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Contribution to the clarification of surface water from the Moringa oleifera: Case M’Poko River to Bangui, Central African Republic
chemical engineering research and design 9 0 ( 2 0 1 2 ) 2346–2352
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Contribution to the clarification of surface water from the Moringa oleifera: Case M’Poko River to Bangui, Central African Republic Nicole Poumaye a , Joseph Mabingui a , Pierre Lutgen b , Muriel Bigan c,∗ a
Laboratoire d’Hydrosciences Lavoisier, Chaire UNESCO sur la gestion de l’eau, Faculté des Sciences, Université de Bangui, B.P.908 Bangui, Centrafrique, Central African Republic b Iwerliewen Fier Bedreete Volleker (IFBV), Luxembourg c Laboratoire ProBioGem, EA1026, Polytech’Lille-IUT « A », Bd Paul Langevin, 59655 Villeneuve d’Ascq cedex, Université Lille Nord de France, France
a b s t r a c t Moringa seeds can be effective in the treatment of water because they contain a cationic electrolyte. They can then replace the sulfate of alumina or other flocculants. In this study, we opted for the clarification of surface water from the river M’Poko using seeds of Moringa oleifera dried and transformed into powder. In the literature, we can find very different quantities of seeds used. We have used a method of experimental design to optimize the treatment of our samples of raw water with the seeds of Moringa. The experimental design used is a full factorial design that determines the importance of various factors and also the relationship between these factors so as to identify the best conditions to meet the target set by this study, which is to clarify a maximum quantity of raw water from the river. Another problem, met in the use of Moringa, is the important contribution of organic matter in the water treated by this natural coagulant. To avoid a bacterial proliferation, in time, in the water so treated, we used sand/coal filtration, which proved to be very effective. The water, treated by Moringa and filtered, possesses turbidity and a quantity of organic matter corresponding to the required standards. Such water can thus, be disinfected by chlorination for human consumption. © 2012 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Keywords: Moringa oleifera; Clarification; Experimental design; Optimization; Filtration; Coagulation; Developing country
1.
Introduction
The presence of undesirable organic or mineral substances causes some problems in obtaining drinking water. These substances are in colloid systems which are stable due to the presence of surface charges and, therefore, surface forces and remove any possibility of elimination by natural setting (Gregory, 1977; Masschelein, 1996). With a population that is growing very fast and in a context of lawlessness, the city of Bangui, capital of the Central African Republic, is experiencing more and more problems relating to drinking water. Indeed, the situation of water supply in urban and semi-urban areas is very precarious. In Bangui the supply rate is only 28%.
∗
However, 72% of the population makes use of other sources of water (traditional wells, rainwater, rivers) which are not clean enough for consumption. Historically, the first coagulants were mineral or vegetable (Gregory and Duan, 2001; Li and Gregory, 1991; Dentel and Gosset, 1987; Jahn, 1999), but the lack of scientific knowledge of their mechanisms of action has led to their replacement by chemicals. Consequently, in some cases, the addition of mineral salts is used and causes the agglomeration of particle that can be removed by decantation or filtration (Alaert and Van Haute, 1981). However, today we need to improve the water quality, because such vegetable coagulants are probably best suited to water treatment in developing countries (Jahn, 1984; Diaz
Corresponding author. Tel.: +33 0 320434934; fax: +33 0 320436963. E-mail address: [email protected] (M. Bigan). Received 29 February 2012; Received in revised form 22 May 2012; Accepted 24 May 2012 0263-8762/$ – see front matter © 2012 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.cherd.2012.05.017
chemical engineering research and design 9 0 ( 2 0 1 2 ) 2346–2352
et al., 1999; Bina et al., 2009). Moringa is a plant with interesting properties (Lürling and Beekman, 2010; Oluduro et al., 2010) and is known to be a natural coagulant since 1979 (Jahn and Dirar, 1979; Berger et al., 1984; Jahn, 1988; Ghebremichael and Gebremedhin, 2011; Yin, 2011; Lea, 2010). Mechanism of coagulation with Moringa oleifera that extracted with distilled water appears to consist of adsorption and neutralization of the colloidal charges. The active agents of the Moringa oleifera seeds have been determined to be cationic peptides that has molecular weight between 6 and 16 kDa (Jahn, 1986; Ndabigengesere and Narasiah, 1998). The aim of this study is not only to optimize the use of Moringa oleifera as a natural coagulant in treatment of surface water (i.e. river M’Poko, Bangui, CAR), but also to eliminate the organic matter accumulated in water treated with Moringa. The advantage of using these seeds of Moringa is to allow the substitution of imported flocculants by a local product which is easily accessible. Therefore it would save substantial foreign exchange for developing countries. On the other hand, this flocculent, unlike alum, is completely biodegradable, which may be interesting in the context of the REACH regulation and sustainable development. Also, the aim of this present work is to study the influence of many factors, such as dose of coagulant, time of stirring, time of decantation on the coagulation performance. The classical way may be to employ the one factor at a time (OFAT) method. Therefore, this method is not only time and energy consuming, but is ineffective in determining the optimal combination of factors due to ignorance of the interaction among them (Mason et al., 2003). The experimental designs method is a better alternative because it includes the influences of individual factors as well as the influences of their interaction with a limited number of planned experiments (Box and Wilson, 1951; Goupy, 1988; Box et al., 1978; Droesbeke et al., 1997; Goupy, 1999). Also for our study, a full factorial design was performed to obtain a high efficiency of water treatment using Moringa as a natural coagulant.
2.
Materials and methods
2.1.
Characteristics of water
This study was performed using water samples taken from the river M’POKO which is the main source of water used by the population of Bangui. The average turbidity of this water is 125 NTU during this study which was performed in the rainy season.
2.2.
Characteristics of the Moringa
Moringa oleifera is a plant that can be grown in all tropical regions except when the temperature drops below 6–8 ◦ C. In Central Africa it is called “Do-ndoko” in the vernacular language. It is used here as a coagulant. Moringa seeds are crushed into fine powder which is used to clarify the water without further modification.
2.3.
Process of water treatment
A solution of Moringa was prepared by weighing of Moringa powder into a beaker containing of distilled water. The mixture in the beaker was stirred to obtain a clear solution. A specific volume of the Moringa solution is added to the water to be treated and the solution was mixed rapidly (100 rpm) for 2 or 5 min; followed by 10 or 20 min of slowly stirring (20 rpm)
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using glass rod to aid in coagulant formation. The suspension was left to stand without disturbance for 30 or 60 min. The supernatants formed were decanted and subjected to turbidity, pH, Oxidation Potential, and coliforms count measurements.
2.4.
Analysis of water
Tests of clarification are made by JLT 6 leaching test jartest (Colin, 1976; Dempsey, 1984). A pH meter (Consort C933) was used to measure the solution pH. Turbidity was measured by the Turdidimeter (2100N, HACH, USA) following the Nephelometric method (standard method 2130B). Suspended Particles (SP) are analyzed by spectrophotometer (DR/2000) and Oxidation Potential (OP) is determined from thermoreactor (FB 15004). Bacterial analysis (coliform, streptococcus and clostridium) are performed by standard methods using petri dishes, membrane filters and programmable autoclaves. These tests are performed on raw water, settled water after treatment by Moringa and filtered water.
2.5.
Filtration process
The filtration is performed on a glass column whose diameter is 3.5 cm and whose height is 42 cm. The column is filled to a height of 24 cm with a mixture of half activated charcoal and sand particles of size 0.2–0.5 mm. At the ends of the column, there are gravel particles of size 2–5 mm, 1 cm and 5 cm at the upper end and lower end respectively. The height of the water column filter is 12 cm. The water filter is kept constant to maintain the same hydraulic load. The water flow is 16 ml per minute.
2.6.
Experimental design
Experimental design was used for detecting more influential factors. Thus, a factorial design can minimize the above difficulties by optimizing all the affecting parameters collectively at the same time (Goupy, 1988). Factorial design is employed to reduce the total number of experiments in order to achieve the best overall optimization of the process. The design determines the effect of each factor on response as well as how the effect of each factor varies with the change in level of the other factors. Interaction effects of different factors could be attained using design of experiments only. Factorial design comprises the greater precision in estimating the overall main factor effects and interactions of different factors. In full factorial design every setting of every factor appears with every setting of every other factor. Factorial designs are strong candidates in examining treatment variations. Instead of conducting a series of independent studies, we can combine these studies into one. A common experimental design is a lot of experience with all input factors set at two-levels each. These levels are called low and high or −1 and +1 respectively. If there are k factors of two levels each, a full factorial design has 2k runs. In the present study, three-factor two-level full factorial design (23 runs) was used for the modeling of the water clarification process by Moringa. In this case three replicates at the center point were added to estimate experimental error. For this study, a concentrated solution of coagulant to 16 g L−1 was prepared. A volume of this solution was added to river water to be treated to a total volume of 900 ml. The mixture is then stirred rapidly and then slowly and finally settled before being analyzed. Factors that have been studied and the
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Table 1 – Coded and natural values of factors. Factors
Level −1
Level +1
Volume of coagulant (ml) Rapid stirring time (min) Slow stirring time (min) Settling time (min)
8 2 10 30
20 5 20 60
Variables X1 X2 X3 X4
relationship between the coded (Xi) and natural variables are shown in Table 1. Experimental design and results concerning the water quality obtained by analysis of this after water treatment by Moringa are shown in Table 2. In order to determine if a relationship existed between the factors and the responses investigated, the collected data was calculated and analyzed statistically using regression analyses. Also, the effects of each factor (or coefficient ˇ) and their interactions are determined from the following mathematical relationship: ˇ = (Xt X)
−1
Xt y
(1)
X is the experiment matrix in coded variables; Xt is the trans−1 posed experiment matrix and (Xt X) is the reverse of the matrix product of Xt by X, y is the matrix of the answers. The experimental design allows a mathematical modeling where the responses (y) can be predicted as a first-order polynomial equation according as follow:
y = ˇo +
ˇi Xi +
i
ˇij Xi Xj + ε
(2)
ij
ˇi is the coefficient of the effect of factor i, ˇij is the coefficient of interaction between factors i and j, and ε experimental error. The coefficient parameters were estimated using a multiple linear regression analysis employing Modde software (Modde5, Umetri, 2000) and to demonstrate the 3D surface contour plots of the response models.
3.
Results and discussion
3.1. Optimization of the method of clarifying water by Moringa Table 3 summarizes the results of the effects of each factors and possible interactions between them. The models are found to be significant at 95% confidence level by the F-test and the coefficients R2 of models are above 0.99 indicating that over 99% of the data could be explained by the model. The p-value is used as a tool to check the significance of each factor and interaction between factors. The larger the magnitude of F-value and, correspondingly, the smaller the p > F, the more significant are the corresponding model and the individual coefficient. The quality of water for consumption must meet the standards that require: turbidity equal to 2 NTU, pH between 6.5 and 8.5, SP equal to 0 mg L−1 , NTU yield the lowest possible and SP yield the highest possible. Overall we can see that for all responses the most important factors are X1 and X3 with interactions between X1X2 and X2X3, because a p-value less than 0.05 indicates that the effect is significant and the smaller p-value expresses the more significant effect (Table 3). In all cases, the factor X4 is insignificant. It should then set the parameter to the lowest level, thus settling time as small as possible (30 min). Fig. 1 illustrates the 3D response surface plots of the first order polynomial model for all responses of the experimental design. These figures show that taking into account the interaction between X2 and X3, the quantity of Moringa (X1) varies either at the lowest level (a) or the highest level (b) and factor X4 is maintained at 30 min.
Table 2 – Experimental design in coded unit and results obtained. Run 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
X1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 0 0 0
X2 −1 −1 +1 +1 −1 −1 +1 +1 −1 −1 +1 +1 −1 −1 +1 +1 0 0 0
X3 −1 −1 −1 −1 +1 +1 +1 +1 −1 −1 −1 −1 +1 +1 +1 +1 0 0 0
X4 −1 −1 −1 −1 −1 −1 −1 −1 +1 +1 +1 +1 +1 +1 +1 +1 0 0 0
R1 Turbidity
R2 SP
R3 pH
R4 Yield Turbidity
R5 Yield SP
3.53 56.7 4.73 8.74 3.54 5.28 5.97 9.99 2.38 57.7 2.6 4.32 1.96 1.95 1.64 9.41 4.02 1.93 1.83
5 16 16 15 9 14 5 3 4 18 8 13 7 11 4 4 11 16 10
7.14 7.06 7.08 7.09 7.06 7.07 7.39 7.03 7.16 7.1 7.08 7.05 7.23 7.2 7.55 7.01 7.36 7.34 7.35
97.1 52.7 96.1 92.7 97.1 95.6 95.1 91.9 98 51.8 97.8 96.4 98.4 98.4 98.7 92.3 96.7 98.4 98.5
83.33 46.66 56.75 59.45 75.67 62.16 83.87 90.32 86.66 40 78.37 64.86 81.08 70.02 87.09 87.09 63.33 46.66 66.66
With R1: Turbidity (NTU); R2: SP (mg L−1 ); R3: pH; R4 Yield Turbidity (%); R5: Yield SP (%).
chemical engineering research and design 9 0 ( 2 0 1 2 ) 2346–2352
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Fig. 1 – 3D surface contour plots for each response using (a) Moringa low and (b) the high level Moringa. It is found that, for turbidity, the greater the amount of Moringa the more turbidity increases. A with low concentration of Moringa slow, stirring time must be the shortest while rapid stirring time has no effect for a turbidity <2 NTU. Concerning the rate of SP, we can notice that the increase in the amount of Moringa increase the rate of SP. To have the lowest
rate of SP possible we must have the shortest rapid stirring time possible while the low stirring time has no effect. For the pH response, we note that, whatever the experimental conditions pH values meet the standards as they are between 6.5 and 8.5. The rate of reduction in turbidity must be near 100%. We find it unnecessary to use a large quantity of Moringa.
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0.869 0.995 0.978
0.00E+00 0.0015 0.01 0.8171 0.6605 0.0018 0.087 0.0304 0.0116 0.0215 0.0293 0.959 0.998 0.993
1.72 0.86 1.92 1.92 0.86 0.86 0.86 0.7 1.92 0.86 0.86 64.99 −9.61 10.98 0.48 −0.41 9.06 2.15 −2.72 10.63 3.79 −3.38 0.474 0.985 0.936 0.788 0.993 0.969
0.02 0.01 0.03 0.03 0.01 0.01 0.01 0.01 0.03 0.01 0.01 7.35 −0.13 −0.19 0.26 0.02 0.01 −0.11 −0.01 −0.17 −0.01 0.02 10.5 2.87 −2 −1.37 0.12 −2.62 −0.75 0.91 −3.12 −1.37 1.25
0.961 0.998 0.993
0.0768 0.0001 0.093 0.0012 0.3344 0.0001 0.263 0.5517 0.001 0.2426 0.7347 1.1 0.55 1.23 1.23 0.55 0.55 0.55 0.45 1.23 0.55 0.55
Fig. 2 – Evolution of the turbidity depending on water quality.
Under these conditions the rapid stirring time may be at the lowest level and the slow stirring time should be at the highest level. Similarly, the amount of Moringa should not be too large in order to have a high rate of SP, but, in this case, the rapid and slow stirring times should be as low as possible. These results indicate that Moringa allows clarification of water from for river M’POKO by suppression of the effect of turbidity and organic matter concentration. The optimization of the process of clarification leads to setting the parameters to the following conditions: the use of a volume of 8 ml of solution concentration Moringa 16 g L−1 , a rapid stirring time of 5 min followed by slow stirring time for 10 min, and, finally a settling time of 30 min.
3.2. Reduction of organic matter in water treatment with Moringa The optimization confirmed the properties of Moringa as a coagulant agent because it allows water clarification. However, Moringa seeds contain oil and organic matter. This organic matter promotes bacterial growth in water (Jahn, 1988). Moreover, it is not advisable to use a chlorine treatment to disinfect water because it reacts with natural organic matter. To reduce the organic matter the filtering process described in the materials and methods will be applied after treatment of water by the Moringa in the conditions found by the experimental design. For this last step, a positively charged nanofiltration membrane can also be used; it has the advantage of eliminating the cationic compounds (Sun et al., 2011). Also, the evolution of turbidity, Oxidation Potential (OP) and bacterial populations were studied in the different phases of processing samples of M’POKO river water: raw water (RW), settled water after treatment with Moringa (SW), then filtered water after treatment (FW).
3.2.1.
Q2 R2 R2 Adj.
2.92 15.03 3 −14.66 −0.63 −12.84 0.75 0.3 15.49 −0.8 0.2 Constant X1 X2 X3 X4 X1X2 X1X3 X1X4 X2X3 X2X4 X3X4
p Coef.
0.66 0.33 0.74 0.74 0.33 0.33 0.33 0.27 0.74 0.33 0.33
0.0005 0.0032 0.0748 0.1622 0.7326 0.0042 0.1099 0.0434 0.0247 0.0258 0.0331
0.00E+00 0.003 0.0099 0.0043 0.1916 0.3877 0.0051 0.2638 0.0133 0.4626 0.2277
97.6 −12.52 −2.47 12.27 0.49 10.72 −0.59 −0.25 −12.9 0.67 −0.17
0.93 0.46 1.04 1.04 0.46 0.46 0.46 0.38 1.04 0.46 0.46
0.00E+00 0.0001 0.0986 0.0013 0.363 0.0001 0.2893 0.559 0.0011 0.2443 0.7329
Std. err. Coef. p Std. err. Std. err. Coef. p Std. err. Std. err.
Coef.
SP (mg L−1 ) Turbidity (NTU)
Table 3 – Effect of factors and interactions for each response.
pH
p
Coef.
Yield turbidity (%)
Yield SP (%)
p
chemical engineering research and design 9 0 ( 2 0 1 2 ) 2346–2352
Evolution of turbidity
The evolution of turbidity was determined on water samples of different quality five times (run 1–5) as shown in Fig. 2. We can observe a very significant reduction in turbidity after treatment with Moringa (2.2 NTU), but it is still lower by step filtration (0.3 NTU). These two values respected the regulations on the quality of water intended for consumption (≤2 NTU). For initial turbidity of 121 NTU the rate of reduction of the
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Table 4 – Comparison of the M’Poko water treated by the Moringa oleifera and treated by Aluminum sulfate and standards. Water
RW
SW Turbidity (NTU) Suspended Particles (mg L−1 ) Oxidation Potential (mg L−1 O2 ) Ph Escherichia coli (UFC ml−1 ) Streptococci (UFC ml−1 )
121.1 23 3.3 8.23 200 6.8
Moringa (16 g L−1 )
Aluminum sulfate (20 g L−1 )
3.35 5 6.1 4.85 1 0
FW
SW
1.04 1 5.4 4.62 2 0
2.2 5 15.11 7.45 102.4 2.6
Standards
FW 1.72 1 4.2 7.4 102 0.6
≤5 0 ≤5 6.5–8.5 0 0
RW: Raw Water, SW: Settled Water, FW: Filtered Water.
turbidity is 98% for settled water after treatment with Moringa and 99.75% after filtration.
3.2.2.
Evolution of organic matter
Oxidation Potential (OP) by potassium permangante aims to determine the content of organic matter in water. It is expressed in mg L−1 of oxygen. This value corresponds to a conventional measure for evaluating the contamination of organic matter from a water sample. A high IP value indicates that there is a high quantity of organic matter present in water. Fig. 3 shows that the treatment of water by the Moringa introduced a quantity of organic matter (15 mg L−1 ) compared to the analysis of the raw water (3.4 mg L−1 ). However, after filtering, the IP value falls to 1.3 mg L−1 which is to conform with regulations on the water consumption that provides a value of ≤5 mg L−1 .
Fig. 4 – Evolution of the bacterial population based on water quality.
4. 3.2.3.
Evolution of bacterial population
Bacterial analysis carried out on the water are often the determination of Streptococci, Escherichia coli and Clostridium. Fig. 4 shows the water contamination by these bacteria according to the treatment used. One can notice a significant drop in bacterial contamination only after treatment with Moringa followed by settling. Clarification of water by the Moringa can, therefore, eliminate 62% of streptococci, 95% clostridium and 47% of Escherichia coli. However, the filtration step can still improve these results.
Conclusion
The process of coagulation–flocculation is necessary in the treatment of water. This work has demonstrated that a natural coagulant can be used in the process of clarifying the water with high efficiency (shown in Table 4). The application of method of experimental design was used to evaluate the effect of coagulant, but also to determine the optimum conditions. These conditions indicate that the volume of 8 ml solution of coagulant concentration of 16 g L−1 must be added to the amount of contaminated water and that the fast and slow stirring times must be 5 and 10 min respectively. This demonstrates that experimental design can be successfully applied for modeling and optimizing the coagulation process and it is thre economical way of obtaining the maximum amount of information in a short period of time and with the least number of experiments. Treatment with Moringa is effective on the clarification of water, but the filtration step is necessary to remove organic matter introduced by the coagulant. However, the use of an effective natural coagulant, such as Moringa, avoids the use of chemicals, and is more compatible with environmental issues.
References
Fig. 3 – Evolution of oxidability as function of water quality.
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Contribution to the clarification of surface water from the Moringa oleifera: Case M’Poko River to Bangui, Central African Republic Nicole Poumaye a , Joseph Mabingui a , Pierre Lutgen b , Muriel Bigan c,∗ a
Laboratoire d’Hydrosciences Lavoisier, Chaire UNESCO sur la gestion de l’eau, Faculté des Sciences, Université de Bangui, B.P.908 Bangui, Centrafrique, Central African Republic b Iwerliewen Fier Bedreete Volleker (IFBV), Luxembourg c Laboratoire ProBioGem, EA1026, Polytech’Lille-IUT « A », Bd Paul Langevin, 59655 Villeneuve d’Ascq cedex, Université Lille Nord de France, France
a b s t r a c t Moringa seeds can be effective in the treatment of water because they contain a cationic electrolyte. They can then replace the sulfate of alumina or other flocculants. In this study, we opted for the clarification of surface water from the river M’Poko using seeds of Moringa oleifera dried and transformed into powder. In the literature, we can find very different quantities of seeds used. We have used a method of experimental design to optimize the treatment of our samples of raw water with the seeds of Moringa. The experimental design used is a full factorial design that determines the importance of various factors and also the relationship between these factors so as to identify the best conditions to meet the target set by this study, which is to clarify a maximum quantity of raw water from the river. Another problem, met in the use of Moringa, is the important contribution of organic matter in the water treated by this natural coagulant. To avoid a bacterial proliferation, in time, in the water so treated, we used sand/coal filtration, which proved to be very effective. The water, treated by Moringa and filtered, possesses turbidity and a quantity of organic matter corresponding to the required standards. Such water can thus, be disinfected by chlorination for human consumption. © 2012 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Keywords: Moringa oleifera; Clarification; Experimental design; Optimization; Filtration; Coagulation; Developing country
1.
Introduction
The presence of undesirable organic or mineral substances causes some problems in obtaining drinking water. These substances are in colloid systems which are stable due to the presence of surface charges and, therefore, surface forces and remove any possibility of elimination by natural setting (Gregory, 1977; Masschelein, 1996). With a population that is growing very fast and in a context of lawlessness, the city of Bangui, capital of the Central African Republic, is experiencing more and more problems relating to drinking water. Indeed, the situation of water supply in urban and semi-urban areas is very precarious. In Bangui the supply rate is only 28%.
∗
However, 72% of the population makes use of other sources of water (traditional wells, rainwater, rivers) which are not clean enough for consumption. Historically, the first coagulants were mineral or vegetable (Gregory and Duan, 2001; Li and Gregory, 1991; Dentel and Gosset, 1987; Jahn, 1999), but the lack of scientific knowledge of their mechanisms of action has led to their replacement by chemicals. Consequently, in some cases, the addition of mineral salts is used and causes the agglomeration of particle that can be removed by decantation or filtration (Alaert and Van Haute, 1981). However, today we need to improve the water quality, because such vegetable coagulants are probably best suited to water treatment in developing countries (Jahn, 1984; Diaz
Corresponding author. Tel.: +33 0 320434934; fax: +33 0 320436963. E-mail address: [email protected] (M. Bigan). Received 29 February 2012; Received in revised form 22 May 2012; Accepted 24 May 2012 0263-8762/$ – see front matter © 2012 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.cherd.2012.05.017
chemical engineering research and design 9 0 ( 2 0 1 2 ) 2346–2352
et al., 1999; Bina et al., 2009). Moringa is a plant with interesting properties (Lürling and Beekman, 2010; Oluduro et al., 2010) and is known to be a natural coagulant since 1979 (Jahn and Dirar, 1979; Berger et al., 1984; Jahn, 1988; Ghebremichael and Gebremedhin, 2011; Yin, 2011; Lea, 2010). Mechanism of coagulation with Moringa oleifera that extracted with distilled water appears to consist of adsorption and neutralization of the colloidal charges. The active agents of the Moringa oleifera seeds have been determined to be cationic peptides that has molecular weight between 6 and 16 kDa (Jahn, 1986; Ndabigengesere and Narasiah, 1998). The aim of this study is not only to optimize the use of Moringa oleifera as a natural coagulant in treatment of surface water (i.e. river M’Poko, Bangui, CAR), but also to eliminate the organic matter accumulated in water treated with Moringa. The advantage of using these seeds of Moringa is to allow the substitution of imported flocculants by a local product which is easily accessible. Therefore it would save substantial foreign exchange for developing countries. On the other hand, this flocculent, unlike alum, is completely biodegradable, which may be interesting in the context of the REACH regulation and sustainable development. Also, the aim of this present work is to study the influence of many factors, such as dose of coagulant, time of stirring, time of decantation on the coagulation performance. The classical way may be to employ the one factor at a time (OFAT) method. Therefore, this method is not only time and energy consuming, but is ineffective in determining the optimal combination of factors due to ignorance of the interaction among them (Mason et al., 2003). The experimental designs method is a better alternative because it includes the influences of individual factors as well as the influences of their interaction with a limited number of planned experiments (Box and Wilson, 1951; Goupy, 1988; Box et al., 1978; Droesbeke et al., 1997; Goupy, 1999). Also for our study, a full factorial design was performed to obtain a high efficiency of water treatment using Moringa as a natural coagulant.
2.
Materials and methods
2.1.
Characteristics of water
This study was performed using water samples taken from the river M’POKO which is the main source of water used by the population of Bangui. The average turbidity of this water is 125 NTU during this study which was performed in the rainy season.
2.2.
Characteristics of the Moringa
Moringa oleifera is a plant that can be grown in all tropical regions except when the temperature drops below 6–8 ◦ C. In Central Africa it is called “Do-ndoko” in the vernacular language. It is used here as a coagulant. Moringa seeds are crushed into fine powder which is used to clarify the water without further modification.
2.3.
Process of water treatment
A solution of Moringa was prepared by weighing of Moringa powder into a beaker containing of distilled water. The mixture in the beaker was stirred to obtain a clear solution. A specific volume of the Moringa solution is added to the water to be treated and the solution was mixed rapidly (100 rpm) for 2 or 5 min; followed by 10 or 20 min of slowly stirring (20 rpm)
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using glass rod to aid in coagulant formation. The suspension was left to stand without disturbance for 30 or 60 min. The supernatants formed were decanted and subjected to turbidity, pH, Oxidation Potential, and coliforms count measurements.
2.4.
Analysis of water
Tests of clarification are made by JLT 6 leaching test jartest (Colin, 1976; Dempsey, 1984). A pH meter (Consort C933) was used to measure the solution pH. Turbidity was measured by the Turdidimeter (2100N, HACH, USA) following the Nephelometric method (standard method 2130B). Suspended Particles (SP) are analyzed by spectrophotometer (DR/2000) and Oxidation Potential (OP) is determined from thermoreactor (FB 15004). Bacterial analysis (coliform, streptococcus and clostridium) are performed by standard methods using petri dishes, membrane filters and programmable autoclaves. These tests are performed on raw water, settled water after treatment by Moringa and filtered water.
2.5.
Filtration process
The filtration is performed on a glass column whose diameter is 3.5 cm and whose height is 42 cm. The column is filled to a height of 24 cm with a mixture of half activated charcoal and sand particles of size 0.2–0.5 mm. At the ends of the column, there are gravel particles of size 2–5 mm, 1 cm and 5 cm at the upper end and lower end respectively. The height of the water column filter is 12 cm. The water filter is kept constant to maintain the same hydraulic load. The water flow is 16 ml per minute.
2.6.
Experimental design
Experimental design was used for detecting more influential factors. Thus, a factorial design can minimize the above difficulties by optimizing all the affecting parameters collectively at the same time (Goupy, 1988). Factorial design is employed to reduce the total number of experiments in order to achieve the best overall optimization of the process. The design determines the effect of each factor on response as well as how the effect of each factor varies with the change in level of the other factors. Interaction effects of different factors could be attained using design of experiments only. Factorial design comprises the greater precision in estimating the overall main factor effects and interactions of different factors. In full factorial design every setting of every factor appears with every setting of every other factor. Factorial designs are strong candidates in examining treatment variations. Instead of conducting a series of independent studies, we can combine these studies into one. A common experimental design is a lot of experience with all input factors set at two-levels each. These levels are called low and high or −1 and +1 respectively. If there are k factors of two levels each, a full factorial design has 2k runs. In the present study, three-factor two-level full factorial design (23 runs) was used for the modeling of the water clarification process by Moringa. In this case three replicates at the center point were added to estimate experimental error. For this study, a concentrated solution of coagulant to 16 g L−1 was prepared. A volume of this solution was added to river water to be treated to a total volume of 900 ml. The mixture is then stirred rapidly and then slowly and finally settled before being analyzed. Factors that have been studied and the
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Table 1 – Coded and natural values of factors. Factors
Level −1
Level +1
Volume of coagulant (ml) Rapid stirring time (min) Slow stirring time (min) Settling time (min)
8 2 10 30
20 5 20 60
Variables X1 X2 X3 X4
relationship between the coded (Xi) and natural variables are shown in Table 1. Experimental design and results concerning the water quality obtained by analysis of this after water treatment by Moringa are shown in Table 2. In order to determine if a relationship existed between the factors and the responses investigated, the collected data was calculated and analyzed statistically using regression analyses. Also, the effects of each factor (or coefficient ˇ) and their interactions are determined from the following mathematical relationship: ˇ = (Xt X)
−1
Xt y
(1)
X is the experiment matrix in coded variables; Xt is the trans−1 posed experiment matrix and (Xt X) is the reverse of the matrix product of Xt by X, y is the matrix of the answers. The experimental design allows a mathematical modeling where the responses (y) can be predicted as a first-order polynomial equation according as follow:
y = ˇo +
ˇi Xi +
i
ˇij Xi Xj + ε
(2)
ij
ˇi is the coefficient of the effect of factor i, ˇij is the coefficient of interaction between factors i and j, and ε experimental error. The coefficient parameters were estimated using a multiple linear regression analysis employing Modde software (Modde5, Umetri, 2000) and to demonstrate the 3D surface contour plots of the response models.
3.
Results and discussion
3.1. Optimization of the method of clarifying water by Moringa Table 3 summarizes the results of the effects of each factors and possible interactions between them. The models are found to be significant at 95% confidence level by the F-test and the coefficients R2 of models are above 0.99 indicating that over 99% of the data could be explained by the model. The p-value is used as a tool to check the significance of each factor and interaction between factors. The larger the magnitude of F-value and, correspondingly, the smaller the p > F, the more significant are the corresponding model and the individual coefficient. The quality of water for consumption must meet the standards that require: turbidity equal to 2 NTU, pH between 6.5 and 8.5, SP equal to 0 mg L−1 , NTU yield the lowest possible and SP yield the highest possible. Overall we can see that for all responses the most important factors are X1 and X3 with interactions between X1X2 and X2X3, because a p-value less than 0.05 indicates that the effect is significant and the smaller p-value expresses the more significant effect (Table 3). In all cases, the factor X4 is insignificant. It should then set the parameter to the lowest level, thus settling time as small as possible (30 min). Fig. 1 illustrates the 3D response surface plots of the first order polynomial model for all responses of the experimental design. These figures show that taking into account the interaction between X2 and X3, the quantity of Moringa (X1) varies either at the lowest level (a) or the highest level (b) and factor X4 is maintained at 30 min.
Table 2 – Experimental design in coded unit and results obtained. Run 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
X1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 −1 +1 0 0 0
X2 −1 −1 +1 +1 −1 −1 +1 +1 −1 −1 +1 +1 −1 −1 +1 +1 0 0 0
X3 −1 −1 −1 −1 +1 +1 +1 +1 −1 −1 −1 −1 +1 +1 +1 +1 0 0 0
X4 −1 −1 −1 −1 −1 −1 −1 −1 +1 +1 +1 +1 +1 +1 +1 +1 0 0 0
R1 Turbidity
R2 SP
R3 pH
R4 Yield Turbidity
R5 Yield SP
3.53 56.7 4.73 8.74 3.54 5.28 5.97 9.99 2.38 57.7 2.6 4.32 1.96 1.95 1.64 9.41 4.02 1.93 1.83
5 16 16 15 9 14 5 3 4 18 8 13 7 11 4 4 11 16 10
7.14 7.06 7.08 7.09 7.06 7.07 7.39 7.03 7.16 7.1 7.08 7.05 7.23 7.2 7.55 7.01 7.36 7.34 7.35
97.1 52.7 96.1 92.7 97.1 95.6 95.1 91.9 98 51.8 97.8 96.4 98.4 98.4 98.7 92.3 96.7 98.4 98.5
83.33 46.66 56.75 59.45 75.67 62.16 83.87 90.32 86.66 40 78.37 64.86 81.08 70.02 87.09 87.09 63.33 46.66 66.66
With R1: Turbidity (NTU); R2: SP (mg L−1 ); R3: pH; R4 Yield Turbidity (%); R5: Yield SP (%).
chemical engineering research and design 9 0 ( 2 0 1 2 ) 2346–2352
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Fig. 1 – 3D surface contour plots for each response using (a) Moringa low and (b) the high level Moringa. It is found that, for turbidity, the greater the amount of Moringa the more turbidity increases. A with low concentration of Moringa slow, stirring time must be the shortest while rapid stirring time has no effect for a turbidity <2 NTU. Concerning the rate of SP, we can notice that the increase in the amount of Moringa increase the rate of SP. To have the lowest
rate of SP possible we must have the shortest rapid stirring time possible while the low stirring time has no effect. For the pH response, we note that, whatever the experimental conditions pH values meet the standards as they are between 6.5 and 8.5. The rate of reduction in turbidity must be near 100%. We find it unnecessary to use a large quantity of Moringa.
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0.869 0.995 0.978
0.00E+00 0.0015 0.01 0.8171 0.6605 0.0018 0.087 0.0304 0.0116 0.0215 0.0293 0.959 0.998 0.993
1.72 0.86 1.92 1.92 0.86 0.86 0.86 0.7 1.92 0.86 0.86 64.99 −9.61 10.98 0.48 −0.41 9.06 2.15 −2.72 10.63 3.79 −3.38 0.474 0.985 0.936 0.788 0.993 0.969
0.02 0.01 0.03 0.03 0.01 0.01 0.01 0.01 0.03 0.01 0.01 7.35 −0.13 −0.19 0.26 0.02 0.01 −0.11 −0.01 −0.17 −0.01 0.02 10.5 2.87 −2 −1.37 0.12 −2.62 −0.75 0.91 −3.12 −1.37 1.25
0.961 0.998 0.993
0.0768 0.0001 0.093 0.0012 0.3344 0.0001 0.263 0.5517 0.001 0.2426 0.7347 1.1 0.55 1.23 1.23 0.55 0.55 0.55 0.45 1.23 0.55 0.55
Fig. 2 – Evolution of the turbidity depending on water quality.
Under these conditions the rapid stirring time may be at the lowest level and the slow stirring time should be at the highest level. Similarly, the amount of Moringa should not be too large in order to have a high rate of SP, but, in this case, the rapid and slow stirring times should be as low as possible. These results indicate that Moringa allows clarification of water from for river M’POKO by suppression of the effect of turbidity and organic matter concentration. The optimization of the process of clarification leads to setting the parameters to the following conditions: the use of a volume of 8 ml of solution concentration Moringa 16 g L−1 , a rapid stirring time of 5 min followed by slow stirring time for 10 min, and, finally a settling time of 30 min.
3.2. Reduction of organic matter in water treatment with Moringa The optimization confirmed the properties of Moringa as a coagulant agent because it allows water clarification. However, Moringa seeds contain oil and organic matter. This organic matter promotes bacterial growth in water (Jahn, 1988). Moreover, it is not advisable to use a chlorine treatment to disinfect water because it reacts with natural organic matter. To reduce the organic matter the filtering process described in the materials and methods will be applied after treatment of water by the Moringa in the conditions found by the experimental design. For this last step, a positively charged nanofiltration membrane can also be used; it has the advantage of eliminating the cationic compounds (Sun et al., 2011). Also, the evolution of turbidity, Oxidation Potential (OP) and bacterial populations were studied in the different phases of processing samples of M’POKO river water: raw water (RW), settled water after treatment with Moringa (SW), then filtered water after treatment (FW).
3.2.1.
Q2 R2 R2 Adj.
2.92 15.03 3 −14.66 −0.63 −12.84 0.75 0.3 15.49 −0.8 0.2 Constant X1 X2 X3 X4 X1X2 X1X3 X1X4 X2X3 X2X4 X3X4
p Coef.
0.66 0.33 0.74 0.74 0.33 0.33 0.33 0.27 0.74 0.33 0.33
0.0005 0.0032 0.0748 0.1622 0.7326 0.0042 0.1099 0.0434 0.0247 0.0258 0.0331
0.00E+00 0.003 0.0099 0.0043 0.1916 0.3877 0.0051 0.2638 0.0133 0.4626 0.2277
97.6 −12.52 −2.47 12.27 0.49 10.72 −0.59 −0.25 −12.9 0.67 −0.17
0.93 0.46 1.04 1.04 0.46 0.46 0.46 0.38 1.04 0.46 0.46
0.00E+00 0.0001 0.0986 0.0013 0.363 0.0001 0.2893 0.559 0.0011 0.2443 0.7329
Std. err. Coef. p Std. err. Std. err. Coef. p Std. err. Std. err.
Coef.
SP (mg L−1 ) Turbidity (NTU)
Table 3 – Effect of factors and interactions for each response.
pH
p
Coef.
Yield turbidity (%)
Yield SP (%)
p
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Evolution of turbidity
The evolution of turbidity was determined on water samples of different quality five times (run 1–5) as shown in Fig. 2. We can observe a very significant reduction in turbidity after treatment with Moringa (2.2 NTU), but it is still lower by step filtration (0.3 NTU). These two values respected the regulations on the quality of water intended for consumption (≤2 NTU). For initial turbidity of 121 NTU the rate of reduction of the
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Table 4 – Comparison of the M’Poko water treated by the Moringa oleifera and treated by Aluminum sulfate and standards. Water
RW
SW Turbidity (NTU) Suspended Particles (mg L−1 ) Oxidation Potential (mg L−1 O2 ) Ph Escherichia coli (UFC ml−1 ) Streptococci (UFC ml−1 )
121.1 23 3.3 8.23 200 6.8
Moringa (16 g L−1 )
Aluminum sulfate (20 g L−1 )
3.35 5 6.1 4.85 1 0
FW
SW
1.04 1 5.4 4.62 2 0
2.2 5 15.11 7.45 102.4 2.6
Standards
FW 1.72 1 4.2 7.4 102 0.6
≤5 0 ≤5 6.5–8.5 0 0
RW: Raw Water, SW: Settled Water, FW: Filtered Water.
turbidity is 98% for settled water after treatment with Moringa and 99.75% after filtration.
3.2.2.
Evolution of organic matter
Oxidation Potential (OP) by potassium permangante aims to determine the content of organic matter in water. It is expressed in mg L−1 of oxygen. This value corresponds to a conventional measure for evaluating the contamination of organic matter from a water sample. A high IP value indicates that there is a high quantity of organic matter present in water. Fig. 3 shows that the treatment of water by the Moringa introduced a quantity of organic matter (15 mg L−1 ) compared to the analysis of the raw water (3.4 mg L−1 ). However, after filtering, the IP value falls to 1.3 mg L−1 which is to conform with regulations on the water consumption that provides a value of ≤5 mg L−1 .
Fig. 4 – Evolution of the bacterial population based on water quality.
4. 3.2.3.
Evolution of bacterial population
Bacterial analysis carried out on the water are often the determination of Streptococci, Escherichia coli and Clostridium. Fig. 4 shows the water contamination by these bacteria according to the treatment used. One can notice a significant drop in bacterial contamination only after treatment with Moringa followed by settling. Clarification of water by the Moringa can, therefore, eliminate 62% of streptococci, 95% clostridium and 47% of Escherichia coli. However, the filtration step can still improve these results.
Conclusion
The process of coagulation–flocculation is necessary in the treatment of water. This work has demonstrated that a natural coagulant can be used in the process of clarifying the water with high efficiency (shown in Table 4). The application of method of experimental design was used to evaluate the effect of coagulant, but also to determine the optimum conditions. These conditions indicate that the volume of 8 ml solution of coagulant concentration of 16 g L−1 must be added to the amount of contaminated water and that the fast and slow stirring times must be 5 and 10 min respectively. This demonstrates that experimental design can be successfully applied for modeling and optimizing the coagulation process and it is thre economical way of obtaining the maximum amount of information in a short period of time and with the least number of experiments. Treatment with Moringa is effective on the clarification of water, but the filtration step is necessary to remove organic matter introduced by the coagulant. However, the use of an effective natural coagulant, such as Moringa, avoids the use of chemicals, and is more compatible with environmental issues.
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Fig. 3 – Evolution of oxidability as function of water quality.
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