Use of Mushroom for Removing Wastewater Turbidity: Characterization and Optimization Study

doi:10.21203/rs.3.rs-4524183/v1

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Use of Mushroom for Removing Wastewater Turbidity: Characterization and Optimization Study

https://doi.org/10.21203/rs.3.rs-4524183/v1

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In the present study, a commercially available mushroom is used as a natural flocculent at different dosages to treat a synthetic suspension containing different concentrations of local clay. Response Surface Methodology (RSM) is used to optimize the values of operating parameters based on residual turbidity and turbidity removal percentage reduction. The highest percent reduction in water turbidity was obtained at a pH of 6.7. The lowest value for residual turbidity (11.1 NTU) is achieved by a clay suspension with a concentration of 1000 ppm, and the highest value for residual turbidity (22 NTU) is achieved by a clay suspension with a concentration of 6000 ppm. The optimum values of mushroom dose were 0.2 and 0.1 g for clay concentrations of 4000 and 5000 ppm, respectively, after a time of 120 minutes of settling. Response Surface Methodology (RSM) is used to optimize the values of the operating parameters and the results of the model fitted well with the experimental results.

Environmental Engineering

Flocculation

Optimization

Turbidity

Mushroom

Coagulation

Mushroom is used on the removal of turbidity of wastewater and water with residual turbidity of 11.1 was obtained
The response Surface Methodology (RSM) is used to determine the optimum values for the operating parameters.
Optimum value of Mushroom dose was 0.2 and 0.1 g/L for clay suspension with concentrations 4000 and 5000 ppm, respectively.

Turbidity is considered a problem in wastewater treatment. Turbidity in water resources is caused by suspended solids such as silt, sand, clay, organic or inorganic matter, colored organic wastes, and microscopic organisms [1]. Turbid water appears as cloudy or muddy. pH is one of the most important parameters affecting turbidity treatment in wastewater [2].Turbidity is measured in nephelometric turbidity units (NTU), which allow the influence of suspended solids on light transmission in water to be measured [3]. The unit of total suspended solids in mg/L is a measure of the concentration of suspended solids in a selected sample [4]. The coagulation/flocculation process is important to reduce turbidity caused by suspended solids and colloidal materials, and it takes place by adding a coagulant [5, 6]. Coagulants are chemicals with a charge opposite to that of suspended solids [7]. The addition of a coagulant to turbid water helps neutralize the negative charges; which are mostly found on non-stable solids such as clay and colored organic matter [8]. The step following coagulation is called flocculation and is a quiescent mixing phase in which the particle size increases from submicroscopic microflocs to visible suspended particles. In case of overmixing, coagulation is not affected, but in case of undermixing, this step remains incomplete [9, 10]. Visible flocs, called pin flocs, are formed when microfloc particles collide and form bonds that hold them together [11, 12]. The sedimentation step occurs when the flocs have reached their strength and optimal size [13]. Various flocculants and coagulants are used in the treatment of turbid water. These substances are divided into two categories: inorganic coagulants (aluminium and iron salts) and organic polymers (polyacrylamide derivatives and polyethylene amine) [14]. Chemical coagulants are preferred due to their low cost, availability, and high efficiency. On the other hand, their use has numerous environmental and health-related shortcomings, such as contamination of water with metals, low biodegradability, and generation of large amounts of sludge [15].

Metals cause water pollution that negatively affects human health, such as aluminum salts that cause Alzheimer's disease. The presence of acrylamide oligomers, which contain the monomer acrylamide, is carcinogenic to humans [16]. In recent years, processes have been carried out to treat turbid water with natural coagulants and flocculants; which are called bio-coagulants and bio-flocculants due to their biological nature and biodegradability [17, 18]. Biocoagulant polymers such as starches, celluloses, alginates, gums, and many plant derivatives [19–22] polyacrylamide-based products such as nonionic polyacrylamides, anionic acrylamide-acrylate copolymers, partially hydrolyzed polyacrylamides, cationic dimethyldiallyl ammonium chlorides, and copolymers of the dimethyldiallyl ammonium ion with acrylamide have been used as flocculants in industrial processes [16]. It offers many advantages such as the ability to form large, compact and strong flocs and better settling performance. The use of biocoagulants has many advantages such as reducing the use of chemicals, sludge production, and cost [23]. In order to reduce the cost of water treatment and reduce the risk resulting from the remaining additional materials, many studies have been conducted to optimize the number of materials used [24].

In the present study, Mushroom was used as a biocoagulant/flocculant to affect the clarification of a clay suspension under different operating conditions. Mushroom is a fast growing plant; which grows on the banks of River Nile, Egypt and near the leakage areas of water disposal pipes. Thus, it has no economic value. Besides, it has a high percentage of protein thus; it could be a viable option for use as a coagulant/ flocculent.

Different parameters are studied and the experimental results obtained were used to find a relation between the suitable dose of coagulant which fits a clay suspension with a specified concentration. This helps in predicting the exact Mushroom dose; thus reducing the amount of sludge produced. Using Response Surface Methodology (RSM), a model is created to investigate and predict the optimal values for the operating conditions that result in maximum values for water clarity.

2.1. Materials

In the present study, locally available River Nile clay and commercial mushroom is obtained from local market. Sulfuric acid (H₂SO₄ 75%, Sigma Aldrich) and sodium hydroxide (NaOH 25%, Sigma Aldrich) are used for pH control.

2.2. Methodology:

2.2.1 Preparation of Mushroom powder:

The fresh mushroom is washed with distilled water, sliced and air dried at 60^OC till constant weight (it takes about 20 hours). The dried material is ground to a fine powder in a kitchen blender and then sieved to obtain particles of mesh size 325 (openings 45 µm). Weighed quantities of fungi are used as coagulants/flocculants at the required concentration in a series of tests. Scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD) are used to characterize the fine Mushroom powder.

2.2.2 Preparation of clay suspension and experimental procedure:

A weighed clay mass is added to one liter of distilled water and the suspension is then mixed at 300 rpm for 60 minutes to achieve uniform dispersion of the clay particles. To complete the hydration of the clay materials, the suspension is allowed to settle for about 24 hours. At the time of the experiment, the prepared suspension is shaken well; the flocculent is added according to the required amount, stirred at high speed of 150 rpm for 3 minutes and then at low speed of 45 rpm for 12 minutes (Fig. 4), and analyzed using the turbidity meter (model TU − 2016).

2.2.3. Experimental design and data analysis:

Response Surface Methodology (RSM) was used to improve process responses (residual turbidity and turbidity reduction) using different slurry concentrations (4000 and 5000 ppm). A central (face-centered) complex experimental design was conducted with three coded levels resulting in nine experimental runs to evaluate the effects of the independent process variables with mushroom dose (0.2, 0.3, 0.4 g/L and 0.1, 0.2, 0.3 g/L for 4000 and 5000 ppm clay suspensions, respectively and time (60, 90, 120 min). The experimental process variables and design levels are listed in Table 1. Design-Expert 10.0.1 software was used for statistical analysis, modeling and optimization.

Table 1

Experimental range and levels of the independent process variables
Independent variable		Symbol	Range and levels
Independent variable		Symbol	-1	0	+ 1
Mushroom dose (g/l)	at 4000 ppm clay	A	0.2	0.3	0.4
Mushroom dose (g/l)	at 5000 ppm clay	A	0.1	0.2	0.3
Time (min)		B	60	90	120

2.1. Materials Characterization:

3.1.1. Characterization of Mushroom and Clay:

Mushroom is a natural, effortlessly obtainable and environmentally friendly product rich in vegetable proteins, chitin and enormous amounts of vitamins. Mushroom is a macro Mushroom with a characteristic fruit shape. Mushroom flakes have a number of advantages, such as nontoxicity, abundance of resources, cheapness, and biodegradability (Fig. 1) [25].

Clay deposits generally exist in many geological regions in the Nile Valley and Delta of Egypt. Many industries, such as ceramics, refractory and Portland cement industries, use clay deposits as an essential part of their production processes. PA analytical Spectrometer (Axios Sequential WD-XRF, 2005) was used to determine the chemical composition of clay. The main constituents of the clay sample are: CaO (15.5%), silica (21.25%) and alumina (7.52%). The percentage of other components is Fe₂O₃ (1.95), TiO2 (0.23), MgO (0.80) and MnO (0.03). In addition, high values of SO₃ (4.83%) and P₂O₅ (4.54%) are indicated, due to the presence of gypsum and apatite. The loss on ignition (LOI) of the clay sample was 42.90%. X-ray diffraction (XRD) analysis of the clay sample was performed using a Philips X-ray diffractometer (Mod. PW 1390). The XRD result indicates that the main constituents of the sample are goethite and gypsum.

3.1.2. SEM, TEM and XRD analysis:

The chitin structure in Mushroom appears as several fine, loosely connected sheets. The auricle powder consisted of a heterogeneous mixture of amorphous fragments with a size distribution between 1 and 50 µm (Fig. 2a).

Analysis of TEM in Fig. 2b revealed that the fungal powders had very similar internal structures, including circular units with a dense cell wall composed of multiple concentric layers embedded in a heterogeneous mass of material with varying textures. The darker areas in this Mushroom were associated with material that was randomly distributed across the section, although it was observed that the inner layers of the circular units also had high electron density (Fig. 2b), suggesting that melanin may not have a systematic spreading form in the Mushroom.

The crystallinity of the Mushroom is determined by XRD analysis. The XRD pattern (Fig. 3a) showed lignocellulose peaks at 2θ = 20° and 2θ = 36°, with the peak at 2θ° closer to 20° being crystalline, while the peak at 2θ° = 36° had an amorphous structure [26].

3.2. Experimental Results:

3.2.1. Effect of pH value:

At different contact times (10-120min), pH ranges (3–10) were used to determine the effect of pH in the clarification process at a clay suspension of 4000 ppm and a fungal concentration of 0.4 g/L. Figure 5 shows that turbidity removal increases with increasing pH up to pH 6.7 and then decreases. Results show that the minimum values of residual turbidity are obtained at pH 6.7, followed by pH 5 and 8, while the least removal of turbidity is obtained at pH 3 and pH 10. The percentage reduction in residual turbidity increased from 59.5% at pH 5 to 60% at pH 6.7 after 120 minutes, which was due to the increase in electrostatic charges on the surface of Mushroom (+ ve) and clay (-ve) as pH increased up to pH 6.7. The percentage of residual turbidity decreased to 57.4% at pH 10. This is because when pH value was risen then the particles tended to acquire more negative charge. This leads to a zero or negative values for Zeta potential. Then the particles in suspension will tend to repel each other and there will be no tendency for the particles to come together [27, 28]. Thus, neutral pH is recommended in the clarification process rather than the alkaline or highly acidic medium. Thus, the following experiments of the study are carried out at a pH value of 6.7.

Mushroom has a high content of amine groups, which provide a cationic charge on the fungal surface at acidic and natural pH. The electrostatic attraction between the cationic charge of Mushroom and the suspended solids weakens the colloidal suspension, promoting the formation of bulky, rapidly settling flocs, which then flocculate. The positive charges of the long-chain polymer of mushroom can efficiently coagulate the negative charges of both the natural particles and the colloidal materials by one or more of the following mechanisms: Sorption, neutralization, and hydrophobic flocculation [29].

3.2.2. Effect of flocculent dose

The effect of flocculent dosage on residual and percent reduction in turbidity was studied at a clay content of 4000 ppm and pH of 6.7 with different Mushroom concentrations (0.2, 0.4, 0.6, 0.8, 1.0, and 1.2 g/L). Figure 6a shows that the best residual turbidity of 11.2 NTU is obtained at a flocculent dose of 0.4 g/L after 120 minutes, while the worst results are obtained using a flocculent dose of 0.2 g/L under the same conditions. The flocculent doses of 0.6, 0.8 and 1.0 g/L gave very similar results. In general, Mushroom is rapidly hydrolyzed in water to form a series of cationic species that can be absorbed by negatively charged suspended particles and neutralize their charge. This is one of the mechanisms by which particles can lose their ability to distribute in solution; which promotes flocculation [30]. Excessive dosages can interfere with turbidity reduction, so careful control of coagulant dosage should be performed in water treatment plants.

Figure 6b shows that a flocculent dose of 0.4 g/L achieves a maximum percent reduction in turbidity of 96.5%, while a flocculent dose of 0.2 g/L achieves a lower percent reduction in turbidity of 93.4%. This means that this concentration of flocculent was not sufficient to cause the deposition of all suspended solids in a reasonable time [31].

3.2.3. Effect of clay concentration:

Effect of clay concentration in absence of flocculent:

Clay suspensions with concentrations between 1000 and 6000 ppm were used to determine the effect of clay concentration on residual turbidity at different settling times (Fig. 7a). This figure shows lower residual turbidity for clay suspensions at 1000 ppm, while higher residual turbidity is observed for suspensions at 6000 ppm. The residual turbidity of clay concentrations 1000, 2000, 3000, 4000, 5000 and 6000 ppm were 16.2, 19.1, 20.1, 24.7, 25.0 and 32.0 NTU, respectively. Therefore, the growth of flocs is promoted with higher clay concentration [29, 16]. Figure 6b shows the percentage reduction of turbidity after 120 minutes for different concentrations of clay suspensions. The maximum percentage of reduction reached 96.5% for the suspension with clay concentration of 4000 ppm, followed by the suspensions with 5000 and 6000 ppm clay concentration. The lowest percentage of reduction was 82.8% for clay suspension with 2000 ppm.

Effect of clay concentration using flocculent (0.4g/l):

Figure 8a shows the change of residual turbidity with settling time under the conditions of adding 0.4 g/L of Mushroom flocculent in the different clay concentrations at pH 6.7. The residual turbidity drops steeply for the clay concentrations 5000 and 6000 ppm after 60 minutes of settling time, after which the change in residual turbidity is very small. The results show that the lowest residual turbidity of 11.1 NTU is observed for the 1000 ppm clay suspension, while the highest value of 22 NTU is observed at 6000 ppm. Therefore, the effect of flocculent is more pronounced at lower suspension concentrations. The slope of the straight line appears to become smaller (lower turbidity reduction) as the clay suspension concentration increases, which is due to the lower influence of agglomerated particles in clearing other suspended particles. Figure 8b shows that the maximum percent reduction in turbidity is 96.5%

3.2.4. Effect of ratio of flocculent dose to clay suspension concentration:

Table 2 shows that a maximum percent reduction in turbidity (96.5%) was achieved when the ratio of flocculent (Mushroom) to clay in suspension was 1:10. Overdosing of the flocculent results in a slight decrease in turbidity removal efficiency, which is due to charge reversal or steric stabilization; where the flocculent produce strong repulsion between particles in the suspension. In addition, overdosing destroys the electrostatic bridge between clay particles and Mushroom, which leads to an increase in residual turbidity [32].

Table 2

Percentage reduction in turbidity with different ratios of Clay/Mushroom for clay concentration 4000 ppm
Flocculent dose, g/l	Ratio (Mushroom/Clay)	Percentage reduction in turbidity %
0.2	1:20	83.4
0.4	1:10	96.5
0.6	1:6.6	94.5
0.8	1:5	94.4
1.0	1:4	94.3
1.0	1:3.3	94.1

3.2.5. Statistical Modeling

The response surface model of the residual turbidity and percentage reduction in turbidity:

The experimental values for residual turbidity and percent reduction in turbidity responses at the design points and for all three noncoding independent variables are shown in Table 3. The experimental data were analyzed and the following regression equations were obtained with respect to the coded factors for the expected values of the initial responses for both models developed (at 4000 and 5000 ppm clay concentration).

For 4000 ppm clay concentration the model is:

Residual Turbidity = + 18.99 + 2.7A – 2.1B + 0.62AB – 2.41A² + 0.22B²

%Reduction in turbidity = + 94.08–0.83A + 0.67B -0.2AB + 0.73A² − 0.067B²

For 5000 ppm clay concentration the model is:

Residual Turbidity = + 17.78 + 0.56A – 0.98B + 0.29AB − 9.12A² – 0.61B²

%Reduction in turbidity = + 95.47–0.15A + 0.25B -0.073AB + 2.35A² + 0.15B²

Figures 9 and 10 show that the expected values for the responses to turbidity removal (residual turbidity and percent turbidity reduction) are significantly close to the actual values for both models developed at a clay concentration of 4000 (Fig. 9a, b) and 5000 ppm (Fig. 10a, b); confirming the consistency of the models created to establish a relationship between the independent process variables (mushroom dose and time) and the responses.

Table 3

Experimental design for turbidity removal process
Run	Mushroom dose (g/l)		Time (min)	Residual Turbidity (NTU)		%Reduction in Turbidity
Run	at 4000 ppm clay	at 5000 ppm clay	Time (min)	at 4000 ppm clay	at 5000 ppm clay	at 4000 ppm clay	at 5000 ppm clay
1	0.3	0.3	60	21.1	9.51	93.4	97.59
2	0.2	0.2	60	16.9	17.6	94.7	95.5
3	0.4	0.3	90	19.25	9.4	94	97.6
4	0.4	0.3	120	17.9	7.5	94.4	98.1
5	0.2	0.2	90	14	17.6	95.6	95.5
6	0.2	0.2	120	11.2	16.9	96.5	95.7
7	0.3	0.1	90	18.9	8.09	94.1	98
8	0.3	0.1	120	17.4	5.9	94.6	98.5
9	0.4	0.1	60	21.12	9.09	93.4	97.7

The statistical significance of the models for residual turbidity and percent reduction in turbidity was evaluated using ANOVA (Table 4). The data in the table show that the F values of the expected models at a clay concentration of 4000 ppm are 223.06 and 272.62 for residual turbidity and percent reduction in turbidity, respectively. The Model F-value of 223.06 and 272.62 imply that there is only a 0.05% and 0.03% chance, respectively that an F-value this large could occur due to noise. This indicates that both models are important. In addition, the F-values of the models for 5000 ppm clay concentration were 80.62 and 88.92 for residual turbidity and percent reduction in turbidity, respectively. The F-value of 80.62 and 88.92 imply that there is only a 0.21% and 0.19% chance, respectively that an F-value this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate that model terms are significant. The R-squared values for the four model equations (0.997, 0.999 and 0.993) indicate that the fit of the quadratic models is high.

Table 4

ANOVA for the predicted quadratic models of the turbidity removal responses
Source		Sum of squares	Mean square	F value	p-value prob > F	Standard Deviation	Squared-R
At 4000 ppm clay model	Residual Turbidity	83.32	16.66	223.06	0.0005	0.27	0.997
At 4000 ppm clay model	% Reduction	8.08	1.62	272.62	0.0003	0.077	0.999
At 5000 ppm clay model	Residual Turbidity	175.04	35.01	80.62	0.0021	0.66	0.993
At 5000 ppm clay model	% Reduction	11.61	2.32	88.92	0.0019	0.16	0.993

3.2.6. Effect of process parameters:

Effect of coagulant dose:

Coagulant dosage is one of the most important factors considered in determining the optimal performance state of coagulants in coagulation and flocculation. Insufficient or excessive dosages can result in poor flocculation performance. For this reason, it is essential to determine the optimal dose to reduce dosing costs and sludge formation and to achieve optimal treatment performance [33, 34]. In this work, the optimal dose of Mushroom (0.4 g/L) was the lowest dose required and it resulted in the maximum turbidity removal. The best performance of the process was at pH 6–7, and the coagulation efficiency of mushroom remained almost constant in the dose range of 0.6-1 g/L. Figure 11 shows the reaction surface curves for both developed models (4000 and 5000 ppm clay concentration). The response surface curves were constructed to show the effects of the independent variables (Mushroom dose and time) on the dependent variables (residual turbidity and percent turbidity reduction) for the four models developed.

3.2.7. Optimization of the operating parameters:

The optimal operating parameters for the turbidity removal process were determined to maximize the percent reduction in turbidity based on the appropriately developed mathematical models. The optimal values for the 4000 and 5000 ppm clay concentration models were as follows: Mushroom dose, 0.2 and 0.1 g/L for 4000 and 5000 ppm clay concentration, respectively, at 120 minutes contact time. The target residual turbidity values achieved under these conditions were 11.38 and 6.21 NTU for 4000 and 5000 ppm clay concentration, respectively, with maximum percent turbidity reduction of 96.4 and 98.4%, respectively [35, 36].

Locally commercial Mushroom is used as a natural coagulant/flocculent to reduce water turbidity. The lowest residual turbidity value (highest percentage reduction) of water turbidity was achieved at an optimal pH of 6.7. The lowest residual turbidity value (11.1 NTU) is achieved by a clay suspension with a concentration of 1000 ppm, and the highest residual turbidity value (22 NTU) is achieved by a clay suspension with 6000 ppm. Mushroom dose of 0.4 g/L gives the lowest value for residual turbidity (11.2 NTU) and the highest value for percent reduction in turbidity (96.5%). Evaluation of ANOVA for statistical validation of the developed models yielded very acceptable R-squared values for the four model equations (0.997, 0.999 for models with 4000 ppm clay concentration and 0.993, 0.993 for models with 5000 ppm clay concentration). The optimization method for maximum percent reduction in turbidity showed the optimum operating conditions (Mushroom dose 0.2 and 0.1 g/L) for 4000 and 5000 ppm clay

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Availability of data and materials

Data supporting the results of the present study could be obtained from the corresponding author on reasonable request.

Conflicts of interest

Authors declare that they have no competing interest; either academic or financial.

Authors' contributions

A. M. T.

Conception, interpretation of data and she has drafted the work and substantively revised it

R. H. O.

Design of the work; analysis of results, interpretation of data and she has drafted the work.

A. M. M.

Interpretation of data and she has drafted the work and substantively revised it

M. A. M.

Design of the work; analysis of results, interpretation of data.

All authors revised the final form of manuscript

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The authors declare no competing interests.

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Use of Mushroom for Removing Wastewater Turbidity: Characterization and Optimization Study

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Abstract

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Article Highlights

1. Introduction

2. Material and Methodology

2.1. Materials

2.2. Methodology:

2.2.1 Preparation of Mushroom powder:

2.2.2 Preparation of clay suspension and experimental procedure:

2.2.3. Experimental design and data analysis:

3. Results and discussion

2.1. Materials Characterization:

3.1.1. Characterization of Mushroom and Clay:

3.1.2. SEM, TEM and XRD analysis:

3.2. Experimental Results:

3.2.1. Effect of pH value:

3.2.2. Effect of flocculent dose

3.2.3. Effect of clay concentration:

3.2.4. Effect of ratio of flocculent dose to clay suspension concentration:

3.2.5. Statistical Modeling

3.2.6. Effect of process parameters:

3.2.7. Optimization of the operating parameters:

Conclusion

Declarations

References

Additional Declarations

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