Surfactant-polluted surface water treatment with Moringa oleifera seed extract
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Surfactant-polluted surface water treatment with Moringa oleifera seed extract J. Sánchez-Martín*, J. Beltrán-Heredia** *Universidad de Extremadura, Department of Chemical Engineering and Physical Chemistry, Avda. de Elvas, s/n, 06071 Badajoz, Spain. Tel: +34 924289 300 Ext: 9033 Fax: +34 924289385 E-mail: jsanmar@unex.es **Universidad de Extremadura, Department of Chemical Engineering and Physical Chemistry, Avda. de Elvas, s/n, 06071 Badajoz, Spain. E-mail: jbelther@unex.es Abstract: Moringa oleifera seed extract has been tested in removing surfactants from polluted surface water. River water has been polluted with sodium lauryl sulphate, a spread surfactant, and Jar-test have been carried out in order to evaluate the efficiency of this natural coagulant agent inside a real surface water matrix. Efficiency has demonstrated to be very high (maximum q of about 2.5 mmol·g−1) and a high surfactant removal is achieved rapidly. Coagulation process may be modelated through Gu and Zhu adsorption hypothesis, so an acceptable r2coefficient is obtained (0.94). Keywords: Moringa oleifera, surfactants, coagulation-flocculation, natural flocculants 1 Introduction Surfactants dumping into the environment has become one of the main concerns in water treatment. Due to the main role in some of the most important fields of soft chemical technology (cosmetics, pharmaceuticals, personal care products…) surfactants have achieved a relevant position in human activity. More than 15 million tonnes per year are used (Edser, 2008), so surfactant-induced pollution is considered a main task to research on (Matthijs et al., 1995). Surfactant presence into surface water, such as rivers or lakes, may lead to a harmful situation for aquatic flora and fauna, due to the fact that may interact with oxygen transfer (Wagner and Pöpel, 1996) by modifying surface tension. Binding ability of these products with other dangerous substances (such as pharmaceuticals) is another hazardous property that may damage environmental equilibrium. Due to these reasons, removing surfactants from water flows has become a priority of a large number of researchers. Nowadays, surfactants can be removed by several mechanisms, most of them imply adsorption on activated carbon, chemical association or chemical degradation. However, new removal methods should be researched on because surfactants and tensioactives impact is high enough. In this sense, we have been researching on Moringa oleifera as a water treatment agent for several years. As a tropical multi-purpose tree, Moringa oleifera is very interesting from the point of view of developing cooperation, as it is a widespread, easy-available water treatment method. The use of Moringa oleifera as water treatment can imply two different ways: a) One concerning its usage as a primary source of activated carbon and b) Another one through seed extraction, whose product works as a coagulant/flocculant agent (Okuda et al., 1999). Last method is rather more effective and accurate, and it replies better to its application in developing countries. Its power lays on the fact that it is not technologically difficult to operate by non-qualified personal, it is easy to work with and it presents not an external dependency of reagents, as it would happen with other products (Al2(SO4)3, FeCl3...). Because of those reasons, it has been recommended by the Food and Agricultural Organization (FAO) as a proper and advisable way for treating water. The main aim of the current investigation is to research on the ability of Moringa oleifera in removing sodium lauryl sulphate (SLS) from a real surface water matrix such as river water. The structure of this surfactant (m.w. 288.38 g mol−1) is showed in Figure 1. Surfactant association with turbidity (humic and fulvic substances) may affect the way SLS-Moringa oleifera coagulation is carried out. Water Practice & Technology Vol 5 No 1 © IWA Publishing 2010 doi: 10.2166/WPT.2010.001
Figure 1: Chemical structure for sodium lauryl sulphate.
2 Materials and methods
2.1 Surface water
It was taken from Guadiana river, at Badajoz (Southwest of Spain, Extremadura Community) in
winter (year 2008). It is pretended with this decision to study the problem from a real point of
view, avoiding turbid water simulation with different chemical-physical procedure such as
kaolin addition (Ghebremichael, 2004). River water was treated the same day it was collected,
and its average characteristics are showed in Table 1.
Table 1: Raw water characterization data
Parameter Units Value
pH 7.5
Conductivity µS cm−1 400
Suspended solids mg L−1 15
Total solids mg L−1 452
Turbidity NTU 123.3
Calcium Ca mg L−1
2+ 37.7
Hardness CaCO3 mg L−1 152
Ammonium N mg L−1 1.81
Nitrate N mg L−1 1.20
Nitrite N mg L−1 0.033
Chloride Cl‐ mg L−1 40.4
KMnO4 oxidability O2 mg L−1 19.3
Phosphate P mg L−1 0.044
Total phosphorus P mg L−1 0.064
Total coliforms Colonies per 100 mL 800
Fecal coliforms Colonies per 100 mL 400
Fecal streptococcus Colonies per 100 mL 140
2.2 Moringa oleifera seed extraction
Seeds were obtained from SETROPA (Holland). The extraction process was carried out in
the following way: seeds were reduced into powder by a domestic mill. A 1M NaCl
(PANREAC) solution was prepared and 5 g of powder were put into 100 mL of it. The NaCl
solution with powder was stirred for 30 minutes time at room temperature (around 25ºC). No
pH modification was needed, as natural pH 7 was achieved. Then, the extract was filtered
twice: once through commercial filter paper on Büchner funnel and once again through a fine
filtering millipore system (0.45 µm glass fiber). The result is a clear, milky-like liquid. The
average composition of this extract is referred in Table 2.
2Table 2: Seed extract characterization.
Parameter Units Value
Dry residue (NaCl excluded) g∙L‐1 3.24
Ammonium N g L‐1 0.06
Nitrate N g L‐1 0.55
Nitrite N g L‐1 0
KMnO4 oxidability O2 g L‐1 1.08
Phosphate P g L‐1 0.05
Total phosphorus P g L‐1 0.07
Isoelectric point (pI)a 10‐11
Molecular weightb kDa 6.5‐14
a
(Kwaambwa and Maikokera, 2007).
b
(Ndabigengesere et al., 1995).
2.3 Jar-test procedure
500 mg·L−1 of sodium lauryl sulphate (ALDRICH) stock solution was prepared. Different
volumes of this stock solution were put into recipients, and controlled quantity of coagulant was
added. Final volume was reached with surface water. A soft blade-stirring agitation (30 rpm)
was applied for 1 h in a Jar-test apparatus (JLT4, Velp Scientifica), until equilibrium was
achieved. Kinetic studies of our specific research (Figure 2) and previous studies carried out
(Beltrán-Heredia et al., 2009) reported this period was enough for guarantee equilibrium. Then,
a sample was collected and it was centrifuged. Surfactant removal was determined by visible
spectrophotometry.
Figure 2: Kinetic study of surfactant removal by coagulation with Moringa oleifera.
2.4 Analytical procedures
All analytical measures were made according to American Public Health Association standard
methods (APHA, 1998).
Anionic surfactants were determined by a method based on methylene blue-anionic
surfactant association (Tôei and Fujii, 1977). 10 mL of clarified sample was put into a
separation funnel. 25 mL of trichloromethane (PANREAC) and 25 mL of methylene blue
solution (PANREAC) were added and funnel was shaken vigorously for 1 min. Organic
3fraction was taken out and put into another separation funnel, in which 50 mL of cleaning
solution were added. Funnel was shaken again for 1 min, and the resultant organic fraction
was put into a 25 mL-flask. It was filled up to the mark with trichloromethane and surfactant
concentration was determined by visible spectrophotometry at 652 nm, with zero made with
pure trichloromethane by using an HEλIOS spectrophotometer.
2.5 Mathematical and statistical procedures
Linear data adjustments were carried out by using Origin v. 7.0 for Windows. Non-linear
multiparametric data adjustments were carried out by using SPSS 15.0.1 for Windows.
3 Results and discussion
3.1 Moringa oleifera seed extract dosage
Figure 3 depicts the influence of coagulant dosage in surfactant removal. Initial surfactant
concentration of 25 mg·L−1 was treated with increasing doses of Moringa oleifera.
As it was supposed, the presence of turbidity enhances the rapid removal of SLS through
coagulation, so the maximum average surfactant removal (ca. 75%) is achieved with
intermediate coagulant dosages of 60-100 mg·L−1 so an increment in efficiency is presented if
compared with the same assay in distilled water (Beltrán-Heredia and Sánchez-Martín, 2009).
Figure 3: Influence of coagulant dosage on surfactant removal.
3.2 Initial surfactant concentration
A fixed dose of ca. 100 mg·L−1 of coagulant was applied in a series that varies the initial
surfactant concentration (ISC) between 0.1 and 0.5 mmol·L−1. As it can be appreciated in
Figure 4, the efficiency of surfactant removal tends to increase as ISC goes up, although
percentual surfactant removal undergoes just a little raise.
4Figure 4: Influence of initial surfactant concentration on surfactant removal.
3.3 Theoretical modelization
Interaction between surfactants and natural polymers (polysaccharides, proteins, etc.) has been
studied for many years because it is important to succeed in product formulations in many areas
(pharmaceuticals, cosmetics, food processing, etc.). Although the basic mechanisms of
surfactant-polymer interaction are reasonably well understood, researchers still disagree at
molecular level. It is generally accepted that their interactions may occur between individual
surfactant molecules and the polymer chain, or in the form of surfactant-polymer aggregate
complexes (micellar or hemimicellar interactions).
By combining data series from sections 2 and 3 and new experiments it is possible to look for
a theoretical model that should explain Moringa oleifera-surfactant interaction phenomena.
According to previous studies (Dymaczewski et al., 1997; Okuda et al., 2001; Miller et al.,
2008; Beltrán-Heredia et al., 2009) coagulation-by removal may be assumed to work as an
adsorption-like process.
Firstly, adsorption capacity (q) has been determined, defined as:
(C0 − C1 )V
q= (1)
w
where
C0 is initial surfactant concentration, (mmol· L−1),
Cl is equilibrium surfactant concentration in bulk solution, (mmol· L−1),
V is the volume of solution, (L),
and W is Moringa oleifera extract mass (g).
The basic forces controlling surfactant-polymer interactions are van der Waals and dispersion
forces, hydrophobic effects, dipolar and acid-base interactions and electrostatic interactions. The
importance of each type will vary with the nature of the surfactant and the polymer.
5Figure 5 shows adsorption capacity values versus equilibrium surfactant concentration for
those experiments carried out varying the coagulant dosage and initial surfactant concentration,
at the same temperature (20ºC).
When a polymer is added to a surfactant solution, it is often observed that processes such
micellization appear to begin at surfactant concentration below the CMC of the surfactant in the
absence of polymer. In many cases, a complex aggregate structure is formed in association with
the polymer at lower concentration of surfactant (Rosen, 2004). This concentration is known as
critical aggregation (or association) concentration (CAC) and varies with the nature of the
polymer. The difference between both concentrations may vary by a factor of 10 - 1000 in some
cases (Myers, 2006).
Figure 5: General equilibrium and adjustment data.
A simple model that has been used to describe the adsorption of surfactants is the regular
behaviour model (Hildebrand et al., 1970). For dilute solutions, this model simplifies to the
Frumkin-Fowler-Guggenheim (FFG) equation (Fowler and Guggenheim, 1939; Frumkin,
1925).
θ1
= c1 ⋅ k12 ⋅ exp(χ12 ⋅ θ1 ). (2)
1 − θ2
where θ l is the ratio between the adsorption and the maximum adsorption:
q
θl = . (3)
q∞
k12 is the adsorption constant, being a measure of the interaction between surfactant and
polymer surface, and and χ12 is the Flory-Huggins parameter (Flory, 1953), defined as:
NA ⋅ z
χ12 = .[(ε12 − 0.5(ε11 + ε22 )]. (4)
R ⋅T
6where:
NA is the Avogadro’s number,
z is the number of the nearest neighbors to a central surfactant molecule,
and ∈11 , ∈22 and ∈12 are the pairwise interaction potentials.
In this model k12 and χ12 should be considered as adjustable parameters expressing the affinity
for the surface and the lateral interactions in the adsorbed layer, respectively. Zhu and Gu
(1991) proposed a very simple model for adsorption of surfactant assuming that the adsorbed
layer is composed of surfactant aggregates. A surfactant aggregate is formed on the surface
before stable aggregates are formed in solution. The model considers that these aggregates are
stabilized by the presence of the surface. This model leads to the following equation 5:
θl n
= k g ⋅ Cl . g
(5)
1 − θl
where ng is the number of monomers in the surfactant aggregate.
Taking into account the definition of θl (5) becomes
n
cl g
q = q∞ ⋅ k g ⋅ n
. (6)
1 + k g cl g
This equation is reduced to the Langmuir equation for ng = 1.
In the equation 6, if the term kg·Clng is much lower than 1, the derived expression is known as
the Freundlich equation 7.
n
q = k f ⋅ Cl f . (7)
where kf is the Freundlich adsorption constant and its value is given by equation 8;
k f = q∞ ⋅ k g . (8)
Equations 2, 6 and 7 lead to three models that have been studied: Freundlich (F), Frumkin-
Fowler-Guggenheim (FFG) and Gu and Zhu (GZ) models. Table 3 shows different parameters
that have been used in these modelizations. Parameter values and statistics summary for the
three models are shown in table 4.
3.3.1 Freundlich model
As it is observed in Figure 4, Freundlich model does not work very well because it does not
include a saturation region (final part of the curve). That is, this model just explain first part of
adsorption phenomena. Taking this fact in consideration, the Freundlich non linear adjustment
2
gives an adjusted correlation factor r equal to 0.79, while the characteristic parameters kf and nf
0.51 0.49
are equal to 4.76 L mmol g-1 and 0.51 respectively. Linear adjustment also corroborate the
validity of the model (Table 4).
3.3.2 Frumkin, Fowler and Guggenheim model
FFG model (Fowler and Guggenheim, 1939) is used when adsorption from dilute solution is
being studied. With this condition, surfactant concentration usually appears far from CMC
(Rosen, 2004). It is considered a simplification from a general model (Hildebrand et al., 1970)
in which several parameters are included. FFG equation is presented in equation 2.
7By carrying out a non-linear fit, it is possible to determine values of χ12, k12 and q∞, this last
parameter needed for θl calculation. This non-linear fit conducts to a χ12 value of 2.39, k12 value
of 6.71 L mmol−1 and q∞ value of 3.17 mmol·g−1.
Table 3: Fitting models parameters.
Parameter Model Symbol Units Expression Reference
Equilibrium surfactant F, GZ, FFG Cl mmol·L−1
concentration in bulk solution
Initial surfactant F, GZ, FFG C0 mmol·L−1
concentration
Adsorbent amount F, GZ, FFG W G
Total volume F, GZ, FFG V L
Adsorption capacity F, GZ, FFG q mmol·L−1 (C0 - C1 ) ⋅V (Freundlich and
Heller, 1939)
W
Freundlich adsorption order F nf none (Freundlich and
Heller, 1939)
Freundlich adsorption F kf Ln (Freundlich and
constant Heller, 1939)
g ⋅ moles n-1
Limiting adsorption ratio FFG θl none q (Esumi and Ueno,
θ1 = 2003)
q∞
Flory-Huggins interaction FFG χ12 none (Rosen, 2004)
parameter
Adsorption constant FFG k12 L·mmol−1 (Rosen, 2004; Esumi
and Ueno, 2003)
Limiting adsorbed surfactant FFG, GZ q∞ mmol·g−1 (Rosen, 2004)
Gu and Zhu adsorption GZ kg (mmol·L−1)-ng (Gu et al., 1992)
constant
Gu and Zhu adsorption order GZ ng none (Gu et al., 1992)
Linear expression of equation 2 allows to correlate data from q and Cl into a linear model.
As it can be seen in Table 4, r2 determination coefficient is high enough again, so it is possible
to conclude this model fits reasonably well to present situation.
Table 4: Parameter values and statistical summary.
Model Expression Parameters r2 Linearization Linear
values expression r2
F n
q = k f ⋅ Cl f kf=4.76 0.79 ln q = n f ⋅ ln Cl + ln k f 0.75
nf=0.51
FFG θl k12=6.71 0.64 θl 0.80
= Cl ⋅ k12 .exp(χ12 ⋅ θl ) q∞=3.17
1 − θl χ12=2.39 1 − θl
ln = = ln k12 + x12 ⋅ θl
Cl
GZ n q∞=2.49 0.94 q 0.80
Cl g ln = ng ⋅ ln Cl + ln k g
q = q∞ ⋅ k g kg=1493
n
1 + k g ⋅ Cl g ng=2.43 q∞ − q
83.3.3 Gu and Zhu model
Gu et al. (1992) proposed a two-step adsorption model for various types of S-shaped adsorption
non-Langmuir isotherms. First step implies adsorption of surfactant molecules as individual
molecules or ions. Second step leads to an adsorption increasing as surface aggregates form
through interaction of the hydrophobic chains of the surfactant molecules with each other.
The physical meaning of this theoretical model may be found in the fact that adsorption
process appears accompanied of some kind of flocculation process, as floc formation is
observed in the experimental assay. This may be due to the hemimicellar formation hypothesis
(Myers, 2006; Rosen, 2004).
Mathematically, GZ model is expressed by equation 6. Figure 4 shows non-linear experimental
data fit and it is possible to observe a very good r2determination coefficient in Table 4 (0.94).
4 Conclusions
This investigation has the following conclusions:
• Moringa oleifera seed extract has a very interesting behavior in removing anionic
surfactants from surface water. A very high efficiency is observed in all of the studied
cases, so it presents a promising future as water treating agent.
• Regarding the influence of the coagulant dose, it is observed that a maximum surfactant
removal is achieved with relatively low coagulant amounts (ca. 100 mg L−1).
• By increasing the initial surfactant concentration, efficiency of the process is enhanced
dramatically.
• Coagulation-flocculation process may be modelated as an adsorption process. Different
adsorption models (Freundlich, Frumkin-Fowler-Guggenheim and Gu-Zhu) have been
tested and the best fit was presented by Gu and Zhu model.
5 Acknowledgments
This investigation has been supported by the Programa de Iniciación a la Investigación,
Universidad de Extremadura, oriented modality, GESPESA subprogram, by COMISIÓN
INTERMINISTERIAL DE CIENCIA Y TECNOLOGÍA (CICYT) CTQ 2007-
60255/PPQ project as well as by JUNTA DE EXTREMADURA under PRI-07A031
project.
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