1

CONCENTRATION OF IRON IN LATERITES USING

IN-SITU CARBONIZED BIOMASS

BY

NJOROGE PETER WAITHAKA

I84/21312/2010

A Thesis submitted in fulfillment of the requirements for the award

of the Degree of Doctor of Philosophy in the School of Pure and

Applied Science, Kenyatta University

July 2014

ii

DECLARATION

I hereby declare that this is my original work and has not been presented for the

award of a degree or any award in any other University.

Signature………………………………………… Date..............................................

PETER WAITHAKA NJOROGE

I84/21312/2010

DEPARTMENT OF CHEMISTRY

This Thesis has been submitted for examination with our approval as the University Supervisors.

1. Prof. NAFTALI T. MURIITHI

Chemistry Department

Kenyatta University

Post humus

2. Dr. JACKSON WACHIRA MUTHENGIA

School of Pure and Applied Sciences

Embu University College

Signature………………………………………. Date…………………………

3. Dr. RUTH WANJAU

Chemistry Department

Kenyatta University

Signature……………………………………… Date…………………………

iii

DEDICATION

This work is dedicated to my wife Florence Waithaka, our children Celine Waithaka and Valerie

Waithaka and my mother Rahab Njoroge.

iv

ACKNOWLEDGEMENTS

I express my gratitude to my supervisors; The late Prof. Naftali T. Muriithi, Dr. Jackson

Wachira Muthengia and Dr. Ruth Wanjau for taking me on when I seemed to have lost

my way and giving me new direction and counsel and supporting me to complete this

degree and renewing my hope. I appreciate your continued sharing of knowledge,

experience and supporting me during the course of my study.

I thank the Kenyan Government for sponsoring this Research work through the National

Council for Science and Technology (NCST) and also through Kenyatta University. I am

also grateful to all lecturers and Technical Staff of Chemistry Department, Kenyatta

University, Natural Resources until April 2013) and International Centre for Research in

Agro-Forestry (ICRAF)for their substantial help during this study.

My heartfelt appreciation goes to my beloved wife Florence for her invaluable support,

care, love, counsel, and encouragement especially during the times when everything

seemed impossible. She always renewed my strength and went to great length in

supporting me and keeping me accountable to completing my studies on time. My

appreciation goes to our children Celine and Valerie for standing with me through the

study period and your constant reminder that I should complete the course.

Above all, I am most thankful to the God Almighty for bringing me this far, the grace and

strength He gave me to go through my study period and carry out all the necessary research

and c omplete this study. May He reward all those who supported me in my Research work.

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TABLE OF CONTENTS

DECLARATION .................................................................................................................... ii

DEDICATION ....................................................................................................................... iii

ACKNOWLEDGEMENTS ................................................................................................... iv

TABLE OF CONTENTS…………………………………………………………………….v

LIST OF TABLES ............................................................................................................... viii

LIST OF FIGURES………………………………………………………………...………...x

LIST OF PLATES .................................................................................................................. xi

ABBREVIATIONS AND ACRONYMS ............................................................................. xii

ABSTRACT ......................................................................................................................... xiv

CHAPTER ONE ..................................................................................................................... 1

INTRODUCTION ................................................................................................................... 1

1.1 Background information ................................................................................................... 1

1.1.1 Occurrence of iron .......................................................................................................... 1

1.1.2 Importance of iron in economic development of any nation.......................................... 1

1.1.3 Sources of iron ............................................................................................................... 2

1.1.4 Occurrence of iron ore in Kenya .................................................................................... 2

1.1.5 Importance of mineral concentration ............................................................................. 3

1.1.6 Kenya's import bill for iron-made products ................................................................... 6

1.1.7 Kenya's Iron rolling mills ............................................................................................... 7

1.1.8 Kenya's export of iron ore .............................................................................................. 7

1.2 Problem statement and justification .................................................................................. 7

1.3 Hypothesis ......................................................................................................................... 8

1.4 Objectives .......................................................................................................................... 8

1.4.1 General objective ............................................................................................................ 8

1.4.2 Specific objectives .......................................................................................................... 8

1.5 Scope and limitation of the study ...................................................................................... 9

vi

1.6 Significance of the study ................................................................................................... 9

CHAPTER TWO ................................................................................................................... 12

LITERATURE REVIEW ...................................................................................................... 12

2.1 Laterites ........................................................................................................................... 12

2.2 Iron-minerals ................................................................................................................... 15

2.3 Concentration of iron ores ............................................................................................... 17

2.3.1 Concentration methods ................................................................................................. 17

2.3.2 Milling iron .................................................................................................................. 19

2.3.3 Gravity concentration .................................................................................................. 19

2.3.4 Froth flotation ............................................................................................................... 20

2.3.5 Magnetic separation ..................................................................................................... 29

2.4 Extraction of iron ........................................................................................................... 31

2.5 Analytical techniques ...................................................................................................... 38

2.5.1 Atomic absorption spectroscopy .................................................................................. 38

2.5.2 Atomic emission spectroscopy ..................................................................................... 40

2.5.3 X-ray diffraction (XRD) spectroscopy ......................................................................... 40

2.5.4 Ethylene diamine tetra acetic acid (EDTA) titratio ...................................................... 42

CHAPTER THREE .............................................................................................................. 44

3.0 MATERIALS AND METHODS ................................................................................... 44

3.1 Sample collection and preparation .................................................................................. 44

3.2 Cleaning of pulverizer, glassware and plastic containers ............................................... 45

3.3 Laterite sample treatment and analytical procedures ...................................................... 46

3.3.1 Weight loss on ignition ................................................................................................ 46

3.3.2 X-ray fluorescence spectrometer (XRFS) analysis ...................................................... 46

3.3.3 Chemical analysis using (AAS) ................................................................................... 47

3.3.4 The EDTA titrimetric analysis ..................................................................................... 47

3.3.5 The X-ray diffraction (XRD) analysis ......................................................................... 48

vii

3.3.6 Froth flotation ............................................................................................................... 48

3.3.7 Concentration equipment ............................................................................................. 49

3.3.8 Optimisation of biomass ............................................................................................... 51

3.3.9 Particle size measurment ............................................................................................. 51

3.3.10 Concentration of iron in laterites using biomass and charcoal ................................... 52

3.4 Data analysis .................................................................................................................. 53

CHAPTER FOUR ................................................................................................................ 55

RESULTS AND DISCUSSION .......................................................................................... 55

4.1 Mineral composition of raw and concentrated laterites ................................................. 55

4.2 Optimization .................................................................................................................... 59

4.3 Particle size variation ...................................................................................................... 61

4.4 Elemental analyses of raw laterites ................................................................................ 64

4.5 Loss on ignation (LOI) ................................................................................................... 67

4.6 Chemical composition after concentration ..................................................................... 69

4.6.1 Results after concentration using charcoal ................................................................... 69

4.6.2 Results after concentration using biomass ................................................................... 70

4.6.3 Results after concentration using froth floatation ........................................................ 71

4.7 Comparison of iron levels in raw and treated laterites ................................................... 74

4.8 Lateries containing low levels of iron ............................................................................. 77

4.9 Concentration using large quantities of Laterites ........................................................ …78

CHAPTER FIVE ................................................................................................................... 80

CONCLUSIONS AND RECOMMENDATIONS ................................................................ 80

5.1 Conclusions ..................................................................................................................... 80

5.2 Recommendations ........................................................................................................... 81

5.2.1 Recommendations from this work ............................................................................... 81

5.2.2 Recommendations for further research ........................................................................ 81

REFERENCES ..................................................................................................................... 83

viii

LIST OF TABLES

Table 1.1 Examples of some typical iron ores…………………………………………….....5

Table 2.1 Iron bearing minerals………………………………………………………….....16

Table 2.2 World iron ore production (Millions of metric tonnes)………………………....16

Table 2.3 Showing percentages of iron ore concentrated using the various methods in the

USA in 1990..........................................................................................................................18

Table 4.1 Mineral content of Laterites from selected Sites in Kamahuha Muranga

County……………………………………………………………………………...…….…56

Table 4.2 Determination of levels of iron using different ratios of biomass to laterites…...59

Table 4.3 Statistical comparison of the various biomass to late riteratios.............................60

Table 4.4 Showing levels of iron after concentration using different particle sizes..............61

Table 4.5 Showing statistical comparison of iron levels obtained using different

particle size.………………………………………………………………………………...62

Table 4.6 Levels of iron in control experiments....................................................................63

Table 4.7 Results of elemental analyses of raw laterites using AAS...............................…..65

Table 4.8 Results of elemental analyses of raw laterites using XRF……………………….65

Table 4.9 Results of elemental analyses of raw laterites using EDTA titrations………….. 66

Table 4.10 Loss on ignition of raw samples………………………………………………..67

Table 4.11 Mean Chemical composition of raw laterites in K1 and statistical comparison

of AAS and XRF and EDTA titrations……………………………………………………..68

Table 4.12 Mean Chemical composition of raw laterites in K4 and statistical comparison

of AAS and XRF and EDTA titrations…………………………………………………......68

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Table 4.13 Levels of the various elements after concentration with charcoal……………...69

Table 4.14 Levels of various elements after concentration with biomass………………….70

Table 4.15 Iron content in concentrate after froth flotation………………………………...71

Table 4.16 Levels of iron in raw laterite and after concentration using charcoal…………..73

Table 4.17 Level of iron in raw laterite and after concentration using biomass…………....74

Table 4.18 Showing levels of iron obtained using the three concentration methods……....75

Table 4.19 Showing statistical comparison of the three methods used for concentration.....75

Table 4.20 Levels of iron in raw laterite from Juja farm and after concentration using

biomass in the ratio1:20………………………………………………………………….....77

Table 4.21 Levels of iron in raw laterite and after concentration using biomass in

the ratio of 1:20 using 5kg of laterite………………………………………..……………...78

Table 4.22 Shows levels of iron in raw laterite and after concentration using different

types of biomass in the ratio of 1:20………………………………………………...….......79

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LIST OF FIGURES

Figure 2.1 a and Figure 2.1 b………………………………………...……………………..21

Figure 2.2 A Floatation cell...……………………………………………………................22

Figure 2.3 The floatation system including many interrelated components…………..……23

Figure 2.4 Types of collectors.………………………………………………………...…...24

Figure 2.5 Adsorption of anionic collector onto a solid surface ………………………...…25

Figure 2.6 Bragg‟s law reflection (Myers, 2002).…………………………………...….….41

Figure 3.1 Iron concentration set-up………………………………….………………….…52

Figure 3.2 The concentration procedure…………..………………………………….…….54

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LIST OF PLATES

Plate 2.1 Soil profile composed mainly of lateritic materials from one of the sampled

sites in Kamahuha, Murang‟acounty Kenya………………………………………………..12

Plate 2.2 A sample of laterite from one of the quarries in Kamahuha area……………...…15

Plate 2.3 Some components of the D2 PhaserDifractometer…………………………….....42

Plate 3.1 Showing a froth flotation cell …………………………………………………....49

Plate 3.2 Showing the gas flow meter used………………………………………………...50

xii

ABBREVIATIONS AND ACRONYMS

AAS Atomic Absorption Spectroscopy

B Magnetic Induction

BIF Banded Iron Formations

DSC Delta Steel Company

ECLAF International Centre for Research in Agro-Forestry

EDA Etherdiamineacetate

EDTA Ethylenediaminetetraacetic Acid

kG kilo Gauss

LOI Loss on Ignition

M Intensity of Magnetization

MIBC Methylisobutylcarbinol

MRG Mount Royal Gabbro

Mt Million Tonnes

PO Propylene Oxide

STC Swedish Trade Council

NIOMCO Nigerian National Iron Mining Company Limited

SY-3 Syenite

T Tesla

SNK Student Newman Keul‟s test it a post ANOVA test.

UAE United Arab Emirates

UNEP United Nations Environmental Programme

USGS United States Geological Survey

xiii

XRD X-ray Diffraction

XRF X- ray fluorescence

xiv

ABSTRACT

Iron occurs in more than 85 minerals. However, among these, only a few are important

ores of the element. For economical extraction of iron, the iron ore must contain over

55% iron. These ores must be concentrated before putting them in a blast furnace. Kenya

has widespread documented huge volumes of laterites. However the country spends huge

amounts of money in importation of iron and iron products despite having these laterites

that are rich in iron. This thesis describes the results of a study undertaken with the aim of

finding out whether the level of iron in laterites (murram), can be increased to a level

above 55% which can placed in a blast furnace for iron extraction. Samples for this study

were obtained from selected murram quarries in, Kamahuha and Juja located in Murang‟a

and Kiambu Counties respectively, in the Republic of Kenya. Total elemental analysis

was carried out with particular interest on the levels of iron in both the raw and treated

samples using Atomic Absorption Spectroscopy (AAS), X-Ray Flourescence

Spectroscopy (XFRS) and EthylenediaminetetraaceticAcid (EDTA) Titrations. The

mineralogical composition of both the raw and treated materials was determined using a

Brucker D2 PhaserDiffractometer. The results of this study show that levels of iron in the

raw laterites from Kamahuha ranged between 24-39% while those form Juja ranged

between 12-17%. The iron in the raw laterites is present predominantly as the minerals

goethite, FeO.OH and haematite, Fe2O3, as shown by presence of peaks at diffraction

angles of 2θ = 21.51˚ and 2θ = 54.11˚respectively, which are attributed to these minerals.

The concentration of iron in the laterites was done by heating a laterite/charcoal mixture

in the temperature range 500-700oC in a ceramic container, under a slow current of air

(0.5-0.7cm3/sec) from a compressed air cylinder. On cooling this mixture, the iron-

containing mineral was readily picked with a permanent horse-shoe magnet (about

92milliteslas). The experiment was repeated using carbonized saw dust, leaves and dried

potato peelings obtained from solid municipal waste in place of charcoal. The optimum

ratio of biomass: laterite was found to be 1:20 by mass. After magnetic-separation iron

was present predominantly as the mineral, magnetite Fe3O4, and had a broad diffraction

peak at 2θ = 36˚.Furthermore, the percentage of iron in the magnet-separated product

from both Kamahuha and Juja had increased to 55-62%. These results show that iron in

the laterites can be increased to a level that can be used for iron extraction. Biomass from

solid municipal waste can be used as a source of carbon monoxide to reduce goethite and

hematite to magnetite. The use of biomass from the solid municipal waste also impacts

positively on the environment. From the results obtained this process should be scaled up

by setting up a pilot plant to concentrate iron laterites and determine the economic

viability of the process.

1

CHAPTER ONE

INTRODUCTION

1.1 Background information

1.1.1 Occurrence of iron

Iron has a relative abundance of 6.46% in the earth‟s crust and is the fourth most abundant

element after oxygen (45.45%), silicon (27.2%) and aluminium (8.3%) (Greenwood and

Earnshaw, 1997). It is noted that whereas the relative abundance values quoted by

different authors may differ slightly, the orders of magnitude and the actual values are

very close to the values reported above (Hammod, 2009).

1.1.2 Importance of iron in economic development of any nation

Iron is produced and used in larger quantities than all the other metals combined (Silver,

1993, Emsley, 2011). This is because of the very wide range of applications that the

metal is put into as illustrated by the following examples: Nails, chain links, iron sheets

for roofing buildings, kitchen utensils, lorries, cars, ships, boats, heavy machinery such

as tractors for road construction and plowing farms, metal pipes for water and

petroleum products and, metal bars in re-enforced concrete for construction of bridges

and multi-storey buildings, (Bramfitt and Benscoter, 2002; Dauphas and Rouxel, 2006).

Furthermore, iron is not only used in many applications but, it is also used in very large

quantities, literally in terms of millions of metric tons. According to the46th

Census of

World Casting Statistics, in the year 2011, some 98,593,122 metric tons of all types of

metals were cast into products of various types. Out of this very large tonnage, iron and

steel contributed 82,376,789 metric tons. Although there have been some years when

the iron and steel consumed decrease slightly, the normal trend is one of increase every

2

year. Thus whereas during the year 2011, around 1000 million metric tons of iron were

produced, during the year 2012, this figure rose to 1,517 million metric tons(World

Steel Association, 2013).

1.1.3 Sources of iron

A mineral is a naturally-occurring crystalline solid whose constituent particles are

inorganic in nature. Iron occurs in well over eighty five minerals (Hammod, 2009).

However, out of this very large number, only a few of them are mined specifically for

extraction of iron. An ore must be in such a volume such that it contains a particular

element in a volume that can be recovered from the ore to make the operation

economical. The few common minerals of iron which are mined specifically to recover

iron and the percentage of iron are: haematite, Fe2O3 (70% iron), goethite,

FeO.OH(63%iron), magnetiteFe3O4 (72.4%iron) and sideriteFeCO3(48%).There are

also a few other minerals which are processed with the aim of recovering other elements

but in the process, iron is also recovered. Examples of such minerals are: Ilmenite,

FeTiO3, which is processed mainly as source titanium and the mineralpyriteFeS2

(otherwise, commonly referred to as fool‟s gold (Kraus et al., 1959) which is

processed mainly as a source of sulphur (Johnsone and Johnsone, 1960).In the process

of recovering titanium from ilmenite and sulphur from the pyrites, iron is also

recovered.

1.1.4 Occurrence of iron ore in Kenya

Kenya has many geologically documented iron ore deposits with varying percentages of

iron in places such as Macalder in Nyanza (45.24%), Ikutha in Kitui County (62-68%),

Samia ranges in Kakamega County (46%) and Marimante in TharakaNthi County

(46%) to mention but a few (Dubois and Walsh, 1970). Besides these deposits, the

lateritic materials (commonly called murram) which are currently being used for

3

surfacing roads have been shown to contain 25-45% iron depending on source

(Muriithi, 1985). This implies that if the source can be shown to contain large enough

quantities, then, the murram should actually be treated as iron ore because, typical iron

ores are said to contain 25-68% iron. (Lepiniski et al., 2004). The murram deposit in

Lela, Western side of Kisumu is estimated to contain 2.726 x 106 cubic metres of the

laterites and since analysis of the material has shown that it contains at least 32% iron

(Muriithi, 1985), then, it is only reasonable to treat it as iron ore (Lepiniski et al., 2004).

Kenya was a British colony until December 1963and any imports including those of

iron-made products came from Britain. Britain got some of its iron ore from places such

as Frodingham where the concentration of the ore is in the range 18-25% (Boltz, 1970).

Thus Britain obtained its iron which was sold to Kenya from ores containing low levels

of iron compared to the murram deposits in Lela.

We note, therefore, that Kenyan Laterites containing 30% to 45% has more iron than

some of the ores that have been used elsewhere in the world to recover the metal. A not

worthy example of such ores is the ore from Frodingham in Britain. Iron in Britain was

processed from ores such as the one from Frodingham (Boltz, 1970).

1.1.5 Importance of mineral concentration

Mineral concentration is one of the most important steps if the operation is to be carried

out economically. We note here that, whereas the pure minerals commonly used for

extraction of iron such as hematite Fe2O3 (70% Fe), goethite FeO.OH (63 % Fe),

Siderite, FeCO3, 48.21% ilimonite FeO(OH).nH2O (60% Fe) and magnetite Fe3O4

(72.4% Fe) contain very high percentage of iron and would be suitable for putting in a

blast furnace directly, in real life situations, they do not occur in pure form but rather,

they are found mixed with other undesirable materials called gangue. For this reason,

4

the percentage of iron in these minerals as they occur in the earth‟s crust varies from

negligibly small quantities to nearly 70% depending on source. When a mineral

contains 25-68% and occurs in sufficiently large deposit, the iron can extracted

economically, of course, after ore concentration (Lepiniski et al., 2004). We note here

that, iron has actually been recovered economically using magnetic separation from ores

with as little as 12% iron (Ohle, 1972; Harry et al., 1973). For economical operations,

ore concentration is one of the most important steps in metallurgy of iron. There are

three reasons for this. First, blast furnace for extraction of iron are never built at the

sites where the ores are mined. In some cases, the ore must be transported over

hundreds of kilometers and some cases, over thousands of kilometres. Japan for

example has been buying iron ore from Liberia, a distance of well over 8,000 kilometres

(Liberia Economy Profile, 2013). If iron ore with low percentage of iron is transported

over such long distances, that iron would actually be very expensive.

A second reason why iron ore must be concentrated is that if an ore with less than 50%

iron is put in a blast furnace, a lot of energy will be wasted heating the gangue. It is

actually recommended that an ore to be put in a blast furnace should contain at least

55% iron (Strassburger I. and Julius H., 1969). The third reason why iron ore must be

refined even when the percentage of iron is high is that impurities such as sulphides or

phosphates are highly undesirable, because sulphur produced forms iron sulphide and

the phosphorus forms iron phosphide. Both products are detrimental to the quality of

steel. In Kenya, iron ore from Ikutha has about 1% phosphorus (Muriithi, 1985), and

thus, it is very similar to the ore from Kiruna mine in Sweden (Kiruna Mining

Technology, 2010). Kiruna mine is one of the largest iron ore deposits known in the

world. In the two cases, the ores are predominantly magnetite (though some is present

5

as haematite) and, in each case, the ore contains about1% phosphorus. Table 1.1 shows

some typical iron ores used by different countries for iron extraction.

Table 1.1 Examples of some typical iron ores

Country District Ore Iron (Fe) %

France Sancy Calcareous 32

France Mont-St-Martin Siliceous 37.3

India Cuddapah Hematite 50.7 to 61.2

Russia Krivoi-Rog Hematite 61

Russia Kerch Brown 40.2

Sweden Kiruna

Magnetite with

Hematite 65 to 68

U.K. Frodinghan Brown Ores 18-24

Various concentration methods have been used in the concentration of iron. Magnetic

separation is mainly affected by the ability of a particle to be magnetized, the intensity

of magnetic field required to magnetise and hold a particle of specific susceptibility and

the Particle velocity which controls the dwell time that the particle is exposed to the

magnetic field. A low velocity will enable the magnetic field to capture and hold a

particle, whereas a high velocity will result in only a deflection and no capture. This

effect is more important as magnetic susceptibility decreases.

Magnetic separation has been widely used to concentrate iron. The method has the

following disadvantages;

(i) High maintenance costs (matrix)

(ii) Prone to matrix plugging

(iii)Dirty operation requiring supervision

(iv) Inefficient separation due to wiping effect of product flow

Concentration using this method works best with strongly magnetic ores. This project

aimed at converting the less magnetic oxides of iron (goethite and hematite) to

6

magnetite which is strongly magnetic this reduces the amount of energy used during the

separation.

Froth floatation is another method used in iron concentration this method works well

with sulphide minerals where frothing agents are not required. The most useful ores of

iron are found in the form of oxides, these minerals require several chemicals to

improve their properties during the separation. This method is therefore limited to:

(i) The pulp must be agitated sufficiently to keep all particles in suspension thus

electric energy is required for the agitation.

(ii) It is often necessary to condition the reagents with the minerals for a period

of time to ensure good coverage with collector.

(iii) In many cases, adding frother in stages along with makeup water may be

necessary to keep the pulp level and froth depth constant.

(iv) The products obtained may not achieve the highest concentration possible

and may require farther concentration. For iron the concentrate obtained is

normally further concentrated using magnetic separation (Kawatra and

Eisele, 2001).

Kenya’s import bill for iron –made products

According to Kenya National Bureau of Statistics published in 2010, during the years

2007, 2008 and 2009, the country imported iron and steel products worth Kshs. 27

billion, 36 billion and 70 billion, respectively. Here, we note a sharp increase in the

import bill as the economic activities increase. Second, whereas seventy billion shillings

is not a lot of money for an economically developed country such as the USA, it is a

colossal sum of money for a growing economy such as Kenya which is struggling even

7

to feed its fast-growing population. A noteworthy point is that some of the imported

products are made using iron extracted from ores with much lower concentration of iron

than that found in some of the ores in Kenya.

1.1.7 Kenya’s iron rolling mills

Currently, Kenya has a number of steel rolling mills in Nairobi, Mombasa and Ruiru.

These are mainly for smelting scrap metal and shape it to different products such as

metal bars used in re-enforced concrete. The country does not have any blast furnace to

extract iron from the ores.

1.1.8 Kenya’s export of iron ore.

As noted in Section 1.1.6, Kenya is spending large amount money to import iron- made

products. It has no blast furnace to extract iron from local ores and instead, the country

is actually exporting its iron ore. For example, there is currently an advertisement in the

Internet by a company called Munoz Associates International for sale of iron ore

containing 60% from Kenya. Another company by the name, Wanjala Mining

Company, is mining iron ore from Taita Taveta and selling it to Chinese Company

(Sunday Nation, 22nd

May, 2011).

1.2 Problem statement and justification

The outline in the forgoing sections has revealed several important factors. First, the

country has many geologically documented iron ore deposits. Second, besides the iron-

rich ores, the country has literally millions of tons of laterites, commonly known as

murram. These laterites contain 15-45% iron depending on source and thus, those

occurring in sufficiently large deposits are actually typical iron ores. Concentration is

one of the most important stages in the recovery of iron from the iron ore. This project

8

aims at using biomass from solid municipal waste in the concentration of iron in

laterites.

1.3 Hypothesis

Laterites contain high levels of iron. The iron minerals in laterites can be reduced to

magnetite using CO generated in-situ by carbonizing biomass. Magnetic separation can

then be used to concentrate the iron after the reduction.

1.4 Objectives

1.4.1 General objective.

To concentrate iron in laterites via biomass carbonization and magnetic separation to a

level which is suitable for putting in a blast furnace.

1.4.2 Specific objectives

i.To determine the mineralogical composition of raw and concentrated laterites using

X-ray-diffraction technique.

ii.To optimize biomass: laterite ratio for concentration of iron in laterites.

iii. To determine the effect of varying the particle size on concentration of iron in

laterites.

iv.To carry out elemental analysis of major elements in raw laterites using XRF, AAS

and EDTA titrations.

v.To carry out elemental analysis of major elements in the concentrated laterites using

AAS after concentration using both charcoal, biomass and froth floatation.

vi.To determine the level to which iron can be concentrated in laterites containing low

levels of iron using biomass.

9

1.5 Scope and limitation of the study

Iron in laterites from selected sites in Kamahuha and Juja in Murang‟a and Kiambu

Counties respectively have been concentrated by heating a charcoal/laterite mixture and

a laterite/biomass mixture in different ratios in the temperature range 500-700 0C in a

controlled current of air. Magnetic separation was carried out using a horse shoe

magnet.

The study did not determine the porosity and density of the laterites. The air flow rate

was limited to a range between 0.5-0.7cm3/second. The study was also limited to

variation in temperature within the working range of 500-700 0C. A cost benefit

analysis to compare the method with other commercial methods was not carried out.

This study was carried out within the following limitations:

i. The concentration equipment had its size limited to the heat exchanger used.

ii. The concentration equipment could not be rotated during the concentration.

iii. The air flow rate remained in the range 0.5-0.7cm3/second since above this rate

the sample would be blown out of the concentration equipment.

1.6 Significance of the study

Kenya is a developing country which has set its development agenda in the vision 2030

blue-print. One of the pillars of vision 2030 is economic development, which outlines

industrialization as a major factor of development. Practically all manufacturing

industries require iron and steel. However, the country depends on imported iron and

steel. Billions of shillings are spent in the importation of these goods. This study is

aimed at developing a new technique to be used in concentration of iron in laterites, the

technique is expected to: -

(i) Use laterites as a source of iron.

10

(ii) Use biomass from solid municipal waste as a source of carbon to be used in the

concentration of iron in laterites.

(iii) Reduce environmental pollution by converting biomass from solid municipal

waste as a resource.

Biomass is a major component of the solid municipal waste is an environmental concern

due to the large volume produced every day. According to United Nations

Environmental Programme report, Nairobi city produces over 2000 tons of garbage per

day (UNEP, 2012).When biomass is heated to about 500oC combustible gases such as

carbon monoxide, hydrogen and methane are produced. These gases are reducing agents

which enhance the reduction of the iron oxides to magnetite. The concentration process

makes use of biomass as a source of carbon. The process will not only concentrate iron

in laterites, it will also help in cleaning of the environment (Funke, 2009).

Concentration of iron in laterites to ore grade levels will be a first step towards extraction

of iron from this resource. If the ore formed is reduced to iron then the resource will give

incentives in setting up other industries in Kenya and have some positive economic

impact on the lives of Kenyans. No doubt, this will impact positively on the

environment. The use of biomass from municipal solid waste in the manufacture of

carbon will assist in solving waste disposal problem. The possibility of using laterites as

a source of magnetite need to be studied since laterites contain high levels of iron and are

available in large quantities in Kenya.

From table 1.1, it is evident that iron ores from countries such as U.K and France have

relatively lower iron concentrations than some laterites found in Kenya (Dubois and

Walsh, 1970). Thus the country should be able to produce iron from these resources. In

this study, iron in laterites was enriched using a newly- developed technique where a

11

laterite-biomass mixture was heated in a current of air at temperature range of 500-

700oC. When biomass is heated to a temperature of 300

oC, it is carbonized. Around

500oC and above, carbon reacts with oxygen in the air to form CO. The CO formed

reacts with haematite in the temperature range 500-700oC to form magnetite

(Bordsworth and Bell, 1972). The magnetite produced is separated from the rest of the

gangue using a magnet. (Keru, 2011).

12

CHAPTER TWO

LITERATURE REVIEW

2.1 Laterites

The term laterite is derived from the Latin word ‘later’ which means a brick (Thurston,

1913). Plate 2.1 shows the soil profile composed mainly of lateritic materials from one

of the sampled sites in Kamahuha, Murang‟a County Kenya.

Plate 2.1 Soil profile composed mainly of lateritic materials from one of the sampled

sites in Kamahuha, Murang’a County Kenya

Laterites are soil types rich in iron and aluminium, formed in hot and wet tropical areas.

Nearly all laterites are rusty-red because of iron oxides. They develop by intensive and

long-lasting weathering of the underlying parent rocks. Aluminous laterites and

ferruginous bauxites are quite common. The most common impurity in both is silica.

Laterite gradually passes into bauxite with decrease in iron oxide and increase in

aluminium oxide. The laterite deposits may be described on the basis of the dominant

extractable minerals in it, aluminous laterite (bauxite), ferruginous laterite (iron ore),

13

manganiferous laterite (manganese ore) and nickeliferous laterite (nickel ore). A laterite

with Fe2O3:Al2O3 ratio of more than 1, and SiO2:Fe2O3 ratio less than 1.33 is termed as

ferruginous laterite while that having Fe2O3:Al2O3 ratio less than 1 and SiO2:Al2O3 ratio

less than 1.33 is termed aluminous laterite (Aleva, 1994; Schell, 1994).

Laterization is a prolonged process of mechanical and chemical weathering which

produces a wide variety in the thickness, grade, chemistry and ore mineralogy of the

resulting soils (Maasch, 1988). A period of active laterization extended from about the

mid-Tertiary to the mid-Quaternary periods (35 to 1.5 million years ago) (Maasch,

1988). The rate of laterization may have decreased with the abrupt cooling of the earth.

Weathering in tropical climates continues to this day, at a reduced rate (Maasch, 1988).

Laterites are formed from the leaching of parent sedimentary rocks (sandstones, clays,

limestones),metamorphic rocks (schists, gneisses, migmatites),volcanic rocks (granites,

basalts, gabbros, peridotites), and mineralized proto-ores (Tardy, 1997). These

processes leave the more insoluble ions, predominantly iron and aluminium intact. The

mechanism of leaching involves acid dissolving the host minerallattice, followed by

hydrolysis and precipitation of insoluble oxides and sulphates of iron, aluminium and

silica under the high temperature conditions of a humid sub-tropical climate (Hill et al.,

2000). An essential feature for the formation of laterite is the repetition of wet and dry

seasons (Yamaguchi and Kosei, 2010). Laterite formation is favoured in low

topographical reliefs of gentle crests and plateaus which prevent erosion of the surface

cover (Hill et al., 2000). The reaction zone where rocks are in contact with water from

the lowest to highest water table levels is progressively depleted of the easily leached

ions of sodium, potassium, calcium and magnesium (Yamaguchi and Kosei, 2010). A

14

solution of these ions can have the correct pH to preferentially dissolve silicon oxide

rather than the aluminium oxides and iron oxides (Yamaguchi and Kosei, 2010).

The mineralogical and chemical compositions of laterites are dependent on their parent

rocks. Laterites consist mainly of quartz and oxides of titanium, zircon, iron, tin,

aluminium and manganese, which remain during the course of weathering (Tardy,

1997). Quartz is the most abundant relic mineral from the parent rock (Tardy, 1997).

Laterites vary significantly according to their location, climate and depth (Hill et al.,

2000). The main host minerals for nickel and cobalt can be either iron oxides, clay

minerals or manganese oxides (Yamaguchi, 2010). Iron oxides are derived from

maficigneous rocks and other iron-rich rocks.

It is estimated that laterites cover about one-third of the Earth's continental land area

(Tardy, 1997). Lateritic soils are the sub-soils of the equatorial forests, of the savannas

of the humid tropical regions, and of the Sahelian steppes (Tardy, 1997). They cover

most of the land area between the Tropics of Cancer and Capricorn; areas not covered

within these latitudes include the extreme western portion of South America, the

southwestern portion of Africa, and the desert regions of north-central Africa, the

Arabian Peninsula and the interior of Australia (Tardy, 1997).

Lateritic materials reflect past weathering conditions (Tardy, 1997). Laterites vary

significantly according to their location, climate and depth (Schellmann, 1994).

According to Schellmann (1994), high grade iron ores on top of tropical deposits of

Banded Iron Formations (BIF) are also attributed to lateritic weathering which causes

dissolution and removal of siliceous constituents in the iron ores. Laterites which are

found in the present day in non-tropical areas are products of former geological epochs,

when that region was near the equator (Guerassimov, 1962). Where laterites occur

15

outside the humid tropical regions they are considered to be the indicators of climatic

change, continental drift or a continuation of both (Hill et al., 2000). In Kenya, laterites

are widely distributed in almost all parts of the country (Du Bois and Watsh1970).

Plate 2.2 A sample of laterite from one of the quarries in Kamahuha area

2.2 Iron- minerals.

Iron occurs in well over 80 minerals (Hill et al., 2000). When a mineral deposit contains

reasonably high concentration of the element of interest such that the particular element

can be recovered economically after any necessary concentration, then such a deposit is

referred to as an ore. The ores may occur as rocks of iron oxides and their colours may

vary from dark grey, bright yellow, deep purple, to rusty red (Hill et al., 2000). According

to Hill et al., 2000), iron itself is usually found in many forms. However, the most

important ones are the oxide ore such as magnetite (Fe3O4),hematite (Fe2O3), goethite

(FeO.OH), limonite (FeO.OH.n(H2O) and the carbonatesiderite, (FeCO3). Hematite is also

known as "natural ore", a name which refers to the early years of mining, when certain

iron ores containing up to 66 percent iron could be fed directly into iron-making blast

furnaces (Bonifas, 1959). Iron ore is the raw material used for making pig iron, which is

one of the main raw materials to make steel. 98 percent of the mined iron ore is used to

16

make steel. Indeed, it has been argued that iron ore is more integral to the global economy

than any other commodity, except oil (Camp and Francis, 1920). Table 2.1 shows some

iron-bearing minerals found world-wide.

Table 2.1 Iron bearing mineral

Iron-rich rocks are found in many countries world-wide. The main producers of iron ore

world- wide are listed in table 2.2 (U.S. Geological Survey, 2006).

Class

Mineralogical

name

Chemical

formula

Common

designation Country

Oxides Magnetite,Hematite

Fe3O4,

Fe2O3

Ferrous-Ferric

oxide

Sweden,

India,

Russia

Ilmenite, FeTiO3 Ferric oxide ,,

Limonite (goethite) HFeO2

Iron-Titanium

oxide, Hydrous

Iron oxide ,,

Carbonates Siderites FeCO3 Iron carbonate

France,

Russia

Silicate

Chamosite,

Silomelane Iron silicates France

Greenalite,

Mineresataite

All are often

complex ,, ,,

17

Table 2.2 World iron ore production (Millions of metric tonnes)

Country Production (Millions of metric tonnes)

China 520

Brazil 300

Australia 270

India 150

Russia 105

Ukraine 73

United States 54

South Africa 40

Canada 33

Sweden 24

Venezuela 20

Iran 20

Kazakhstan 15

Mauritania 11

Others 43

Total 1690

2.3 Concentration of iron ores

Beneficiation is the process of increasing the concentration of a particular element in an

ore(Carter and Grant, 2007). According to Carter and Grant (2007), the most common

mineral beneficiation processes include sample preparation, comminution, size

classification, and concentration. During beneficiation, extracted ore from mining is

separated into mineral and gangue(Carter and Grant, 2007). Beneficiation methods of iron

vary depending on the type of mineral. Those used commonly include jiggling, flotation

and magnetic separation (Sharma, 2004).

2.3.1 Concentration methods.

Concentration also referred to as “ore Beneficiation” refers to any process that improves

the properties of an ore for the extraction of a given element. The process may include

many steps such as milling (crushing and grinding), washing, filtration, sorting, sizing,

18

gravity concentration, magnetic separation, flotation, and agglomeration (pelletizing,

sintering, briquetting, or nodulizing). Although the literature suggests that all these

methods have been used to beneficiate iron ore, information provided by members of the

American Iron Ore Association indicates that milling and magnetic separation are the most

common methods used (Ryan, 1991). Gravity concentration is seldom used at existing

U.S. facilities. In any case, gravity concentration works best when concentrating minerals

with large differences in their densities such as gold (spg = 19.5and quartz, spg = 2.65;

(Ryan, 1991).

Flotation is primarily used to upgrade minerals with high affinity for air such as sulphide

ores (Ryan, 1991). Oxide minerals are also concentrated using froth flotation to separate

sulphide-containing portions from oxide portions. Most beneficiation operations will result

in the production of one of three materials: a concentrate; a middling or very low-grade

concentrate, which is either reprocessed (in modern plants) or stockpiled; and a tailing

(waste), which is discarded. Table 2.3 shows a comparison of percentages of total

domestic ore treated by each iron ore beneficiation method in the USA in 1990 (Ryan,

1991).

Table 2.3 Percentages of iron Ore concentrated using the various methods in the

USA in 1990

Method used % of iron concentrated using the

method

Magnetic Separation 41.6

Flotation following Magnetic Separation 51.2

Flotation 6.3

Gravity Concentration < 1

19

Beneficiation of iron ore when using froth flotation is carried out in water. In addition,

many pollution abatement devices use water to control dust emissions. At a given

facility, these techniques may require between 2700 and 315000 litres of water per ton

of iron ore concentrate produced, depending on the specific beneficiation method used.

Beneficiation of iron ores in general takes the following steps.

2. 3.2 Milling iron of the ores

Beneficiation begins with milling of extracted ore in preparation for further activities to

recover iron values. Milling operations are designed to produce uniform size particles

by crushing, grinding, and wet- or dry- classification. The capital investment and

operation costs of milling equipment are high. Typically, primary crushing and

screening take place at the mine site. Primary crushing is accomplished by using

gyratory and cone crushers (Weiss 1985). Primary crushing yields chunks of ore

ranging in size from 15 to 102.5cm. The ore is then crushed and sized at a secondary

milling facility (Weiss, 1985). Secondary milling (comminution) further reduces

particle size and prepares the ore for beneficiation processes that require finely-ground

ore feed. The product resulting from this additional crushing is usually less than 1 inch

(1/2 to 3/4 inches). Subsequent fine grinding further reduces the ore particles to the

consistency of fine powder (325 mesh, 0.0017 inches, 0.44 microns) (Weiss, 1985).

2.3.3 Gravity concentration

Although gravity concentration was once widely used in the beneficiation of iron ores,

less than one percent of total domestic iron ore produced in the USA was beneficiated

using this method by the early 1990s. The decline of this method may be chiefly due to

the low cost of employing modern magnetic separation techniques (Ohle, 1972)and the

fact that magnetic separation is used to concentrate iron ore containing low levels of

20

iron (Ohle, 1972). Furthermore, gravity concentration works best when separating

minerals with widely varying densities (Weiss, 1985).This separation process is based

primarily on differences in the specific gravities of the materials and the size of the

particles being separated. A big draw-back of gravity concentration is that if the particle

sizes vary too much, then even valuables may actually be removed along with the

gangue material (tailings) despite differences in densities (Weiss, 1985).

2.3.4 Froth flotation

Froth flotation is a process for selectively separating hydrophobic materials from

hydrophilic ones (Eisele and Kawatra 1992; Barry, 1997). The flotation process is used

for the separation of a large range of sulfides, carbonates and oxides prior to further

refinement (De Gennes, 2004). Flotation commences by crushing and grinding process

which is used to increase the surface area of the ore for subsequent processing. The

basic principle in froth flotation is that some minerals have higher affinity for air

bubbles than others (Barry, 1997). When finely-ground particles are introduced into a

water bath and the latter is aerated, the hydrophyhilic mineral particles attract air

bubbles and hold onto the surface. The overall density of the mineral particle plus the

attached air bubbles becomes lower than that of the liquid medium, hence the mineral

particle floats with a sheath of the air bubbles attached to it. This property of attracting

air bubbles is common in sulphide- minerals. Separation in froth flotation is illustrated

in figure 2.1a and 2.1b.

21

Laterite partical before aeration, the

particals remain at the bottom

Mineral particles + air bubbles overall

density is lower than that of the liquid

medium hence mineral particle floats

Particals that have no affinity

for air remain at the bottom

Air bubble

Figure 2.1 a

Figure 2.1 b

Figure 2.1a and Figure 2.1b

There are minerals which do not have affinity for air. In that case chemicals known as

frothing agents are used. For example when concentrating iron in iron oxides,

methylisobutylketone (MIBK) may be used as a frothing agent (De Gennes, 2004).

Where bubbles are larger than the ore particles and the particles are equal to or less than

1mm radius, then particles will rise into the froth layer (De Gennes, 2004). Those

particles which are larger than the bubbles also rise into the froth. Since each of these

particles is buoyed by a swarm of bubble forming a stable froth, the froth is then

skimmed off to another container as illustrated in figure 2.2 (Eisele and Kawatra, 1992).

22

Rotation of rotor

Figure 2.2 A flotation cell

Froth flotation is a good example of an engineering “system”, in that the various

important parameters are highly inter-related, as shown in figure 2.3 (Eisele and

Kawatra, 1987).

23

Figure 2.3 The flotation system including many interrelated components

According to Eisele and Kawatra (1987), it is important to take all of these factors into

account in froth flotation operations. Changes in the settings of one factor (such as feed

rate) will automatically cause or demand change in other parts of the system (such as

flotation rate, particle size recovery, air flow and pulp density. As a result, it is difficult

to study the effects of any single factor in isolation. Compensation effects within the

system can keep the process changing from producing the expected effects (Klimpel,

1995).

24

Graham and Madeley (1966) studied the effect of pH and flotation-collector type upon

the flotation rates of natural rutile particles. The study has shown that from pH of 2.5,

flotation rate decreases with increasing pH for anionic collectors and increases with

increasing pH fora cationic collectors. At a fixed pH, the rate of flotation is influenced

by the length of the carbon chain associated with the collector. Below pH of 2.5, the

flotation rate with anionic collectors decreases with fall in pH, whereas with the cationic

type a small increase in rate is shown as pH of 1 is approached (Graham and Madeley,

1966). Types of common collectors are shown in figure 2.4 (Eisele and Kawatra, 1992).

Figure 2.4 Showing types of collectors

Anionic collectors are weak acids or acid salts that ionize in water, producing a

collector that has a negatively-charged end that will attach itself to the mineral surfaces.

25

An anionic collector has a hydrocarbon chain that extends out into the liquid, as shown

in figure 2.5 (Eisele and Kawatra, 1992).

Figure 2.5 Showing adsorption of anionic collector onto a solid surface

The anionic portion is responsible for the attachment of the collector molecule to the

mineral surface, while the hydrophobic part alters the surface hydrophobicity (Eisele

and Kawatra, 1992). Examples of anionic collectors are sodium oleate and fatty acids

which occur in vegetable oils, and are found with polar group such as RCOO-, ROSO3

-,

RSO3-

ROCS2-

andR2O2PS2-. They are strong collectors with low selectivity for hematite

and other metal oxide minerals. Sulfur atoms, for instance, chemically bond to sulfide

mineral surfaces (Eisele and Kawatra, 1992). Other chemical reagents used as frothers

are methylisobutylcarbinol (MIBC), pine oil and cresylic acid (Klimppel, 1995).

Modifiers are substances which influence the way the collectors attach themselves on

mineral surfaces. Modifiers either increase the adsorption of the collector on a given

mineral (activators) or, prevent collectors from adsorbing onto a mineral (depressants)

(Eisele and Kawatra, 1992). An example of an activator is copper sulphate which acts as

26

an activator for sphalerite (ZnS) flotation with xanthate collectors (Fuerstenau et al.,

1985). Depressants prevent collectors from being adsorbed onto particular mineral

surfaces. Their typical use is to increase selectivity by preventing one mineral from

floating while allowing another mineral to float (Eisele and Kawatra, 1992).

Chemical reagents used in floatation of minerals may be classified into three main

groups. These are: (i) Collectors (ii) frothers and (iii) antifoams (Weiss, 1985; U.S.

EPA, 1985).

(i) Collectors/ amines. These cause adherence between solid particles and air

particles in a flotation cell.

(ii) Frothers: These compounds act as air- bubble stabilizers. They stabilize air

bubbles so that they will remain well-dispersed in the slurry.Frothers also

form a stable froth layer that can be removed before the bubbles burst. The

most commonly used frothers are alcohols, particularly,

methylisobutylketone (MIBC) or 4-methyl-2-pentanol (a branched-chain

aliphatic alcohol) or any of a number of water-soluble polymers based on

propylene oxide (PO) such as polypropylene glycols (Eisele and Kawatra,

1992).

(iii) Antifoams or depressants react with surfaces of gangue materials in the

flotation cell, preventing them from remaining in the froth and instead, fall

to the bottom as tailings. According to Fuerstenau (1970), several factors are

important when conditioning ore for flotation with chemical agents. These

include thoroughly mixing and dispersing reagents through the pulp,

repeated contact between the reagents and all the relevant ore particles and

27

allowing time for the development of contact of the reagent and ore particles

to produce the desired reactions (Fuerstenau, 1970).

Cationic collectors are water-repellants and are based on tetravalent nitrogen. According

to Eisele and Kawatra (1992) these collectors use ammoniumcation to attach

themselves.They are mainly used for flotation of silicate, SiO44-

, aluminate, Al(OH)4-

and certain rare-metal oxides. They are also used for separation of potassium chloride

(sylvite) from sodium chloride (halite) (Eisele and Kawatra, 1992).Examples of cationic

collectors are RNH3+

,R2NH2+

andR3NH+

where R is an alkyl group. The process of using

cationic collectors is known as reverse froth flotation. This involves obtaining mainly

the silicate and aluminate ions in the froth leaving out the mineral concentrate in the

sinter.

Reverse cationic flotation was carried out at Joda iron ores in India to float silica and

alumina gangue using amine-based cationic collectors (Thella et al., 2010). Potato

starch was used as a depressant for iron-bearing minerals. Sodium hydroxide was used

as a pH regulator at pH 9.5. Around 50 percent of the slimes were present in less than

25 Micron fractions having 58.28% iron, 4.76% silica, 3.43% alumina. The result

obtained was 64.5% iron, 2.18% alumina, and 1.69 % silica. This was an increase of

about 7% Fe(Thella et al., 2010). The result shows that reverse flotation is a suitable

method for removal of aluminosilicates from laterites thus improving iron concentration

in iron beneficiation.

Reverse flotation has also been investigated in iron ores from the Samarco, Mariana, Minas and

Gerais mines, in Brazil. Rabelo and Turrer (1999), carried out flotation tests with a Wemco

agitation cell containing 1150 g of ore, which resulted in 45 percent of solids in the pulp.

Flotation tests were carried out considering the process conditions used in the Samarco plant.

28

The amounts of reagents used were: - (i) Collector amine known as etherdiamineacetate (EDA)

flotigam (different concentrations) and (ii) Depressor starch 300 g/t and pH of 10.5. Condition

time was 3 minutes dispersing of ore, 5 minutes conditioning of starch, 3 minutes conditioning

of amines and 5 minutes of floatation (Rabelo and Turrer, 1999). It was observed that the iron

content increased from 54 percent to 66 percent with increasing concentration of collector. The

opposite happened with amount. The recovery of iron decreased with the increasing amount of

collector (Rabelo and Turrer,1999).

Some iron-rich ores are normally comminuted and classified. For low-grade iron ores

such as the Brazilian Itabirite found at the Ponto Verde iron ore, the mineral is

concentrated using gravity and magnetic concentration or reverse flotation (Iwasaki,

1983). This improves the grade from 44.5 percent to over 60 percent Fe. Brazilian

Itabirite ore is mainly characterized by layering of iron ore within silica mineralization

(Iwasaki, 1983; Iwasaki and Numela, 1986). The final product is sold either to the local

or export markets for the production of steel. Reverse flotation is the most important

concentration method, which is utilized in low concentration iron ores (Iwasaki and

Numela, 1986). Today, flotation is primarily used to upgrade concentrates resulting

from magnetic separation. Over 50 percent of all iron ore is upgraded using this

technique. Froth flotation, when used alone as a beneficiation method, accounts for

approximately 6 percent of all ore treated (Ryan, 1991).

During this study, froth floatation technique was used for comparison purposes.

Whereas unquestionably, positive results were obtained (see data on page 76), magnetic

separation appears a more superior technique in that:-

i. Use of expensive chemicals is avoided

29

ii. The CO used for reduction in this procedure is generated in situ using cheap

and locally available biomass. More importantly, Biomass from Municipal

solid waste can be used as the carbon source and thus, help in cleaning the

environment. No doubt, energy is needed to dry the biomass. Some of the

biomass dried initially, can be used as the source of energy to dry the

biomass.

2.3.5 Magnetic separation

Magnetic separation is the method of using a magnet to separate materials with different

magnetic intensity (Svoboda, 1987). Magnetic separation is the most popular method

used to beneficiate black metal ore. There are two kinds of magnetic separation, normal

and high density (Harry et al., 1973). Normal magnetic separation is adopted to separate

magnetite. High density magnetic separation is used to separate hematite and other ores

which are weakly magnetic. The unit of measurement of magnetic flux density or

magnetic induction (B), which is the number of lines of force passing through a unit

area of material, is tesla (T). The magnetizing force, which induces the line of force

through a material, is called the field intensity (H). The intensity of magnetism or the

magnetization (M) of a material relates to the magnetization induced in the material as

shown in equation 2.1 (Svoboda, 1987).

B = µ0 (H + M) …………………………………………………………......2.1

In vacuum, M = 0 and it is extremely low in air, therefore Equation 2.1 reduces to

Equation 2.2

B = µ0H ………………..…………………………………………………. .2.2

30

The capacity of a magnet to lift a particle is not only dependent on field intensity but

also on field gradient (Svoboda, 1987). Paramagnetic minerals have higher magnetic

permeability than surrounding medium. They concentrate the line of force of an external

magnetic field. The magnetic susceptibility in the particle increases with increase in the

magnetic field intensity. Diamagnetic minerals have lower magnetic susceptibility than

their surrounding medium and hence expel the lines of force of the external magnetic

field (Cohen, 1986). The magnetic separation involves passing the sand and dust over a

magnetically-charged rotating chamber. The particles with some iron stick to the drum,

and are then scraped off on the other side of rotating drum. 98 percent of the loam soil

would simply pass through and not interact with the magnet (Harry et al., 1973).A

magnetic separation for processing iron from fly ash is able to remove around 92

percent iron using magnetic coating of up to 11.8 kilo Gauss (kG) from low grade iron

ore by reduction treatment (Morsi and Youssef, 1998). The iron recovery of 90 percent

can also be achieved by using wet low intensity magnetic separator and assaying about

55 percent Fe from low percent of iron in the original ore (Morsi and Youssef,

1998).Whereas in using magnetic separation, iron ores with 25% iron and above are the

most economical (Harry et al., 1973), iron has actually been recovered economically

from ores with as little as 12% iron (Ohle, 1972) using magnetic separation. The main

disadvantages of magnetic separation are that the equipment should be maintained

consistently. The equipment must be washed regularly in order to remove the

accumulated magnetic materials. On the other hand the technique consumes much

electric energy when separating ores that are not strongly magnetic.

2.4 Extraction of iron

Iron is extracted in a blast furnace. The purpose of a blast furnace is to chemically

reduce and physically convert iron oxides into liquid iron called "hot metal". The blast

31

furnace is a huge, steel stack lined with refractory brick, where iron ore, coke and

limestone are dumped into the top, and preheated air is blown into the bottom. The raw

materials require 6 to 8 hours to descend to the bottom of the furnace where they

become the final product of liquid slag and liquid iron (Rayner-Canham and Overton,

2006). These liquid products are drained from the furnace at regular intervals. The hot

air that was blown into the bottom of the furnace ascends to the top in 6 to 8 seconds

after going through numerous chemical reactions. Once a blast furnace is started it will

continuously run for four to ten years with only short stops to perform planned

maintenance (Rayner-Canham and Overton, 2006).

Iron oxides can be brought to the blast furnace plant in the form of raw ore, pellets or

sinter. The raw ore is removed from the earth and sized into pieces that range from 0.5

to 1.5 inches. This ore is either hematite (Fe2O3) or magnetite (Fe3O4) and the iron

content ranges from 50% to 70% (American Iron and Steel Institute, 2005). If such an

ore is free of poisonous elements such as sulphur or phosphorus, it can be put in a blast

furnace without any further processing. Iron ore that contains a lower iron content must

be processed or beneficiated to increase its iron content. Pellets are produced from this

lower iron content ore. This ore is crushed and ground into a powder so the waste

material called gangue can be removed. The remaining iron-rich powder is rolled into

balls and fired in a furnace to produce strong, marble-sized pellets that contain 60% to

65% iron. Sinter is produced from fine raw ore, small coke, sand-sized limestone and

numerous other steel plant waste materials that contain some iron. These fine materials

are proportioned to obtain desired product chemistry then mixed together. This raw

material mix is then placed on a sintering strand, which is similar to a steel conveyor

belt, where it is ignited by gas fired furnace and fused by the heat from the coke fines

into larger size pieces that are from 1.25 to 5.0 mm. The iron ore, pellets and sinter then

32

become the liquid iron produced in the blast furnace with any of their remaining

impurities going to the liquid slag (American Iron and Steel Institute, 2005).

The coke is produced from a mixture of coals. The coal is crushed and ground into a

powder and then charged into an oven. This coke contains 90 to 93% carbon, some ash

and sulfur but compared to raw coal is very strong. The strong pieces of coke with a

high energy value provide permeability, heat and gases which are required to reduce

and melt the iron ore, pellets and sinter (Rayner-Canham and Overton, 2006).

The final raw material in the iron making-process is limestone. It is crushed and

screened to a size that ranges from 15 mm to 45 mm to become blast furnace flux. This

flux can be pure high calcium limestone, dolomitic limestone containing magnesia or a

blend of the two types of limestone. The reacts with any silica present as an impurity to

form the slag. This helps to remove any sulphur and other impurities. The blast furnace

operator can actually blend different stones to produce the desired slag chemistry and

create optimum slag properties such as a low melting point and a high fluidity

(American Iron and Steel Institute, 2005). Once these materials are charged into the

furnace top, they go through numerous chemical and physical reactions while

descending to the bottom of the furnace. The main reactions taking place in a blast

furnace and the temperatures at which they occur are as follows:

3Fe2O3(S)+CO(g) CO2(g) +2Fe3O4(S)From 4550C……………….2.3

Fe3O4 + CO(g) CO2(g) + 3 FeO(S)From 600 0C………………2.4

FeO + CO(g) Fe(l) + CO2(g)From 7050C……………… 2.5

33

At the same time the iron oxides are going through these purifying reactions, they soften

and then melt and finally trickle as liquid iron through the coke to the bottom of the

furnace. The coke descends to the bottom of the furnace to the level where the

preheated air or hot blast enters the blast furnace. The coke is ignited by this hot blast

and immediately reacts to generate heat as shown in equation 2.6

C + O2 CO2 + Heat………………………….……. 2.6

Since the reaction takes place in the presence of excess carbon at a high temperature the

carbon dioxide is reduced to carbon monoxide as shown in equation 2.7 (American Iron

and Steel Institute, 2005).

CO2+ C 2CO……………………………………….2.7

The product of this reaction, carbon monoxide, is necessary to reduce the iron ore as

seen in the previous iron oxide reactions. The limestone descends in the blast furnace

and remains a solid while going through its first reaction as shown in equation 2.8

CaCO3 CaO + CO2…………………………………...2.8

This reaction requires energy and starts at about 1600°F. The CaO formed from this

reaction is used to remove sulfur from the iron which is necessary before the hot metal

becomes steel. The sulfur removing reaction is as shown in equation 2.9 (American Iron

and Steel Institute, 2005).

FeS + CaO + C CaS + FeO + CO……………..........2.9

The CaS becomes part of the slag. The slag is also formed from any remaining Silica

(SiO2), alumina (Al2O3), magnesia (MgO) or calcia (CaO) that entered with the iron ore,

34

pellets, sinter or coke. The liquid slag then trickles through the coke bed to the bottom

of the furnace where it floats on top of the liquid iron since it is less dense.

Another product of the iron making process, in addition to molten iron and slag, is hot

dirty gases. These gases exit the top of the blast furnace and proceed through gas

cleaning equipment where particulate matter is removed from the gas and the gas is

cooled. This gas has a considerable energy value so it is burned as a fuel in the "hot

blast stoves" which are used to preheat the air entering the blast furnace to become "hot

blast". Any of the gas not burned in the stoves is sent to the boiler house and is used to

generate steam which turns a turbo blower that generates the compressed air known as

"cold blast" that comes to the stoves (Yakovlev, 1957).

Iron is mainly important when mixed with certain other elements such as Cr, Ni, V, etc.

and with carbon to form steels (Martin, 2007). Powdered iron is mainly used in

metallurgy products, magnets, high-frequency cores, auto parts and catalyst.

Radioactive iron (Fe 59) is used in medicine, tracer element in biochemical and

metallurgical research. Iron blue on the other hand, is used in paints, printing inks,

plastics, cosmetics (eye shadow), artist colors, laundry blue, paper dyeing, fertilizer

ingredient, baked enamel finishes for autos and appliances and industrial finishes. Black

iron oxide is used as pigment in polishing compounds, metallurgy, medicine, magnetic

inks and in ferrites for electronics industry (Camp and Francis, 1920).

Iron catalysts are traditionally used in the Haber - Bosch process for the production of

ammonia and the Fischer-Tropsch process for conversion of carbon monoxide to

hydrocarbons for fuels and lubricants (Kolasinski, 2002). Powdered iron in an acidic

solvent was used in the Bechamp reduction, the reduction of nitrobenzene to aniline

(McKetta, 1989). Iron (III) chloride finds use in water purification and sewage

35

treatment, in the dyeing of cloth, as a coloring agent in paints, as an additive in animal

feed, and as an etchant for copper in the manufacture of printed circuit boards

(Wildermuth et al., 2000). Iron is dissolved in alcohol to form tincture of iron, Iron (II)

sulfate is used as a precursor to other iron compounds as well as reducing chromate in

cement (Durupt et al., 2000). According to Durupt et al. (2000), iron is also used to

fortify foods and treat iron deficiency anemia. Iron (III) sulfate is used in settling minute

sewage particles in tank water. Iron (II) chloride is used as a reducing flocculating

agent, in the formation of iron complexes and magnetic iron oxides, and as a reducing

agent in organic synthesis (Holleman et al., 1985).

The Kiruna mine in Sweden is the largest and most modern underground iron ore mine

in the world (Kiruna Iron Ore Mine Report, 2010). The mine is located in Norrbotten

County, Lapland. The original reserve at Kiruna was some 1,800million metric tonnes.

As of at the end of 2008, the Luossavaara-Kiirunavaara AB (LKAB), a Swedish mining

company, estimated that the current proven reserve at the mine is 602million metric

tonnes grading at 48.5 percent iron, with probable reserves of 82 million metric tonnes

at 46.7 percent iron (Kiruna Iron Ore Mine report, 2010). Sweden has an annual

production capacity of over 25 million tones Mt of iron ore (USGS, 2011). The ore

grade is more than 60 percent iron and an average of 0.9 percent phosphorus. Since

mining began at the site over 100 years ago, LKAB has produced over 950million

metric tonnes of ore (Kiruna Iron Ore Mine report, 2010). The Swedish Trade Council

(STC) has been exporting its iron and steel products mainly to United Arab Emirates

(UAE) over the years. In the year 2007, STC exports of iron and steel products grew

from 99.76 million kronor in 2006 to 332.74 million kronor, with a 234 percent

increase. In addition, exports of agricultural machinery to the (UAE), increased from

36

2.38 million kronor in 2006 to 6.62 million kronor in 2007 which was 179 percent

increase (Kiruna Iron Ore Mine report, 2010).

Extraction of iron has been practiced for hundreds of years. Thus the blast furnace

chemistry is not new. However partial reduction of oxides of iron as a means of

concentrating iron in laterites is a recent contribution in iron production (Purwanto et

al., 2003).

In 2003 Purwanto and co-workers showed that when a stream of CO/CO2 was passed

over heated laterites in the temperature range 673-973 K, the goethite present is

converted to hematite on dehydration. The hematite is then reduced to magnetite in a

process that follows equations 2.10 and 2.11 below (Purwanto et al., 2003).

Fe2O3.H2O Fe2O3 + H2O ……………….2.10

3Fe2O3(S)+ CO(g) CO2(g) +2Fe3O4(S) ………………...2.11

It should be noted that these are the reactions that take place in a blast furnace and have

been known for a long time. The importance of this study is that it showed that one

could use the process to concentrate iron in laterites by carbonizing biomass, oxidizing

the carbon to CO, reducing hematite to magnetite. The magnetite is then the separated

by magnetic separation.

At temperatures of 973 K and above, hematite was converted to magnetite which is

more strongly magnetic as compared to goethite and hematite. The iron in the laterite

could therefore be removed by use of a permanent magnet (Purwanto et al., 2003). In

the experiment CO gas was generated elsewhere and was later used to reduce goethite

and hematite to magnetite.

37

In the current study, a laterite-charcoal mixture in the ratio of 20:1 was heated in a

current of air in a temperature range of 500-700oC in a heat exchanger. This was done

for experimental purposes since charcoal is not an option. The experiment was repeated

using biomass in place of charcoal but in the same ratio. In the experiment, the biomass

used was first dried in an oven to eliminate water. Air was allowed to flow though out

the heating process. Carbonization of biomass took place where the biomass was

converted to carbon with elimination of water (at a temperature of 300oC and above).

The carbon formed was then oxidized to carbon (II) oxide in situ by oxygen in the

flowing air. The nitrogen in the air served as the carrier gas in the process. At a

temperature of 400oC and above, this temperature the goethite is dehydrated into

hematite, followed by reduction of the hematite to magnetite by the CO at temperature

of 600oC and above. The reactions involved are given by equations 2.12, 2.13, 2.14 and

2.15

Biomass C (s) + H2O………………………………2.12

2C (s) + O2 (g) 2CO(g)……………………..................2.13

Fe2O3.H2O(s) Fe2O3(s) + H2O ………...2.14

3Fe2O3(S)+ CO(g) CO2(g) + 2Fe3O4(s) ………........2.15

Goethite and hematite minerals are weakly attracted by magnet while magnetite is

attracted by magnetic field very strongly. Owing to this property, all magnetite was

separated by use of a permanent horse shoe magnet of about 92 milli Teslas. In practical

situation one would naturally go for an electromagnet. In this experiment both charcoal

and biomass were used.

38

2.5 Analytical techniques

The main methods used in the analysis of laterite samples included atomic absorption

spectroscopy, atomic emission spectroscopy and complexometric titration using

ethylenediamine tetra-acetic acid (EDTA).

2.5.1 Atomic absorption spectroscopy

In this technique, elements which are not atomized easily are analysed (Mendham et al.,

2000). The light of the right wavelength impinges on a free, ground state atom, where

the atom may absorb the light as it enters an excited state through a process known as

atomic absorption. Atomic absorption measures the amount of light at the resonant

wavelength which is absorbed as it passes through a cloud of atoms (Mendham et al.,

2000). As the number of atoms in the light path increases, the amount of light absorbed

increases in a predictable way. By measuring the amount of light absorbed, a

quantitative determination of the amount of analyte element present can be made (Gary,

2003). The use of special light sources and careful selection of wavelength allow the

specific quantitative determination of individual elements in the presence of others.

The atom cloud required for atomic absorption measurements is produced by supplying

enough thermal energy to the sample to dissociate the chemical compounds into free

atoms. Aspirating a solution of the sample into a flame aligned in the light beam serves

this purpose (Gary, 2003). Under the proper flame conditions, most of the atoms will

remain in the ground state form and are capable of absorbing light at the analytical

wavelength from a source lamp (Skoog et al., 1992). The ease and speed at which

precise and accurate determinations can be made with this technique have made atomic

absorption one of the most popular methods for the determination of metals. The

technique requires standards with known analytical content to establish the relation

39

between the measured absorbance and the analytical concentration and relies therefore

on Beer-Lambert‟s law shown in equation 2.8 (Mendham et al., 2000).

10LogA (I

I o ) = . .c L ……………………………….2.16

Where; A - Absorbance, I0 - incident radiation at a given wavelength, I - transmitted

intensity or attenuated radiation, L - the path length through the sample (cm), c -

concentration of the absorbing species (moldm-3

), - molar absorptivity or extinction

coefficient (Lmol-1

cm-1

).

Molar absorptivity is a constant which is a fundamental molecular property in a given

solvent, at a particular temperature and pressure. The method is largely free from

spectral and radiation interferences. This is because every metal has its own

characteristic absorption wavelength. For an unexcited atom, each electron is in ground

state, otherwise it is excited.

2.5.2 Atomic emission spectroscopy

In atomic emission, a sample is subjected to a high energy, thermal environment in

order to produce excited state atoms, capable of emitting light. The energy source can

be an electrical arc, a flame or plasma (Skooget al., 1992). The emission spectrum of an

element exposed to such an energy source consists of a collection of the allowable

emission wavelengths, commonly called emission lines, because of the discrete nature

of the emitted wavelengths. This emission spectrum can be used as a unique

characteristic for qualitative identification of the element (Gary, 2003).

Atomic emission using electrical arcs has been widely used in qualitative analysis

(Mendham et al., 2000). For a quantitative analysis, the intensity of light emitted at the

wavelength of the element to be determined is measured. The emission intensity at this

40

wavelength will be greater as the number of atoms of the analyte element increases. The

technique is mainly used for the analysis of alkali and alkali earth metals (Mendham et

al., 2000). During the current study the sodium and potassium were determined using

AES while AAS was used for the other elements.

2.5.3 X-ray diffraction (XRD) spectroscopy

The XRD analysis utilizes X-rays of a known wavelength that are passed through a

sample for identification of the crystal structure. The wave nature of the X-rays

diffracted by the lattice of the crystal, gives a unique pattern of the peaks at different

angles and of different intensity. This condition is given by Bragg equation 2.17 (Myers,

2002).

………………………………………………...2.17

Where; d - spacing between diffracting planes in the atomic lattice, λ - wavelength of

the incident ray, θ – the angle between the incident ray and scattering plane, n – is an

integral which is a multiple of the wavelengths for the phases of nth

number of beams

that strikes the layers of atoms in a mineral.

Figure 2.6 Bragg's law reflection (Myers, 2002)

nd sin2

41

Bragg diffraction occurs when two beams of X-rays with identical wavelength and

phase approach a crystalline solid and are scattered off by two different atoms within it

(Myers, 2002). The lower beam traverses an extra length of 2dsinθ. Constructive

interference occurs when this length is equal to an integral multiple of the wavelength

of the radiation (Myers, 2002). The most common X-rays used are of the copper metal,

with a wavelength of 1.54056 x 10-10

m. Copper is used because it is easily kept cool

and has high thermal conductivity, and which produces strong Kα and Kβ lines

(Jeruzalmi, 2006). The Kβ line is sometimes suppressed with a thin (~10 µm) nickel

foil. The simplest and cheapest variety of sealed X-ray tube has a stationary anode (the

Crookes tube) and produces ~2 kW of X-ray radiation. The more expensive variety has

a rotating-anode type source that produces ~14 kW of X-ray radiation (Jeruzalmi,

2006).

Every mineral has a set of unique d-spacing. Therefore the X-ray detector moves around

the sample and measures the intensity of these peaks and the position of these peaks

(diffraction angle 2θ). The measurement is achieved by comparison of d-spacing

(Moore and Reynolds, 1997) with standard referencing pattern. The intensity of the X-

rays is measured on the Y axis, and increasing values of the 2θ are shown on the X axis.

The height of the peaks (intensity) depends upon the number of crystallites diffracting

the X-Rays, thus a sample more finely ground will give higher but narrower peaks than

the same sample coarsely ground. The area under the graph measuring crystallinity will

yield the same result in each case whether the sample is finely or coarsely ground

(Moore and Reynolds, 1997). Plate 2.3 shows the basic components of the D2 phaser x-

ray difractometer available at International Centre for Research in AgroForestry

(ICRAF).The D2 Phaser is the most compact and fastest, all-in-one crystalline phase

42

analysis tool available. The instrument is low power operation XRD where the X-ray

tube has a long life.

Plate 2.3 Showings some components of the D2 phaserdifractometer

2.5.4 Ethylene diamine tetra acetic acid (EDTA) titrations

This technique involves titrating metal ions with a complexing agent or chelating agent

(ligand) and is commonly referred to as complexometric titration (Gary, 2003). This

method represents the analytical application of a complexation reaction. In this method,

a simple ion is transformed into a complex ion and the equivalence point is determined

by using metal indicators or electrometrically. Various other names such as chilometric

titrations, chilometry, chilatometric titrations and EDTA titrations have been used to

describe this method (Mendham et al., 2000). These chilons react with metal ions to

form a special type of complex known as chelate.

43

Ethylenediaminetetraacetic acid, (EDTA) anion has four carboxyl groups and two

amine groups that can act as electron pair donors, or Lewis bases (Gary, 2003). The

ability of EDTA to potentially donate its six lone pairs of electrons for the formation of

coordinate covalent bonds to metal cations makes EDTA a hexadentate ligand.

However, in practice EDTA anion with molecular formula [C10H16N2O8]4-

is usually

only partially ionized, and thus forms fewer than six coordinate covalent bonds with

metal cations (Gary, 2003). Disodium salt of EDTA is a water-soluble chelating agent

and is always preferred. It is non-hygroscopic and a very stable sequestering agent.

These are chelating agents that form water-insoluble chelates with metal ions, for

example oxine or 8-hydroxy quinoline (Gary, 2003). The disodium salt of EDTA was

used since it chelates well with iron and was easy to determine the levels iron in the

various samples under analysis.

44

CHAPTER THREE

MATERIALS AND METHODS

3.1 Sample collection and preparation

Laterite samples were collected from Kamahuha in Murang‟a county which lies

between the latitude 1° 12' 26'' S and 1° 13' 52'' S and between longitude of 37° 40' 40''

E and 37° 40' 12'' E. The samples collected from this county were collected in four

quarries marked as K1, K2, K3 and K4. The rest of the samples were collected from

Juja in Kiambu County with which lies between the latitude 1° 14' 02'' S and 1° 15' 01''

S and between longitude of 37° 41' 54'' E and 37° 54' 58'' E. The samples were collected

in two quarries marked as J1andJ2.All the samples were obtained at depths of 0.15m,

0.5m and 1m horizontally on the quarry walls, a total of three samples were collected

from each quarry. The samples weighing about 10kg were packed separately in plastic

buckets, covered and labeled accordingly. All the quarries sampled were at the time

being used by road construction companies as sources of the laterites. The two sites

were selected on the basis that the levels of iron in the laterites from Kamahuha ranged

between 32 to 39% (Muriithi, 1985). These levels of iron were relatively higher

compared to 13 to 16% iron in the samples from Juja (Keru, 2011). This study required

laterites with both low and high levels of iron. Figure 3.1 and 3.2 show maps of

Murang‟a and Kiambu counties respectively where the laterite samples were collected.

45

Figure 3.1 Showing Kamahuha (•K) and Juja (•J) sampling sites

3.2 Cleaning of pulverizer, glassware and plastic containers

All glassware used was cleaned by soaking them in 1:1 nitric acid overnight. They were

thereafter cleaned using detergent, rinsed with distilled water and then dried in an oven

at 105 oC. Pulverizer was washed using distilled water after each sample was pulverized

then dried using gas pump. Plastic containers were washed with 1:1 nitric acid, followed

46

by appropriate detergent and rinsed with distilled water. They were then dried in an

oven at 50 oC.

3.3 Laterite sample treatment and analytical procedures

The laterite sample was weighed and put into a paper bag and transferred into the oven

for drying at 105 0C for 12 hours. Samples were removed from the oven and cooled.

The samples were pulverized to 300 microns (150 meshes) using a pulverizer and

packed separately. Minerals present were determined using aD2 phaser X-ray

difractometer while chemical analyses were carried out using XRF, AAS and EDTA

titrations.

3.3.1 Weight loss on ignition

About 3g of pulverized samples were weighed into crucible boats. The sample was

heated in an oven for 6hours at 1050C to completely remove all the water. About 1g of

the dry samples were weighed into crucible boats and then transferred into a furnace

where they were heated to 1000 0C for about 6 hours to burn all organic materials. The

samples were cooled in a desiccator, re-weighed and the percentage difference

determined (Table 4.5) (Ben and Banin, 1989; Nelson and Sommers, 1996).

3.3.2 X-ray fluorescence spectrometer (XRFS) analysis

About 10.00 g of pulverized sample was weighed; about 5.0 g of flux starch added and

the mixture mixed in a motor using a pestle. The resulting mixture was made into

pellets using Herzog Hydrolyric Jack pelleting machine with a minimum load capacity

of 170 Kilo Newtons (kN). The pellets were loaded into sample holder cups. Sequential

X-ray Fluorescence Analysis was done using Minipal-2 version 4 Panalytical Model.

The results were recorded in terms of the oxides of the elements (Table 4.3).

47

3.3.3 Chemical analysis using (AAS)

About 0.100 g of the pulverized sample was weighed using analytical balance Model

Mettler AJ150 and put into a labeled 150-ml plastic bottle. 1 ml of aqua-regia was

added followed by 3.0 ml of hydrofluoric acid. The samples were left to digest for 12

hours. 50.0 ml of concentrated boric acid was added in each container and left to digest

for one hour. Distilled water was added to make the total volume of 100. ml. Syenite

(SY-3) and Mount Royal Gabbro (MRG) Rock were used as standards; they were

therefore digested following the same procedure used in the samples. Dilutions of the

sample solutions were made by putting 5.0 ml in 100 ml labeled volumetric flask and

made up to the mark using distilled water (Abbey and Gladney, 1986). The samples

were analyzed using AAS instrument (Spectr AA.10 model from SEANAC Company)

(Table 4.2).

3.3.4 The EDTA titrimetric analysis

About 1.00 g of pulverized laterite sample was weighed into 250-ml beaker. 25 ml of

aqua-regia was added. The sample was digested on a hot plate to expel fumes. The

volume was reduced as much as possible without allowing it dry up. The beaker was

removed from hot plate and 10 ml of distilled water was added and allowed to settle.

The content was filtered using filter paper number 541 and washing was done at least 4

times with hot water portion. The filtrate was transferred into 250-ml volumetric flask

and made to the mark using distilled water. Aliquot of 25 ml was taken into 250-ml

beaker and its pH adjusted to between 2 and 3 using 1:1 HCl acid. Titration was done in

triplicate using 0.1M EDTA as a titrant and potassium thiocynate as indicator. The

average titre was used to calculate the amount of iron using Equation 3.1.

VEM EM A .W of Fe = mg of Fe……………………….…………… 3.1

48

Where; VEM is Volume of EDTA,

EM is Molarity of EDTA and A.W is Atomic

Weight of iron (55.847) (Table 4.4).

3.3.5 The X-ray diffraction (XRD) analysis

X- ray diffraction was carried in a D2 phaser defractometer. About 3.0g of the sample

was poured into the well of a low background sample holder. The holder was tapped on

a bench to help fill and properly pack the sample and avoid sample displacement which

causes peak shifts. Using a sharp razor, the sample surface was slowly tapped into either

direction pushing excess sample slowly to the end of the well and finally scrapping it

off the holder. The sample was then loaded into the X-ray defractometer and

measurements taken (Appendices 4.1 - 4.8).

3.3.6 Froth flotation

Ground laterite samples weighing about1000.0 g were put in a 2000 ml beaker. About

1000.0 ml distilled water were added to make 1:1 slurry. The mixture was put in a

flotation cell shown in plate 3.3 and agitated for 5.0 minutes to make the slurry. About

10.0 ml of 0.1M NaOH was added as a conditioning reagent. The conditioning reagent

was meant to ensure that any soluble iron was precipitated. The mixture was agitated for

5.0 more water was added to the mixture to make slurry with about 30% solid. The pH

of slurry was adjusted to between 8 and 9 using sodium hydroxide and hydrochloric

acid solutions. About 30.0 ml of oleic acid was added and the mixture agitated for 10.0

minutes. About 3.0 ml of cresylic acid was added and mixture agitated for 3.0 minutes.

Air was bubbled through and froth collected in plastic containers. Flotation was done

for 10.0 minutes.

Both the froth and tailings were separately filtered using vacuum filtration. The solid

residue on the filter paper was rinsed with 50.0 ml of a mixture of water and diethyl

49

ether in the ratio 1:1 and finally twice with water. The residues were then dried in an

oven at 105 o C for 6.0 hours.

The dry residue was then pulverised to 300 microns, levels of iron were determined

(Table 4.12).

Plate 3.1 Showing a froth flotation cell

3.3.7 Concentration equipment

The concentration equipment comprised of a ceramic container and a heat exchanger.

The ceramic container used is a hollow tube of length 60cm and a diameter 15cm. The

two openings of the tube are narrow with a diameter of 3cm. A thermocouple terminal

was inserted through the other end to record the temperature. The equipment was

fabricated in the Department Fine art and Science workshop in Kenyatta University.

The ceramic container was then placed on top of a heat exchanger (jiko) whose fuel is

charcoal. The purpose of the heat exchanger is to provide heat energy since the reaction

takes place at a temperature range between 500-7000C (Purwanto et al., 2003). In an

industrial setting a different fuel should be used since charcoal burning has negative

50

impacts on the environment. To minimize energy loss the concentration container was

covered with a ceramic cover. A current of air flowing at between0.5-0.7cm3 per second

was passed from a compressed air cylinder from one end using a steel tube. Clay was

used to seal this end of the concentration equipment to ensure that only air from the

compressed air cylinder entered into the equipment. The air flow rate was measured

using a gas flow meter model 270134.003 from TA Instruments, (Plate 3.1) available in

Kenyatta University physics laboratory. The air flow was regulated using a compressed

air cylinder regulator until the air flow range used was achieved. Plate 3.1 below shows

the air flow meter used.

Plate 3.2 Showing the gas flow meter used

To regulate the temperature inside the concentration compartment, the air inlet was

opened to raise the temperature or closed to lower the temperature. The regulation was

done to keep a temperature range of 500-7000c.

51

Figure 3.1 Showing iron concentration equipment set-up

3.3.8 Optimization of biomass

The optimization of biomass was carried out by mixing different ratios of biomass to

laterite. The mass of the laterite used was maintained constant at about 500g. The

mixtures were then concentrated as explained in the procedure 3.3.7 above. The heating

was timed at four hours to ensure that all the biomass was carbonized. The levels of iron

in the concentrated products were then analysed and statistical comparison was carried

out (Table 4.9).

3.3.9 Particle size measurement

The particle size is an important factor during concentration. Three different particle

sizes were used to determine the effect of varying the particle size. The three were

determined using three sieves of different meshes. The laterites were first crushed using

a hummer. The pulverized laterites were then placed on the 100 mesh (0.149mm). On

shaking the mesh the particles that passed were placed on a (120 mesh) sieve. Those

that did not go through the 120 mesh were labeled as 100 mesh. A similar procedure

52

was carried out using 50mesh (0.297mm) and 18 mesh (1.00mm). A 60 and 20 mesh

sieves were used to control the particle in the 50 and 18 mesh particle sizes. The various

portions containing the different particle size were concentrated using biomass in the

ratio of 1:20 biomass to laterite. The concentration time and the mass of laterite biomass

mixture was maintained constant within experimental error for all the experiments.

3.3.10 Concentration of iron in laterites using biomass and charcoal

About 500.0 g of dry laterite sample and 25 g of dry biomass (saw dust) was mixed and

transferred into the concentration equipment (Fig.3.1) where a current of air was

allowed to pass from a compressed air cylinder at a flow rate of 0.5-0.7cm3 per second.

The mixture was heated at temperature range of 500 - 700 0C in a heat exchanger. After

2 hours, the sample mixtures were allowed to cool to room temperature. A permanent

magnet was used to pick the magnetic portion. Serial magnetic separation was carried

out where the portion picked by the magnet was placed in a container, the magnetic

portion from this container was again picked using the magnet and placed in another

container. The picking by the magnet continued until all the material was picked. The

same procedure was repeated using laterite/charcoal mixture where charcoal replaced

biomass (Table 4.10 and 4.11). This procedure was repeated using 5kg of laterite

maintaining a ratio of 1:20biomass to laterite (Table 4.20).Concentration of iron in

laterites with raw levels of iron also followed the same procedure (Table 4.19). Figure

3.2 Shows the concentration procedure used.

53

Figure 3.2 showing the concentration procedure

3.4 Data analysis

The results of the analyses in all measurements were done in triplicate and the

arithmetic mean obtained by use of Equation 3.2.

i

i nxx / ..................................................................................... 3.2

54

Where; x - Arithmetic mean of the samples, ix - Sample measurements and n -

Population.

Comparison of experimental means of methods of analysis, AAS, XRF and EDTA

titration was done using ANOVA (Miller and Miller, 1984; Harvey, 2000).

55

CHAPTER FOUR

RESULTS AND DISCUSSION

4.1 Mineral composition of raw and concentrated laterites

Laterite samples from identified sampling sites in Kamahuha Murang‟a County were

analyzed for their mineral content using X-ray diffraction technique. The minerals in the

raw samples were identified using the XRD spectra appendix 1, 3, 5 and 7 for the

samples K1, K2, K3 and K4 respectively. The XRD spectra Figure 2, 4 and 6 and 8

show minerals present after concentration of K1, K2, K3 and K4 respectively.

The XRD spectrum of the raw laterite sample KI (Appendix 1) showed peaks at 2θ =

26.2o assigned to quartz, a broad peak at2θ = 21.51

oassigned to goethite and a peak at 2θ

= 24.8o was assigned to rutile. The two broad peaks at 2θ = 33.51

o and 54.11

o were

assigned to hematite while the peak at 2θ = 64owas assigned to nacrite (John, 1989).

After concentration the spectrum (Appendix 2) was obtained and had peaks at 2θ =

26.2o

assigned to quartz and a peak at 2θ = 24.8o assigned to rutile. However those

peaks associated with goethite and nacrite disappeared. New peaks including a broad

peak at 2θ = 36o

associated with magnetite appeared. Also noted were two peaks

associated with illmenite at 35.4o and 32.1

oon the 2θ scale. Illmenite is also strongly

attracted by a magnet. This explains why its concentration increased after magnetic

separation.

XRD spectrum for the raw sample K2 (Appendix 3) showed that the laterite sample

contained quartz, goethite, nacrite with their respective peaks on the 2θ scale as in K1

above. Two peaks at 54.11o and 33.51

oon the 2θ scale were observed and are associated

with the mineral hematite (John, 1989). After concentration the spectrum (Appendix 4)

the minerals quartz, illmenite and Magnetite were present as shown by the various

56

peaks associated in these two minerals. This therefore suggested that the iron minerals

had been converted to magnetite (John, 1989).

The raw sample K3 on analysis gave the spectrum (Appendix 5) had minerals quartz,

goethite, hematite and rutile. These minerals are identified due to the peaks associated

to each of the minerals. On concentration sample K3 showed the spectrum (Appendix 6)

which had peaks associated with quartz at 2θ = 26.2o, rutile at 2θ 24.8

o, illmenite at 2θ =

35.4o and magnetite at 2θ = 36

o. Magnetite has several other peaks as identified in

appendix 6 (John, 1989).

The raw laterite sample K4 showed peaks associated with the minerals quartz, goethite

and rutile. A peak at2θ = 25o

associated with fayalite was observed (Appendix 7). On

concentration the spectrum (Appendix 8) was obtained magnetite, illmenite and quartz

remained. This is shown by the various peaks as identified in the Spectrum (Appendix

8). Table 4.1 shows a summary of the minerals in both raw and concentrated laterites

(John, 1989).

57

Table 4.1 Shows Mineral content in the sampled laterites

X-ray diffraction spectra for the raw laterites showed that the minerals quartz (SiO2),

fayalite (Fe2SiO4) goethite (FeO(OH), hematite (Fe2O3), rutile (TiO2) and nacrite

(Al2Si2O5(OH)4 were present. The peaks for the mineral were observed on the 2θ scale

at quartz (26.2), fayalite (25o) goethite (21.51

o), hematite (54.11

o& 33.51

o), rutile

(24.8o) and nacrite (64

o). After the concentration process the peaks for the minerals

Sample Minerals In Raw

Sample

2θ Mineral After

Concentration

2θ

K1 Quartz (SiO2) 26.2o Quartz (SiO2) 26.2

o

Goethite (FeO(OH) 21.51o Magnetite (Fe4O3) 36

o

Nacrite

(Al2Si2O5(OH)4

64o Illmenite FeTiO3 35.4

o,32.1

o

Rutile (TiO2) 24.8o Rutile (TiO2) 24.8

o

K2 Quartz (SiO2) 26.2o Quartz (SiO2) 26.2

o

Goethite (FeO(OH) 21.51o Magnetite (Fe4O3) 36

o

Hematite (Fe2O3) 54.11o,33.51

o Rutile (TiO2) 24.8

o

Nacrite

(Al2Si2O5(OH)4

64o Illmenite FeTiO3 35.4

o,32.1

o

Illmenite FeTiO3 35.4o,32.1

o Illmenite FeTiO3 35.4

o,32.1

o

K3 Quartz (SiO2) 26.2o Quartz (SiO2) 26.2

o

Goethite (FeO(OH) 21.51o Magnetite (Fe4O3) 36

o

Rutile (TiO2) 24.8o Rutile (TiO2) 24.8

o

Illmenite FeTiO3 35.4o,32.1

o Illmenite FeTiO3 35.4

o,32.1

o

K4 Quartz (SiO2) 26.2o Quartz (SiO2) 26.2

o

Fayalite Fe2SiO4 25o

Goethite (FeO(OH) 21.51o Magnetite (Fe4O3) 36

o

Rutile (TiO2) 24.8o Rutile (TiO2) 24.8

o

Illmenite (FeTiO3) 35.4o,32.1

o Illmenite (FeTiO3) 35.4

o,32.1

o

58

fayalite Fe2SiO4 , goethite (FeO(OH), hematite (Fe2O3) disappeared and an enlarged

peak at 2θ = 36o appeared.This peak is associated with the mineral magnetite, the

appearance of this peak shows that the minerals goethite and hematite have been

converted to magnetite.Together with this peak, there appeared two peaks at 2θ = 35.4o

and 32.1o. This peaks are associated with the mineral illmenite.

The XRD spectra were interpreted using a reference data stored in the D2 phaser X-ray

difractometer. The XRD reference data is a collection of single-phase X-ray powder

diffraction patterns for the three most intense D values in the form of tables of

interplanar spacing (D), relative intensities (I/Io), mineral name and chemical formulae

(John, 1989).

The results from the spectra suggest that all goethite and hematite minerals were

converted to magnetite. This is confirmed by the disappearance of peaks for goethite (2θ

= 21.51o) and hematite (2θ= 54.11

o& 33.51

o) in the spectra of the raw samples, and

increasing intensity of the magnetite peaks (2θ = 36o) in the beneficiated samples.

Biomass in the mixture was heated to produce carbon, which was oxidized to CO gas

in-situ. The CO then reduced hematite and goethite to magnetite. Since magnetite is

strongly attracted by a magnet than goethite and hematite, magnetite was separated from

the gangue using a permanent magnet. The reactions involved are given by equations

4.1 and 4.2.

2C (s) + O2 (g) 2CO(g) ……………………….……..……4.1

3Fe2O3.H2O (s) + CO (g) 2Fe3O4 (s)+ CO2 (g)+ 3H2O(g) ……..4.2

Purwanto et al. 2003), while working with laterite from Indonesia was able to convert

goethite to magnetite using CO/CO2 in the ratio of 1:3.Keru (2011), while working with

59

Ruiru laterites in Kenya, was also able to convert goethite to magnetite by heating a

charcoal/laterite mixture in the ratio 3:20. This technique of beneficiation provides a

convenient method which when used may help to exploit iron from laterite/Murrams

materials than relying only on the iron ore deposit available in the country.

4.2 Optimization

The levels of iron in different ratios of biomass to laterites are given in table 4.2.

Table 4.2 Determination of levels of iron using different ratios of biomass to laterites

Biomass : laterite Ratio Percentage of (Fe2O3) after treatment Percentage

iron

1:05 88.58±0.04 62.28

1:07 88.95±0.02 62.45

1:10 88.74±0.05 62.74

1:15 88.45±0.03 62.25

1:20 88.25±0.03 62.25

1:25 84.69±0.03 61.29

1:30 80.28±0.03 61.10

1:40 81.61±1.20 57.13

1:50 79.79±0.58 55.85

1:60 77.37±0.79 54.16

1:70 75.11±0.31 52.58

1:80 73.19±0.18 51.20

Biomass obtained from solid municipal waste is usually regarded as waste, however this

project made use of it as an important source of energy to concentrate the iron in

laterites. The cost involved in obtaining the biomass is mainly due to sorting the

biomass, drying and transport from dumping sites. In a commercial setting it is

important to determine the optimum ratio of biomass to laterite during the concentration

process. The results obtained above were compared statistically to determine the most

appropriate ratio for use in the concentration. The comparison is shown in table 4.3.

60

Table 4.3 Statistical comparison of the various biomass to laterite ratios

Biomass:laterite Mean±SD

1:5 88.73±0.23g

1:7 88.63±0.37g

1:10 88.73±0.18g

1:15 88.56±0.29g

1:20 88.58±0.20g

1:25 84.12±0.63f

1:30 80.46±0.48d

1:40 81.61±1.20e

1:50 79.79±0.58d

1:60 77.37±0.79c

1:70 75.11±0.31b

1:80 73.19±0.18a

p-value <0.001

Mean values followed by the same small letter within the same column are not

significantly different (α=0.05, One-way ANOVA, SNK-test)

Ratios 1:5 up to 1:20 showed a significantly higher concentration of Iron (III) oxide

than the other ratios with lower quantities of biomass (p<0.001 at 95% confidence level,

One-Way ANOVA). Since the ratio 1:20 contained the lowest amount of biomass but

gave significantly high concentration of iron, this ratio was found to be the most viable

for reduction of iron oxides in laterite samples to form magnetite. Ratios with higher

proportion of biomass gave the same level of iron as that of 1:20 biomass to laterite

within statistical error. This implies that some of the biomass used was converted to

carbon and further oxidized to CO but all the goethite and hematite had already been

converted to magnetite. A ratio of 1:20 biomass to laterite was therefore used in all the

other concentration processes in this project. The same ratio was used when

concentrating iron using charcoal. The laterite samples were concentrated using various

methods.

61

4.3 Particle size variation

Three different particle sizes were used in this experiment. Table 4.4 and figure 4.1

shows the level of iron obtained for each particle size used. Statistical comparison of the

levels of iron when different sizes were used is shown in table 4.5

Table 4.4: Showing levels of iron after concentration using different particle sizes

Samp

le

Particle sizes

100 mesh

(0.149mm)

50mesh

(0.297mm)

18mesh(1.0

mm)

Mean± SE %

Fe

Mean± SE %

Fe Mean±SE

% Fe

K1A 87.47±0.14 61.8 88.17±0.12 61.6 88.37±0.14 61.8

K1B 86.07±0.13 60.2 86.57±0.01 60.3 87.07±0.28 60.9

K1C 85.87±0.62 60.0 85.87±0.68 60.0 85.37±0.63 59.5

K2A 88.53±0.30 61.9 88.93±0.50 62.2 87.53±0.67 61.2

K2B 88.23±0.66 61.7 88.03±0.64 61.6 89.23±0.06 62.4

K2C 87.53±0.97 61.2 87.50±0.40 61.2 89.53±0.07 62.5

K3A 87.91±0.41 61.5 87.61±0.20 61.3 88.01±0.31 61.6

K3B 89.73±0.74 62.8 88.73±0.35 62.1 88.73±0.54 62.1

K3C 88.57±0.19 62.0 88.00±0.25 61.6 87.57±0.13 61.2

K4A 86.97±0.73 60.8 87.97±0.34 61.5 88.96±0.70 62.2

K4B 88.27±0.82 61.7 88.29±0.42 61.8 86.22±0.25 60.3

K4C 88.17±0.68 61.6 88.55±0.82 61.9 88.87±0.55 62.2

62

Figure 4.1: Showing levels of iron obtained using different particle sizes

Table 4.5 Showing statistical comparison of iron levels obtained using different

particle sizes

Mean values followed by the same small letter within the same column are not

significantly different (α=0.05, One-way ANOVA, SNK-test)

When concentration was carried out using different particle sizes (100, 50, 18 mesh) it

was found that there was no significant difference in the different sizes used. This

observation could be attributed to two important factors that play a big role in

concentration when reduction is carried out using a gas formed in presence of air. These

two factors are porosity of the particles and the air circulation. The CO used may have a

limitation in reaching the iron minerals in large particles with low porosity. On the other

hand very tiny particles hinder passage of air through them. This is explained by the

Particle size Mean±SE

100 mesh (0.149mm) 61.38±1.47a

50 mesh (0.297mm) 61.42±0.79a

18 mesh (1.0 mm) 61.49±0.19a

p-value <0.001

63

very tiny inter-particle spaces. As the particle size increases it is expected that air will

circulate well between the particles. However if the laterite is not porous enough,

reduction will not take place in the iron minerals inside such large particles. Further

studies need to be carried out on the porosity of the laterites. The particle sizes used in

this experiment were all relatively small. The effect of particle size variation cannot be

concluded without further experiments using larger particles and determination of the

laterite porosity. Two control experiments were carried out. The results are shown in the

table 4.6 below.

Table 4.6 Levels of iron in control experiments

Sample Raw laterite Laterite biomass

mixture heated in a

closed furnace

Laterite heated in a current

of air without biomass

mean±se mean±se Mean±SE

K4A 39.22±0.22 39.52±0.04 40.32±0.03

K4B 38.77±0.03 39.04±0.12 39.21±0.10

K4C 39.42±0.02 39.52±0.04 39.91±0.03

Figure 4.2 Showing levels of iron in the control experiment

37.5

38

38.5

39

39.5

40

40.5

K4A K4B K4C

% I

ron

Sample

Raw laterite

Laterite biomass mixture heated

in a closed furnace

Laterite heated in a current of air

without biomass

64

In the first control experiment a mixture of laterite and biomass in the ratio of 20:1 was

heated in a closed furnace to temperatures between 500 – 7000C for period of two

hours. The levels of iron rose by less than 0.5% percent. The slight rise in the level of

iron is attributed to the air enclosed in the furnace. This results show that a flow of air is

needed for the conversion to take place. Air is required to oxidize carbon to CO which

is responsible for the reduction of goethite and hematite to magnetite. Without air the

formation of CO is not possible, furthermore the air should also come into contact with

the carbon formed when biomass goes through carbonization process. In the second

control experiment the laterite was heated to the same treatment temperature without

biomass. The experiment was meant to determine the importance of biomass in the

concentration process. Without biomass carbon from which CO is formed will not be

formed. However it is worth noting that most soil will contain some form of biomass

from plants that grows on the soil. In this experiment, levels of iron rose by less than

0.5% this rise is attributed to the biomass present in the soil. The experiment showed

that biomass was a requirement for the concentration process.

4.4 Elemental analyses of raw laterites

The elemental analysis was carried out using AAS table 4.7, XRF table 4.8 and EDTA

titrations table 4.9. The average concentrations of the various oxides are shown in figure

4.3

65

Table 4.7 Results of elemental analyses of raw laterites using AAS

Table 4.8 Results of elemental analyses of raw laterites using XRF

SiO2 Al2O3 K2O Na2O CaO TiO2 MnO4 Fe2O3 %Fe

Mean± SE Mean± SE Mean±SE Mean±SE Mean±SE Mean±SE Mean±SE Mean± SE

K1A 18.41±0.72 18.12±2.47 0.06±0.03 0.08±0.08 0.07±0.04 7.87±0.38 0.40±0.13 52.50±0.89 36.4

K1B 18.84±0.72 18.52±2.47 0.06±0.03 0.09±0.08 0.07±0.04 6.77±0.38 0.40±0.13 51.50±0.99 36.05

K1C 19.41±0.72 17.12±2.47 0.06±0.03 0.08±0.08 0.07±0.04 7.87±0.38 0.40±0.13 53.50±0.89 37.45

K2A 22.34±6.13 18.32±1.78 0.30±0.07 0.20±0.08 0.10±0.01 7.13±0.32 1.63±0.75 49.50±0.69 34.65

K2B 22.34±6.13 17.32±1.70 0.30±0.07 0.20±0.08 0.10±0.01 7.23±0.42 1.63±0.75 48.50±0.69 33.95

K2C 22.34±6.13 18.32±1.68 0.30±0.07 0.20±0.08 0.10±0.01 6.93±0.52 1.63±0.75 48.50±0.69 33.95

K3A 21.43±3.70 21.20±4.73 0.28±0.14 0.19±0.10 0.08±0.03 7.76±0.33 1.27±0.39 45.47±0.58 31.82

K3B 20.43±3.70 22.20±4.73 0.28±0.14 0.19±0.10 0.08±0.03 7.79±0.33 1.27±0.39 46.47±0.58 32.53

K3C 21.43±3.70 21.20±4.73 0.28±0.14 0.19±0.10 0.08±0.03 7.56±0.33 1.27±0.39 46.47±0.58 32.53

K4A 21.35±3.86 15.80±1.75 0.16±0.08 0.13±0.05 0.10±0.02 5.77±0.44 0.57±0.45 56.34±0.32 39.44

K4B 21.35±3.86 15.60±1.75 0.16±0.08 0.14±0.05 0.20±0.02 5.95±0.44 0.37±0.45 55.35±0.32 38.75

K4C 21.35±3.86 15.70±1.75 0.16±0.08 0.12±0.05 0.10±0.02 6.25±0.44 0.57±0.45 56.35±0.32 39.44

SiO2 Al2O3 K2O Na2O CaO TiO2 MnO4 Fe2O3 %Fe

Mean± SE Mean± SE Mean±SE Mean±SE Mean±SE Mean±SE Mean±SE Mean± SE

K1A 18.48±0.06 19.67±0.16 0.03±0.03 0.08±0.01 0.08±0.01 6.78±0.01 0.28±0.12 51.67±0.17 36.11

K1B 19.27±0.14 17.07±0.04 0.02±0.02 0.08±0.02 0.07±0.00 7.86±0.06 0.28±0.12 53.51±0.01 37.45

K1C 23.35±0.02 17.42±0.02 0.31±0.21 0.21±0.02 0.12±0.01 7.24±0.01 1.64±0.03 53.58±0.31 36.51

K2A 21.35±0.00 16.28±0.04 0.31±0.01 0.21±0.41 0.14±0.03 6.92±0.01 1.64±0.01 50.51±0.01 35.4

K2B 21.34±0.01 21.50±0.30 0.40±0.01 0.10±0.01 0.11±0.02 7.61±0.01 1.28±0.04 47.47±0.31 33.2

K2C 22.43±0.58 21.50±0.25 0.30±0.01 0.23±0.04 0.10±0.01 7.57±0.01 1.28±0.01 46.48±0.01 32.55

K3A 21.74±0.02 15.91±0.01 0.8±0.02 0.13±0.03 0.21±0.07 5.66±0.01 0.38±0.41 46.80±0.02 32.48

K3B 21.35±0.03 15.71±0.01 0.17±0.01 0.13±0.00 0.12±0.01 6.46±0.11 0.58±0.01 46.39±0.02 32.48

K3C 18.48±0.06 19.67±0.16 0.03±0.03 0.08±0.01 0.08±0.01 6.78±0.01 0.28±0.12 47.67±0.17 33.11

K4A 19.27±0.14 17.07±0.04 0.02±0.02 0.08±0.02 0.07±0.00 7.86±0.06 0.28±0.12 52.51±0.01 38.45

K4B 23.35±0.02 17.42±0.02 0.31±0.21 0.21±0.02 0.12±0.01 7.24±0.01 1.64±0.03 55.51±0.31 38.61

K4C 22.35±0.00 18.28±0.04 0.31±0.01 0.21±0.41 0.14±0.03 6.92±0.01 1.64±0.01 57.51±0.01 39.9

66

Table 4.9 Results of elemental analyses of raw laterites using EDTA titrations

Figure 4.3: Showing average levels of the laterites

Results of the elemental analysis showed high levels of iron (III) oxide, which ranged

between 45 percent and 56 percent, this translates to32 and 39percent iron. The results

0

5

10

15

20

25

30

35

40

45

50

% O

xid

e

Major Oxides In The Laterites Major Element Oxide in Laterite Samples

SiO2 Al2O3 K2O Na2O CaO TiO2 MnO4 Fe2O3

22.34 18.32 0.3 0.2 0.1 6.93 1.63 48.5

Al2O3 CaO MnO4 Fe2O3 Fe

Mean± SE

Mean±

SE Mean±SE Mean±SE Mean±SE

K1A 18.57±0.16 0.12±0.01 0.34±0.10 54.67±0.00 38.22

K1B 16.07±0.03 0.09±0.00 0.31±0.15 52.43±0.01 36.71

K2A 18.27±0.02 0.32±0.05 1.33±0.07 51.54±0.08 36.08

K2B 17.00.08 0.42±0.03 1.64±0.01 49.66±0.09 34.76

K3A 23.53±0.36 0.31±0.02 1.40±0.03 47.56±0.05 33.29

K3B 22.53±0.27 0.20±0.54 1.32±0.08 48.46±0.04 33.92

K4A 17.91±0.21 0.31±0.06 0.44±0.41 55.44±0.08 38.81

K4B 14.73±0.24 0.29±0.07 0.88±0.04 57.30±0.77 40.11

K1A 18.57±0.16 0.12±0.01 0.34±0.10 54.67±0.00 38.22

K1B 16.07±0.03 0.09±0.00 0.31±0.15 52.43±0.01 36.71

K2A 18.27±0.02 0.32±0.05 1.33±0.07 51.54±0.08 36.08

K2B 17.0±0.08 0.42±0.03 1.64±0.01 49.66±0.09 34.76

67

showed that iron is distributed in all the four quarries sampled, with levels which are

convenient for extraction. It was also found that the level of titanium oxide was also

high. As expected the levels of both silicon oxide and aluminium oxides were high.

Quarry K4 had the highest level of iron. The levels of iron in laterites from this region

are higher than the level of iron from Frodingham with 24% iron which is used for

commercial iron production.

4.5 Loss on ignation (LOI)

Table 4.10 shows the results for loss on ignition of raw samples.

Table 4.10 Loss on ignition of raw samples

The results of analysis showed that there was some loss on ignition. The various

samples gave different values. The values of loss on ignition ranged between 1.14% and

5.77%. These values represent the percentage of organic matter in the laterite samples.

The range observed is an indication that the organic matter in the laterite samples was

not equally distributed.

Three methods of analysis were used to determine the levels of the various elements in

the samples. This was done to ensure that the data used was reliable. The comparison

was done for two sites K1 and K4. Tables 4.11 and 4.12 show levels of the various

elements obtained through the three methods and their statistical comparisons.

K1A K1B K1C K2A K2B K2C K3A K3B K3C K4A K4B K4C

LOI

4.17±

3.06

5.17±

0.38

2.87±

1.38

1.14±

0.32

1.28±

0.42

2.43±

1.52

3.15±

1.33

1.46±

0.23

3.54±

0.35

5.77±

3.45

2.95±

0.54

3.15±

1.64

68

Table 4.11 Mean Chemical composition of raw laterites in K1 and statistical

comparison of AAS and XRF and EDTA titrations

K1 Al2O3 SiO2 K2O Na2O CaO MnO4 MgO Fe2O3

Mean±SE Mean± SE Mean±SE Mean±SE Mean±

SE

Mean±

SE Mean±SE Mean± SE

AAS 18.57±0.1

8

21.62±0.4

7 0.36±0.00 0.23±0.04 0.33±0.19 1.42±0.01 0.31±0.03 49.30±0.40

XRF 19.75±0.8

1

24.83±0.5

5 0.20±0.09 0.12±0.02 0.78±0.07 0.59±0.03 0.44±0.07 49.09±0.90

EDTA 20.83±0.4

8 - - - 0.89±0.02 0.65±0.04 49.80±0.30

P-

VALUE 0.73 - - - 0.053 0.12 - 0.701

Table 4.12 Mean Chemical composition of raw laterites in K4 and statistical

comparison of AAS and XRF and EDTA titrations

K4 Al2O3 SiO2 K2O Na2O CaO MnO4 MgO Fe2O3

Mean±SE Mean±SE Mean±SE Mean±SE Mean±SE Mean±SE Mean±SE Mean±SE

AAS 16.57±0.95 20.96±0.35 0.17±0.02 0.23±0.03 0.13±0.01 0.42±0.01 0.28±0.01 55.97±0.27

XRF 16.08±0.41 21.83±0.12 0.23±0.03 0.18±0.03 0.31±0.05 0.52±0.01 0.34±0.02 55.08±0.56

EDTA 16.81±0.44 - - - 0.19±0.03 0.68±0.04 - 55.82±0.33

p-value 0.73 - - - 0.052 0.101 - 0.129

Mean values with p-value < 0.05 shows a significant difference between the three

methods for the elements sodium and potassium. This was expected since XRF does not

give accurate values for elements with atomic numbers below 13, despite this short

coming the method was used since the main interest was the concentration of iron

which has a higher atomic number. There was no significant difference in the three

methods for the rest of the elements analyzed. This comparison was carried out to

ensure that the levels of iron obtained were reliable. Table 4.13 below shows the levels

of the various elements after concentration with charcoal.

69

4.6 Chemical composition after concentration

4.6.1 Results after concentration using charcoal

The concentrations of elements after charcoal concentration are given in table 4.13.

Table 4.13 Levels of the various elements after concentration with charcoal

SiO2 Al2O3 K2O Na2O CaO TiO2 MnO4 Fe2O3 Fe

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE Mean± SE %

K1A 2.25±0.72 2.16±0.47 0.07±0.03 0.07±0.08 0.07±0.04 9.17±0.68 2.20±0.36 86.40±0.89 60.2

K1B 3.84±0.72 3.52±1.47 0.07±0.23 0.06±0.18 0.06±0.04 8.62±0.03 0.23±0.03 87.30±0.99 60.9

K1C 3.11±0.72 3.12±1.41 0.08±0.03 0.78±0.08 0.03±0.04 8.27±0.31 0.30±0.11 86.40±0.89 60.5

K2A 2.95±0.13 3.42±1.41 0.50±0.72 0.03±0.72 0.20±0.72 8.13±0.72 0.13±0.72 87.44±0.72 61.1

K2B 3.34±0.14 3.41±1.70 0.10±0.17 0.30±0.28 0.20±0.01 8.53±0.41 0.13±0.75 86.40±0.69 60.5

K2C 4.64±0.13 3.35±1.68 0.30±0.07 0.20±0.28 7.98±0.21 013±0.22 2.25±0.75 88.50±0.69 61.7

K3A 3.63±1.70 3.40±2.73 0.18±0.24 0.29±0.11 0.18±0.04 8.26±0.53 0.17±0.39 85.45±0.58 59.7

K3B 3.23±0.70 2.70±1.73 0.30±0.14 0.29±0.11 0.16±0.13 9.79±0.23 0.22±0.32 86.67±0.51 60.7

K3C 3.47±3.71 4.30±4.73 0.18±0.24 0.22±0.11 0.21±0.03 9.16±0.23 0.27±0.31 87.47±0.58 61.2

K4A 2.35±3.86 4.30±1.75 0.16±0.08 0.13±0.05 0.20±0.02 7.71±0.44 0.17±0.45 88.35±0.32 61.8

K4B 3.35±2.84 4.60±1.75 0.16±0.08 0.24±0.01 0.12±0.02 8.22±0.27 0.19±0.45 88.95±0.32 62.2

K4C 2.45±1.86 5.30±0.73 0.20±0.28 0.28±0.15 0.23±0.12 8.31±0.34 0.26±0.45 89.45±0.31 62.5

From the results obtained in table 4.13, it is clear that the level of iron increasedto over

62% after the laterites were concentrated using charcoal. This was expected since when

the charcol was heated,in a current of air it was oxidised to CO which reduced goethite

and hematite to magnetite. the magnetite was separated from the gangue using a

magnet. The portion abtained using the magnet therefore contained mainly magnetite. It

should however be noted that charcoal obtained from cutting down of trees is not an

option for iron concentration due to its cost and the effect of producing it on the

environment. Biomass obtained from solid municipal waste was used in place of

70

charcoal. Table 4.14 below shows levels of the various elements after concentration

with biomass.

4.6.2 Results after concentration using biomass

Levels of various elements after concentration with biomass are given in table 4.14.

Table 4.14 Levels of various elements after concentration with biomass

SiO2 Al2O3 K2O Na2O CaO TiO2 MnO4 Fe2O3 Fe

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE

Mean±

SE Mean± SE %

K1A 2.05±0.32 1.16±0.41 0.10±0.03 0.07±0.08 0.09±0.04 9.01±0.28 0.20±0.31 87.41±0.29 61.2

K1B 2.05±0.32 3.02±1.30 0.14±0.03 0.06±0.08 0.03±0.04 8.91±0.90 0.23±0.13 88.30±0.99 61.9

K1C 1.14±0.70 3.02±1.21 0.18±0.03 0.16±0.02 0.02±0.03 8.72±0.31 0.30±0.16 87.40±0.17 61.2

K2A 2.31±0.10 1.48±1.01 0.31±0.03 0.23±0.02 0.20±0.72 8.70±0.55 0.13±0.65 88.48±0.60 61.9

K2B 2.31±0.10 2.50±1.31 0.13±0.14 0.23±0.28 0.21±0.01 8.88±0.41 0.13±0.75 87.20±0.61 61.0

K2C 4.64±0.13 3.35±1.68 0.30±0.07 0.20±0.28 7.98±0.21 013±0.22 2.25±0.75 88.50±0.69 61.9

K3A 2.09±1.70 2.70±1.7 0.08±0.16 0.29±0.21 0.48±0.06 8.72±0.53 0.17±0.39 86.65±0.58 60.6

K3B 2.23±0.70 2.60±1.73 0.10±0.14 0.28±0.12 0.18±0.11 8.99±0.23 0.22±0.32 87.68±0.51 61.1

K3C 2.45±1.61 2.90±1.03 0.28±0.24 0.28±0.10 0.22±0.13 8.19±0.23 0.27±0.31 88.49±0.58 61.9

K4A 2.35±3.86 2.39±1.89 0.26±0.18 0.23±0.05 0.21±0.02 7.61±0.44 0.17±0.45 89.35±0.32 62.5

K4B 2.39±1.14 2.60±1.90 0.26±0.03 0.14±0.11 0.20±0.12 8.61±0.27 0.19±0.45 88.95±0.32 62.2

K4C 2.87±1.20 2.87±0.73 0.25±0.22 0.18±0.10 0.20±0.14 8.21±0.34 0.26±0.45 89.85.±0.32 62.89

When biomass was used in place of charcoal, in the same ratio, it was observed that the

level of iron rose to over 62.5%.This showed that the biomass was first carbonized

before being oxidized to CO (Funke, 2009). The CO formed reduced hematite to

magnetite. For the reduction to take place thermal contact between the CO and laterite is

required. It should also be noted that the level of titanium remained high in the two

experiments above. FeTiO3 is also strongly attracted by a magnet. Illmenite is therefore

picked by the magnet together with the magnetite. This explains why the levels of

titanium were high in the concentrated samples.

71

Froth floatation is a commercially used method of concentration, it was carried on the

laterite samples and table 4.15 below shows the levels of iron after concentration.

4.6.3 Results after concentration using froth floatation

Percentages of iron after froth flotation are given in table 4.15 and figure 4.4.

Table 4.15 Iron content in concentrate after froth flotation

Sample

Percentage Of iron

in raw laterites

Percentage of iron in

concentrated laterites

Percentage of iron

in the tailing

K1A 36.7 43.8 11.2

K1B 36.0 41.3 10.9

K1C 37.4 41.2 11.3

K2A 34.7 42.1 12.7

K2B 33.9 41.3 10.9

K2C 33.9 41.8 11.3

K3A 31.8 39.9 9.6

K3B 32.5 44.6 9.5

K3C 32.4 40.9 8.6

K4A 39.3 52.0 8.9

K4B 38.7 51.5 10.1

K4C 39.4 52.6 10.2

72

Figure 4.4: Showing levels of iron in the froth and tailing on froth floatation

Froth floatation is a known method of concentrating iron in iron ores. The levels of iron

obtained after concentrating the iron using froth floatation ranged between 41 to 52%.

This method uses chemicals which may not be easily recovered hence increasing the

cost of the method. It is worth noting that these chemical may end up in the

environment causing pollution. The low levels of iron obtained after concentration are

attributed to the iron mineral obtained after concentration using froth floatation. The

percentage of iron in hematite is 70% while the percentage of iron in magnetite is

72.4% iron. When concentration is carried out through froth floatation hematite is

obtained but if concentration is via reduction using CO the mineral magnetite is formed.

Even though froth floatation is used in concentration of iron, froth floatation works best

in sulphide ores. There was a significant difference between the levels of iron obtained

through froth floatation and the other two methods described in this thesis. Levels of

iron in both raw and concentrated laterites using charcoal are shown in table 4.13.

73

Table 4.16 Levels of iron in raw laterite and after concentration using charcoal

Sample

Percentage Of iron in

raw laterites

Percentage Of iron in

concentrated laterites

K1A 36.7 60.2

K1B 36.0 60.9

K1C 37.45 60.5

K2A 34.7 61.1

K2B 33.9 60.4

K2C 33.9 61.7

K3A 31.8 59.7

K3B 32.5 60.7

K3C 32.4 61.2

K4A 39.3 61.8

K4B 38.7 62.2

K4C 39.4 62.5

The results showed that when charcoal is used in the same ratio as biomass to

concentrate the iron in laterites the levels of iron rose to over 62% iron. The charcoal

used in this experiment was obtained through burning of trees. It is therefore not an

option for commercial concentration of iron since it has negative environmental

implications. The cost of such charcoal is also very high, which makes the method

uneconomical. Levels of iron in both raw and concentrated laterites using biomass are

shown in table 4.17.

74

Table 4.17 Level of iron in raw laterite and after concentration using biomass

After concentrating the iron in all the samples collected it was found that the level

increased from 31 to over 62% iron. This results show that when one ton of dry biomass

is mixed with laterites, it is possible to recover 20 tons of iron ore with a concentration

of 62% iron. Iron ores containing over 55% iron can be placed directly into the blast

furnace. This method of concentration needs to be scaled up by setting a pilot plant to

concentrate iron in laterites via carbonized biomass. It was also observed that the

conversion took place in all the samples used. Use of biomass has the advantage in that

it is itself considered a waste. Thus consumption of biomass from solid municipal waste

will go hand in hand with cleaning the environment.

4.7 Comparison of iron levels in raw and treated laterites

A comparison of iron level obtained on using the three methods is shown in table 4.18

while table 4.19 shows the statistical comparison of the levels of in the three methods

used.

Sample Percentage Of iron in raw

laterites

Percentage of iron in

concentrated laterites

K1A 36.7 61.2

K1B 36.0 61.9

K1C 37.4 61.2

K2A 34.7 61.9

K2B 33.9 61.0

K2C 33.9 62.0

K3A 31.8 60.6

K3B 32.5 61.4

K3C 32.4 61.2

K4A 39.3 62.0

K4B 38.7 62.3

K4C 39.4 62.9

75

Table 4.18 Showing levels of iron obtained using the three concentration methods

Sample Percentage

of iron in

raw laterites

Percentage of

iron obtained

after Froth

Flotation

Percentage Of

iron obtained

on using

charcoal

Percentage

of iron

obtained on

using

biomass

K1A 36.7 43.8 60.2 61.2

K1B 36.0 41.3 60.9 61.9

K1C 37.45 41.2 60.5 61.2

K2A 34.7 42.1 61.1 61.9

K2B 33.9 41.3 60.4 61.0

K2C 33.9 41.8 61.7 62.0

K3A 31.8 39.9 59.7 60.6

K3B 32.5 44.6 60.7 61.4

K3C 32.4 40.9 61.2 61.2

K4A 39.3 52.0 61.8 62.0

K4B 38.7 51.5 62.2 62.3

K4C 39.4 52.6 62.5 62.9

Table 4.19 Showing statistical comparison of the three methods used for

concentration

Method Mean±SE

Froth floatation 44.42±1.38a

Charcoal 61.08±0.24b

Biomass 61.63±0.19b

p-value <0.001

Mean values followed by the same small letter within the same column are not

significantly different (α=0.05, One-way ANOVA, SNK-test)

Charcoal and biomass showed no significant difference in the levels of Iron, while Froth

floatation showed lower levels of Iron (P<0.001, α=0.05, One way ANOVA). Both

charcoal and biomass (saw dust) yielded similar levels of iron. The two concentrate iron

through reduction of goethite and hematite to magnetite. The carbonization of biomass

takes place first to form the charcoal. Froth floatation works well with sulphides since

they bind with the air bubbles and are easily suspended to the water surface where they

76

separate from the rest of the gangue. The iron minerals in the laterites were oxides and

not sulphides. Thus frothing agents were used these agents may not have been 100 %

effective. This is evidenced by presence iron in the tailing. Figure 4.11 shows a

comparison between the iron levels for the three methods used.

Figure 4.5 Showing levels of iron obtained using the three methods

On comparing the levels of iron obtained when the three concentration methods are

used, it is found that Froth flotation which is a commercial method yields lower levels

of iron. Charcoal on the other hand has levels that are almost equal to those obtained

when biomass is used. This comparison shows the use of biomass as an alternative

method for concentrating iron in laterites. It should be noted that froth flotation requires

frothing agents for minerals that are not sulphides. In this project the minerals were

present as oxides of iron hence frothing agents were required. Charcoal obtained from

cutting of trees on the other hand is expensive and not an option in the process of

concentrating iron in laterites. Use of such charcoal will give very expensive product

apart from the negative effects on the environment due to cutting down of trees.

77

Biomass obtained from solid waste offers the best alternative since biomass from solid

municipal waste has no cost and is regarded as a waste. Such biomass is found in all

urban and rural settings. The main cost of obtaining biomass is mainly sorting,

transporting and drying the biomass.

4.8 Laterites containing low levels of iron

The laterite samples obtained from Juja were concentrated in the same way using a

similar ratio of biomass. Table 4.20 shows the levels of iron after concentration.

Table 4.20 Levels of iron in raw laterite from Juja farm and after concentration

using biomass in the ratio1:20

Sample

Percentage of iron in raw

laterite Percentage of iron after concentration

J 1 16.31 55.3

J 2 13.55 52.5

The laterites from Juja Farm were found to contain low levels of iron compared to those

obtained from Kamahuha region. The two samples collected from two sites had iron

levels of 13.5 and 16.3 %. Concentration was carried out using a similar procedure with

a ratio of 1:20 biomass to laterite. On concentration the levels of iron increased to over

55%. This showed that the initial level of iron does not affect the conversion of goethite

and hematite to magnetite. This method of concentration therefore offers a viable

method even when using ores with low levels of iron. The data on this table show iron

can be recovered from laterites with very low levels of iron.

78

4.9 Concentration using large quantities of Laterites

Due to the low cost of obtaining biomass this project provides a method that should be

scale up through a pilot project to assess the possibility of using the method

commercially. Table 4.21 and figure 4.6 shows levels of iron obtained when the amount

of laterite was scaled up to 5kg.

Table 4.21 Levels of iron in raw laterite and after concentration using biomass in the

ratio of 1:20 using 5kg of laterite

Sample Percentage of iron in raw laterites

Percentage of iron after

concentration

K4A 39.4 61.4

K4B 38.7 60.2

K4C 39.4 62.5

Figure 4.6 Showing levels of iron when 5kg of sample was concentrated using

biomass

The effect of varying the quantities of materials is very important for any process before

scaling up a process to produce any product, in this case magnetite. The results obtained

79

when the mass of the mixture is scaled up ten times (from 500g to 5000g of laterite), the

level of iron obtained is above 62% which is obtained from laterites originally

containing about 39% iron before concentration. From these results then it is possible to

scale up the quantities to a pilot project that would produce larger quantities of

magnetite. If this is achieved then a feasibility study should be carried out to determine

the possibility of using laterites as a source of magnetite. The type of biomass used was

an important factor to take into consideration. Table 4.22 shows levels of iron obtained

when concentration was carried out using different types of biomass.

Table 4.22 Shows levels of iron in raw laterite and after concentration using different

types of biomass in the ratioof1:20

Biomass obtained from the solid municipal waste exist in several forms including

leaves, waste food parts such as potato and fruit peelings saw dust among others. This

project used three forms of biomass for purposes determining the effectiveness of each

of them. The different types of biomass gave almost equal levels of iron when the

treatment was carried the same way. The small difference is probably due to the

difference in surface. This shows that biomass required for concentration of iron in

laterites need not be of a specific type. Any form of biomass may be used for this

treatment.

Sample Raw

laterite

Concentrated

using

sawdust

Concentrated

using dry

leaves

Concentrated

using banana and

potato peelings

Mean±SE Mean±SE Mean±SE Mean±SE

K4A 39.22±0.22 61.47±0.03 61.22±0.03 60.43±0.03

K4B 38.77±0.03 60.51±0.10 60.21±0.10 60.18±0.10

K4C 39.42±0.02 62.57±0.03 61.21±0.03 61.97±0.03

80

CHAPTER FIVE

CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions

(i) Laterites from Kamahuha contain the iron minerals goethite and hematite.

(ii) Iron levels in the laterites from Kamahuha range between 24 and 36%.

(iii) The optimum ratio of biomass to laterite required for iron concentration in

laterites containing the mineral goethite and hematite is 1:20.

(iv) Iron in laterites can be concentrated by mixing the biomass with laterite in the

ratio of 1:20 followed by heating to temperatures between 500-7000C in a

stream of air.

(v) The iron levels in laterites can be concentrated to over 62%, such an ore can be

used in the blast furnace for extraction of iron.

(vi) The minerals goethite & hematite are converted to magnetite via the

concentration process.

(vii) The laterites being used for surfacing roads are, indeed, potential iron ores.

Whereas no doubt, some energy will be used for collection and drying the

millions of tones of biomass being generated in cities. The results of this study

show beyond any reasonable doubt that they are, indeed a resource in the

concentration of iron in iron ores containing both goethite and hematite.

81

5.2 Recommendations

5.2.1 Recommendations from this work

(i) Biomass which is an environmental concern especially in major urban areas

should be used to concentrate iron in Laterites and other iron ores containing

goethite and hematite.

(ii) Laterites that are currently used in building of the roads should be used as a

source of iron since the iron in these laterites can be concentrated to a level that

can be put in a blast furnace for extraction of iron. However more work needs to

be done to scale up the process to a pilot level and determine the economic

viability of the concentration process.

5.2.2 Recommendations for further research

(i) The concentration should be carried out in a pressured system to ensure

maximum thermal contact between CO and laterite. Such a set-up should be

constructed to facilitate a larger scale conversion of goethite and hematite to

magnetite.

(ii) A mechanism should be established to ensure that solid municipal waste is

sorted at the source so that the biomass is separated from the rest of the waste.

(iii)Concentration process and its efficiency depend on factors such as density,

particle size, and porosity of the ore and chemical composition of the ore.

Further studies should therefore be carried out to determine the effects of these

factors in the concentration of iron in laterites.

(iv) A cost benefit analysis should be carried out to determine the economic viability

of the iron concentration method.

82

(v) A pilot study is necessary to determine the possibility of extracting iron from the

concentrated laterites.

83

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APPENDICES:

APPPENDIX 1

XRD Spectrum for Raw Laterite Sample K1

G-Goethite

Q-Quartz

H-Hematite

N-Nacrite

R-Rutile

Lin

(C

oun

ts)

2-Theta - Scale

1000

1100

1200

1300

0

100

200

300

400

500

600

700

800

900

5 10 20 30 40 50 60 70

G Q

H

G

H N

R

90

APPENDIX 2

XRD Spectrum for Concentrated Laterite Sample K1

91

APPENDIX 3

XRD Spectrum for Raw Laterite Sample K2

2-Theta - Scale

1000

1100

1200

1300

0

100

200

300

400

500

600

700

800

900

5 10 20 30 40 50 60 70

G Q

H

G

H N

G-Goethite

Q-Quartz

H-Hematite

N-Nacrite

R-Rutile

Lin

(C

oun

ts)

R

92

APPENDIX4

XRD Spectrum for Concentrated Laterite Sample K2

93

APPENDIX 5

XRD Spectrum for Raw Laterite Sample K3

2-Theta - Scale

1000

1100

1200

1300

0

100

200

300

400

500

600

700

800

900

5 10 20 30 40 50 60 70

G Q

H

G

H

G-Goethite

Q-Quartz

H-Hematite

R-Rutile

Lin

(Cou

nts

)

R

94

APPENDIX 6

XRD Spectrum for Concentrated Laterite Sample K3

95

APPENDIX 7

XRD Spectrum for Raw Laterite Sample K4

2-Theta - Scale

1000

1100

1200

1300

0

100

200

300

400

500

600

700

800

900

5 10 20 30 40 50 60 70

G Q

H

G

H N

G-Goethite

Q-Quartz

H-Hematite

N-Nacrite

R-Rutile

F-Fayalite

Lin

(Cou

nts

)

R F

96

APPENDIX 8

XRD Spectrum for Concentrated Laterite Sample K4

97

APPENDIX 9

Map of Kenya showing Murang’a and Kiambu counties

98

Appendix 10

Silica calibration curve used in AAS

y = 0 R² = #N/A

y = 0.0012x + 0.0005 R² = 0.9997

Ab

sorb

an

ce

Percentage concentration

Silica calibration curve

99

Appendix 11

Aluminium calibration curve used in AAS

y = 0.0402x - 0.0128

R² = 1

Ab

sorb

an

ce

Percentage concentration

Aluminiun calibration curve