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
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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
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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
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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.
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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