht 2006; Val del Río et al. 2012). As a consequence, the analysis of granulation using GW, looking at the effect of its particular composition on the process, is important in order to assess the viability of this technology as a feasible alternative for the treatment of this type of effluent. Consequently, the present study aims to study the granulation process in an SBR using GW compared to a reference system fed with a balanced synthetic medium (SM), as well as to look at the effect of the specific organic loading rate on the stability and properties of the biomass.

MATERIALS AND METHODS

Aerobic SBR

Two Plexiglas columns of 3.3 L working volume, with a height H = 62 cm and an H/D ratio of 10.2 were used as the SBR. Oxygen was provided by a 70 W air blower through fine bubble diffusers fixed at the bottom of each reactor (Figure 1). The influent was fed through a port located near the bottom, and the effluent was discharged through a port located at the middle of the working height. The on-off operation of pumps and blowers was controlled with timers.
Figure 1

Schematic representation of the SBR operation. V0 and S0 are the feed volume and its substrate concentration respectively, V is the volume remaining after the discharge stage and S its substrate concentration. VT is the reactor working volume (VT = V + V0) and Si the substrate concentration at the beginning of the aeration stage.

Figure 1

Schematic representation of the SBR operation. V0 and S0 are the feed volume and its substrate concentration respectively, V is the volume remaining after the discharge stage and S its substrate concentration. VT is the reactor working volume (VT = V + V0) and Si the substrate concentration at the beginning of the aeration stage.

Considering that the SBR operation involves the repetition of the cycles under the same conditions, the hydraulic (HRT) and sludge (SRT) retention times, as well as the specific organic loading rate (Bx) can be defined according to Equations (1)–(3). 
formula
1
 
formula
2
 
formula
3
where F0 (L d−1) is the influent volume exchanged per day, X is the mixed liquor suspended solids (MLSS), Xe is the solids content in the effluent (gTSS L−1) and S0 corresponds to the substrate concentration at the inlet. During the filling stage, S0 is diluted with the remaining medium from the previous cycle (V, S), resulting in the substrate concentration at the beginning of the reaction stage Si (Equation (4)). 
formula
4
Defining an exchange coefficient ‘a’, as the ratio of the remaining volume after the discharge and the volume fed into the system (a=V/V0), Si can be expressed as follows (Equation (5)): 
formula
5

Operation

One of the reactors (GWr) was fed with GW collected from a household in Mexico City, by making composite samples from the kitchen sink, bathroom and washing machine. The other reactor (SMr) was fed with an SM and a trace solution prepared according to Beun et al. (1999), except for the carbon source concentration (sodium acetate), which was adjusted in the range of 0.65 to 1.49 g L−1 to give a chemical oxygen demand (COD) close to that of the GW, and the mono- and dibasic potassium phosphate concentration, which were in the range of 0.32 to 0.37 and 0.41 to 0.47 g L−1, respectively. All samples were stored in 20 L containers at 8.0 ± 1.0 °C and its composition is shown in Table 1. Both reactors were inoculated with a flocculant activated sludge (X0 = 3.2 g VSS L−1) obtained from the ‘Cerro de la Estrella’ sewage treatment plant in Mexico City.

Table 1

Composition of the SM and GW used as feed in the SBR

 SMGW
tCOD (mg O2 L−1840–1,908 610–2,610 
sCOD (mg O2L−1840–1,908 273–1,190 
N (mg NH4+-N L−142 0.36–10.5 
P (mg PO43-P L−1149–172 3.6–45.1 
COD/N (mg O2/mg NH4+-N) 26–45 1,694–249 
COD/P (mg O2/mg PO43−-P) 7.4–11 169–58 
N/P (mg NH4+-N/mg PO43−-P) 0.28–0.24 0.1–0.23 
Anionic surfactants (mg L−1– 5.3–90.3 
TSS (g L−1– 0.19–1.25 
 SMGW
tCOD (mg O2 L−1840–1,908 610–2,610 
sCOD (mg O2L−1840–1,908 273–1,190 
N (mg NH4+-N L−142 0.36–10.5 
P (mg PO43-P L−1149–172 3.6–45.1 
COD/N (mg O2/mg NH4+-N) 26–45 1,694–249 
COD/P (mg O2/mg PO43−-P) 7.4–11 169–58 
N/P (mg NH4+-N/mg PO43−-P) 0.28–0.24 0.1–0.23 
Anionic surfactants (mg L−1– 5.3–90.3 
TSS (g L−1– 0.19–1.25 

Both SBRs were operated in cycles of 4 h, with fixed 10 and 3 min periods for the feeding and discharge stages. The settling time was gradually reduced during the first eight weeks, leading to an increase in the reaction time and in the minimum settling velocity (vs = settling height/settling time), from 2.4 to 19.2 m h−1 in the reactor fed with SM, and from 2.4 to 6.4 m h−1 in the reactor fed with GW. These settling velocities allowed the washout of the slow-settling sludge during the discharge stage, in such a way that a fraction of biomass was continuously purged through the effluent (Xe), determining the SRT (Equation (2)). Furthermore, three biomass purges were carried out in SWr and one in GWr, just when the height of the settled granular sludge bed was close to the discharge port.

Aeration rate was maintained at 1.4 VVM (min−1), equivalent to a superficial airflow velocity of 1.43 cm s−1. Temperature was controlled at 30 ± 2.0 °C, and the exchange coefficient was set at a= 1.

Analytical methods

Determination of total and soluble chemical oxygen demand (tCOD, sCOD), total and volatile suspended solids (TSS, VSS), SVI and zone settling velocity (ZSV) were carried out following Standard Methods (APHA 1998). Ammonia was assessed after centrifugation of samples at 66.7 g for 15 min, using a Hanna electrode, model HI 83141. Anionic surfactants were analyzed according to Jurado et al. (2006). Granule solids concentration (Cg = mass of solids in granule per volume of granule) was analyzed by the blue dextran method described by Beun et al. (2002). The biomass disintegration coefficient (δ%) was determined by the ratio of the solids in the supernatant to the total weight of the granular sludge, after stirring a sample at 200 rpm for 5 min, using an orbital shaker (Ghangrekar et al. 2005). Particle size distribution was measured as recommended by Laguna et al. (1999). Pictures of the biomass morphology were taken with a Nikon optical microscope (model BX50) and a digital cell camera.

Aerobic granular sludge kinetics

The granular biomass kinetic constants were obtained with the Lineweaver-Burk model (Equation (6)), following the batch substrate consumption and cell growth rates. For this, a sample of granules was taken from each SBR and crushed with mortar and pestle. The culture from the SMr was fed with SM (14.0 g tCOD L−1, 91.6 mg NH4+-N L−1, 265.7 mg PO43−-P L−1), while that from GWr with GW (5.6 g tCOD L−1, 12 mg NH4+-N L−1, 26 mg PO43−-P L−1, anionic surfactants 132 mg L−1). The experiments were carried out under the same aeration and temperature conditions used in the SBR. 
formula
6
where μ is the specific growth rate constant (h−1), μmax is the maximum specific growth rate constant (h−1), S is the limiting substrate concentration (g L−1) and Ks is the affinity constant (g L−1).

The correlation between μmax and Ks in the Monod model made it necessary to perform an analysis of variance (ANOVA) of the linear regression of the experimental data. This analysis allowed the (1-α) confidence limits from the slope and intercept (Equation (6)) to be obtained, and subsequently those of the kinetic constants (μmax and Ks).

The cell mass yield coefficient (Yx) was calculated considering the solids content of the effluents (X) due to the continuous washout of biomass observed during the whole operation, as shown in Equation (7): 
formula
7
where X0 and X (gVSS L−1) represent the biomass content in the reactor at the beginning of the determination and after n operation cycles respectively, while S0 and S (g L−1) are the tCOD in the influent and effluent through the n operation cycles.

The determination of the specific substrate uptake rate (qs) was conducted by analyzing the COD removal in the SBRs themselves, maintaining the same operational conditions used during the whole experimental period and taking 10 mL samples at defined intervals. Subsequently, the particulate matter was removed by filtering the samples through 0.45 μm pore size filters, and the supernatant obtained was used for COD analysis.

RESULTS AND DISCUSSION

In spite of being operated at the same hydraulic conditions, the results of both systems considering the granulation process and the COD removal efficiencies were appreciably different, confirming that the influent complexity had a direct effect on the morphology and physical properties of the granular biomass as discussed below.

System performance

GW used in this study had a higher pollutant concentration than typical values (National Academies of Sciences 2016). This was due to the lower water availability in Mexico City (79 vs 99 L c−1d−1), and the inclusion of the kitchen samples, considered to be one of the most contaminated components (Eriksson et al. 2002). Both GW and SM presented excess phosphorus, whereas only GW was nitrogen limited considering the COD:N:P ratio of 100:5:1.0 recommended for aerobic treatment (Tchobanoglous et al. 2003). This limitation was not considered a concern in the granulation process since, on the contrary, it has been reported that nitrogen-limited conditions promote the formation of dense granular biomass (Arellano-Badillo et al. 2014).

Figure 2 shows the total COD in the influent (S0), at the beginning of the aeration stage (S1), the soluble and particulate COD (sCOD, pCOD) in the effluent and the MLSS (X) in both reactors.
Figure 2

Behavior of SBR fed with SM (a) and GW (b). S0 (●), SI (x), pCOD (○), sCOD (▴) and X (▪).

Figure 2

Behavior of SBR fed with SM (a) and GW (b). S0 (●), SI (x), pCOD (○), sCOD (▴) and X (▪).

The overall tCOD removal efficiency of SMr and GWr were 74.2% and 83.0%, respectively. In both reactors, the biomass with lower settling velocities than the minimum imposed by the settling time was washed out during the discharge stage, increasing the particulate COD (pCOD) and affecting the effluent quality. The amount of biomass purged was higher in effluents from SWr than those from GWr. As a result, the effluents from SWr showed a lower quality, with an average pCOD of 207 mg L−1, whereas effluents from GWr presented a pCOD of 77 mg L−1. Furthermore, the higher amount of biomass purged from SMr led to a lower average SRT of 7.5 d compared with that for GWr (9.4 d).

Granulation process

Figure 3 shows the evolution of the biomass settling properties (SVI and ZSV) during the experiment. For both reactors, three granulation periods of different lengths and behaviors considering the evolution of the settling properties were observed. As a result, the granulation times between SMr and GWr were different.
Figure 3

Evolution of SVI (●) and ZSV (x) in SMr (a) and GWr (b).

Figure 3

Evolution of SVI (●) and ZSV (x) in SMr (a) and GWr (b).

Period I was characterized by the washout of the slow settling biomass and the increase in the SVI up to approximately 300 mL g−1, alongside the formation of small (~0.2 mm) aggregates in both reactors. Consequently, during period II of SMr, the SVI showed an appreciable improvement, and during period III the biomass exhibited stable SVI values lower than 50 mL g−1, with a continuous increase in the ZSV up to values close to 18 m h−1 (Figure 3(a)).

In the case of GWr, during period II the SVI recovered down to 250 mL g−1 at a slower pace than the SMr, while the velocity remained at around 4 m h−1. However, in period III, the SVI and ZSV showed a substantial improvement, reaching values close to 80 mL g−1 and 9 m h−1, respectively (Figure 3(b)).

The continuous improvement in the SVI observed during Period II of SMr was the result of the formation of the first granules. Subsequently, in period III, the flocs were totally replaced by small size (50% of particles with 2.8 mm > D > 0.9 mm) compact granules (Figure 4(c) and 4(d)). For GWr, the poor SVI during the second period was due to the predominance of filamentous granules (Figure 4(a)), with a high size (80% of particles with D > 2.8 mm). Afterwards, during period III, the settling properties improved accordingly with an evolution in the granules’ morphology, which changed to more compact and non-filamentous granules (Figure 4(b)), as well as with an increase in the granule solids concentration (Cg) and the disintegration coefficient (δ%). As shown in Table 2, the compact, well-defined granules on day 253 exhibited better physical properties than the filamentous granules on day 139.
Table 2

Physical properties of the biomass from SMr and GWr on different days of period III

BiomassCg (g L1)δ (%)Predominant size Dd (mm)
GWr (d 139) 13.1 4.2 D > 4.8 
(d 253) 21.7 2.0 2.8 < D < 4.8 
SMr (d 139) 56.7 0.4 0.9 < D < 1.7 
(d 217) 31.4 0.6 1.7 < D < 2.8 
BiomassCg (g L1)δ (%)Predominant size Dd (mm)
GWr (d 139) 13.1 4.2 D > 4.8 
(d 253) 21.7 2.0 2.8 < D < 4.8 
SMr (d 139) 56.7 0.4 0.9 < D < 1.7 
(d 217) 31.4 0.6 1.7 < D < 2.8 
Figure 4

Morphology of granules from GWr (days 139 (a) and 264 (b)) and SMr (days 139 (c) and 224 (d)).

Figure 4

Morphology of granules from GWr (days 139 (a) and 264 (b)) and SMr (days 139 (c) and 224 (d)).

Despite the improvement attained in the characteristics of the GWr granules during period III, the physical properties of this biomass were never better than those of granules cultivated with SM, suggesting that the influent composition is an influencing factor on the biomass properties and morphology. In this case, the growth of filamentous granules in GWr was probably related to the presence of particulate and slowly biodegradable matter in GW, which must be hydrolyzed at the granules’ surface, leading to the existence of substrate micro-gradients and consequent biomass instability (De Kreuk et al. 2010). These results agree with those reported by Schwarzenbeck et al. (2005), De Kreuk & van Loosdrecht (2006) and Val del Rio et al. (2012), who reported the presence of filamentous granules in the treatment of complex wastewater with pollutants in soluble, colloidal and suspended forms, while the development of granules with high compactness (SVI) and a well-defined morphology has been mainly observed when SM is used (Beun et al. 2002; Liu & Tay 2015; Liu et al. 2016).

Although both reactors were operated with an anaerobic filling time of 10 min and 3.6 h of aeration, it is possible that the length of this anaerobic period would be enough to allow the absorption of the easily biodegradable compounds present in the SM by phosphate and glycogen accumulating organisms (PAO and GAO), which provide a high stability to the granular biomass (Pronk et al. 2015). These same short anaerobic times were probably not enough to achieve the absorption of the slowly biodegradable matter in the GWr, which needs to be hydrolyzed first. Thus, a longer anaerobic feeding time is necessary for hydrolysis of complex substances and its subsequent absorption and conversion into storage polymers. This condition can give PAO and GAO a competitive advantage over the filamentous organisms.

Analysis of Bx and its effect on the granulation process

During the experimentation, considerable fluctuations of the biomass content (X) in both reactors (Figure 2) were observed. These fluctuations, alongside the variation in the influent COD, led to operation at wide Bx ranges, from 0.4 to 7.2 kg COD kg VSS−1 d−1. When plotted as a function of X (Figure 5) it can be appreciated that the GWr was operated at higher Bx due to the low biomass content observed during most of the experiments (Figure 2), while the operation of SWr at higher X led to the application of lower Bx.
Figure 5

Correlation between Bx and X for SMr (●) and GWr (▴).

Figure 5

Correlation between Bx and X for SMr (●) and GWr (▴).

Considering that the operation of both SBRs was carried out by maintaining the same HRT and aeration conditions throughout the experimental period, it was thought that the evolution of the physical properties and morphology of the granules from GWr was enhanced by the reduction of the specific organic loading rate (Bx). The average Bx applied during the first 120 days was 4.4 kg COD kg VSS−1 d−1. Thereafter the Bx was reduced to an average 2.7 kg COD kg VSS−1 due to a decrease in the influent COD and the increase in the X during the last 80 days (Figure 2(b)). In the case of SMr, the average Bx applied was appreciably lower (0.84 kg COD kg VSS−1 d−1) due to the high X (4.5 g VSS L−1) kept during periods II and III, when the SVI was constant. Therefore, the biomass from the SMr was not subjected to the same stress by substrate overloads, and only the highest Bx values were applied during period I. Further information about the evolution of Bx with respect to X and the COD for both reactors is available in the supplementary material (available with the online version of this paper).

Effect of Bx on SVI and COD removal efficiency (η)

The Bx applied had a direct effect on the SVI (Figure 6(a)). In the case of SMr, a Bx lower than 2.0 kg VSS−1 d−1 did not adversely affect the SVI. However, the application of higher Bx resulted in an increasing trend of SVI, reaching values up to 750 ml g−1. In the GWr, the increase in the Bx also had a negative effect on the SVI, but at a lower rate than that exhibited by the SMr, suggesting a lower tolerance of the granular biomass cultivated with SM to the operation at high Bx. Consequently, in order to avoid the loss of compactness of the aerobic granules, it is recommended to apply a Bx lower than 2.0 kg COD kg VSS−1 d−1.
Figure 6

Effect of Bx on the SVI of the granular biomass (a), and on the tCOD removal efficiency (b) of SMr (●) and GWr (▴).

Figure 6

Effect of Bx on the SVI of the granular biomass (a), and on the tCOD removal efficiency (b) of SMr (●) and GWr (▴).

Alongside the structure and compactness of the biomass, the Bx also affected the COD removal efficiency (η) of both systems (Figure 6(b)). It was found that there is a range of Bx where the system is able to operate without affecting its performance. However, when the Bx is increased there is a point where the biomass is not able to withstand the organic load, leading to a fall in the efficiency of the system.

In this study, the best efficiencies of 80–90% for GWr and 65–90% for SMr, were obtained by applying a Bx lower than 2.0 kg COD kg VSS−1 d−1. In both cases, the operation at higher Bx had a negative effect on the η (Figure 6(b)). However a larger impact was observed in the SMr system, since in GWr the η decreased with a smaller slope, showing that the granular biomass grown using GW had a higher resistance to organic overloads.

In GWr, operation at high Bx led to the swelling and loss of compactness of the granules, which subsequently resulted in the flotation of a fraction of biomass and its washout, affecting the effluent quality. The biomass swelling at high Bx could be related to an increase in the oxygen diffusion limitations due to larger adsorption of particles at the granules’ surface, resulting in a sharp dissolved oxygen gradient in the granules’ structure, which, according to Mosquera-Corral et al. (2005), leads to a loss of stability in the granular biomass.

Regarding the SMr, the increase in Bx above 2.0 kg COD kg VSS−1 d−1 encouraged the biomass growth, from which a fraction corresponded to flocs with low ZSV which were continuously washed out from the reactor, also affecting the effluent’s quality and subsequently the η.

Kinetics of granular biomass

Specific activity of the aerobic granular biomass

During the 226 days of operation, 13 individual COD degradation kinetics were taken for GWr and five for SMr. The analysis of these data showed that in SMr the substrate was consumed at high rates, giving linear uptake dynamics (r2 = 0.94) and a high average degradation activity, with a qs of 14.5 kg COD kg VSS−1 d−1. In the case of GWr, the substrate was consumed at reduced rates and thus the uptake dynamics showed a lower linearity (r2 = 0.77) and degradation activity (qs = 7.4 kgCOD kg VSS−1 d−1).

The specific substrate uptake rate is compared against Bx in Figure 7(a). As can be observed, the qs of both reactors increased with the Bx. Moreover, at the same values of Bx, the qs of SMr was appreciably higher than that of GWr. This behavior was probably related to the difference in complexity between both kind of influents, since in the SM the carbon source was a readily biodegradable compound (sodium acetate), while in GW there are several hundred organic compounds in soluble, colloidal or solid form, from which a high fraction are slowly biodegradable (Eriksson et al. 2002). Therefore, feeding with a readily biodegradable influent leads to higher uptake rates than feeding with a complex influent.
Figure 7

Relationship between the specific loading and the specific uptake rate for SMr (●) and GWr (▴) (a). Lineweaver-Burk plot for granular growth in SMr (●) 1/μ = 1.079*1/S + 4.632 and GWr (▴)1/μ = 1.241*1/S + 8.744 (b).

Figure 7

Relationship between the specific loading and the specific uptake rate for SMr (●) and GWr (▴) (a). Lineweaver-Burk plot for granular growth in SMr (●) 1/μ = 1.079*1/S + 4.632 and GWr (▴)1/μ = 1.241*1/S + 8.744 (b).

It is considered that the substrate uptake kinetic parameters alongside the biomass settling properties are parameters that must be considered in the design of the cycles of the granular SBR. Specifically, the SVI and the ZSV could be used to define the settling time in an accurate way, avoiding excessive biomass washouts when the applied settling time is so short, or dead times by the application of long settling times. Furthermore, the substrate uptake kinetic parameters could be used to fix the time of the reaction stage just to allow the substrate degradation, avoiding long starvation periods. These conditions would result in the design of compact cycles and an increase in the volumetric capacity of the reactors.

Determination of Monod parameters

Kinetics of substrate degradation and cell growth using the Lineweaver-Burk method for both types of granular biomass were also analyzed (Figure 7(b)). The values of μmax and Ks indicate that granules from GWr were composed of slow growing microorganisms with a high substrate affinity, while SMr granules were formed by fast growing microorganisms with a lower substrate affinity (Table 3). This is in accordance with Chiesa & Irvine (1985), who reported that filamentous organisms tend to present higher substrate affinities and a lower μmax than the non-filamentous organisms.

Table 3

Kinetics parameters of granular biomass with different substrates

SystemSubstrateX (g VSS L1)Ks (g L1)μmax (h1)Yx (g VSS g COD1)Reference
Granular SBR SM (acetate) 4.53 0.22 < 0.24 < 0.26 0.16 < 0.22 < 0.33 0.28 < 0.50 < 0.72 This work 
GW (complex) 1.80 0.13 < 0.15 < 0.17 0.1 < 0.12 < 0.15 0.08 < 0.14 < 0.21 This work 
SM (acetate) 4.7 – – 0.23 Chen et al. (2008)  
SM (glucose) 8.0 0.27 – 0.18–0.25 Liu et al. (2005)  
SystemSubstrateX (g VSS L1)Ks (g L1)μmax (h1)Yx (g VSS g COD1)Reference
Granular SBR SM (acetate) 4.53 0.22 < 0.24 < 0.26 0.16 < 0.22 < 0.33 0.28 < 0.50 < 0.72 This work 
GW (complex) 1.80 0.13 < 0.15 < 0.17 0.1 < 0.12 < 0.15 0.08 < 0.14 < 0.21 This work 
SM (acetate) 4.7 – – 0.23 Chen et al. (2008)  
SM (glucose) 8.0 0.27 – 0.18–0.25 Liu et al. (2005)  

Confidence limits for Ks and μmax were calculated from Figure 7(b) at α = 0.1, with 11 degrees of freedom for GWr and 4 for SMr. Confidence limits of Yx were calculated with 3 degrees of freedom.

The Ks values of the granules cultivated in SMr using sodium acetate as a carbon source are similar to that reported by Liu et al. (2005) for granules cultivated using glucose. However, the Yx of the granules cultivated with sodium acetate is considerably higher. This difference can be attributed to the differences in the operation conditions between both experiments. Moreover, it is important to note that values of μmax for granular biomass cultivated with GW were not found, so the values obtained in this experiment cannot be compared with others.

It was found that the cell growth kinetics of the granular biomass play an important role in the performance of the reactors. It was observed that the cell mass yield coefficient (Yx) had an effect on the rate of solids purged from the system during the discharge stage. The higher the Yx, the higher the biomass produced during the reaction stage, which must be purged to maintain a stable value of X inside the reactor. In this study, the high Yx of the granules cultivated in SMr (Table 3) led to the washout of a great amount of solids, resulting in an average concentration in the effluents of 0.31 g TSS L−1. In contrast, the lower Yx of GW-grown granules produced a considerably lower content of solids in the effluents (0.073 g TSS L−1).

CONCLUSIONS

GW, despite being a nutritionally unbalanced medium, could support the growth of granular biomass with an SVI of 98 mL g−1 and a ZSV of 13 m h−1, allowing good removal rates and efficiencies (rs = 2.24 g COD L−1d−1 and ηCOD = 83%) at 30 °C, which is about the temperature these systems are designed for in house dwellings just after being generated.

The influent complexity and the specific organic loading rate determine the morphology and the physical and kinetic properties of the aerobic granular biomass. Feeding with a simple, readily biodegrable medium leads to the formation of fast-growing aerobic granular biomass, with a defined morphology and high settling properties, whereas with a complex, nutritionally unbalanced medium the formation of filamentous granules, with low settling properties and growth rates, is observed. However, it was found that reduction in the Bx induces an improvement in the biomass settling properties as a result of a reduction of filamentous microorganisms in the granules' structure. In this work, a reduction of 50% in the Bx led to an improvement of 40, and 30% in the SVI and ZSV, respectively. Thus, regarding the practical operation of granular systems with GW, it is recommended that the system is operated at low Bx by allowing the increase in X.

Probably, to avoid the formation of filamentous granules at high Bx, it is necessary to have a longer anaerobic feeding time, which allows the hydrolysis of all the complex substances and their subsequent absorption and conversion into storage polymers. This fact could result in the growth of PAO and GAO and in the consequential improvement in the SVI.

REFERENCES

REFERENCES
Adav
S. S.
Lee
D. J.
Show
K. Y.
Tay
J. H.
2008
Aerobic granular sludge: recent advances
.
Biotechnology Advances
26
(
5
),
411
423
.
APHA
1998
Standard Methods for the Examination of Water and Wastewater
, 19th edn.
American Public Health Association
,
Washington, DC
.
Arrojo
B.
Mosquera-Corral
A.
Garrido
J. M.
Méndez
R.
2004
Aerobic granulation with industrial wastewater in sequencing batch reactors
.
Water Research
38
(
14–15
),
3389
3399
.
Beun
J. J.
Hendriks
A.
van Loosdrecht
M. C. M.
Morgenroth
E.
Wilderer
P. A.
Heijnen
J. J.
1999
Aerobic granulation in a sequencing batch reactor
.
Water Research
33
(
10
),
2283
2290
.
Beun
J. J.
Hendriks
A.
van Loosdrecht
M. C. M.
Morgenroth
E.
Wilderer
P. A.
Heijnen
J. J.
2002
Aerobic granulation in a sequencing batch
.
Water Research
36
(
3
),
702
712
.
Chen
Y.
Jiang
W.
Liang
D. T.
Tay
J. H.
2008
Biodegradation and kinetics of aerobic granules under high organic loading rates in sequencing batch reactor
.
Applied Microbiology and Biotechnology
79
(
2
),
301
308
.
De Kreuk
M. K.
van Loosdrecht
M. C. M.
2006
Formation of aerobic granules with domestic sewage
.
Journal of Environmental Engineering
132
(
6
),
694
697
.
De Kreuk
M. K.
Kishida
N.
Tsuneda
S.
van Loosdrecht
M. C. M.
2010
Behavior of polymeric substrates in an aerobic granular sludge system
.
Water Research
44
(
20
),
5929
5938
.
Eriksson
E.
Auffarth
K.
Henze
M.
Ledin
A.
2002
Characteristics of grey wastewater
.
Urban Water
4
(
1
),
85
104
.
Hernández Leal
L.
Temmink
H.
Zeeman
G.
Buisman
C. J. N.
2010
Comparison of three systems for biological greywater treatment
.
Water
2
,
155
169
.
Hyun
K.
Choi
J.
Ki
D.
Park
J.
Ahn
S.
Oh
U.
Choung
Y. K.
2015
Bathroom wastewater treatment in constructed wetlands with planting, non-planting and aeration, non-aeration conditions
.
Desalination and Water Treatment
57
(
2
),
709
717
.
Laguna
A.
Ouattara
A.
Gonzalez
R. O.
Baron
O.
Fama
G.
El Mamouni
R.
Guiot
S.
Monroy
O.
Macarie
H.
1999
A simple and low cost technique for determining the granulometry of UASB reactor sludge
.
Water Science and Technology
40
(
8
),
1
8
.
Lamine
M.
Samaali
D.
Ghrabi
A.
2012
Greywater treatment in a submerged membrane bioreactor with gravitational filtration
.
Desalination and Water Treatment
46
(
1–3
),
182
187
.
Liu
L.
Wang
Z.
Yao
J.
Sun
X.
Cai
W.
2005
Investigation on the formation and kinetics of glucose-fed aerobic granular sludge
.
Enzyme and Microbial Technology
36
(
4
),
487
491
.
Morel
A.
Diener
S.
2006
Greywater Management in Low and Middle-Income Countries, Review of Different Treatment Systems for Households or Neighbourhoods
.
Swiss Federal Institute of Aquatic Science and Technology (Eawag)
.
Dubendorf
,
Switzerland
.
Mosquera-corral
A.
de Kreuk
M. K.
Heijnen
J. J.
van Loosdrecht
M. C. M.
2005
Effects of oxygen concentration on N-removal in an aerobic granular sludge reactor
.
Water Research
39
,
2676
2686
.
National Academies of Sciences, Engineering, and Medicine
2016
.
National Academies Press
.
Washington, DC
.
Pronk
M.
Abbas
B.
Al-zuhairy
S. H. K.
Kraan
R.
Kleerebezem
R.
van Loosdrecht
M. C. M.
2015
Effect and behaviour of different substrates in relation to the formation of aerobic granular sludge
.
Applied Microbiology Biotechnology
99
,
5257
5268
.
Schwarzenbeck
N.
Borges
J. M.
Wilderer
P. A.
2005
Treatment of dairy effluents in an aerobic granular sludge sequencing batch reactor
.
Applied Microbioly and Biotechnology
66
(6),
711
718
.
Tchobanoglous
G.
Franklin
L. B.
Stensel
H. D.
2003
Wastewater Engineering: Treatment and Reuse
. 4th edn.
Metcalf and Eddy Inc., New York, NY, USA
.
Travis
A.
Wiel-Shafran
A.
Weisbrod
N.
Adar
E.
Gross
A.
2010
Greywater reuse for irrigation: Effect on soil properties
.
Science of the Total Environment
408
(
12
),
2501
2508
.
Val del Río
A.
Figueroa
M.
Arrojo
B.
Mosquera-Corral
A.
Campos
J. L.
García-Toriello
G.
Méndez
R.
2012
Aerobic granular SBR systems applied to the treatment of industrial effluents
.
Journal of Environmental Management
95
,
S88
S92
.
Wang
S. G.
Liu
X. W.
Gong
W. X.
Gao
B. Y.
Zhang
D. H.
Yu
H. Q.
2007
Aerobic granulation with brewery wastewater in a sequencing batch reactor
.
Bioresource Technology
98
(
11
),
2142
2147
.

Supplementary data