In the process of the wastewater treatment, growth rate of microorganisms is related to consumption of the organic substances in the aeration reactors, and during this stabilization, new cells of the microorganisms are generated. This relationship between the consumption of the organic substances and the generation of new biomass creates the new biological, physical and, chemical balances. Mathematical equations or kinetics, are used to express these interactions [2]. Monad kinetic coefficient (Y, µmax, k, kd and, Ks), described and recommended the normal value of them to predict the microbial growth rate in ASP (Table 3).
Table 3
Monad kinetic coefficient in ASP
Kinetic coefficient | Parameters | Value | Reference |
k (g COD/g VSS.d) Ks (mg COD/L) kd (d− 1) Y (kg VSS/kg COD) µmax (d− 1) | Maximum specific substrate utilization rate Heterotrophic half-saturation substrate concentration Decay coefficient Yield coefficient Maximum specific microbial growth rate | 8–12 1–10 0.2 0.33 0.4-1.0 | [2] [25] [26] [27] [28] |
Monad equations are basic, widely and commonly model for express the relationship between microorganisms growth rate and substrate consumption in ASP, is simply as follows [26].
µ = \(\frac{({\mu }_{max} . S)}{{K}_{s}+S}\) (1)
Where, µ was the specific microorganism growth rate (d-1) and, S was substrate concentration (mg/L).
The rate of BOD removal or substrate consumption rate (\(\frac{ds}{dt})\)in ASP is estimated as follows:
µ. X = - Y \(\frac{ds}{dt}\) (2)
Where, X was MLVSS concentration (mg /L)
For estimated k, kd and, Ks it is necessary to use linear regression equation in statistically software, such as, SPSS (version 26). In this software, the values of variables Ks and k from plots \(({X}_{Ѳ}/({S}_{0}-S)\) versus \(\left(\frac{1}{S}\right)\) will be obtained and, Y and, kd from plots \(\left(\frac{1}{{Ѳ}_{c}}\right)\) versus \(\left({S}_{0}-\frac{S}{XѲ}\right)\)can be calculated.
At the beginning of the systems operation processes, the mean concentration of BOD5 (S0) was 145.3 mg/L. Since the change of BOD5 concentration had the original work on the other parameters, we had to use the mean of them (149 mg/L) for all series of the reactors.
3.1. Application of SMFs on ASM 1
In ASP, the aeration reactors have a basic role on the wastewater treatment procedure. Nowadays, use of an aeration diffuser is the most popular method than surface aeration, while it has higher efficiency [29]. Nevertheless, 50–90% of energy consuming in WWTPs dedicated to the aeration of sewage. Therefore, it seems logical that any processes that can reduce the aeration costs or increase the efficiency of the aeration process could reduce the operating and maintenance costs of the system [30, 31].
When the SMFs applied to the aeration reactor, changes of the operational and functional parameters over time happened. To summarize the data collected during one month of using the systems, every 5 days' data collected based on BOD5 is illustrated in Table 4.
Table 4
Basic parameters of the operational and functional CMAS processes in ASM 1
Time (d) | Mean of S0 (mg/L) | S (mg/L) | Ѳc (d) | X (mg/L) | S0-S (mg/L) | XѲ (mg/L.d) | F/M (mg/L) |
1 | 149 | 13.5 | 15.0 | 1800 | 135.5 | 225.00 | 0.66 |
5 | 149 | 15.8 | 14.3 | 1860 | 133.2 | 232.50 | 0.64 |
10 | 149 | 20.2 | 13.1 | 2005 | 128.8 | 250.63 | 0.59 |
15 | 149 | 24.1 | 11.3 | 2155 | 124.9 | 269.38 | 0.55 |
20 | 149 | 28.9 | 9.4 | 2320 | 120.1 | 290.00 | 0.51 |
25 | 149 | 33.4 | 7.8 | 2500 | 115.8 | 312.50 | 0.48 |
30 | 149 | 39.1 | 5.4 | 2700 | 109.9 | 337.50 | 0.44 |
The concentration of BOD5 (S0) in the effluent of secondary clarifier during the operation, were increased (65%). It is important to note that the steady state of the system, where the concentration of MLVSS is 2500 (mg/L), took place on the 25th day of the operation. The concentration of MLVSS (mg/L) or biomass in the aeration reactors improved (33%) from 1800 (mg/L) related to seeding the reactor at the beginning of the start-up the system, to 2700 on the 30th day.
According to Monod model, by use of ASM 1 the biokinetic coefficients k and Ks was related to Fig. 2 and, kd, Y and, µmax were estimated based on the results extracted from the Fig. 3.
A linear regression was a slope of the graph when estimated of k and Ks considered. However, a quadratic equation obtained for yield coefficient and, maximum specific microbial growth rate was based on the results of Fig. 3.
3.2. Application of SMFs on ASM 2
By the application of 15 mT intensity of SMFs on the clarifier reactor for 1 hour daily, during one month of the operation of CMAS process, the change of the functional and operational parameters were obtained (Table 5)..
Table 5
The functional and operational parameters by application of the SMFs on ASM 2
Time (d) | Mean of S0 (mg/L) | S (mg/L) | Ѳc (d) | X (mg/L) | S0-S (mg/L) | XѲ (mg/L.d) | F/M (mg/L) |
1 | 149 | 27.5 | 15.0 | 1800 | 121.5 | 225.00 | 0.66 |
5 | 149 | 28.6 | 14.1 | 1899 | 120.4 | 237.38 | 0.63 |
10 | 149 | 31 | 12.9 | 2003 | 118.0 | 250.38 | 0.60 |
15 | 149 | 33.2 | 11.0 | 2142 | 115.8 | 267.75 | 0.56 |
20 | 149 | 37 | 9.0 | 2286 | 112.0 | 287.75 | 0.52 |
25 | 149 | 39.5 | 7.2 | 2404 | 109.5 | 300.50 | 0.50 |
30 | 149 | 41.8 | 5.0 | 2515 | 107.2 | 314.38 | 0.47 |
The intercept and slope of the linearized graphs from Figs. 4 and 5 were used to calculate the values of Monad kinetic coefficients.
As it is clear, there was a linear correlation between data to calculate the value of k and Ks. However, to estimate the amount of kd, µmax and, Y a second order reaction was established instead of a first order relationship. Furthermore, high R2 values (R2 > 0.9) indicated the suitability of the model to fit the data.
3.3. Application of SMFs on the ASM 3
The sludge returning system in this study was a peristaltic pump that got sludge (5 mL/min) from the bottom of the clarifier and, pumping into the aeration reactors. The results of the applied the SMFs on the sludge returning system for determine the operational and, functional parameters is illustrated in Table 6.
Table 6
Change of operational and functional parameters by application of the SMFs on ASM 3
Time (d) | Mean of S0 in (mg/L) | S out (mg/L) | Ѳc (d) | X (mg/L) | S0-S (mg/L) | XѲ (mg/L.d) | F/M (mg/L) |
1 | 149 | 33 | 15 | 1800 | 116 | 225.00 | 0.66 |
5 | 149 | 34.8 | 14.1 | 1865 | 114.2 | 233.13 | 0.64 |
10 | 149 | 37 | 12.9 | 2005 | 112 | 250.63 | 0.59 |
15 | 149 | 39.4 | 11.0 | 2180 | 109.6 | 272.50 | 0.55 |
20 | 149 | 41.6 | 9.0 | 2286 | 107.4 | 285.75 | 0.52 |
25 | 149 | 43.3 | 7.2 | 2403 | 105.7 | 300.38 | 0.50 |
30 | 149 | 45.8 | 5.0 | 2510 | 103.2 | 313.75 | 0.47 |
In the case samples, where the return sludge exposed to SMFs, the efficiency of the process in removing the organic substances entering the system has decreased compared to the previous cases (ASM1 & ASM 2). The key point in the discussion of applying the SMFs is the contact or exposure time. It seems that the rapid passage of the return sludge (5 ml/min) through the SMFs did not provide the right opportunity to apply remarkable effects on the microorganisms in the flocs.
To estimate five main Monad kinetic coefficients, as it was used in the previous examples, it is necessary to use the graphs and that is depicted in Figs. 6 and 7.
The degree of the reaction for the calculation of k and, Ks was in the first order and for the calculation of the kd, Y and, µmax was the second order. The high value of R2 also indicated the high correlation and fit of the line equation with the collected data.
3.4. Comparison of the Monad coefficients in all series of systems
The data related to biokinetic coefficients extracted from the use of 15 mT SMFs in three location of ASP is presented in Table 7.
Table 7
The biokinetic coefficients data
Model of the systems | k (d− 1) | Ks (mg/L) | kd (d− 1) | Y (d− 1) | µmax (d− 1) |
ASM 1 | 0.667 | 2.67 | 0.070 | 0.29 | 0.197 |
ASM 2 | 0.649 | 57.11 | 0.054 | 0.5 | 0.324 |
ASM 3 | 0.515 | 73.8 | 0.516 | 0.6 | 0.309 |
One main parameter for evaluation of aerobic microbial activity is Ks. A high value of Ks shows the activeness of ASP [32, 33]. It must be mentioned that the structures of the organic matters, scale, configuration and, type of the reactor are well-known factors that have influence on the amount of Ks [27].
Relationship between substrate consuming by microorganisms and Ks is an inverse correlation. When the concentration of available substrate in the culture or wastewater is high, then completion of microorganisms to receive food is in the low range and, a value of Ks is low [34]. Organism variety, flocs structures and, mixing conditions are three main factors that have effect on the Ks value [34]. However, the active attribute of cell membrane to diffusion of substrate into the bacteria is a mechanism that has main effect on the value of Ks [35]. Lebkowska et al. reported that the SMFs have this properties to increase the permeability of the membranes [36]. Therefore, the low range of Ks (2.67) in the application of SMFs in the aeration reactors showed that the15 mT intensity of SMFs for one hour daily, have been effective in the reduce value of Ks, rather than indicated of 95.3% and 96.4% reduction when compared to the application of SMFs in clarifier reactors and, sludge returning system, respectively. It is interesting that when the SMFs were applied in the clarifier reactor, this KS value is 29.2% lower than use of SMFs on sludge returning system.
The value of Ks in the domestic wastewater has been between 10 and 180 (mg/L) in ASP when the mechanical aeration systems are the method for the agitation and supply oxygen [37]. In our study, the value of Ks when the SMFs applied in the aeration reactor was 7.33 (mg/L) less than the low range of recommended. However, this value for application of SMFs on the clarifier reactor (57.11mg/L) and, the sludge returning system (73.8 mg/L) were in the recommended ranges.
Y as respirometric test is a main ratio to calculate the rate of substrate utilization, biomass concentration and, biodegradable fraction of substrate. Some of the researches recommended this parameter must be less than 0.2 mg COD per mg MLVSS or 0.58–0.61 (mg cell/mg COD) [38]. Although high ratio of Y can indicate a high percentage of biodegradability of the organic materials, furthermore, it requires a large amount of energy to aerate the wastewater and, increase microbial growth in order to more consume the substrate, finally [39]. µmax or maximum specific growth rate is related to concentration of substrate. When the low concentration of substrate is limited factor, affinity constant or Ks (K-strategists) is used instead of µmax. In other words, it can be said that a half the µmax is equal to Ks and, Ks is the main parameters that has fundamental effect on the microbial growth rate.
The value of correlation coefficients (R2) in all models were between 0.9767 and, 0.9962 that represents Monad model for experimental data was appropriate. A Noor et al. reported that the value 0.9914 for R2 in their bench-scale model of extended aeration activated sludge is suitable and well fit model [40].
3.4. Effect of SMFs on the concentration and percentage of the trace elements
The question raised here is whether changes in the content of the chemical elements in the sludge occur when the SMFs is applied or not? Moreover, know the fraction of elements concentration in the generated sludge is important. Effect of the treatment processes on the concentration of elements on the content and, possibility of moving elements from one phase to another during the processes can be considerable [41]. Oxidation-reduction potential has main role on the mobility of elements. The microorganisms in biological processes participate in this discussion and cause the release of metals in solutions [42]. In addition, other physical and chemical processes have inherent function in changing the concentration of trace elements in the solution and the environment [43].
Application of 15 mT intensity of SMFs for 1 hour on the ASM 1, ASM 2 and, ASM 3 has affected on the concentration and percentage distribution of the trace elements of dried sludge. When the results of EDS (Energy dispersive X-ray spectroscopy) analyses in those three location of applied SMFs compared to each other (Fig. 8) by the atomic weight percent, C, O and, Si were in the first rank, respectively, as illustrated in Table 8.
Table 8
The mean atomic weight percent of trace elements in the dried sludge
Trace element | | | The atomic weight percent (mean) |
Magnetization | |
| ASM 1 | ASM 2 | ASM 3 | USEPA |
C | Dia* | 53.33 | 56.98 | 54.55 | 30.77 |
O | Para** | 23.33 | 21.37 | 22.53 | 20.43 |
Si | Para | 10.44 | 9.24 | 10.37 | 5.13 |
Ca | Para | 2.97 | 2.04 | 1.88 | 2.75 |
Na | Para | 2.93 | 2.57 | 3.07 | - |
N | Dia | 5.15 | 3.75 | 3.70 | 3.97 |
P | Dia | 0.66 | 1.30 | 0.97 | 1.76 |
Mg | Para | 0.60 | 0.92 | 0.95 | - |
Al | Para | 0.43 | 0.74 | 0.75 | 1.10 |
S | Dia | 0.16 | 0.61 | 0.61 | 1.18 |
K | Para | ND**** | 0.28 | 0.26 | - |
Fe | Ferro*** | ND | 0.19 | 0.16 | 1.42 |
*Dia = diamagnetic |
**Para = paramagnetic |
***Ferro = ferromagnetic |
****N.D = non-detected |
Use of SMFs on the change of the atomic weight percent in ASM 1 when compared to other samples (ASM 2 and ASM 3) caused a slight increase in elements such as Si and Ca. However, the changes for N was statistically significant. The atomic weight percent of Na, N, P, Mg, Al and, S in ASM 1 was lower than the other series of reactors. An exceptional element in this list is oxygen, whose concentration was adjusted artificially in the aeration reactors in all series of reactors (2–3 mg/L). Other interesting cases were potassium and iron, that their concentrations could not be detected in ASM 1.
T. Cloete et al. analyzed the cell clusters for detected weight range of the trace elements in AS process. They reported that Na (0.3–1.5%), Mg (16.9–18.7%), P (58.4–61.4%), S (0.2–1.7%), K (17.1–20.5%) were the weight of samples. In this study, for Al, Si, Ca and, Fe no data provided [44].
Trace elements concentration (weight percent) in the sludge of three WWTPs in Swaziland analyzed by Joseph S. Mtshali et al. The range of the trace elements in this study for Na (0.08%), Mg (0.25%), P ( 1.6%), K (0.19%), Fe (2.25%), Si (0.05%) and, Ca (0.67%) was reported. The weight percent for Al in one sit was 0.45% however, this weight percent concentration in other two sites was zero based on the average value [45].
According to U.S.EPA report on the elemental analyses of samples from the targeted national sewage sludge survey, the following median percent of elements concentration in sewage sludge for quality control recommended: C (30.77%), O (20.43%), Si (5.13%), Ca (2.75%), N (3.97%), P (1.765%), Al (1.10%), S (1.18%) and, Fe (1.42%).
In all samples of our study the mean concentration of C was higher than the recommended concentration. Since the fundamental of the organic matters is C and, the higher generation of biomass was happened in all reactors, the higher concentration of C was not far from expected. Higher concentration of Si in all samples were related to combined sewer system of the Sanandaj.
Other mean atomic weight percent of the trace elements more and less were around recommended concentration. The key point that should be noted that in the chemical analysis is that the type of analysis method can affect the measured values.