Journal of Environmental Protection, 2010, 1, 24-29
doi:10.4236/jep.2010.11004 Published Online March 2010 (http://www.SciRP.org/journal/jep)
Comparative Performance and Computational Approach of
Humic Acid Removal by Clay Adsorption
Chao Yu1, Jiaqian Jiang2*
1Department of Mathematics, East China Normal University, Shanghai, China; 2Division of Civil, Chemical and Environmental En-
gineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK.
Received January 3rd, 2010; revised February 3rd, 2010; accepted February 3rd, 2010.
ABSTRACT
The effective removal of humic acid is an important factor influencing th e qua lity of treated waters. Adsorption is one of
major techniques used for the removal of humic acid. This study demonstrated that modified clays could be used as
alternatives to activated ca rbons for adsorbing humic acid. Both Al-Fe modified and Fe modified clays had high affinity
to humic acid and then high removal efficien cy. Al-modified clay had less removal capacity for adsorbing humic acid.
Mathematics formulas were developed to predict the adsorption performance of modified clays for the humic acid
removal via the parameters of UV254 absorbance and DOC concentrations. The optimal clay dose could be predicted
using the developed model. The F test was used to validate t he model developed by examining if it fells into the reject field.
The reject field varied accordi ng to each F test. The res ults showed that the model devel oped was 99% confident and can
be used to perform the simulation.
Keywords: Adsorption, Clay, Humic Aid (HA), Mathematics Approach, Modification, Water Treatment
1. Introduction
Humic acid in surface water causes a lot of problems
such as colour, taste, odour and lower efficiency in water
treatment process. In addition to this, in the chlorination
process, humic acid reacts with chlorine and produces
disinfection-by-products (DBPs) [1]. The World Health
Organization (WHO) has recommended the maximum
concentrations of the DBPs and these parameters have
been regulated in most countries’ environmental agencies.
The effective removal of humic acid is thus an important
factor influencing the quality of treated waters. Among
techniques used for the removal of humic acid, coagu-
lation, adsorption and membrane processes are widely
adapted.
Clay is one of the most common earth’s minerals,
which are the residue of weathering or hypothermal ac-
tion. The classification and origin of clay depends on
particle size, physical characteristics, chemical composi-
tions and common crystal structural characteristics.
Clay’s size is less than 2 micrometers with plastic prop-
erties when moist. Fundamentally, clay exhibits a layered
structure and itself can be subdivided into groups ac-
cording to its underlying structure and layer’s charge. An
ideal structure of the most rigid clays is the 2:1-layered
silicates which can be seen in Figure 1. The 2:1 notation
means that the host layers consist of two tetrahedral sili-
cate sheets sandwiching one octahedral sheet. The two
other subclasses of clays have a 1:1 layer type and a 2:1
inverted ribbon structure, respectively [2]. At the central
of the tetrahedral layers are silicon or aluminium ions,
while the number of A1 ions in tetrahedral sites deter-
mines the net negative charge of the host layer. Those
oxygens forming the tetrahedral bases border the inter-
lamellar gallery and are arranged in hexagonal rings that
form a kagom´e lattice.
The approximate chemical formula for the vermincu-
lites is (Mg3(Si3Al)O10(OH)2)(Mg0.5(H2O)y); where the
first set of brackets denotes the host layer, the second set
denotes the guest layer, and the hydration state is vari-
able. The host layers in clays can adopt a number of in-
teresting stacking arrangements to form ordered, partially
ordered, or disordered three-dimensional structures. Par-
ticular clays are prone to form poly-types in which dif-
ferent stacking sequences are associated with lateral layer-
to-layer shifts.
Overall, natural mineral clays possess specific surface
chemical properties, e.g., cation exchange capacity, and
adsorptive affinity for some organic and inorganic com-
pounds, and then have attracted research interesting to
investigate the potential use of clays as adsorbents for
treating heavy metals and organic pollutants, or as co-
agulant aids for improving the settling performance in
coagulating low particle content water. By replacing the

Comparative Performance and Computational Approach of Humic Acid Removal by Clay Adsorption 25
Oxygens ●Aluminum Hydroxyls
Silicons replaced by aluminums
Oxygens ●Aluminum Hydroxyls
Silicons replaced by aluminums
Oxygens ●Aluminum Hydroxyls
Silicons replaced by aluminums
Figure 1. Diagrammatic illustration of 2:1 layer lattice (af-
ter [2])
natural inorganic exchange cations with alkylammonium
ions, clay surfaces are converted from being primarily
hydrophilic to hydrophobic, which enable them to interact
strongly with organic vapours and organic compounds
dissolved in water [3]. Previous studies [4,5] have dem-
onstrated that the polymeric Al/Fe species are the most
efficient coagulating/adsorbing chemicals for removing
natural and synthetic organic impurities in potable water
treatment. The combination of the natural mineral clays
with polymeric Al/Fe species may produce somewhat
optimal properties and enhance the adsorption of metal
and organic compounds from the solution. The feasibility
of this idea has been confirmed by preceding work [6–
10], where, modified clays had comparatively great af-
finities for the heavy metals, and phenol and dye struc-
tured pollutants.
The aim of this paper is to use modified clays for humic
substances removal and to develop a model to forecast the
operating conditions based on the experimental results of
using modified clay to adsorb humic acid. It is expected
that using the developed model, the most efficient outcome
of adsorption of humic acid could be predicted.
2. Materials and Methods
2.1 Modifying and Characterising Clays
The raw clay used in this study, montmorillonites KSF,
and the other chemicals were supplied by
Sigma-Aldrich Chemicals Corporation UK. The modi-
fication of clays was following an established procedure
[7]. The modification involved with the mixing of the
given amount of clays with polymeric metal species for
four hours at 55℃ and then the mixtures were separated
by filtration to obtain the solid phase of the modified
clays. The resulting clays were dried using a freeze
dryer (Dry Winner3, HETO Ltd., UK) operating at
–0.5MPa and –52℃. The chemical composition of the
modified clays were analysed using X-ray Fluorescence
(XRF), and the XRF data was collected on a Philips
PW1480 XRF Spectrometer.
The clays used in the study were raw montmorillonites
KSF (termed as raw clay), poly-aluminium modified mont-
morillonites KSF (Al-clay), poly-iron modified montmo-
rillonites KSF (Fe-clay) and poly-aluminium and iron
modified montmorillonites KSF (Al-Fe-clay).
2.2 Procedures of Adsorption Experiments and
Water Quality Measurement
The model water containing humic acid (HA) was pre-
pared using a commercial HA (Fisher, UK), and the HA
concentration was 6.5 mg/L, giving UV254 abs of 15 1/m
and dissolved organic carbon (DOC) concentration 3.2
mg/L as C.
The adsorption experiments were carried out using the
batch equilibration technique. For each isotherm, given
amount of clay was weighed into 40 mL polypropylene
centrifuge tubes, and 30 mL of the above stated HA solu-
tion were added. The pH value of HA solution was pre-
adjusted to 5. The suspensions were mixed on a rotary
tumbler for 4 hours, which has been tested to be sufficient
to reach the equilibrium status under the study conditions.
After phase separation by centrifugation, the concentration
of HA in the supernatant was determined by UV- absorb-
ance at wavelength of 254 nm and DOC analysis. The
analytical procedures were following the AWWA standard
methods [11]. The adsorbed HA quantities were then de-
termined using the mass balance equation:
Cs m = V (C0 – Ce)
where, Cs is sorbed HA concentration on clay (mg/g), m
is the weight of clay used (g), V is volume of HA solu-
tion (L), C0 is HA initial concentration (here expressed as
DOC mg/L), and Ce is HA equilibrium concentration
(DOC mg/L). Percentage removal of humic acid was
calculated based on the original and treated DOC con-
centrations.
2.3 Mathematical Approach
The regression procedures and the least square method
were used to set up a model and to analyze the data. In
terms of the experimental results of humic acid removed
by clays, a model was developed to forecast humic acid
removal efficiency by adsorption with clays. Finnaly, the
F test was used to validate the model developed.
3. Results and Discussion
3.1 Characterisation of the Modified Clays
Figure 2 shows an example XRD traces for the modified
montmorillonites. The peaks marked by (x) are the d001
reflections indicative of 2:1 swelling clays. The other
peaks are impurities corresponding to quartz, plagioclase
feldspar, illite and mica. Illite is a non-swelling 2:1 clay,
mica is a non-swelling 2:1 phyllosilicate (sheet silicate)

Comparative Performance and Computational Approach of Humic Acid Removal by Clay Adsorption 26
mineral and plagioclase is tectosilicate (three dimen-
sional structure similar to zeolite framework).
The XRD results also demonstrated that increase in
basal spacing (which is an indication of expanding
clay’s inter-layers; a high basal spacing value means
more inter-layer volume) occurs in the modified mont-
morillonites but the extents of changes are very differ-
ent (Table 1). The values of d001 basal spacing of Al-
or Fe-clays only slightly increased or was different
from that of the raw clay but d001 basal spacing of Al-
Fe-clay increased markedly. The possible reason for
this could be that the single Al or Fe polymeric species
have probably undergone subsequent hydrolysis prior
to XRD analysis, resulting in partial collapse of the
interlayer spacing back to near the original value. How-
ever, polymeric aluminium-iron species probably are
stable, which results in the larger spacing being re-
tained. However, the d001 basal spacing values alone
cannot explain the modification mechanism, which is
the exchange of the interlayer Ca2+ ions for the poly-
meric Al or Fe species in solution. The XRF analysis
revealed that Ca2+ content in the treated clays signify-
cantly decreased and which is equivalent to 99.5% for
the Al- or Fe-clays, and 98.6% for the Al-Fe-clay, in-
dicating that the polymeric Fe or Al species are defi-
nitely entering the internal structure of the clays.
3.2 Adsorption of Humic Acid
Tables 2 and 3 show the adsorption of humic acid vs.
doses of clays. Al-Fe- and Fe-clays demonstrated superior
0
100
200
300
400
500
600
700
800
900
0 10203040506070
De grees 2-theta
Counts
Figure 2. XRD trace of Al13-polycation modified montmoril-
lonite
Table 1. Basal spacing for modified montmorillonites KSF
clays
Type of clay Basal spacing (d001)/Å
Raw clay 15.5
Al-clay 15.3
Fe-clay 15.9
Al-Fe clay 17.8
humic acid removal efficiency when doses were above
400 mg/L. whilst Al-clay did not show good adsorption
performance under study conditions. It is well docu-
mented that the interaction of iron (III) with humic acid
involves complexing, charge neutralization, precipita-
tion and adsorption [12]. Most common pH used for
removing humic acid is 4-6 and complexing species is
Fe(III), therefore, both Al-Fe-clay and Fe- clay per-
formed superior to Al-clay. The best performance was
achieved by Al-Fe clay since the modifier used in this
clay is polymeric alumino-iron species, which has been
demonstrated to have the highest cationic charge in
comparison with other Al/Fe metal species [13].
The superior adsorption performance of modified
clays could be attributed to their specific properties;
i.e., high hydrophobicity and specific chemical com-
plexation. After modification, the modified clays either
became more hydrophobic in nature or increased in-
teractions with functional groups of the humic acid
(e.g., carboxyl, hydroxyl and carbonyl). Most possibly,
the combination of two mentioned mechanisms can be
used to explain the enhanced humic acid adsorption
with Al-Fe-clays.
3.3 Development of Mathematics Models
The following formula (Equation 1) was set up to be fit-
ted with the adsorption operating conditions stated pre-
Table 2. DOC adsorption vs. clay dose
Clay/DOC
Clay dose
(mg/L) Al-Fe- Al- Fe-
0 3.1 3.2 3.2
200 2.85 2.86 3.47
400 0.16 2.44 0.16
600 0.09 2.30 0.09
800 0.08 2.11 0.09
1000 0.09 1.93 0.10
Table 3. UV254 adsorption vs. clay dose
Clay/ UV254 (m-1)
Clay dose
(mg/L) Al-Fe- Al- Fe-
0 0.252 0.257 0.260
200 0.232 0.230 0.282
400 0.013 0.196 0.013
600 0.007 0.185 0.007
800 0.006 0.169 0.007
1000 0.007 0.155 0.008

Comparative Performance and Computational Approach of Humic Acid Removal by Clay Adsorption 27
viously, i.e., that the Al and Fe have an equally fixed
ratio towards clay when they were modified, Al, Fe and
clay are independent variables, i.e. they won’t interfere
with each other when performing as adsorbents.
0112233

   yxxx (1)
where y represents the remaining DOC or UV254 treated
by Al-Fe-clay; x1, x2, and x3 represent the remaining
DOC or UV254 treated by Al-, Fe- and raw clay respec-
tively;

i are unknown parameters (i=0,1,2,3);

is
the random error item which satisfy:
() 0

E and 2 ()

 Var
The purpose of the above model is to predict the ad-
sorption performance of either Al-Fe-clay (y) or other
clays (xi). The influence of three factors were considered:
Al content, Fe content and raw clay. And the least square
method was used to obtain

i. Take the form
0112233
 
  
iiiii
yxxx,1, 2, 3...,in
where, 3n.
A matrix form was written as follows:
12
( ,,...,)T
n
Yyy y
11 1213
123
4
1
1





 
nn n
n
xxx
X
xxx
0123
(,,,)

 T
12
( ,,...,)

  T
n
Thus, the original equation was written as:

 YX
Compute the parameters. According to the least square
method, the estimated vector

 was found which
should satisfy:
012
2
0120 123 123
1
2
0112233
,, 1
(,,) ()
min ()

 
 







n
iiii
i
n
iiii
i
Qyxxx
yxxx
The parameters were then computed by using method from
multivariable calculus and were written in the matrix form:
()0 


T
XYX
Since T
X
X is a non-singular matrix, thus the formula
was obtained to compute

1
() 

TT
X
XXY
In real practice, Matlab could be used to compute the
above calculation.
For the DOC value,


= (-0.1813, 0.0833, 0.8057, 0.1391)T, and then
Equation 2 was obtained,
123
ˆ0.1813 0.08330.80750.1391

 
DOC
yxxx (2)
Similar procedures were applied to UV254-abs removal
prediction, or, Equation 3:
123
ˆ0.013 0.0730.80720.1448

 
UV
yxxx (3)
Figures 3 and 4 show the remaining DOC concen-
trations and UV254 abs. after clay adsorption via either
the experimental and the model simulated data. Both
approaches deliver significantly consistent results
indicating that the developed model could be used to
predict the humic acid adsorption performance by
clays.
3.4 Hypothesis Test
The F test was used to validate the model developed,
which determines whether y and x1, x2 and x3 are linear
correlated at a significant level (alpha equals to 0.01), i.e.,
whether it is appropriate to represent y with beta0 +
0
0.5
1
1.5
2
2.5
3
3.5
02004006008001000 1200
Dose (mg/L)
Remaining DOC (mg/l)
Experimental
Simulated
Figure 3. Model simulated and experimental remaining
DOC
0
0.05
0.1
0.15
0.2
0.25
0.3
0200 400 600 80010001200
Dose(mg/L)
Remaining UV
254
(m-1)
Experimental
Simulated
Figure 4. Model simulated and experimental remaining
UV254

Comparative Performance and Computational Approach of Humic Acid Removal by Clay Adsorption 28
beta1*x1 + beta2*x2 + beta3*x3 with the confidence level
of 99%. The F value is examined to see if it fells into the
reject field. If it is, the developed model is wrong, and
has to be reconstructed. The reject field varies according
to each F test.
As shown in the following equations, that the F test
needs three components to locate, which are 0.01, 4 and
3, respectively. The 0.01 means the confident level
(equals to 99%), 4 and 3 are the degree of freedom which
are set due to the data numbers. 16.69 stands for the re-
ject field (obtainable from the table provided with statis-
tics books). If the F value computed is less than 16.69,
then the hypothesis that original model is correct would
be rejected. As the F value in this case is greater than
16.69 (Equations 4 and 5), it means that the developed
model was 99% in confidence (with the coefficients beta0
- beta3 are not all zero) for its accuracy, and can be used
to simulate and predict the adsorption performance.
00 1 23
:0

H Versus
10123
:( , ,,) (0,0,0,0)

H
22 2
111
ˆˆ
()() ()

 


nnn
Tyy iiii
iii
RE
S lyyyyyy
SS
4(4,4 1)
41


R
E
S
FFn
S
n
∼
254 0.01
26322.29>(4,3) 16.69
UV
FF
(4)
0.01
7748.875>(4,3) 16.69
DOC
FF (5)
So H0, was rejected and the parameters can be fit to the
model significantly at the 99% confidence.
The developed models were verified, and then they
can be used to predict that when the clays’ doses are
about 400~600 mg l-1, the overall adsorption of UV254
and DOC could reach to the maximum. Furthermore, if
the remaining UV254 or DOC could be known, the
outcome of Al-Fe modified clay at the same dose level
could be forecasted.
4. Conclusions
This study demonstrated that modified clays could be
used as alternatives to activated carbons for humic acid
removal. Both Al-Fe modified and Fe modified clays
have high affinity to humic acid and then high removal
efficiency. Al-modified clay has less removal capacity
for adsorbing humic acid. Higher d-spacing values of
Al-Fe modified and Fe modified clays could explain such
phenomena.
Mathematics formulas were developed to predict the
adsorption performance of modified clays for the humic
acid removal via the parameters of UV254 absorbance
and DOC concentrations. The optimal clay dose could be
predicted using the developed models.
The F test was used to validate the model developed
by examining if it fells into the reject field. The reject
field varied according to each F test. The results showed
that the model developed was 99% confident and can be
used to perform the simulation.
5. Acknowledgement
The authors would like to thank UK Engineering Physi-
cal Science Research Council (EPSRC) for funding Chao
Yu’s internship at the University of Surrey under the
Knowledge Transfer Award Scheme.
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