Optimization of sunlight photo-catalytic treatment coupled to a coagulation-flocculation process

doi:10.21203/rs.3.rs-1959503/v1

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Optimization of sunlight photo-catalytic treatment coupled to a coagulation-flocculation process

https://doi.org/10.21203/rs.3.rs-1959503/v1

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The oleic industry is one of the most polluting in food industry sector. Among other harmful by-products, it generates charged sludge. Coagulation–flocculation is a relatively simple physico–chemical technique that ensures excellent separation of solid particles from dissolved ones. To obtain acceptable treated water quality, this method is used along with TiO₂-based sunlight photo-catalysis. We optimize this binary process to treat mill wastewater collected from the region of Mahdia, east center of Tunisia, by applying a combination of mixture design (3 components-mixture: lime water, iron solution and cactus mash) and full factorial design 2² (2 process factors: dilution ratio (aqueous solution/water) and used TiO₂ mass). Both the phenolic compounds removal and solution decolorization are closely monitored. The quadratic models for those two responses indicate optimum conditions to a coagulation-flocculation performance using a mixture of 48.48% of lime water with 51.52% of cactus mash with low level of dilution rate and high level of TiO₂ mass. Experience of those conditions validated calculi, and they give a decolorization of 92.57 ± 0.90% and an organic degradation of 96.19 ± 0.97% in good concordance with the mathematic predictions that yield 93.06% of decolorization and 98.70% of organic degradation.

Mill wastewater

photo-catalysis

coagulation

flocculation

optimization

For centuries, Mediterranean basin countries have been at the forefront of the international olive oil industry. In Tunisia, the total olive oil production capacity stands at 45,000 tons per day in average (ONAGRI, 2022). According to ONAGRI, National Observatory of Agriculture, Tunisian production of olive oil is about 400,000 tons in 2020, about 350,000 tons of which are dedicated to exportation (Elkadri, et al., 2022). Olive oil is, consequently, fundamental to the country’s economy. In addition to oil, this industry produces soap either directly from oil or by chemical extraction from pomace. However, according to the Tunisian Ministry of Environment, it also generates important quantities of olive mill wastewater (OMW), reaching 950,000 m³ per year (Sierra et al., 2022).

Many researchers (Elkadri et al., 2022, Sierra et al., 2022, Kovačević et al., 2022) consider this agro-industrial waste as one of the heaviest and most difficult to manage

This type of sludge is a dark viscous fluid with malodors. It consists of more than 80% of water and sugar, nitrogen, organic acids, polyphenols, polyalcohols, pectines, mucilage, tannins and inorganic substances (Zghari et al., 2018, Juárez et al., 2008). Their composition depends on many factors like region, climatic conditions, nature of the soil and even the trituration method (Aggoun et al., 2016). Residual oily substances of OMW float to the surface, inhibit evaporation, and create anaerobic conditions favorable for stench, which complicates the treatment of OMW and engenders several environmental impacts. The current techniques largely employed in the treatment of this type of waste could be divided into three types: physico-chemical, biological, and advanced oxidative methods. Even though the techniques under the last type are very efficient and enable a reduction in chemical oxygen demand (COD) by more than 70%, they are still very expensive and energy-demanding (Rivas et al., 2001, Ugurlu et al., 2007). Biological techniques are also efficient in terms of COD reduction, but they are very slow and difficult to manage (Yesilada et al., 1998 ; Jarboui et al., 2009). Physico-chemical methods seem to be very appropriate because of their low cost and simplicity. However, Boukhoubza et al.(2009), contested their efficiency compared to other methods (2009). Since rapid and easy intervention for the treatment of all these effects is required to reduce the environmental impact of OMW accumulation, we propose in this work to implement an efficient process combining coagulation-flocculation and sunlight photo-catalysis. In this study, we tried to determine the optimum conditions of this process by means of experiments using two types of design: mixture design and full factorial design.

2.1. Reagents and materials

A soap production factory in the Mahdia governorate, Tunisia. OMW provides us olive mill wastewater, 24 hours after the olive oil trituration process.

Cactus rackets were collected from the campus of Tunis El Manar to the north of Tunisia. They were washed with faucet water and then peeled. The pulp was mixed in a grinder to obtain a greenish juice.

Lime water was dissolved in water to obtain a solution of 30 g · L^− 1. Ferric chloride (99%) Merck was used to prepare a 1.5 g.L^− 1 solution.

The TiO₂ catalyst was prepared by the sol-gel method. Titanium isopropoxide was mixed with isopropanol and acetyl acetate to form the sol. Jellification was made by 0.1 mol · L^− 1 of nitric acid solution.

2.2 Physico-chemical analysis

OMW is characterized by the following measurements after homogenization and at the reception of the samples. Each measurement is repeated 3 times:

The pH measurement is achieved via a pH-meter calibrated with buffers of pH = 4, 7, and 10 (Flanzy et al., 2019).

The dry matter (DM) consists of organic and inorganic as well as solid and dissolved matter in the mill sample. It corresponds to the residue of constant mass after evaporation of 10 mL of sample at 105°C. It is expressed in g · L^− 1 (Flanzy et al., 2019).

Ash contain (AC) is constituted of inorganic matter. It corresponds to the residue after calcination of the DM during 24 h at 550°C. It is expressed in g · L^− 1 (Flanzy et al., 2019).

COD represents the quantity of oxidable matter. It is determined by placing 50 mL of the OMW in a 500-mL-refluxing flask, with 1 g of HgSO₄, 5 mL of a mixture of Ag₂SO₄ prepared in concentrated sulfuric acid, and 25 mL of a solution of the oxidant K₂Cr₂O₇ in concentrated sulfuric acid. The mixture stays heated under reflux after vigorous mixing for two hours. The K₂Cr₂O₇ that has not been consumed for oxidation is then quantified by titration with an aqueous solution of Fe(NH₄)₂SO₄. The residual K₂Cr₂O₇ oxidizes the Fe²⁺ of the titrant Fe(NH₄)₂SO₄ to give Fe³⁺. When all the residual K₂Cr₂O₇ is consumed (reduced by Fe²⁺), the indicator ferroin, which has to be added to the wastewater/K₂Cr₂O₇ mixture prior to titration, turns from blue-green to reddish brown. At this end-point of titration, the volume of the Fe(NH₄)₂SO₄ is read from the burette and the residual amount can be calculated of the oxidant K₂Cr₂O₇ after oxidizing the organic constituents in the wastewater sample (Flanzy et al., 2019).

Measurement of the absorbance a 288 nm by spectrophotometer at 288 nm permits to determinate of phenolic compounds concentration relatively to calibration curve of gallic acid, after dilution 10 times for treated samples and 200 times for centrifuged fresh OMW (Flanzy et al., 2019).

Solution decolorization is quantified by RBG color measurement (Coleman et al., 2019) using image J, a multi-platform public domain software. All the samples are photographed at the same time. A representative square region of the glass center is selected. From the menu “Analyze”, then the option “Measure” which calculates the intensity of the color, absorbance is calculated using relation (1):

(1)\(A = {log}_{10}\left(\frac{{I}_{0}}{I}\right)\)

where I is the color intensity of the measured solution; I₀ the color intensity of water taken as reference.

The same procedure is applied to treated samples and OMW.

2.3. Design of experiments

Coagulation is performed by mixing 50 mL of OMW (characterized by initial color and initial phenol concentration) vigorously with 50 mL of a mixture composed of: lime water (A), iron solution (B), and cactus mash (as coagulant, C) as presented in Fig. 1. The proportions (A, B, and C) of the mixture used in this step are determined by means of the experimental mixture design (type simplex lattice design). Table 1 and Fig. 2 present the corresponding experimental points. One hour after, agitation is stopped, and the mixture is transferred to cylinder. Decantation is established during ~ 5 days to obtain a perfect separation of the aqueous solution from sludge. Once separation is carried out, the aqueous solution is diluted with water (1 or 2 mL in 10 mL) defining the first process factor noted by X₁. The corresponding high (1mL/10 mL) and low (2mL/10 mL) levels are presented in Table 1 as coded levels: -1 and + 1, respectively. A volume of 20 mL of the obtained mixture (obtained for each experimental condition defined in Table 1) is mixed with an appropriate mass (20 mg (low level: -1) or 40 mg (high level: +1)) of the TiO₂ catalyst defines the second process factor noted by X₂ (Table 1). Solution is kept 45 min in the dark, then exposed to sunlight for 24 h. During this step, the emission of CO₂is established.

Table 1

Low and high levels used for mixture simplex lattice design / full factorial design 2²
Run	Lime water^*	Iron solution^*	Cactus mash^*	X₁ Dilution^**	X₂ TiO₂ mass^**	Decolorization (%)	Organic degradation (%)
1	1	0	0	-1	-1	67.63	99.02
2	0.5	0.5	0	-1	-1	92.54	98.32
3	0.5	0	0.5	-1	-1	93.57	98.38
4	0	1	0	-1	-1	97.36	97.6
5	0	0.5	0.5	-1	-1	83.97	98.1
6	0	0	1	-1	-1	79.37	98.18
7	0.333	0.333	0.333	-1	-1	90.84	98.02
8	1	0	0	1	-1	92.45	97.94
9	0.5	0.5	0	1	-1	79.33	96.56
10	0.5	0	0.5	1	-1	90.53	97.5
11	0	1	0	1	-1	40.26	95.8
12	0	0.5	0.5	1	-1	57.14	95.9
13	0	0	1	1	-1	50.22	96.3
14	0.333	0.333	0.333	1	-1	43.52	96.06
15	1	0	0	-1	1	99.59	99.36
16	0.5	0.5	0	-1	1	91.11	98.78
17	0.5	0	0.5	-1	1	98.12	98.88
18	0	1	0	-1	1	66.69	97.92
19	0	0.5	0.5	-1	1	78.57	98.42
20	0	0	1	-1	1	78.75	98.46
21	0.333	0.333	0.333	-1	1	76.69	98.46
22	1	0	0	1	1	87.32	98.2
23	0.5	0.5	0	1	1	75.04	97.28
24	0.5	0	0.5	1	1	86.65	97.9
25	0	1	0	1	1	36.25	95.76
26	0	0.5	0.5	1	1	42.94	97.00
27	0	0	1	1	1	47.85	96.44
28	0.333	0.333	0.333	1	1	41.78	95.98
^: proportions level (0–1) of mixture design; ^*: coded variable for X₁ and X₂ of full factorial design 2².

Decolorization and organic degradation measured in percentage (%) and defined as two different responses for this study are calculated as follows:

The choice of these two responses presents an important fact in this study. It places the accent on the treatment influence on the combination of decolorization performance (translated by decolorization percentage) and organic matter reduction (in the form of organic degradation percentage).

The quadratic model describing both responses (decolorization and organic degradation) is expressed by Eq. (3) as a function of mixture components (lime water (A), iron solution (B), and cactus mash (C)) and process variables (X₁: Dilution and X₂: TiO₂ mass):

wherestands for the modeled response in % (decolorization or organic degradation); A: lime water proportion; B: iron solution proportion; C: cactus mash proportion; X₁: coded value of the dilution factor as a first process variable; X₂: coded value of TiO₂ mass as second process variable; : model coefficients.

The design of experiments (28 attempts, Table 1, Fig. 1), determination of model coefficients, all statistical tests, optimum determination, and all figures’ drawings are performed with the Minitab®16.2.1 Software.

3.1. OMW characterisation

OMW is one of the worst and most polluting effluents. It is also one of the most difficult to treat because of the heavy amounts of pollutants they include such phenolic compounds in solid suspension. Treated OMW is characterised by a pH of 4.62 ± 0.01 and CDO 52.1 ± 0.02 (gO₂ · L^− 1). Dry matter is estimated to 108.0 ± 0.5 (g.L^− 1) and ash contain to 17.5 ± 0.8 (g.L^− 1).

3.2. Coagulation – flocculation trials

Regarding the importance of DM content in this effluent, coagulation seems to be the most appropriate method as first treatment. It allows the reduction of solid suspensions into composted or pyrolyzed materials. Based on the results of recent research on the topic, use of natural products in this process is more widely used. More and more natural elements are attracting interest in coagulation. We can site chitosane (Patel and Vashir, 2013), seed of moringa oleifera (Desta and Bote, 2021) and cactus (Shilpaa et al., 2012, Taa et al., 2016). According to the work reported by Ndabigengesere and Narasiah (1996) cation concentration had considerable impact on coagulation. However, the anions effect seems to be insignificant. That is why we studied the possibility of improving the cactus effect in presence of lime and ferric solutions. Lagoudianaki et al. (2007) have reported the positive impact of the use of those metals for odor reduction. After coagulation treatment and decantation, the final pH varies from 5.92 using only cactus mash to 11.67 when using lime water only. The quantity of sludge is minimum (about 48%) when using the ferric solution, lime water, and cactus mash together; and it is maximum (70%) when using lime water only.

However, this treatment is not sufficient. Liquid proportions have to undergo additional treatment because it stills charged with toxic compounds, mainly soluble phenols. Photo-catalysis under sunlight is a cheap and easy method renowned for its good results for wastewater treatment. We used TiO₂ with an adsorption period of 1 hour. Then, sunlight exposure continues overnight (about 16 hours of ligh on August (Fig. 1)). Final pH of the mixtures is about 8.50 and DCO of the middle point is 7.64 ± 0.02 gO₂ · L^− 1. Phenolic compounds expressed as gallic acid are reduced to 0.2 ± 0.01 10^− 5 mg.L^− 1.

3.3. Design of experiments results

Table 1 presents the obtained results of decolorization (%) and of organic degradation (%) for each experimental condition. It is clear that the decolorization is from 36.25 to 99.59% with a mean value of 73.79 ± 20.52%, and the organic degradation is from 95.76 to 99.36% with a mean value of 97.59 ± 1.09%. Those results confirm efficiency of this process mainly for organic degradation.

In Table 2 regroups the t-test for both responses (decolorization and organic degradation) and for all determined model coefficients in each case (Eq. 3).

For the decolorization response, it is clear that only the interaction existing between iron solution (B) proportions and dilution (X₁) (p < 0.05) has a significant, and negative, influence on this response. However, for the organic degradation response, six terms are influencing this response significantly: three proportions of used components (p < 0.001), and three linear terms (with negative coefficients) of interaction existing between components proportions and dilution (X₁) (p < 0.05).

Moreover, the corresponding models’ regressions used for both responses are evaluated with different statistical criteria (Table 3).

Table 3

Statistical quality fit of both responses: decolorization and organic degradation
Statistical criterion	Decolorization (%)	Organic degradation (%)
Significance of model regression	0.062	p = 0.001 < 0.01
Coefficient of determination (R²)	81.70%	93.71%
Adjusted coefficient of determination (R²_adj)	50.59%	83.03%
Root mean squared error (RMSE)	14.422%	0.448%

The fit quality of the model applied to organic degradation seem more important to those applied to decolorization as shown by the statistical parameters reported in Table 3. In fact, the relative regression is characterized by a very significant regression (p = 0.001 < 0.01), a very high coefficient of determination (R² = 93.71%), a high adjusted coefficient of determination (R²_adj = 83.03%), and a very low root mean squared error (RMSE = 0.448% - unit of organic degradation).

Figure 3 presents the iso-responses evolution of decolorization (Fig. 3.a) and organic degradation (Fig. 3.b), as function of components proportions and process variables. Figure 3 (a and b) shows that the presence of high concentrations of lime water (> 40%) increases the processes of decolorization and, more importantly, organic degradation. This is true for all levels of dilution rate (X₁) and of TiO₂ catalyst mass (X₂) (Fig. 3). Moreover, it can be seen that the highest decolorization (> 92%) and organic degradation (> 98.5%) percentages can be obtained if we apply low dilution rate (X₁) and low or high TiO₂ catalyst mass (X₂) while using a ternary mixture of the used three components charged mostly by lime water (Fig. 3.b).

The determination of the optimal conditions maximizing equally and simultaneously both responses was established by means of the optimizer of Minitab Software (Fig. 4). This step is paramount because it determines not only the optimum composition of the ternary mixture, but also the optimum level of each process variable. Indeed, in this study, it is recommended (from these pure mathematical optimization results) to apply a mixture free of the iron solution (0%) composed of 48.48% of lime water with 51.52% of cactus mash with low level of dilution rate and a high level of TiO₂ mass (Fig. 4). This combination can give us a decolorization of 93.06% and an organic degradation of 98.70% (Fig. 4). Three replicas of experiences in optimum conditions validated calculi. The obtained results were a decolorization of 92.57 ± 0.90% and an organic degradation of 96.19 ± 0.97%. It is clear that the experimental results obtained are, on the one hand, replicable (since the standard deviations are very low), and, on the other, very close to the mathematical optimization results.

Additionally, another factors combination can be a promising competitor to the determined optimum, namely the experimental condition presented in run 15 of Table 1: the use of 100% of lime water, low level of dilution rate and high level of TiO₂ mass. This condition can give 99.59% of decolorization and 99.36% of organic degradation. However, this last solution, even with its very satisfying results regarding water quality, constitutes the worst process when evaluating the quantity and quality of sludge generated. Using only lime as coagulating agent generates the greatest quantity of sludge (69.9%).

Coagulation-flocculation is one of the simplest and lowest-cost methods. It ensures acceptable results mainly for wastewater charged with particles. However, its outcome is not satisfactory. That is why we opted in this study to combine coagulation-flocculation with sunlight photo-catalysis. The process was optimized by means of mixture and full factorial design applied to decolorization and phenolic compound degradation, viz coagulant composition and photo-catalytic test conditions. Metals, lime and organics are the most largely used families of coagulants.

Mixture design allowed us to test iron, lime and cactus in this process. Catalytic tests were conducted with 2 levels of dilution and 2 levels of TiO₂ mass as catalyst. Optimum conditions found are: 0% iron and 48.48% of lime water with 51.52% of cactus mash with low level of dilution rate and high level of TiO₂ catalyst. These conditions permitted to reach a decolorization of 92.57 ± 0.90% and an organic degradation of 96.19 ± 0.97% when tested 3 times separately. They confirmed mathematic predictions that yielded 93.06% of decolorization and 98.70% of organic degradation. Coagulation with 100% of lime was also efficient and gave 99.59% of decolorization and 99.36% of organic degradation. But this methodology generated the most important quantity of sludge which is not of great interest.

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Author contribution

Sahar Raissi : carrying out experiences and redaction

Fatma Fakhfakh : catalyst synthesis revision

Bilel Hadrich : design of experiences and redaction

Funding

This study was carried out with no financial support of any part.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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All data generated or analysed during this study are included in this published article

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Optimization of sunlight photo-catalytic treatment coupled to a coagulation-flocculation process

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Abstract

Figures

1. Introduction

2. Experimental Section

2.1. Reagents and materials

2.2 Physico-chemical analysis

2.3. Design of experiments

3. Results And Discussion

3.1. OMW characterisation

3.2. Coagulation – flocculation trials

3.3. Design of experiments results

4. Conclusion

Declarations

References

Table 2

Supplementary Files

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