Optimal conditions of Al and Fe extraction from laterite soil usingD-optimal design

Abbas F. M. Alkarkhi • Yusri Yusup •

Tjoon Tow Teng

Published online: 9 August 2012

� Springer Science+Business Media, LLC 2012

Abstract This paper reports pioneering work in identi-

fying an alternative coagulation agent of wastewater treat-

ment, given the availability of commonly used agents are of

a higher cost relative to more natural sources, such as soil.

The alternative proposed is laterite soil from northern

Malaysia because it contains high amounts of Al and Fe,

which are well-known coagulants. The soil was grinded and

sieved to obtain uniform particle sizes of\250 lm. Al and

Fe were extracted from the soil. Extraction agents: (1) HCl,

(2) NaOH, and (3) HCl ? NaCl were chosen. It was found

that the most effective agent to extract Fe was 5 N HCl

while to extract Al was HCl ? NaCl, 2 and 4 N, respec-

tively. D-optimal design observed that extraction time t,

temperature T, and ratio of amount of laterite soil to amount

of extractants r, showed a significant effect on Al extrac-

tion. In contrast, the combination of factors t and r exhibited

insignificant effect on Fe extraction while other factors were

significant. The optimum conditions for extraction of both

Al and Fe were 90 �C, 40 min, for r = 1:15, which gave

[Fe] = 1,870 mg/l and [Al] = 0.17 mg/l and 90 �C,

90 min, for r = 1:10, which gave [Fe] = 2,900 mg/l and

[Al] = 0.130 mg/l. Since concentration of Fe extracted

from laterite soil was high, it was concluded that laterite soil

can be considered as an alternative and novel source of

coagulant applicable in a wastewater treatment coagulation

process.

Keywords Alternative coagulant � Laterite soil �Wastewater treatment � Liquid extraction

1 Wastewater treatment and laterite soil

The human population is increasing exponentially with

time whereas the amount of usable water to sustain this

population remains limited. Aside from domestic use, the

rapid growth of industrialization also contributes to the

large consumption of fresh water and the consequent

transformation to wastewater. In order to protect water

resources from exhaustion, treatment of generated waste-

water is employed. These treatment techniques include

adsorption, precipitation, coagulation-flocculation, filtra-

tion, chemical oxidation, electro-dialysis, flotation, and

ultra filtration. Among these methods, the coagulation-

flocculation process is a common treatment technology

with a wide range of applications in water supply and

wastewater treatment facilities.

1.1 Al and Fe in coagulation-flocculation in wastewater

treatment: an overview

Coagulation-flocculation is widely used for water treatment

since it is efficient and simple to operate. In this process,

many factors influence its efficiency, i.e., the type and dosage

of coagulant and flocculant, mixing speed and time, pH,

temperature, and retention time. Coagulation is considered

to encompass all reactions and mechanisms, which results in

particle aggregation within the liquid (water) being treated,

as well as in situ coagulant formation (when applicable),

chemical particle destabilization, and physical inter-particle

contacts. On the other hand, flocculation refers to the

bridging between particles by a polymer chain, which causes

the particles to form ‘‘flocs’’ or ‘‘aggregates’’. These flocs

float or sink, making them accessible to be removed physi-

cally from the water treatment system. The commonly used

metal coagulants fall into two general groups, those based

A. F. M. Alkarkhi � Y. Yusup (&) � T. T. Teng

Environmental Technology, School of Industrial Technology,

Universiti Sains Malaysia, 11800 USM, Penang, Malaysia

e-mail: yusriy@usm.my

123

Environmentalist (2012) 32:453–463

DOI 10.1007/s10669-012-9410-9

on: (1) Al and (2) Fe. Examples of Al coagulants include

aluminum sulfate, aluminum chloride, sodium aluminate,

aluminum chlorohydrate, poly-aluminum chloride, etc.,

whereas the Fe coagulants include ferric sulfate, ferrous

sulfate, ferric chloride, poly-ferric sulfate, etc. Other chem-

icals used as coagulants are hydrated lime, magnesium car-

bonate (Bratby 2006), and magnesium chloride (Pang et al.

2009; Tan et al. 2000).

1.2 Laterite soil

Laterite soils are generally found in warm, humid, and

tropical areas of the world. ‘‘Red soil’’ is a generic name

used to identify any soil exhibiting yellowish to reddish

color. The term is frequently used to express an image of

red, infertile, and acidic soils in the tropics (Siradz 2008).

The main elements present in laterite soil are Fe, which is

responsible for the reddish color of the soil, and Al. Other

elements existing in laterite soil are K and Ca. The

chemical properties of laterite soils are also characterized

by low pH and low cation exchange capacity (CEC).

Generally, soil pH values are low, ranging from 4.4–6.6

while the CEC ranges from 2.23 to 20.3 cmolc kg-1 and in

most soils the exchangeable acidity is high, reflecting their

acidic pH (Wilson et al. 2004). Proportions vary from

80–90 % oxides of Fe with 5–10 % Al. Small amounts of

titanium oxide, typically 1–5 % are usually present. Ca,

Mg, K, Na, and Mn vary from 0 to\1 %. Fe is entirely in

ferric forms, mainly goethite (FeO OH), haematite (Fe2O3),

and amorphous oxides while Al exists as gibbsite

(Al2O3.3H2O) and boehmite (Al2O3 H2O) (Young 1976).

The geotechnical properties of laterite soils are rela-

tively different from those of soils produced in temperate

or cold regions of the globe since soil is influenced by

climate, geology, and the degree of weathering (Mahal-

inga-Iyer and Williams 1991; Ko et al. 2006). Laterite

soils are the product of thorough weathering (high tem-

perature, rainfall, and humidity conditions) called ‘‘lateri-

zation’’ under tropical and sub-tropical climatic conditions.

Laterization is defined as a process of leaching out of Si

and alkali and also the accumulation of hydrated Fe and

oxides of Al (Mahalinga-Iyer and Williams 1991), result-

ing in high contents of sesquioxides. Furthermore, under

this condition, exchangeable bases and silicon will ulti-

mately be eliminated and only the more resistant minerals

such as iron and aluminum oxides will remain in the soil

profile.

The total area of laterite soil in zones all over the world

is approximately 64 million ha, accounting for 45.2 % of

the earth’s total land area, with 2.5 billion people, or 48 %

of the global population (Shui et al. 2008). Laterite soils are

primarily found in South America, Central Africa, South

and Southeast Asia, China, India, Japan, and Australia

(Wilson et al. 2004). In the United States soil taxonomy,

laterite soils are usually classified under the orders of

Oxisols, Ultisols, and occasionally Alfisols, Mollosols, and

even Inceptisols (refer to Table 1).

The rapid weathering in the tropical environment of

Malaysia results in soils dominated by kaolinite and oxides

of Al and Fe. According to soil taxonomy, these soils have

been classified as ‘‘Oxisols’’. These soils are often deep,

friable red soils, which initially appeared excellent for

agriculture. Upon close scrutiny, they are often rich in Fe

and Al, excessively drained, and have a very low CEC.

Most of the physico–chemical properties of these soils are

related to their mineralogy. These soils are in oxic stage of

soil formation and are dominated by oxides and oxyhy-

drate-gibbsite, goethite, and haematite, with kaolinite as

the dominant aluminosilicate mineral. As these minerals

have low nutrient retention properties, this implies that

with progressive weathering, the soil is reduced almost to

an inert medium. Besides the low fertility status, many

such soils also have a high Fe content. Chemically, these

Oxisols present problems, as the mineralogical composi-

tion gives special charge characteristics to the soil. In some

Oxisols in Malaysia, the net charge is low or even positive,

indicating low nutrient retention capacity. The charge in

these Oxisols is dominated by a high pH-dependent or

variable charge. They are often excessively dry, so the

crops grown on them experience moisture stress, especially

young, developing plants. Even cover crops for plantation

agriculture find it difficult to thrive. The low cation

retention of these soils also results in most of the cations

such as K? from fertilizers being easily lost through

leaching. The high iron content also results in phosphorus

fixation problems. Hence, the highly weathered Oxisols of

Malaysia can be considered problem soils. However, these

laterite soils are still considered as Class 1 or 2 soils and

limited to rubber, oil palm, cocoa, and tropical fruit trees

plantations (Wilson et al. 2004).

Table 1 National classification system of laterite soils [adapted from

Siradz (2008)]

System Name

Soil taxonomy Ultisols, Oxisols, Alfisols and Inceptisols

United States of

America

Red soils, yellow soils, laterite soils, lateritic

soils, yellow podzolic, red podzolic (Terra

Rossa), yellowish brown laterite, and reddish

brown lateritic

Australia Lateritic podzolic soils, red podzolic soils,

yellow podzolic soils, yellow earth, lateritic

krasnozems, lateritic red earth, red podzolic,

and yellow podzolic

FAO/UNESCO Ferralsols, acrisols, nitosols, and gleysols.

454 Environmentalist (2012) 32:453–463

123

1.3 Liquid extraction process

Single extraction procedures are broadly used in soil sci-

ence. These procedures consist of several single extractions

on separate soil samples to determine the mobility of the

various forms of the element under study (Walna et al.

2005). According to Bhattacharya (2007), single extraction

includes a large spectrum of extractants. They range from

very strong acids, such as aqua regia, HNO3 or HCl, to

neutral unbuffered salt solutions, mainly CaCl2 or NaNO3.

The chemical reactions between the solid phases and the

extraction agents are dependent on different parameters,

such as concentration, pH, temperature, reaction time, and

intensity (Bhattacharya 2007). The extraction process can

range from the simple, adding the extractant to the soil

sample in an Erlenmeyer flask and mixing (shaking or

stirred), to the complex, involving Soxhlet extractor,

ultrasonic, microwave-assisted, accelerated solvent, or

supercritical fluid extraction.

According to Rao et al. (2010), extractants can be

divided into several categories: (1) mild extractants, (2)

complexing extractants, and (3) acid extractants. The mild

extractants are NaNO3, CaCl2, and NH4NO3. It was

reported that the extraction yields are very low and when

detected are usually\1 % of the pseudo total content. The

complexing extractants, the chelating agents, such as eth-

ylenediamine tetra-acetate (EDTA) and diethylenetriamine

penta-acetate (DTPA) have been used in other works.

Relevant to the current work, two acid extractants, acetic

acid and HCl have been used by other researchers since

dilute acid extractions provide a more sensitive means of

assessing the environmentally labile and biologically

available fraction of soils due to the fact that concentrated

acid extractions often do not differentiate between residual

and labile fractions. The HCl reagent had been studied

extensively and the 4-h extraction time gave the most

consistent results. The extraction yields vary widely from

element to element and also between samples.

Specifically, there are many Al-extracting agents, e.g.,

KCl, NH4Cl, CaCl2, BaCl2, CuCl2, Na2S2O4, EDTA, HCl,

and DTPA (Matus et al. 2006). The concentrations: 0.5 mol/l

NaOH, 1 mol/l HCl, 1 mol/l KCl, 1 mol/l NH4Ac, and

0.1 mol/l BaCl2, are usually used to extract Al3? in soil.

However, 0.5 mol/l of NaOH is usually used for leaching

Al3? in Chinese soils, which are quite different from Euro-

pean soils. The presence of high content of Cl-, from salt

compounds such as NaCl or KCl, in addition to acidic con-

ditions, increases the solubility capacity of Fe and Al (Poulin

et al. 2008). The majority of Chinese soil has variable

charges and also consists of red soil. The content of Fe2O3 is

about 8 % in red soil. Fe3? is extracted from red soil solution

with 1 mol/l HCl where the concentration of Fe3? ranges

from 30–50 mg/ml. Consequently, Fe(OH)3 (precipitates)

will be formed when the pH is adjusted to 5. This, in turn,

adsorbs some Al3? and affects its extraction (Luo and Bi

2003).

According to Poulin et al. (2008), HCl gave better

extraction efficiency than H2SO4. An increase in leaching

time, acid concentration, and temperature generally resulted

in an increase in Fe and Al extracted from red mud. However,

leaching time has the least effect on the Al and Fe solubili-

zation. Additionally, Al solubilization is less affected by

these parameters than Fe solubilization. They also showed

that HCl is an effective leaching agent for Fe and Al.

1.4 Justification and objectives of research

The commercially available wastewater coagulants are

based on Al and Fe. Accordingly, many researchers have

successfully produced coagulant from clay (another soil

type similar to laterite) (Jiang et al. 2004; Lee et al. 2004).

Since laterite soil is rich in Fe and Al, it can be conjectured

that this soil has the capacity to act as a comparable,

alternative, and novel raw material in producing another

class of coagulant. Likewise, laterite soil is a natural

resource and abundant in Malaysia and other similar-cli-

mate countries. Research on extraction of Al and Fe from

‘‘red mud’’ is more widespread (Poulin et al. 2008) com-

pared to laterite soil, which is less frequent, thus justifying

the need of this research direction. From yet-to-be pub-

lished results of a preliminary study in our laboratory on

directly applying ‘‘raw’’ laterite soil to treat wastewater, it

was found to produce less sludge compared to the com-

mercially available ‘‘alum’’ with almost similar efficacy. In

addition, silica is also naturally present in this soil, which

can act as a flocculant.

In Peninsular Malaysia, more than 70 % of the total land

area is covered by acidic soils of which Ultisols and Oxi-

sols are the most abundant. As stated previously, the highly

acidic laterite soil can be considered inapplicable to the

general agricultural environment. Extraction of Al and Fe

from laterite soil to act as coagulants is another option in

exploiting the relatively ineffectual laterite soil (Wilson

et al. 2004), which is copious in Malaysia. Thus, the

objectives of this study are:

I. To determine the best extractant to use in extracting

[Al] and [Fe] (brackets denoting concentration) from

laterite soil.

II. To investigate the effect of three factors: (1) temper-

ature T, (2) time t, and (3) ratio of amount of red soil

to amount of extractants (weight/volume) r, on Fe and

Al extracted from laterite soil.

III. To determine the optimal conditions to extract Fe and

Al simultaneously from laterite soil using D-optimal

statistical design.

Environmentalist (2012) 32:453–463 455

123

2 Materials and methods

2.1 Preparation of laterite soil

Laterite soil was collected from Sungai Petani, Kedah,

Malaysia. The collected laterite soil was dried in an oven at

80 �C for 48 h. The dried laterite soil was then ground into

powder using a mortar grinder and sieved using a vibrator

sieve shaker to ensure that the particle size was consistently

\250 lm. Finally, the finely ground and sieved laterite soil

sample was stored in a sealed plastic container.

2.2 Materials and chemicals used

Materials, chemicals, equipment, and instruments used in

this study are summarized in Tables 2 and 3.

2.2.1 Extractant preparation: hydrochloric acid, HCl

1, 2, 3, 4, and 5 N concentrations of HCl aqueous solutions

from Qrec with an assay of 37.0 % were prepared. For 1 N

concentration, 83.5 ml of HCl was added into distilled water

and topped up to 1 l. For the concentration of 2 N, 167 ml of

HCl was required whereas 251 ml of HCl was required for

the concentration of 3 N. In addition, the concentration of

4 N needed 334 ml of HCl while 418 ml of HCl was required

for the concentration of 5 N.

2.2.2 Extractant preparation: sodium chloride, NaCl

Similarly, 1, 2, 3, 4, and 5 N concentrations of NaCl

solutions from Merck KGaA with an assay of 99.5 % were

prepared. For 1 N concentration, 58.5 g NaCl was added

into distilled water and topped up to 1 l. For the concen-

tration of 2 N, 117 g of NaCl was required whereas 176 g

NaCl was required for 3 N. Furthermore, for the 4 N

concentrations, 234 g NaCl was required while 293 g NaCl

was required for the 5 N concentrations.

2.2.3 Extractant preparation: sodium hydroxide, NaOH

1, 2, 3, 4, and 5 N concentrations of NaOH from Systerm

with an assay of 99.0 % were prepared. For 1 N concen-

tration, 40 g NaOH was added into distilled water and

topped up to 1 l. For 2 N concentrations, 80 g NaOH was

required whereas 120 g NaOH was needed for 3 N con-

centrations. Lastly, for the 4 N concentrations, 160 g

NaOH was required while 200 g NaOH was acquired for

the 5 N concentrations.

Table 2 Materials and chemicals used

Materials and

chemicals

Formula Assays Supplier Purpose

Filter paper – Grade 1 Whatman To separate

soil and

filtrate

Hydrochloric

acid

HCl 37.0 % Qrec An extracting

agent

Sodium

chloride

NaCl 99.5 % Merck

KGaA

An extracting

agent

Sodium

hydroxide

NaOH 99.0 % Systerm An extracting

agent

AluVer� 3

aluminum

reagent

powder

pillow

– – HACH To determine

aluminum

concentration

Ascorbic acid

powder

pillow

– – HACH To determine

aluminum

concentration

Bleaching 3

reagent

powder

pillow

– – HACH To determine

aluminum

concentration

Fe – 1,000 mg/

l

Merck

KGaA

Calibration for*AAS

analysis

* Atomic absorption spectroscopy

Table 3 Equipment and instruments used

Equipment

and instruments

Model Brand Purpose

Oven – Binder To remove the

moisture content of

laterite soil

Mortar grinder – Pascall To grind the laterite

soil into smaller

particle sizes

Vibrator sieve

shaker

AS 200 Retsch To obtain uniform

particle size of

laterite soil

Analytical balance AL 204 Mettler

Toledo

To measure the weight

of laterite soil

Electrical shaker – Wiseshake To shake the mixture

of laterite soil and

extracting agent

Incubated shaker KBLee

1001

DAIKI To shake the mixture

of laterite soil and

extracting agent with

constant temperature

Spectrophotometer DR/

2010

HACH To determine

aluminum

concentration

Atomic absorption

spectroscopy

(AAS)

Perkin-

Elmer

P.E.

AAnalyst

100

To determine iron

concentration

456 Environmentalist (2012) 32:453–463

123

2.3 Experimental procedures

2.3.1 Determination of a suitable extracting agent

Volume of 100 ml of 1 N HCl was added into 5 g of laterite

soil in a conical flask. It was then shaken for 1 h at 150 rpm.

It was then filtered and tested for Al and Fe contents. This

process was repeated for 2, 3, 4, and 5 N of HCl using two

replicates. The latter steps were also repeated for 50 ml

HCl ? 50 ml NaCl and 100 ml NaOH as extracting agents.

2.3.2 Sample analysis: Al

Al concentration was measured using a HAACH DR/2010

spectrophotometer following the American Public Health

Association (APHA) ‘‘Standard Methods for the Examina-

tion of Water and Wastewater’’ guidelines. Aluminon

(an Al indicator) when combined with the Al in the sample

would exhibit a red-orange color. The intensity of color is

proportional to the Al concentration. Ascorbic acid was

added before the AluVer 3 reagent to remove iron inter-

ference. To establish a reagent blank, the sample was split

after the addition of the AluVer 3. Bleaching 3 Reagent was

then added to one-half of the split sample to bleach out the

color of the Al-Aluminon complex. The AluVer 3 Alumi-

num reagent, packaged in powder form, shows exceptional

stability and is applicable for fresh water applications. Test

results were measured at a wavelength of 522 nm.

2.3.3 Sample analysis: Fe

Fe concentrations were measured using Perkin-Elmer (P.E.

AAnalyst 100) Atomic Absorption Spectroscopy (AAS).

Detection limits were determined and calibration for the

AAS analysis was achieved with the prepared external

standards through the standard curve approach. The

external metal standard solutions for the AAS calibration

curve were prepared by dilution using 1,000 mg/l standard

solutions. Metal standard solutions for Fe were prepared in

five different concentrations for instrument calibrations.

Deionized water was used as a blank solution for analysis

of standard solutions for the purpose of analyzing standard

readings to verify baseline stability. Calibration curves

obtained were acceptable during verification of a given

analysis with regards to the variations of parameters and

the effects of concomitants. Finally, standard solutions

were then analyzed and the calibration curve plotted before

the Fe concentration of the sample could be determined.

2.4 Statistical analysis

Response surface methodology (RSM) was used to find the

optimum operating conditions for the selected factors

(Montgomery 2005) that result in maximum extracted [Al]

and [Fe]. D-optimal design was used to study the effect of

T, t, and r on Al and Fe concentrations as two responses.

The D-optimal design was specifically constructed for

this experiment. There were three parameters used in this

design, which were temperature, T (�C), time, t (min), and

ratio of soil to extractant, r (mg/l). T was set at 30 �C (low)

and 90 �C (high) while t was 30 min (low) and 90 min

(high), and r at 1:5, 1:10, and 1:15. The total number of

experimental runs was 20. A model was developed to

optimize the process by finding the best operating condi-

tions to maximize metal concentrations extracted.

3 Results and discussion

3.1 Best Fe and Al extractants from laterite soil

3.1.1 Fe extraction

Acid concentration influences the concentration of Fe

extracted from laterite soil. It was found that the 5 N HCl

extractant exhibited the highest [Fe] extracted from the soil

due to low pH condition, supported by Takahashi and Tor-

iyama (2004). They stated that higher concentrations of acids

(or low pH) produce more extracted yield of Fe2? ions. Acid

dissolution of iron oxides involved in the breakdown of the

Fe–O ionic bonds. The ionic radius of Fe2? is larger than

Fe3?, therefore the Fe2?–O bond will be longer and weaker

than the Fe3–O bond. Aside from this, the breakdown of the

Fe3? compounds can be accelerated by the presence of Fe2?

in the solution, which reduces Fe3? ions exposed at the

compounds’ crystal surface (Sidhu et al. 1981).

3.1.2 Al extraction

Different molar concentrations of HCl give different con-

centrations of Al extracted; 3 N HCl yielded the highest

amount of Al, which was 0.0665 mg/l followed by 5 N

HCl (0.0600 mg/l), 4 N HCl (0.0480 mg/l), 1 N HCl

(0.0125 mg/l), and lastly 2 N HCl (0.00900 mg/l). The 3 N

HCl was able to extract marginally more Al compared to

5 N HCl. This was caused by the fact that acid was the

limiting reactant in this reaction. The combination of 2 N

HCl and 4 N NaCl exhibited the highest extraction value,

which was 0.152 mg/l followed by 4 N HCl and 2 N NaCl

(0.102 mg/l). The concentration of Al extracted was more

than 0.100 mg/l making it the best extractant of Al. How-

ever, each molar concentration of NaOH extractant showed

insignificant effects on Al extracted (\0.00800 mg/l of Al;

under analytical range).

From the results obtained, it can also be concluded that

the laterite soil collected was rich in Fe compared to Al.

Environmentalist (2012) 32:453–463 457

123

3.2 D-optimal statistical design

Once the best extractants and their concentrations have

been established for Al and Fe extraction, respectively,

other factors were studied to determine their role in the

extraction process of Al and Fe from laterite soil. Three

factors were thought to be influential on the concentrations

of Al and Fe extracted from laterite soil from literature

(as discussed previously). The factors were T (30, 90 �C),

t (30, 90 min), and r (1:5, 1:10, and 1:15). The levels of the

selected factors were chosen based on logical ranges of

values (as well as literature) and preliminary experiments.

Response surface methodology (RSM) was carried out

to investigate the effect of selected factors on [Fe] and [Al].

D-optimal design with 20 runs was used to cover all pos-

sible combination of the selected factor levels. All exper-

iments were conducted in random order.

The results of 20 run D-optimal design with three factors

are given in Table 4 including the levels of the selected

factors and observed (experimental) values for [Fe] and [Al].

The results obtained from D-optimal design were analyzed

using analysis of variance (ANOVA) and a regression model

was built for [Fe] and [Al] to explore the effects of selected

factors (T, t, and r) on these two responses.

3.2.1 Regression models of [Fe] and [Al]

Regression models for [Fe] and [Al] extracted from laterite

soil were derived to describe the behavior of [Fe] and [Al]

at different levels of selected factors in order to optimize

the process by finding the best settings of T, t, and r.

Regression models for [Fe] and [Al] in terms of coded

variables are given in Eqs. (1) and (2), respectively.

½Al� ¼ 0:160� 0:0100 T � 0:0130 t � ð5:50� 10�3Þ r1

þ ð9:50� 10�3Þ r2 � 0:0140 T t þ 0:0190 T r1

� ð9:80� 10�3Þ T r2 þ ð7:80� 10�3Þ t r1

þ 0:0130 t r2 ð1Þ

Table 4 The results of D-optimal design

Input variable Responses

T (�C) t (min) *r (mg/l) [Al] (mg/l) [Fe] (mg/l)

30 60 1 0.130 168

90 30 2 0.150 843

30 30 3 0.200 316

90 90 2 0.140 298

90 90 3 0.0800 324

90 30 3 0.190 147

30 90 2 0.190 257

30 30 2 0.170 235

60 60 3 0.180 126

60 30 1 0.140 259

60 90 1 0.160 779

90 60 1 0.150 1,310

60 45 2 0.190 677

30 30 1 0.160 148

90 30 1 0.200 533

30 90 1 0.150 165

90 30 3 0.180 1,730

90 90 3 0.0800 3,260

30 30 3 0.170 322

30 90 2 0.200 266

* r, 1 = 1:5; 2 = 1:10; 3 = 1:15

Fig. 1 Normal probability plot

of the studentized residuals for

(a) [Fe] and (b) [Al]

458 Environmentalist (2012) 32:453–463

123

½Fe� ¼ 1010þ 839 T þ 414 t � 335 r1 þ 36:8 r2 þ 461 T t

� 271 T r1 þ 0:550 T r2 � 72:8 t r1 þ 131 t r2 ð2Þ

(Note: Subscripts 1 and 2 denote codes of ‘‘dummy vari-

ables’’ where ratio 1 (1:5), r1 = 1; r2 = 0; ratio 2 (1:10),

r1 = 0; r2 = 1; ratio 3 (1:15), r1 = 0; r2 = 0).

The models obtained for [Fe] and [Al] were satisfactory

since the values of the coefficient of determinations (R2)

were high. Close to 1 values of R2 indicate that the model

fitted the data reasonably. The values of R2 for the [Fe] and

[Al] models were 0.99 and 0.82. This suggested that

0.82–0.99 of the total variation was explained by the

models. All terms were included in the model to keep the

model hierarchical. The positive sign (?) of the coeffi-

cients in the regression model indicates that the factor has

synergistic effects on the responses ([Al] and [Fe]) while

the negative sign (-) indicates that the factor has antago-

nistic effects.

3.2.2 Model checking

The following is the quality check conducted on the

regression models developed. The regression models

obtained (Eqs. 1 and 2) were checked for the normality

assumption through the normal probability plot for the

studentized residual as shown in Fig. 1a, b. All points were

located along the straight line with the range of studentized

residuals ±3. This indicates that there was no doubt on the

violation of the normality assumption for both [Fe] and

[Al].

In addition, the assumptions for constant variance and

independence between the residuals were investigated.

Figure 2a, b show the studentized residuals versus pre-

dicted (fitted) values for [Fe] and [Al], respectively. There

were no unusual structures observed since the residuals

revealed that they were structure-less and thus unrelated to

any other factors, including the predicted response. This

indicates that the constant variance assumption was

satisfied.

Plotting the residuals in order of run numbers (time) is

helpful in detecting the correlation between the residuals.

A plot of residual versus time is shown in Fig. 3. From

observations, there was no reason to suspect any violation

of the independence or constant variance assumption.

Thus, the models fitted the data properly and can be used to

study the effect of selected factors on [Fe] and [Al].

3.2.3 Testing the main effects and interactions of T, t,

and r on [Fe] and [Al]

The results of the analysis of variance (ANOVA) for [Fe]

and [Al] are given in Table 5. It can be seen that the

regression models for [Fe] and [Al] are statistically sig-

nificant, which means that the selected factors influence

the extraction process. Furthermore, T, t, and r exhibited

Predicted

Stud

entiz

ed R

esid

uals

Residuals vs. Predicted

-3.00

-1.50

0.00

1.50

3.00

-12 1612 3236

(a) [Fe]

Predicted

Stud

entiz

ed R

esid

uals

Residuals vs. Predicted

-3.00

-1.50

0.00

1.50

3.00

0.087 0.144 0.201

(b) [Al]

Fig. 2 Plot of studentized residuals versus predicted (fitted) values

for (a) [Fe] and (b) [Al]. Upper and lower solid lines represents the

theoretical range of studentized residuals ±3; the middle line is the

mean of the studentized residuals

Environmentalist (2012) 32:453–463 459

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significant effects on [Fe] extracted from laterite soil (refer

to Table 5). On the other hand, only the main effects of

t showed significant effect whilst the main effect of T and

r did not show any significant effect on [Al]. The latter has

also been observed by Poulin et al. (2008) for red mud.

More time was needed to solubilize Al compared to Fe,

even though oxides of Al and Fe are easily soluble in acids,

using the chosen extractant. From literature and also seen

Fig. 3 Plots of studentdized

residuals versus run numbers

(time) for (a) [Fe] and (b) [Al].

Solid lines represent ±3

permissible limits for the error

while the middle block linerepresents the mean of the errors

Table 5 The results of ANOVA for [Fe] and [Al] extracted from laterite soil

Sum of variances SSa dfb MSc F value P value

[Fe]

Model 2.04 9 107 9 2.27 9 106 120 \0.000100

T 6.16 9 106 1 6.16 9 106 326 \0.000100

t 3.11 9 106 1 3.11 9 106 165 \0.000100

r 1.59 9 106 2 7.96 9 105 42.2 \0.000100

T and t 1.60 9 106 1 1.60 9 106 85.0 \0.000100

T and r 5.98 9 105 2 2.99 9 105 15.9 \0.000800

t and r 1.20 9 105 2 60,200 3.19 0.0848

Error 1.89 9 105 10 18,900

Total 2.06 9 107 19

[Al]

Model 0.0200 9 2.20 9 10-3 5.07 \0.00920

T 3.48 9 10-4 1 3.48 9 10-4 0.800 0.392

t 2.72 9 10-3 1 2.72 9 10-3 6.26 \0.0313

r 1.58 9 10-3 2 7.90 9 10-4 1.82 0.212

T and t 1.50 9 10-3 1 1.50 9 10-3 3.44 \0.0932

T and r 2.40 9 10-3 2 1.20 9 10-3 2.76 0.111

t and r 2.00 9 10-3 2 10.0 9 10-4 2.30 0.151

Error 4.35 9 10-3 10 4.35 9 10-4

Total 0.0240 19

a SS sum of squaresb df degree of freedomc MS mean sum of squares

460 Environmentalist (2012) 32:453–463

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in this work, Fe showed obvious extracted differential

changes in extracted quantities at low temperature (circa

50 �C) that became less apparent with higher temperatures

([100 �C) (Poulin et al. 2008). Furthermore, oxides of Fe

is readily more soluble in acids than oxides of Al, thus it is

intuitive that it becomes more dependent on other physical

parameters, i.e., T (by the second law of thermodynamics)

and r (more volume), plus the differential changes more

evident than what can be seen for Al.

In addition to the main effects, the interactions among T,

t, and r were studied. Interactions between T and t and

between T and r exhibited strong significant effect on [Fe]

extracted from laterite soil; the interaction between r and

t was significant at p \ 0.0850 (refer to Table 5). However,

the effect of factors interactions exhibited different

behavior on [Al] also shown in Table 5. The interactions

showed less effect on [Al] compared to [Fe] since the

interaction between T and t was significant at p \ 0.0900

and the p value for other interactions was higher than

0.100. These results reinforced the explanation given in the

previous paragraph.

3.2.4 Three-dimensional response surface

Three-dimensional response surface plots for [Fe] and [Al]

as a function of t and T at three settings of r are given in

0

512

1023

1535

2047

[Fe

]

30.0

45.0

60.0

75.0

90.0

30.00

45.00

60.00

75.00

90.00

T t

(a) r = 1:5

100

825

1550

2275

3000

[Fe

]

30.0

45.0

60.0

75.0

90.0

30.0

45.0

60.0

75.0

90.0

T t

(b) r = 1:10

50

913

1775

2638

3500

[Fe

]

30.0

45.0

60.0

75.0

90.0

30.0

45.0

60.0

75.0

90.0

T t

(c) r = 1:15

Fig. 4 Three-dimensional

response surface plot for [Fe] as

a function of t and T at

a r = 1:5, b r = 1:10, and

c r = 1:15

Environmentalist (2012) 32:453–463 461

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Figs. 4, 5, respectively, showing the behaviors of [Fe] and

[Al] at different values of T and t to study the changes on

[Fe] and [Al]. It can be seen that the effect of t and T on

extraction of Fe showed similar trend for all three settings

of r. In summary, maximum [Fe] can be achieved at high

temperatures (T = 90 �C) and time (t = 90 min) as seen in

Fig. 4. The three-dimensional plot for [Al] showed differ-

ent behaviors than that of [Fe] (refer to Fig. 5) since the

effect of t and T depended on r. Figure 5a, c show that the

maximum [Al] that can be achieved is by setting a high

T and low t while Fig. 5b suggests that maximum [Al] can

be achieved by using the maximum t = 90 min and low

T = 30 �C. Higher temperature would result in more Al

dissolving in the extractant at shorter amount of time.

However, these inconsistent observations (or indepen-

dence) were probably due to the low concentrations of Al

(compared to Fe) present in the collected laterite soil while

the impartiality of [Al] extracted from T and t was also

observed by other researchers (Poulin et al. 2008).

3.3 Optimization of the experiment

Optimization of the process can be done based on the

results of the D-optimal design and regression models

0.100

0.120

0.140

0.161

0.181

[A

l]

30.0

45.0

60.0

75.0

90.0

30.0

45.0

60.0

75.0

90.0

T t

(a) r = 1:5

0.100

0.125

0.150

0.175

0.200

[A

l]

30.0

45.0

60.0

75.0

90.0

30.0

45.0

60.0

75.0

90.0

T t

(b) r = 1:10

0.050

0.088

0.125

0.163

0.200

[A

l]

30.0

45.0

60.0

75.0

90.0

30.0

45.0

60.0

75.0

90.0

T t

(c) r = 1:15

Fig. 5 Three-dimensional response surface plot for [Al] as a function of t and T at a r = 1:5, b r = 1:10, and c r = 1:15

462 Environmentalist (2012) 32:453–463

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developed. Once the models have been derived and

checked for adequacy, the optimization criteria can be set

to determine the optimum operating conditions. The goal

was to maximize [Fe] and [Al] extracted from laterite soil.

Thus, the optimum operating conditions to obtain maxi-

mum [Fe] and [Al] simultaneously were: high T (90 �C)

and t (40 min) with r = 1:15 and the results were

1,870 mg/l [Fe] and 0.170 mg/l [Al]. At a lower ratio of

r = 1:10, the settings of the combined factors were high

T = 90 �C and t = 90 min, which resulted in 2,900 mg/l

[Fe] and 0.130 mg/l [Al].

4 Conclusions

The 5 N HCl extractant was found to exhibit the highest

[Fe] extracted from laterite soil while the combination of

2 N HCl and 4 N NaCl exhibited the highest extraction

value for [Al]. NaOH was not effective in extracting Al or

Fe from the soil. Temperature T, time t, and extractant-to-

soil ratio r, (and their interactions) were found to affect

concentration of Fe extracted. However, only time was

significant for Al. From D-optimal statistical design,

extraction settings based on the above factors were deter-

mined to maximize extracted Al and Fe concentrations

simultaneously, which were: (1) r = 1:10; T = 90 �C;

t = 40 min and (2) r = 1:15; T = 90 �C; t = 90 min.

Acknowledgments The authors would like to thank Universiti

Sains Malaysia for providing the infrastructure and financial assis-

tance that made this work possible. The authors would also like to

acknowledge the meticulous laboratory work done by Tan Lean Ping

and the effort given by Lim Han Khim.

References

Bhattacharya P (2007) Arsenic in soil and groundwater environment:

biogeochemical interactions, health effects and remediation.

Trace metals and other contaminants in the environment, vol 9.

Elsevier, Amsterdam

Bratby J (2006) Coagulation and flocculation in water and wastewater

treatment, 2nd edn. IWA Pub, Seattle, WA

Jiang JQ, Zeng ZQ, Pearce P (2004) Evaluation of modified clay

coagulant for sewage treatment. Chemosphere 56(2):181–185.

doi:10.1016/j.chemosphere.2004.03.007

Ko T-H, Chu H, Lin H-P, Peng C-Y (2006) Red soil as a regenerable

sorbent for high temperature removal of hydrogen sulfide from

coal gas. J Hazard Mater 136(3):776–783. doi:10.1016/j.jhazmat.

2006.01.010

Lee JF, Liao PM, Lee CK, Chao HP, Peng CL, Chiou CT (2004)

Clay-catalyzed reactions of coagulant polymers during water

chlorination. J Colloid Interface Sci 270(2):381–387. doi:10.10

16/j.jcis.2003.08.065

Luo M, Bi S (2003) Solid phase extraction-spectrophotometric

determination of dissolved aluminum in soil extracts and ground

waters. J Inorg Biochem 97(1):173–178. doi:10.1016/s0162-013

4(03)00243-5

Mahalinga-Iyer U, Williams DJ (1991) Engineering properties of a

lateritic soil profile. Eng Geol 31(1):45–58. doi:10.1016/0013-79

52(91)90056-q

Matus P, Kubova J, Bujdos M, Medved J (2006) Free aluminium

extraction from various reference materials and acid soils with

relation to plant availability. Talanta 70(5):996–1005. doi:10.101

6/j.talanta.2006.05.045

Montgomery DC (2005) Design and analysis of experiments, 6th edn.

Wiley, Hoboken, NJ

Pang FM, Teng SP, Teng TT, Kadir MOA (2009) Heavy metals removal

by hydroxide precipitation and coagulation-flocculation methods

from aqueous solutions. Water Qual Res J Can 44:174–182

Poulin E, Blais J-F, Mercier G (2008) Transformation of red mud

from aluminium industry into a coagulant for wastewater

treatment. Hydrometallurgy 92(1–2):16–25. doi:10.1016/j.hydr

omet.2008.02.004

Rao CRM, Sahuquillo A, Lopez-Sanchez JF (2010) Comparison of

single and sequential extraction procedures for the study of rare

earth elements remobilisation in different types of soils. Anal

Chim Acta 662(2):128–136. doi:10.1016/j.aca.2010.01.006

Shui J-G, Wang Q-Z, Liao G-Q, Au J, Allard JL (2008) Ecological

and economic benefits of vegetation management measures in

citrus orchards on red soils. Pedosphere 18(2):214–221. doi:

10.1016/s1002-0160(08)60009-0

Sidhu PS, Gilkes RJ, Cornell RM, Posner AM, Quirk JP (1981)

Dissolution of iron oxides and oxyhydroxides in hydrochloric

and perchloric acids. Clays Clay Miner 29(6):269–276

Siradz SA (2008) Mineralogy and chemistry of red soils of Indonesia:

I. General soil properties. Jurnal Ilmu Tanah dan Linkungan 8(1):

16–32

Takahashi T, Toriyama K (2004) Method to evaluate ‘‘uplandization’’

in converted field from a paddy based on crystallinity of free iron

oxides, vol 38. vol 3. Ministry of Agriculture, Forestry, and

Fisheries, Ibaraki, Japan

Tan BH, Teng TT, Omar AKM (2000) Removal of dyes and industrial

dye wastes by magnesium chloride. Water Res 34(2):597–601.

doi:10.1016/s0043-1354(99)00151-7

Walna B, Spychalski W, Siepak J (2005) Assessment of potentially

reactive pools of aluminium in poor forest soils using two

methods of fractionation analysis. J Inorg Biochem 99(9):

1807–1816. doi:10.1016/j.jinorgbio.2005.06.026

Wilson MJ, He Z, Yang X (2004) The red soils of China: their nature,

management, and utilization. Kluwer, Dordrecht

Young A (1976) Tropical soils and soil survey. Cambridge geo-

graphical studies, vol 9. Cambridge University Press, Cam-

bridge, NY

Environmentalist (2012) 32:453–463 463

123