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This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The other, swelling, richer in montmorillonite, is associated with kaolinite, illite and quartz. Seven factors including these two clays were taken into account in a series of experimental designs in order to model and optimize the acidic activation process favoring a better phosphate removal. In addition to the choice of clay nature, the study was also interested in the identification of the mineral acid, between hydrochloric acid and sulfuric acid, which would promote this acidic activation. Response Surface Methodology (RSM) was used for this purpose by sequentially applying Plackett and Burman Design and Full Factorial Design (FD) for screening. Then, a central composite design (CCD) was used for modeling the activation process. A mathematical surface model has been successfully established. Thus, the best acidic activation conditions were obtained by activating the montmorillonite clay with a 2N sulfuric acid solution, in an acid/clay mass ratio of 7.5 at 100°C for 16H. The phosphate removal maximum rate obtained was estimated at 89.32% ± 0.86%.

Phosphorus is after nitrogen the fertilizing element that most often limits the development of crops [

There are biological treatments [

In this context, adsorption appears to be an easy, more efficient and, above all, reusable technique by appropriate desorption processes [

Acidic activation is one of the techniques used to improve the adsorption properties of clays [^{3+}, Mg^{2+} and Fe^{3+}) and Si^{4+}, respectively hosted in the octahedral and tetrahedral sites [

It turns out that the studies of phosphate ions removal do not focus on optimizing the activation conditions favoring this adsorption. Activation factors are most often fixed, and the study focuses on the optimization of adsorptions parameters such as pH, adsorption time, mass of sorbent, the normality of the sorbate [

Working tool that facilitates decision-making, experimental design is here used to optimize and modeling clays acidic activation. In this study, seven (7) factors that may influence acidic activation process were considered. These are the type and normality of the acid solution, the acid/clay mass ratio, the temperature and activation duration, the nature or the type of the clays as well as their granulometries. This work aims to model this activation process by the establishment of a predictive mathematical model and to determine the optimal conditions that would favor a better phosphate ions removal and investigate the interactions between the different factors.

Ultimately, what type of clay and mineral acid does the activation process promote? And under what conditions of acid normality, temperature and duration of activation will this be achieved? The interest of this study lies in the methodology used to achieve the expected objective. Response Surface Methodology (RSM) operated through Plackett and Burman Design (PBD), Full Factorial Design (FD) and Central Composite Design (CCD) are used for this purpose. The results obtained, compared with those of the literature on acid activation of montmorillonite and kaolinite, were used to judge the relevance of the methodology used.

The interest of this study lies in the fact that the clays used in this work, one swelling and the other non-swelling, were never used simultaneously for this type of work. The use of experimental designs made it possible to study for the first time the interactions between the factors influencing the acid activation process of clays for phosphate ions removal. Finally, the other element of interest derives from the modeling of this activation process which makes it possible to predict, depending on the nature of the clay and other factors such as the normality of the acid solution, the temperature and the duration of activation, the probability that acidic activation will contribute to promote phosphate ions capture.

The Clays was collected from two cities of Côte d’Ivoire. One was collected at the northern in the savannah zone, on a site of geographical coordinates 08˚08.94'N and 05˚05.95'W [

Each clay is separated into two granulometric fractions: One less than 50 μm and the other less than 2 μm. The first phase is obtained by wet sieving. The powders are obtained after drying in an oven at 105˚C and are denoted MTMO_{50} for the clay MTMO and KAO_{50} for the KAO clay. The second phase is extracted from the first according to the Holtzapffel protocol [_{2}O_{2} (50%, MERCK) followed by a 0.5 N hydrochloric acid solution (37%, MERCK) treatment. These attacks aim to eliminate organic matter and carbonates respectively. The treatment is followed by washing this sample in a 1 M solution of sodium chloride (PROLABO) for 24 hours, three times and each time the exchange solution (NaCl) was renewed. This treatment aims to facilitate the separation of clay particles from silts and fine sand and to promote homo-ionization. The granulometric phases of 2 μm size noted MTMO_{2} and KAO_{2}, are obtained in the last step by siphoning and drying the supernatant of the upper 20 cm of a test tube of 2 L, after 24 hours of sedimentation.

The activation was carried out either with hydrochloric acid or with sulfuric acid in a reactor consisting of a three-necked flask of 500 cm^{3}, surmounted by a refrigerant. The flask is kept stirring in a heat bath. The clay masses and the amounts of acid are set in various mass acid/clay ratios. The duration time t of the activation is counted from the moment; the temperature in the flask reaches that fixed for the activation. The activated clay is then centrifuged at 4000 rpm for 15 minutes and then washed with distilled water until acid is removed. Washing is stopped when the supernatant no longer gives any reaction of sulfates with barium chloride for activation with sulfuric acid and, in the case of hydrochloric acid, when silver nitrate test is negative. The activated clay is then dried at 105˚C.

Activation effectiveness is evaluated from the abatement rate Y of the H 2 PO 4 − ions representing the removal rate of these ions, expressed in percentage; Equation (1).

Y = C 0 − C C 0 ∗ 100 (1)

C_{0} and C in mg∙L^{−1}, respectively represent the initial and residual mass concentrations of H 2 PO 4 − ions.

Tests were carried out at 30˚C in an oscillating water bath of JULABO SW1 type. Each time, 1 g of activated clays is introduced into a 100 mL flask containing 25 mL of a 40 mg/L synthetic KH_{2}PO_{4} (MERCK) solution. The pH was adjusted at 4.7 using 1N sulfuric acid solution or 1 M sodium hydroxide solution according to previous works [

The optimization was carried out through Response Surface Methodology (RSM). This technique aims to quantitatively determine the response function variation represented in this study by the abatement rate Y, with respect to the factors having a significant influence [_{i}) and non-coded (U_{i}) values of the seven variables examined as well as

Coded variables (X_{i}) | Factors (U_{i}) | Experimental Domain | |
---|---|---|---|

Low level (−1) | High level (+1) | ||

X_{1} | U_{1}: Temperature (˚C) | 35 | 80 |

X_{2} | U_{2}: Acid type | H_{2}SO_{4} | HCl |

X_{3} | U_{3}: Acid normality (N) | 1 | 5 |

X_{4} | U_{4}: Activation duration (H) | 3 | 10 |

X_{5} | U_{5}: Clay granulometry (µm) | 2 | 50 |

X_{6} | U_{6}: Mass ratio | 3.5 | 7.5 |

X_{7} | U_{7}: Clay nature | montmorillonite | kaolinite |

*The low (−1) and high (+1) levels represent limits of possible values or states of the factors.

the experimental domain used for this design.

The matrix is obtained by right circular permutation of the basic pattern about seven factors: +++−+−− [_{i} factors. This relationship is presented in the form of a 1^{st} degree model where all interactions between factors are neglected [

Y = b 0 + ∑ i = 1 7 b i X i (2)

where, b_{0} represents the constants (or average effect) of the model and bi the factors effects determined by the least square method or by software. The factors coefficients obtained at the end of this screening have helped to show the relevance of factors. The coefficient b_{i} is statistically different from zero and the factor X_{i} is considered for the following of the study if the absolute value of its b_{i} coefficient is greater than two times the experimental standard deviation σ e [

σ e = σ n (3)

σ is the standard deviation of the repetitions average performed under the conditions of one of the tests if there is a qualitative factor or, from the test at the center if there are only quantitative factors [

The second experimental design used is the Full Factorial Design (FD; 2^{k}) with the k factors considered relevant from the previous design. FD allowed to investigate the possible interactions between these factors, to face modeling of the activation process by a first-degree model taking into account the interactions (Equation (4)), as well as to define the final experimental domain to be used for optimization [

Y = b 0 + ∑ b i X i + ∑ ∑ b i j X i X j ; i ≠ j (4)

Here b_{ij} represent the interaction effects of 2 order. At the end of the data processing, the Pareto diagram gives the effective contribution of each factor. These contributions are calculated with Equation (5):

P i = b i 2 ∑ i = 1 6 b i 2 (5)

b_{i} are the main coefficients and interaction coefficients. Experimental results led to a CCD with the q factors having the highest contributions.

The CCD experiment matrix has been built using three sets of essays, including 2^{q} in FD, 2 × q star essays and n central essays [

Tests at the center will be used to estimate the experimental error and to enforce the optimality criteria characterized by the pseudo-orthogonality of the matrix and the isovariance of the response throughout the experimental domain. CCD allowed establishing a second-level model to describe the process being studied. The corresponding mathematical model is given in the form of Equation (6) below:

Y = b 0 + ∑ b i X i + ∑ ∑ b i j X i X j + ∑ b i i X i 2 + e ; i ≠ j (6)

where b_{ii} represents the coefficients of the squares and e is a random error. The optimal conditions for activation are subsequently deduced.

A multiple linear regression program using the NEMROD-W 9901 French version software [^{2} and R A 2 given by NEMROD-W. R A 2 corresponds to the adjusted value of R^{2}. R^{2} is defined as the ratio between the explained variance and the total variance [^{2}, allows to consider the number of variables necessary for the theoretical model establishment because a high value of R^{2} can sometimes be due to an excess of factors [^{2} is greater than 0.80. But for Baudot [^{2}; R A 2 has to be greater than 0.77.

These conclusions were tested by other statistical analysis tools such as Analysis Of Variance (ANOVA) or coefficient of variation C.V (Equation (7)) from the residuals which represent the difference between the experimental values and the values calculated from the predictive model.

C .V = 1 N [ ∑ i = 1 N | Y exp − Y calc Y exp | ] × 100 (7)

N is the number of tests. According to these data, the model is accepted if the coefficient of variation is less than 5% [

_{e}. The experimental standard deviation σ_{e} 1.48 was determined with the five-run repeat of the test 1; the values obtained as percentage of abatement being respectively 29.75; 28.25 and 24.75. The analysis of the coefficients suggests that the acid solution normality (X_{3}), the duration of activation (X_{4}) and clay’s nature (X_{7}) are the most influential factors. This result would support the idea that the acidic activation would depend on the nature of the clay [

According to Srasra et al. [

n˚ exp | Factors | Phosphate Removal Y_{exp} (%) | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

Coded Variables | Real Variables | ||||||||||||||

X_{1} | X_{2} | X_{3} | X_{4} | X_{5} | X_{6} | X_{7} | U_{1} (˚C) | U_{2} | U_{3} (N) | U_{4} (H) | U_{5} (µm) | U_{6} | U_{7} | ||

1 | +1 | +1 | +1 | −1 | +1 | −1 | −1 | 80 | HCl | 5N | 3 | 50 | 3.5 | MTMO | 28.75 |

2 | −1 | +1 | +1 | +1 | −1 | +1 | −1 | 35 | HCl | 5N | 10 | 2 | 7.5 | MTMO | 38.75 |

3 | −1 | −1 | +1 | +1 | +1 | −1 | +1 | 35 | H_{2}SO_{4} | 5N | 10 | 50 | 3.5 | KAO | 22.5 |

4 | +1 | −1 | −1 | +1 | +1 | +1 | −1 | 80 | H_{2}SO_{4} | 1N | 10 | 50 | 7.5 | MTMO | 58.75 |

5 | −1 | +1 | −1 | −1 | +1 | +1 | +1 | 35 | HCl | 1N | 3 | 50 | 7.5 | KAO | 23.75 |

6 | +1 | −1 | +1 | −1 | −1 | +1 | +1 | 80 | H_{2}SO_{4} | 5N | 3 | 2 | 7.5 | KAO | 20 |

7 | +1 | +1 | −1 | +1 | −1 | −1 | +1 | 80 | HCl | 1N | 10 | 2 | 3.5 | KAO | 38.75 |

8 | −1 | −1 | −1 | −1 | −1 | −1 | −1 | 35 | H_{2}SO_{4} | 1N | 3 | 2 | 3.5 | MTMO | 42.5 |

Coefficients | b_{1} | b_{2} | b_{3} | b_{4} | b_{5} | b_{6} | b_{7} | b_{0} | |||||||

Values | 2.35 | −1.725 | −6.725 | 5.5 | −0.8 | 1.1 | −7.975 | 34.225 | |||||||

Experimental error 2σ_{e} | 2.96 |

to them, induce an increase of their specific surface area and the average pore volume, thereby contributing to improving their adsorption and discoloration capacity. The other sample, consisting only of non-swelling clay (kaolinite and illite), for which the access of protons to their octahedral layers is strongly restricted, does not benefit from the effect of acid activation on adsorption.

However, the nature of the clay being a qualitative factor, it has been fixed for the continuation. From then on, we would have only two factors left. However, the temperature (X_{1}) with a coefficient b_{1} of 2.35 close to 2 × σ_{e}, has been considered in the following as a relevant factor for this process. At the end of this screening, three factors were selected: Normality, temperature and duration of activation. This selection of factors is consistent with that of Gannouni et al. [

The normality of the acid solution, for example, influences the kinetics of attack [_{i}. Thus, the optimization of the activation for this phosphate removal was sought by using the MTMO clay with 2 μm particle size activated by sulfuric acid in an acid/clay mass ratio of 7.5.

The use of sulfuric acid for activation experiments agrees with those of other studies. In fact, Pushpaletha et al. [

This FD conducted with three factors was interpreted after eight (2^{3}) essays. The experimental area of this design is defined as follows: The temperature factor (U_{1}) with a low level set at 65˚C and the high level at 90˚C; the normality factor (U_{2}) with the low level 0.5N and the high level 2N, then the activation duration factor (U_{3}) with the low level 8H and the high level 12H.

The data processing with the software, gives the first-degree polynomial (Equation (8)).

n˚ exp | Factors | Phosphate removal Y_{exp} (%) | Theoretical phosphate removal Y_{calc} (%) | Coefficient of variation (%) | |||||
---|---|---|---|---|---|---|---|---|---|

Coded variables | Real variables | ||||||||

X_{1} | X_{2} | X_{3} | U_{1} (˚C) | U_{2} (N) | U_{3} (H) | ||||

1 | −1 | −1 | −1 | 65 | 0.5 | 8 | 31.25 | 34.22 | 9.5 |

2 | +1 | −1 | −1 | 90 | 0.5 | 8 | 51.25 | 48.28 | 5.8 |

3 | −1 | +1 | −1 | 65 | 2 | 8 | 38.75 | 35.78 | 7.66 |

4 | +1 | +1 | −1 | 90 | 2 | 8 | 42.5 | 45.47 | 6.99 |

5 | −1 | −1 | +1 | 65 | 0.5 | 12 | 43.75 | 40.78 | 6.79 |

6 | 1 | −1 | +1 | 90 | 0.5 | 12 | 53.76 | 56.72 | 5.51 |

7 | −1 | +1 | +1 | 65 | 2 | 12 | 43.75 | 46.72 | 6.79 |

8 | +1 | +1 | +1 | 90 | 2 | 12 | 61.25 | 58.28 | 4.85 |

Y = 45.78 + 6.41 X 1 + 0.78 X 2 + 4.84 X 3 − 1.09 X 1 X 2 + 0.47 X 1 X 3 + 1.09 X 2 X 3 (8)

According to _{1}) and the activation duration (X_{3}) have the highest contributions. The interactions between the factors as well as the contribution of normality remain marginal because their effects are statistically null. Temperature and activation duration appear as the most relevant in the activation process for H 2 PO 4 − ions removal. Their global contribution is 95.26% corresponding to 60.67% for temperature and 34.59% for the activation duration.

This result agrees with the observations of Khoek et Lim [_{2}.

Validation of the first-degree model was examined based on the statistical data provided by the NEMROD software through ANOVA. These include the coefficients of determination R^{2} and R A 2 with respective values of 0.885 and 0.194, the average of the coefficient of variation of 6.73%, the contribution of residues of 11.51% in the total sum of the squares and 58.6% of model significance. These data do not allow to validate this model because although R^{2}, lower than 0.80 is acceptable [

With the two factors those are temperature and activation duration (q = 2), the CCD consisted of four FD tests, four in-star tests and five central essays [^{q}^{/4} i.e. between −1.414 unit and +1.414 unit. These coded values translate into real values 50˚C and 100˚C chosen as the limit of the experimental domain for the temperature (U_{1}); 8 hours and 16 hours for the duration (U_{2}). The explored experimental domain and the levels attributed to each variable are presented in

−r = −1.414 | −1 | 0 | +1 | +r=+1.414 | |
---|---|---|---|---|---|

X_{1} (˚C) | 50 | 57 | 75 | 93 | 100 |

X_{2} (H) | 8 | 9 | 12 | 15 | 16 |

Test results, predicted responses, residuals, and percentages of deviation are shown in

Equation (9) represents the theoretical response of the abatement rate of phosphate removal.

Y = 43.120 + 6.380 X 1 + 10.901 X 2 + 10.901 X 1 2 + 4.775 X 2 2 + 3.718 X 1 X 2 (9)

The coefficients of determination associated with this model, given by the NEMROD software are 0.952 for R^{2} and 0.917 for R A 2 all higher than respectively to 0.80 and 0.77 and the average of the deviation percentages 2.67%, which is less than 5%. These statistical results show that the 2-degree polynomial model proposed for modeling the clay activation for H 2 PO 4 − ions removal is satisfactory. This conclusion is supported by the analysis of the variance (ANOVA) for the predicted response (Equation (9)) of this process as reported in

n˚ exp | Factors | Experimental Phosphate removal Y_{exp} (%) | Theorical phosphate removal Y_{calc} (%) | Residues (%) | Coefficient of variation (%) | |||
---|---|---|---|---|---|---|---|---|

Coded variables | Reals variables | |||||||

X_{1} | X_{2} | U_{1} (˚C) | U_{2} (H) | |||||

1 | −1 | −1 | 58 | 9 | 39.97 | 38.66 | 1.31 | 3.28 |

2 | +1 | −1 | 93 | 9 | 40.8 | 42.06 | −1.26 | 3.09 |

3 | −1 | +1 | 58 | 15 | 5551 | 54.1 | 1.41 | 2.54 |

4 | +1 | +1 | 93 | 15 | 69.05 | 72.22 | −3.17 | 4.59 |

5 | −1.414 | 0 | 50 | 12 | 41.32 | 42.83 | −1.51 | 3.65 |

6 | +1.414 | 0 | 100 | 12 | 67.25 | 64.08 | 3.17 | 4.71 |

7 | 0 | −1.414 | 75 | 8 | 38.75 | 37.25 | 1.5 | 3.87 |

8 | 0 | +1.414 | 75 | 16 | 69.45 | 68.08 | 1.37 | 1.97 |

9 | 0 | 0 | 75 | 12 | 43.75 | 43.12 | 0.63 | 1.44 |

10 | 0 | 0 | 75 | 12 | 42.97 | 43.12 | −0.15 | 0.35 |

11 | 0 | 0 | 75 | 12 | 43.38 | 43.12 | 0.26 | 0.60 |

12 | 0 | 0 | 75 | 12 | 41.75 | 43.12 | −1.37 | 3.28 |

13 | 0 | 0 | 75 | 12 | 43.75 | 43.12 | 0.63 | 1.44 |

Source of variation | Sum of squares | Freedom degree | Middle square | Ratio | Significance |
---|---|---|---|---|---|

Regression | 1602.76 | 5 | 320.553 | 464.4344 | *** |

Residue | 81.3053 | 7 | 11.615 | ||

Validity | 78.5445 | 3 | 26.1815 | 37.9332 | ** |

Error | 2.76 | 4 | 0.6902 | ||

total | 1684.0653 | 12 |

The theoretical response area depicted in

Resolution of Equation (9) indicates that this theoretical maximum is obtained with temperature equal to +1.414 in coded value i.e. 100˚C in real value and duration of activation of +1.414 i.e. 16H. The high duration obtained is related to the low acidic solution concentration. Indeed, Jahouach [

For the confirmation of the process studied here, three additional control tests were carried out with the activated montmorillonite clay sample under the conditions defined by the coordinates of the theoretical optimum (

n˚exp | Factors | Theorical phosphate removal Y_{calc} (%) | Experimental Phosphate removal Y_{exp} (%) | Average Experimental Phosphate removal Y_{exp} (%) | |||
---|---|---|---|---|---|---|---|

Coded variables | Reals variables | ||||||

X_{1} | X_{2} | U_{1} (˚C) | U_{2} (H) | ||||

14 | +1.414 | +1.414 | 100 | 16 | 93.30 | 88.65 | |

15 | +1.414 | +1.414 | 100 | 16 | 93.30 | 89.03 | 89.32 |

16 | +1.414 | +1.414 | 100 | 16 | 93.30 | 90.30 |

4.26% compared to the theoretical maximum of 93.20%, less than 5% validates the conclusions of this optimization although there is a difference between them. This difference taken into account by the model through the ANOVA revealed according to

_{50}, MTMO_{2} and activated clay MTMO_{2A}, obtained under the optimal activation conditions with MTMO_{2}.

This _{50} and MTMO_{2}. In fact, clay treatment favors aluminum-silicon chemical binding breaks. So, sites where H 2 PO 4 − ions can be adsorbed increases. Due to their lower size, MTMO_{2} clay offers more active sites for phosphate ion adsorption and the phosphate removal increase for this sample. These sites could be the non-satisfied valences (+Al-OH) of broken bindings in layer edges according to Wey [_{2A}.

This study aimed to determine the optimal conditions for acidic activation of two clays respectively rich in montmorillonite and kaolinite for dihydrogen phosphate ions removal in aqueous solution through surface response methodology. Seven factors that are acidic solution type and normality; activation duration and temperature; nature and particle size of the clays as well as the acid/clay mass ratio were considered for this purpose. A preliminary screening study showed the interest of working with montmorillonite clay for which acid activation was beneficial as opposed to kaolinite-rich clay. The activation process was subsequently interpreted using a CCD by a second order polynomial model.

Optimal activation conditions are finally summarized in the use of Montmorillonite clay of 2 μm particle size, activated with 2N sulfuric acid, in a mass ratio of 7.5 at 100˚C for 16 H. An abatement rate of 89.32% with a standard deviation of 0.86 was achieved under these conditions. This work ultimately determined, depending on the nature of the clay and other acid activation factors, the likelihood that acidic activation of clay would favor phosphate ions removal.

Our acknowledgements go to the Heads of the Laboratories of Soil Mechanics, the Laboratory of Pedology and the Laboratory of Industrial Processes Synthesis and New Energies of the National Polytechnic Institute Felix Houphouet Boigny of Yamoussoukro for the framework.

The authors declare no conflicts of interest regarding the publication of this paper.

Adjoumani, Y.J., Dablé, P.J.M.R., Kouassi, K.E., Gueu, S., Assémian, A.S. and Yao, K.B. (2019) Modeling and Optimization of Two Clays Acidic Activation for Phosphate Ions Removal in Aqueous Solution by Response Surface Methodology. Journal of Water Resource and Protection, 11, 200-216. https://doi.org/10.4236/jwarp.2019.112012