EFFECTS OF MICELLAR SOLUTION ON THE …chemistry.uonbi.ac.ke/sites/default/files/cbps/sps/chemistry/IJBCP... · degradation, thereby rendering ... Dicofol is used as a substrate in

International Journal of BioChemiPhysics, Vol. 22, December 2014

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EFFECTS OF MICELLAR SOLUTION ON THE ELECTROCATALYTIC

ACTIVITY OF CYANOCOBALAMIN TOWARDS THE REDUCTION OF ORGANOCHLORINE PESTICIDE 2,2,2-TRICHLORO-1,1-BIS(4-

CHLOROPHENYL)ETHANOL (DICOFOL) ON A PYROLYTIC

GRAPHITE ELECTRODE

Tabitha W. Wanjau1*

, Silas M. Ngari3, Catherine N. Muya

4, Geoffrey N. Kamau

2*

1 Kisii University, School of Health Sciences, P.O. Box 408-40200 Kisii, Kenya 2School of Physical Sciences, University of Nairobi, P.O. Box 30197-00100 Nairobi, Kenya 3Faculty of Science, Egerton University, Department of Chemistry, P.O. Box, 536 Njoro, Kenya 4Faculty of Physical Science and Technology, Technical University of Kenya, P.O. Box 52428-00200, Nairobi, Kenya

ABSTRACT This paper reports on electrocatalytic reduction of dicofol using cyanocobalamin in micellar solutions,

prepared from sodium didodecyl sulfate (SDS) and water. Anionic surfactant media (SDS) was found to

influence the course of electrochemical reactions. A well-defined cyclic voltammmogram for the redox

reversible reactions of cyanocobalamin was observed at about -0.750 ± 0.024 V. Dicofol exhibited a single

reduction peak at -1.198±0.038 V versus SCE. Cyanocobalamin exhibited a remarkable electrocatalytic

activity towards the reduction of dicofol. The electrode processes were diffusion controlled with diffusion

coefficients of 7.32 x 10-7 cm2s-1 for dicofol and 1.823x10-8 cm2s-1 for cyanocobalamin. Upon electrocatalysis,

the reduction potential for dicofol was shifted to more positive values, exhibiting enhanced reduction current.

The enhanced rates were attributed to preconcentration step of the reactants on the electrode surface. The

mass transfer electrode process for electrocatalysis was not diffusion-controlled and the current efficiencies

decreased with scan rate as expected.

Keywords: Current efficiency, Dicofol, Electrocatalysis, Micelles and Surfactant media.


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INTRODUCTION

It is vital to the well being of man that he

needs to clean up the environment, thereby

removing toxic residues. Effective formulation of

pesticides using halide functional groups has

caused organohalides to be major pollutants, with

varying degrees of toxicity, within our environment

[1].

Accidental or deliberate release of halogenated

hydrocarbon materials into soil, watercourses and

air can exert long-term toxic effects to non-target

organisms, directly or indirectly, via the food

chain. The accumulation halogenated materials in

the environment over the years pose an urgent need

for designing methods that will eventually cause

degradation, thereby rendering them less toxic [2].

An important requirement of any feasible

detoxification procedure is that major

decomposition products be harmless to life forms.

Additionally, the procedure should be

economically feasible, should not employ difficult

to obtain materials and should not result in the

introduction of other harmful materials into the

environment. Bacterial decomposition and

chemical hydrodechlorination take place very

slowly [3].

On the other hand, direct uneconomical

electrolytic reduction of halogenated compounds

has also been previously used. It involves the

injection of electrons into an organic halide, which

leads to the fragmentation of the carbon–halogen

bond. However, this direct electrochemical

activation of carbon–halogen bonds is kinetically

slow and requires high negative electrode

potentials, which are typically between –1.3 and –

2.4 V. Such high potentials require a significant

cost in electrical power and overall energy. These

reactions are often carried out in pure, expensive,

water-free and often toxic organic solvents. The

high potentials also run the risk of interference

from reduction of water competing with

organohalides reduction, thus limiting the

usefulness of the technique for field sensing [4].

Therefore, it is against the above background

that this paper reports electrocatalysis in surfactant

media as one of the methods for the decomposition

of organohalides. It emphasizes the use of water-

based micelle solutions, over the isotropic solvents,

which mimic natural mechanism. The use of

surfactants to bring oil and water together produces

a “new” class of solubilization media. They are

specifically needed for synthesis in industries and

destruction of organohalide pollutants. This is in

line with the public health outcry for the use of

more friendly, less toxic media in the environment

[1].

Water based medium should cost less and be

less toxic than alternative organic solvents. It does

not require excess chemical reagents, and is

tolerant to water and particles found with the

pollutants. It is in this view that Couture et al.,

began an exploration of the use of surfactants

solutions for dechlorination [5].

Sodium dodecylsulfate (SDS) and

Cetyltrimethylammonium Bromide (CTAB) are

typical ionic micelle-forming surfactants [6]. The

concentration at which surfactants begin to form

micelle is known as the critical micelle

concentration (CMC). The CMC of SDS and

CTAB in pure water at 250C is 0.0084M and 1x10-3

M, respectively [7], which is the concentration at

which compartmentalization of solutes of interest

takes place.

Dicofol is used as a substrate in this study to

represent persistent organochlorine pesticides. It is

a persistent, toxic miticide used on a wide variety

of fruit, vegetable, ornamental and field crops

against red spider mite with a chemical formula

C14H9Cl5O. Its chemical name is 2,2,2-Trichloro-

1,1-bis(4-chlorophenyl)ethanol (figure 1).

Figure 1: Structural Formula of Dicofol.

In a number of studies, dicofol residues on treated

plant tissues have been shown to remain unchanged

for up to 2 years [8].

Surfactants containing hydrophobic and

hydrophilic groups can change the properties of the

electrode/solution interface and subsequently

influence the electrochemical processes of other

substances. Adsorption of surfactant aggregates on

the electrode surface might significantly facilitate

the electron transfer, enhance the peak current

significantly, change the redox potentials or charge

transfer coefficients or diffusion coefficients, as

well as alter the stability of electro-generated

intermediates or electrochemical products [9].

Rusling, et al., had previously applied

surfactant solutions to electrochemical catalysis


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[10]. A guiding aim was to enhance rates of

second-order electron transfers by creating large

local concentrations of catalyst and substrate at the

surface of the electrode.

Because of their concurrent interest in

decomposing environmental pollutants, these

researchers used dehalogenation of aryl and alkyl

halides as model reactions in surfactant media.

These non-polar compounds bind to surfactant

aggregates at the hydrophobic sites, thereby

providing excellent substrates for rate

enhancements. By the early 1990s, effective

dehalogenation of toxic organics such as PCBs and

DDT had been demonstrated and later extended to

other organic pollutants [11].

Catalytic reductions of aryl halides have been

studied in micellar systems, aimed at enhancing

reaction rates [12]. Kamau et al., [13, 14] had

earlier reported the electrolytic reduction of allyl

chloride by tris (2,2’-biphenyl) Cobalt (II) in

aqueous SDS and CTAB micelles.

Moreover, Kamau and coworkers compared

the reduction of 1,2-dibromobutane, trans-1,2

dibromo-cyclohexane and trichloroacetic acid in

bicontinuous microemulsions and in isotropic

acetonitrile-aqueous solution [15].

Rustling et al., studied and reported the

reduction of vicinal dihalides, catalyzed by

cyanocobalamin, a Co(II) corrin complex in

water/oil microemulsions. The substrates used were

ethylene dibromide (EDB), 1,2-dibromobutane

(DBB) and trans-1,2-dibromocyclohexane (t-DBC)

[7].

Kamau, et al., also compared the reduction

of 1,2-dibromobutane (DBB), trans-1,2

dibromocyclohexane (t- DBCH) and trichloroacetic

acid (TCA) mediated by Nickel and copper

Phthalocyaninetetrasulfonates (MPcTs) in a

bicontinuous microemulsions and in isotropic

acetonitrile- aqueous solutions [7, 15]. According

to these researchers and others, a great deal remains

to be understood about the fundamental and

practical aspects of electrode reactions in

microemulsions and micellar solutions [12].

Use of cyanocobalamin as an electrocatalyst

has been widely discussed as well. The mediated

electrosynthetic pathway involves the

electrochemical generation of a ‘supernucleophile’

intermediate, which in the case of cyanocobalamin,

Co(III)L, is the Co(I)L complex [16-23].

Taking into consideration the above

highlighted work, the current research work was

aimed at studying the direct electrode reduction and

catalysis of dicofol, which according to our current

knowledge has not been studied in details.

EXPERIMENTAL

Electrochemical experiments were performed

in a three-electrode glass cell, using a computer-

controlled potentiostat (Autolab PGSTAT12

electrochemical analyzer; Princeton Applied

Research (PAR) 174A) and software, General

Purpose electrochemical system (GPES).

The working electrode was pyrolitic graphite

(PG), while the counter and reference electrodes

were a platinum wire and Standard Calomel

Electrode (SCE), respectively. The working

electrode was polished using alumina slurry on soft

lapping pads prior to experiment in order to have

new working surface. In all experiments, solutions

were thoroughly purged with oxygen-free nitrogen

(BOC Gases) for about 10 minutes. Oxygen is

known to interact with Co(II) and Co(I) species.

All experiments were done at ambient temperature

(25±1°C) and the chemicals were used as received.

Cyanocobalamin was obtained from Aldrich,

dicofol from Pesticides Control Board and the rest

from Sigma Aldrich.

Aqueous solutions of 0.05M SDS was used to

prepare 1x10-4 M cyanocobalamin and 1x10-3 M

dicofol. Direct reduction potentials for the substrate

alone and the catalyst alone were studied first, prior

to investigating electrocatalytic reactions. No

supporting electrolyte was required for

electrochemical catalysis in surfactant media

experiments.

RESULTS AND DISCUSSION

Reduction of 1x10-4 M cyanocobalamin in SDS

exhibited well defined cathodic wave at -

0.750±0.024 V vs SCE but insignificant anodic

wave at low scan rates (figure 2).


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Figure 2: Cyclic voltammogram for 1x10-4 M

cyanocobalamin at Pyrolytic Graphite electrode in

SDS at a scan rate of 0.01V/s.

At low scan rates, a reverse peak was missing.

Absence of anodic peaks in the reverse scan

indicated irreversible nature of electron transfer

process. This implies that the reduced species of

cyanocobalamin could not stand slow scan rates as

it is unstable and underwent further possible

homogenous chemical reaction. However, it was

reversible at fast scan rates (figure 3). Under these

conditions the anodic peak became pronounced.

Reversibility requires that the electron transfer

kinetics be fast enough to maintain the surface

concentrations of oxidized species and reduced

species at the values required by the Nernst

equation. Hence, reversibility depends on the

relative values of electron transfer rate constant (ks)

and the rate of change of potential scan rate (v). In

addition, shift in the geometry of the coordination

sphere which is characteristic of transition metal

complexes may also explain irreversibility [24]

observed in the present case.

Anodic peak was however observed for higher

scan rates and at higher concentrations of the

catalyst (figure 3).

Figure 3: Cyclic voltammogram for 1x10-4 M

cyanocobalamin in SDS at a scan rate of 0.04 V/s

vs SCE

This suggests that at high scan rate, the process

of reduction of cyanocobalamin in SDS is quasi-

reversible. This is also confirmed by the values of

∆Ep ≠ 0.059/n and Ipa/Ipc ≠1. According to Bard

and Faulkner, if the Nernstian concentrations

cannot be maintained due to uncompensated

solution resistance and non-linear diffusion

(characteristic of slow electron transfer kinetics),

the process is said to be quasi reversible.

Dicofol in SDS exhibited one reduction

peak at at -1.198±0.038 V versus SCE. However, a

small non-diffusional wave in the cathodic scan

was observed around the reduction potential (-

0.769V vs. SCE) of cyanocobalamin ( figure 4)?.

This is believed to be due to the reduction of

surface-bound (adsorbed) cyanocobalamin. Its size

however, decreased with increase in scan rate. It is

almost absent at high scan rates. This implies that it

is non-diffusional in shape, and its magnitude was

observed to be linearly dependent on scan rate,

which is expected for surface bound chemical

species. Anodic peak is also missing in direct

reduction of dicofol. This also implies an

irreversible electrode process.


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Figure 4: Voltammogram for 1.0x10-3M dicofol in

SDS at 0.01V/s versus SCE.

Micellar solutions are able to dissolve

significant amounts of solutes of different polarities

[5], suggesting possible different behavior of

chemical species compared to a homogeneous

solvent.

We have previously reported direct reduction

of cyanocobalamin and dicofol in acetonitrile-

aqueous solution [25]. The effect of SDS on the

electrochemical behavior becomes evident by

comparing the voltammograms in

acetonitrile/water with the ones in SDS. There is a

remarkable increase in cathodic peak current (ipc)

in SDS. Also, the absence of anodic peak in the

reverse scan for cyanocobalamin at low scan rates

and presence of non-diffusional peak prior to

dicofol peak, suggests surface active phenomenon

properties of the surfactant (figures 5 and 6).

Figure 5: Cyclic Voltamogramms of 1x10-4M

cyanocobalamin in SDS (a) and in Acetonitrile-

water (b) at a scan rate of 0.01 V/s versus SCE.

Figure 6: Cyclic voltammograms of 1x10-3 M

dicofol in acetonitrile-water and in SDS at 0.01V/s

versus SCE.

Peak current enhancement occurs due to pre-

concentration step of reactants on the surface of the

electrode [12]. Current density is about how much

current is flowing across a given area. In surfactant

media the current density was 2.74±0.03 A/m2.

This was almost ten times higher than that in

acetonitrile-aqueous solution (0.335±0.12 A/M2)

[25]. The current density also depends on the

nature of the electrode, not only its structure, but

also physical parameters such as surface roughness.

Factors that change the composition of the

electrode include passivating oxides and adsorbed

species on the surface, which in turn influences the

electron transfer. The nature of the electroactive

species (the analyte) in the solution also critically

affects the exchange current densities, both the

reduced and oxidized form. Less important, but still

relevant, are the environment of the solution

including the solvent, nature of the electrolyte and

temperature [26].

The peak current enhancement increased with

increase in scan rate. This can be explained by the

size of diffusion layer and the time taken to record

the voltammogram. In slow voltage scan, the

diffusion layer grows much further from the

electrode in comparison to a fast scan rate.

Consequently, the flux to the electrode surface is

small at slow scan rate than it is at fast scan rates.

Since the current is proportional to the flux towards

the electrode, the magnitude will be lower at low

scan rates and higher at high scan rates.

Using acetonitrile-aqueous solution, we have

previously shown that cyanocobalamin exhibit

(a) (b)


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electrocatalytic activity (figure 7) towards the

reduction of dicofol [25].

Figure 7: Cyclic voltammograms of 1.0x10-4M

cyanocobalamin alone (a), 1x10-3M dicofol alone

(b) and 1x10-4M cyanocobalamin with added 1x10-

3M dicofol (c) in acetonitrile-water (1:1) at 0.01V/s

vs SCE.

Reduction of dicofol in the presence of

cyanocobalamin in SDS showed similar catalytic

activity, as that in acetonitrile-water solution.

However, there was a distinguishable lowering of

overpotential from about -1.198V to -0.750 V

(figure 8).

Figure 8: Cyclic voltammograms of 1.0x10-4M

cyanocobalamin alone (a), 1x10-3M dicofol alone

(b) and 1x10-4M cyanocobalamin with added 1x10-

3M dicofol (c) in SDS at 0.04V/s vs SCE.

The effect of SDS on electrocatalytic activity

of cyanocobalamin is clearly demonstrated in the

overlaid voltammograms of electrocatalysis in

acetonitrile-aqueous solution and electrocatalysis in

SDS (figure 9). There is more enhancement of peak

current compared to that in acetonitrile- water as

well as a slight shift in reduction potential.

Figure 9: Overlay of electrocatalysed reduction of

dicofol in (a): acetonitrile/water (1:1) and in (b)

SDS at 0.02 V/s versus SCE.

The electrocatalytic reduction of dicofol occurs

at significantly lowered overpotential in SDS

relative to reduction in organic solvent and to their

direct reduction. Micellar solution is able to

significantly facilitate the electron transfer, change

the redox potentials, diffusion coefficients and

greatly enhance the peak current, thereby providing

enhanced catalytic rates.

It is worth noting that the concentrations for

dicofol and cyanocobalamin are the same as those

used in acetonitrile/water. Hence, the peak current

enhancement and the slight shift in peak potentials

are not as a result of concentration changes. This

could be explained further by the fact that

surfactants can assemble in the bulk solution into

aggregates (vesicles, or micelles). The micellar

solution brings together the ionic and non-polar

reactants in close proximity, consequently

amplifying the analytical sensitivity. It is likely

that the catalyst and the substrate have been

encapsulated within the same region of the micelle,

thus increasing their concentration and interaction

at the surface of the electrode.

The significant improvement of peak current

together with the sharpness of the peak (figures 8

and 9) clearly demonstrate the fact that micellar

solution acts as an efficient electron transfer media

in the electrocatalytic reduction of dicofol, leading


7

to a considerable improvement in the analytical

sensitivity.

The lowering of overpotential makes

electrocatalytic reduction more thermodynamically

favourable. Further, the effect of scan rate on the

electrode reduction of both cyanocobalamin and

dicofol was investigated using cyclic voltammetry.

Correlation of peak current (iP) with square root of

sweep rate (ν1/2) resulted in linear relationship

(figure 10).

Figure 10: A plot of cathodic peak current versus

square root of scan rate for 1x10-4M

cyanocobalamin in SDS.

This fact together with figure 11 below

confirmed diffusion controlled redox processes,

with a diffusion coefficient of 1.823x10-8 cm2s-1 for

cyanocobalamine? This is slightly lower than that

in acetonitrile water [25], which could be due to

viscocity of the surfactant media.

Figure 11: Peak current dependence on scan rates

for dicofol in SDS.

Just like in the case of acetonitrile-aqueous

solution, electrocatalysis in SDS does not show a

linear relationship between peak currents and

square root of scan rate. This implies that

electrocatalyis is not diffusion controlled. The

current efficiency in SDS decreased with increase

in scan rate (figures 12 and 13), as expected [14,

15]. This is due to the decrease in the time the

catalyst and the substrate interact on the surface of

the electrode.

Figure 12: Variation of current efficiency with

scan rate in SDS.

Figure 13: Cyclic voltammograms of

electrocatalysed reduction of dicofol with

cyanocobalamin in SDS at different scan rates.

CONCLUSION

Cyanocobalamin has been found to be a

suitable catalyst for decomposition of dicofol.

Electrocatalysis is more kinetically favourable

compared to direct electrochemical activation of


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carbon–halogen bonds. Electrical energy required

to drive catalytic reduction of dicofol in SDS is

much lower than that in acetonitrile/water. This

makes electrocatalytic reduction more

thermodynamically favourable in surfactant media

than in organic solvents.

RECOMMENDATION

Electrocatalysis is a special field in

electrochemistry that has gained a special growth

after the late eighties due to the application of new

hybrid techniques. However, most of the

applications have been run for academic purposes,

but not for technical uses in the industry. Industrial

electrocatalytic processes have only been presented

in the literature from the chemical engineering

point of view. In this research, the authors

recommend that the new concepts of electro-

catalysis be made available for industrial

electrochemical processes. Emphasis should be put

on alternative methods of pest control such as

biological control, crop rotation, intergrated crop

management which establishes chemical use on a

need basis only. Organic vs Non-organic farming:

The authors of this work also recommend organic

farming that would minimize excessive exposure to

pesticide residues. Even though some organic foods

contain significantly less amounts of pesticides

than non-organically produced products, they still

contain certain amounts of residue levels that are

persistent in the environment. The methods of

organic farming prohibit the use of pesticides.

Further work is anticipated, aimed identifying fully

the products of decomposition of dicofol, following

electrocatalysis reactions.

ACKNOWLEDGEMENT

The authors acknowledge greatly the research grant

provided by DAAD.

REFERENCES

[1] Geoffrey N. Kamau and Bernard Munge, Pure

Appl. Chem., Vol. 76, No. 4, pp. 815–828

(2004).

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M. Kargin and O. G. Sinyashin, Russian

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[3] Welderufael G. Kiflom, Shem O.Wandiga, and

Geoffrey N. Kamau, Pure Appl.Chem, 73,

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[4] Abdirisak Ahmed Isse, Giacomo Berzi, Luigi

Falciola, Manuela Rossi, Patrizia R. Mussini,

Armando Gennaro, Journal of Applied

Electrochemistry 39:2217–2225 (2009).

[5] E .C. Couture, J. F. Rusling, S. Zhang, Trans I

Chem E, 70, Part B, (1992).

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81(1991).

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“Chemosphere”, 28, 961 (1994).

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[13] G.N. Kamau, T. Leipert, S.S. Shukla, J.F

Rusling, Journal of Electronalytical

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Electronalytical Chemistry, 240: 217-226

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[15] G.N. Kamau, J.F. Rusling, Langmuir 8, 1042-

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[19] J. F. Rusling, T. F. Connors and A. Owlia,

Anal. Chem., 59, 2123 (1987).

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11

STUDY OF MINERALS IN THE WATER AND SOURCE ROCKS OF

RURII SPRING IN MERU COUNTY, KENYA

G.N. Mungai1, L.W. Njenga

1, E.M. Mathu

2 and G.N. Kamau

1

1Department of Chemistry, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya. 2Department of Geological Sciences, South Eastern Kenya University, P.O. Box 170-90200, Kitui, Kenya.

ABSTRACT

This study was aimed at investigating the minerals in the water and surrounding rocks of Rurii spring which

is located in Meru County, Kenya. The spring is well known for discharging highly carbonated and salty

water for many years, but no research has been done previously with regard to this phenomenon. The

sampling was done twice during the dry and rainy seasons, that is, months of September and November 2012,

respectively. Ten samples or replicates of the mineral water, rocks and sediments were collected and analysed

in each case. The analytical methods used were AAS, XRF, UV/VIS and Titrimetry. The mineral water was

found to be very rich in free CO2 and HCO3-, with almost two to three litres of carbon dioxide per litre of

mineral water at room temperature. The CO2 most likely originates from the earth’s crust and rises to the

surface through a volcanic vent where it gets mixed with the water to form H2CO3. Sodium level was

1,043±35.0 mg/l and 954.4±20.3 mg/l, while chloride was 950.9±13.1 mg/l and 853.6±10.0 mg/l, during the dry

and rainy periods, respectively. The high NaCl content contributed to the salty taste in the water. Basically,

the water had somewhat high level of mineral ions content which in turn was responsible for the large TDS

(5,056.7±51.2 mg/l and 4,923.1±40.7 mg/l) as well as very high electrical conductivity (6,014.0±41.0 µS/cm and

5,986.0±40.0 µS/cm), in dry and rainy seasons, respectively. The overall mineral analysis of the water, rocks

and sediments revealed possibility of having dolomite, CaMg(CO3)2 and feldspar, (K,Na,Ca)Al2Si2O8

containing rocks in the studied area. The F-test showed no significant difference between the results obtained

for the dry and rainy seasons.

Keywords: carbon dioxide, earth’s crust, volcanic vent, mineral ions, dolomite and feldspar rocks

INTRODUCTION

In a geologically active environment like

Rift Valley, groundwater frequently has higher salt

content. High temperatures increase solubility of

many compounds in water, which explains the high

level of salinity. Water that comes from a natural

spring and contains minerals is called mineral water [1]. The most abundant cationic constituents in

groundwater are the more soluble alkali elements

(Na+, K+) and the alkaline earth elements (Ca2+,

Mg2+), while the most common anions are

bicarbonate (HCO3-), Chloride (Cl-) and Sulphate

(SO42-). However, other less common (trace) cations

and anions are dissolved in small quantities. The

quality of water is also greatly influenced by human

activities such as disposal of domestic, urban,

industrial and agricultural wastes [1].

CO2-rich springs have been reported from

all over the world. The occurrence of these springs is

related to major faults and volcanoes. In South

Korea, many CO2-springs are found in Mesozoic

granitoids and the surrounding rocks. The CO2-rich

water can be classified into three-chemical-water

types; Ca-HCO3 water, Ca(Na)-HCO3 water, and Na-

HCO3 water. Most of the soda waters show a high

CO2 concentration (PCO2 0.12 atm to 5.21 atm),

slightly acidic, pH (4.8-6.76) and high ion


12

concentration [2]. CO2-rich cold springs occur near the

active volcanoes at Wudalianchi, North East China.

The springs are rich in CO2, with HCO3 as the

predominant anion and have elevated contents of

total dissolved solids >1000 mg/l [3].

A study of CO2-rich (up to 3000mg/l),

mineral (up to 460 meq/l) and cold (2 0C–9 0C)

springs of the lower Engadine region in the Swiss

Alps, indicate the existence of Ca-HCO3 water, Na-

HCO3, Cl- water and NaMgHCO3, SO42- water [4]. By

the close of the 19th Century, CO2 gas was found in

free state in many of Saratoga Springs in New Yolk.

The springs discharge carbonated mineral water

along Saratoga fault which is bottled and sold

commercially [5].

The CO2 in mineral springs may be derived

from a variety of sources, including liberation of CO2

by metamorphic processes, magmatic degassing,

oxidation of organic matter, and interaction of water

with sedimentary carbonate rocks. The origin of the

CO2 gas can be determined by isotopic analysis of 13C, which indicates whether it is derived from the

mantle, biogenic activity in the soil, metamorphic

devolatilization or carbonate rocks [6].

In Kenya, CO2-rich mineral springs occur at Mount

Margaret in Kedong Valley, Lake Magadi, Esageri

near Eldama Ravine and Kireita near Uplands [7].

Free carbon dioxide is currently being mined in

Kenya at Kireita springs in Kiambu County. The

amount of CO2 mined in year 2011 was 16,275 tones

which earned the Government of Kenya Kshs 105

million in foreign exchange [8].

Rurii Spring in Meru County is

characterized by discharge of highly carbonated

water which has a mixture of bitter and salty taste. It

is consumed by the local community and is said to

have therapeutic effects such as relief for heart-burn

and other indigestion related problems. The water is

liked by livestock due to its salty taste. Carbon

dioxide is most probably discharged naturally from

the earth’s crust since the area has numerous volcanic

hills. Interaction of CO2-rich water with the rocks

containing calcium, magnesium, potassium and

sodium salts can result in enrichment of minerals in

the spring water.

MATERIALS AND METHODS

Sampling site

The Rurii spring is within Meru-Isiolo area which

lies in the South-Eastern quarter of degree sheet 36

(Kenya) and is bounded by the latitudes 0o and 0o

30’N and by longitudes 37o 30’ and 38o E. It is

approximately 35 KM East of Meru Town in Igarii

location, Tigania East Sub-County, Meru County,

Kenya [9]. The place is semi-arid and sparsely

populated. The spring is in a valley at the floor of

Nyambene range on the southern end, adjacent to

Thuguri and Panga hills. There is a marshy ground at

a short distance from the spring and sand is mined

from the nearby Mukongoro River. The exact GPS

location for Rurii spring is 0o 01’ 47.88” N, 37o 53’

22.96” E and an elevation of 2,943 ft. above sea level

(Figures 1 and 2).

Sampling procedure

The samples were collected from the study area in the

months of September and November 2012,

representing the dry and rainy seasons, respectively.

The materials sampled included mineral water,

sediments and rocks from the Rurii spring (An area

approximately 50 M2). Ten samples (replicates) of

each material were collected at random per season.

Water samples were collected straight from the

spring in thoroughly cleaned and sterilized

polypropylene bottles and carried in an ice box. The

surface rock and sediment samples were collected in

clean polythene bags at intervals of 5 metres distance

away from the spring.


13

RURII SPRING (GPS: 0o 01’ 47.88” N, 37o 53’ 22.96” E, elevation 2943 feet above sea level) Figure 1: Geological map of the Meru-isiolo area [9].


14

Figure 2: The Physical Map of Igarii sub-location showing Rurii spring [9].


15

Sample treatment

Water samples intended for AAS analysis were

filtered after sampling and then preserved

immediately to pH <2 by adding 1.5 ml concentrated

nitric acid per litre to minimize precipitation and

adsorption of cations on the container walls. The

acidified samples were stored in a refrigerator at

approximately 4 oC to prevent change in volume due

to evaporation [10]. The containers and caps used had

been thoroughly cleaned with non-ionic detergent

solution, rinsed with tap water, soaked in 50% HNO3

(v/v) for 24 hours at 70 oC, and then rinsed with de-

ionized water. The preserved water samples were

digested in order to reduce interference by organic

matter and convert metals associated with

particulates into free form that could be analyzed by

atomic absorption spectrometer (AAS). The rock and

sediment samples were dried, grinded and then

digested before being analyzed with AAS [11].

Analysis of water

Field measurements like temperature, pH and

electrical conductivity were carried out in situ. The

CO2 and various anions such as sulphate, nitrate,

nitrite, ammonia-nitrogen, total phosphorus, chloride

and fluoride were determined using the standard

methods for examination of water [10]. Digested water

samples were analysed for various metals using

atomic absorption spectrometer (VARIAN

SPECTRA A-10) after calibrating the instrument

with the respective standards [12].

Analysis of rocks and sediments

Digested rock and sediment samples were analysed to

determine the percentage of the major oxides (SiO2,

Na2O, K2O, CaO, MgO, Al2O3, Fe2O3, MnO and

TiO2), using AAS method after calibrating the

instrument with the respective standards. For

comparison purpose, samples for both rocks and

sediments were scanned with XRF instrument

(MINIPAL 2), using a current of 2 µA and a potential

of 25 keV to obtain the percentage of the major

oxides stated above [10].


Two sets of data were obtained representing the dry

and rainy seasons. Ten replicates were analyzed for

each parameter. Table 1 indicates results for the

physical and chemical analysis of the mineral water.

The tabulated literature F values for N-1=9 (95%

confidence level) is 3.18; hence, the results indicated

no significant difference between the variance of the

dry and rainy seasons.


16

Table 1: Physical and Chemical analysis of mineral water.

Parameters Dry Season* Rainy Season** F Values

PHYSICAL

Temperature (0C)

pH (pH scale)

conductivity(µS/cm)

TDS (mg/l)

CHEMICAL (mg/l)

Free carbon dioxide

Carbonate

Hydrogen Carbonate (HCO3-)

Sulphate

Nitrate

Nitrite

Ammonia-Nitrogen

Phosphorus

Chloride

Fluoride

Bromide

Sodium

Potassium

Calcium

Magnesium

Iron

Manganese

Lead

Barium

Strontium

Cadmium

Copper

Aluminium

Chromium

Zinc

20.8±0.1

7.5±0.1

6,014±41.0

5,056±51.2

931.3±2.0

16.7±0.2

5,511.4±67.2

492.5±17.7

2.8±0.3

0.0055±0.0

Not detected

115.68±1.5

950.9±13.1

0.73±0.1

0.97±0.1

1,043±35.0

121.6±2.1

124.2±1.8

73.6±0.5

0.82±0.1

0.097±0.0

<0.05

0.677±0.1

1.469±0.1

<0.002

<0.01

0.290±0.0

0.056±0.0

<0.005

19.8±0.3

7.5±0.1

5,986±40.0

4,923±40.7

1,015.0±2.9

17.1±0.2

5,632.6±64.2

420.1±25.3

2.0±0.2

0.0037±0.0

Not detected

96.42±1.7

853.6±10.0

0.67±0.1

0.59±0.1

954.4±20.3

116.7±2.2

94.2±1.6

70.4±0.3

0.49±0.1

0.075±0.0

<0.05

0.537±0.1

1.304±0.1

<0.002

<0.01

0.205±0.0

0.055±0.0

<0.005

2.2

1.0

1.0

1.6

2.1

1.0

1.0

1.4

2.2

-

-

1.3

1.7

1.0

1.0

3.0

1.1

1.1

2.8

1.5

-

-

1.0

1.0

-

-

-

-

-

*September 2012, **November 2012, < Below AAS detection limit.


17

The water was characterized by remarkably high

Total Dissolved Solids (5,056±51.2 mg/l and

4,923±40.7 mg/l, in dry and rainy seasons,

respectively) and electrical conductivity (6,014±41.0

µS/cm and 5,986±40.0 µS/cm, in dry and rainy

seasons, respectively). The high electrical

conductivity and Total Dissolved Solids (TDS) were

as a result of the excessive mineral content. The total

alkalinity of water was very high due to the presence

of large amount of bicarbonate. This was confirmed

by the huge mineral content found in the water

especially HCO3-, free CO2, Cl- and Na+. The CO2

gas possibly comes from the earth’s crust and rises

through volcanic vent to the surface where it mixes

with water to form H2CO3 [3]. Other important

minerals found in fairly large quantities were

potassium, calcium, magnesium, sulphates and total

phosphorus. The pH was slightly alkaline which was

mainly contributed by HCO3- ion.

Sodium bicarbonate and sodium chloride were

apparently the most abundant salts in the water.

These mineral salts found in the water originated

from neighbouring rocks which contained substantial

oxide percentages of calcium, sodium, magnesium,

and potassium (Tables 2). In other words, the rocks

largely comprised of bicarbonates, carbonates,

chlorides and sulphates which were the major anions

present in the water.

Dissolution of carbonate and feldspar rocks could be

the main source of Na+, K+, Ca2+, Mg2+ and HCO3- in

the water as shown in reactions 1, 2 and 3 [2].

CaCO3v + CO2 + H2O → Ca2+ + 2HCO3-

(1)

MgCO3 + CO2 + H2O → Mg2+ + 2HCO3-

(2)

(K,Na,Ca)Al2Si2O8 + H2O + 2H+ → Al2Si2O5(OH)4

+(K+,Na+,Ca2+) (3)

Table 2 represents results for rocks analysis (%) of

the major oxides which included SiO2, Na2O, K2O,

CaO, MgO, Al2O3, Fe2O3, MnO and TiO2. Loss on

ignition (LOI) was also determined. The highest three

percentages were SiO2 > Fe2O3 > Al2O3. The least was

MnO.

Table 2: AAS and XRF percentage oxide analysis of rocks.

Oxides

(%)

AAS Results XRF Results F Values

Dry season Rainy season Dry season Rainy season AAS XRF

SiO2

A12O3

CaO

MgO

Na2O

K2O

TiO2

MnO

Fe2O3

LOI

38.773±2.818

13.534±1.009

9.264±1.019

3.261±0.265

4.203±0.640

1.770±0.495

2.355±0.381

0.340±0.052

18.420±0.970

6.38±2.190

36.344±1.613

13.074±1.518

10.360±1.241

3.084±0.228

4.593±0.558

1.683±0.305

2.461±0.249

0.360±0.040

19.080±1.100

7.042±1.866

39.00±2.60

21.80±2.20

11.043±0.85

-

-

1.83±0.39

1.95±0.22

0.452±0.05

23.10±2.70

-

38.40±2.30

21.41±1.93

10.982±0.90

-

-

1.747±0.36

1.94±0.19

0.417±0.06

22.94±2.04

-

3.05 1.28

2.26 1.30

1.48 1.12

1.35 -

1.32 -

2.63 1.17

2.34 1.34

1.69 1.44

1.29 1.75

1.38 -

Total (%) 98.3±9.839 98.081±8.718 99.175±9.01 97.836±7.78 1.27 1.34

-Not analysed.


18

Table 3 indicates results for sediment analysis (%) of

the major oxides stated above and loss on ignition

(LOI). The top three percentages were SiO2 > Fe2O3 >

Al2O3. Na2O and K2O were moderately high which

can be attributed to salt deposits left behind after the

mineral water evaporates.

Table 3: AAS and XRF percentage oxide analysis of sediments.

Oxides

(%)

AAS Results XRF Results F Values

Dry season Rainy season Dry season Rainy season AAS XRF

SiO2

A12O3

CaO

MgO

Na2O

K2O

TiO2

MnO

Fe2O3

LOI

57.515±2.116

12.537±1.806

1.598±0.344

0.671±0.107

2.659±0.080

2.229±0.454

1.346±0.248

0.193±0.024

11.331±0.762

8.947±2.097

57.165±2.410

11.804±1.675

1.742±0.462

0.497±0.093

2.349±0.102

2.185±0.317

1.008±0.294

0.121±0.026

11.836±1.214

8.707±1.746

56.100±2.80

20.030±1.34

1.785±0.24

-

-

3.020±0.99

1.745±0.26

0.285±0.01

16.756±1.16

-

56.320±2.42

19.700±1.20

1.594±0.22

-

-

2.893±0.80

1.768±0.24

0.234 ±0.01

15.661±1.47

-

1.30 1.34

1.16 1.25

1.80 1.19

1.32 -

1.62 -

2.05 1.53

1.40 1.17

1.17 1.00

2.54 1.60

1.44 -

Total (%) 99.026±8.038 97.414±8.339 99.721±6.80 98.170±6.36 1.08 1.14

-Not analysed.

The comparison between the results (Tables 2) for

AAS and XRF analysis of rocks, indicate that both

analysis were in agreement to a large extent, looking

at the order of percentages from the highest to the

lowest (SiO2 > Fe2O3 > Al2O3 > CaO > Na2O > MgO

> TiO2 > K2O > MnO). Absence of Na2O and MgO

in the case of XRF analysis could have resulted in the

increase of Al2O3 and Fe2O3 due to interference. The

XRF technique was used for a general survey of most

elements, except for lighter elements like sodium and

magnesium. The total percentage was slightly below

100 since there may be other minor metal oxides that

were not accounted for. Loss on Ignition (LOI) was

higher in the sediments as compared to rocks

indicating that the former had more volatile matter.

The tabulated literature F values for N-1=9 (95%

confidence level) is 3.18; hence, the results indicated

no much difference between the variance of the dry

and rainy seasons (Tables 2 and 3).

According to the literature values, silicon, aluminium

and iron are the most abundant metals in the earth’s

crust with the following percentages, 28%, 8% and

4.6% in that order. They are followed by calcium

(3.5%), sodium (2.8%), magnesium (2.7%) and

potassium (1.84%) [13]. Thus, the results obtained did

not deviate very much from the distribution of these

elements in the earth’s crust. However, the

percentage of Fe2O3 in the rocks was more than that

of Al2O3; hence, iron minerals are more prevalent in

this area compared to aluminium minerals. TiO2 in

the rocks was also significantly high; however,

titanium species are usually insoluble in water. This

accounts for the absence of titanium metal in the

water. The average abundance of manganese in the

earth’s crust is only 1060 mg/l and that is why MnO

is quite low [10]. The percentage of Na2O, K2O and

CaO were reasonably high and this could explain

why these metals were present in the spring water


19

and sediments in large amounts especially sodium

which is more soluble (Tables 1 and 3).

CONCLUSION

From the results obtained, crucial minerals especially

carbon dioxide are available at the Rurii spring.

These minerals can be utilized commercially in the

production of mineral water, salt licks for livestock,

baking powder, pharmaceutical products, cement,

laboratory chemicals, fertilizers, carbonated drinks,

dry ice for refrigeration and fire extinguishers.

Moreover, the spring can be developed into a modern

Spa Park. Mining of such minerals can create

employment, generate additional foreign exchange

and accelerate the Country’s economic growth in

tandem with the Kenya Vision 2030.

This research should be advanced further to cover

other similar springs within the region and determine

the full extent of commercial worth of the minerals

found there. It is also necessary to analyse further for

the 13C isotope of the CO2-rich water to determine the

external source of the CO2 and know whether it is

derived from the mantle, metamorphic processes,

biogenic activity or from the surrounding carbonate

rocks.

ACKNOWLEDGEMENT

We would like to sincerely thank Edward Mwangi of

Mines and Geology Department and Mercy Muthoni

of Central Water Testing Laboratories in Nairobi, for

offering excellent additional technical assistance in

the laboratory work.

REFERENCES

1. I. P. Murigi, Groundwater quality monitoring in

Makuyu Division of Maragua District,

M.Sc. Thesis. Nairobi: University of Nairobi,

p33-40 (2004).

2. J. Chan Ho, K. Hak Jun, L. Sung Yeop,

Geothermal journal, 39, 520-534 (2005).

3. X. Mao, Y. Wang, V. C. Oleg, X. Wang, Journal

of Earth Sciences, 20 (6), 959-970 (2009).

4. W. Pierre, C. Felice, M. Emanuel, Journal of

Hydrology, 104 (1-4), 77-92 (1988).

5. S. Zink, New Yolk office of parks, recreation and

Historic preservation, Saratoga –

Capital District region, Saratoga Springs. N.Y:

Person Communication, p11-14 (1993).

6. C. D. Laughrey, Journal of environmental

sciences, 10 (3), 107-122 (2003).

7. J. Walsh, C. Bubois, Geological Survey of Kenya:

Minerals of Kenya. Nairobi: Ministry of

Mining, p17-70 (2007).

8. Kenya National Bureau of Statistics, Republic of

Kenya Statistical Abstract. Nairobi: The

Government Printer, p49 (2012).

9. P. Mason, Geology of the Meru - Isiolo Area

Report No.31. Nairobi: Mines and Geology

Department, Ministry of Mining, p1-2 (2007).

10. D. Andrew, Standard Methods for Examination

of Water and Waste Water, 21st edition.

New York: America Public Health Association

(APHA), American Water Works Association

(AWWA), Water Environment Federation

(WEF), chapter 3, p1-99 (2005).

11. D.A. Skoog, D.M. West, F.J. Holler, S.R. Crouch,

Fundamentals of analytical

chemistry, 8th edition. USA: Thomson Brooks/

Cole, p771-772, 1041-1044 (2004).

12. G. D. Christian, Analytical chemistry, 6th edition.

USA: John Willey & Sons, Inc., p52-53

(2004).

13. F. Rutley, Rutleys elements of mineralogy 27th

edition. New Delhi: CBS publisher and

Distributors, p151-170 (1988).


20


21

GREEN SYNTHESIS OF SILVER NANOPARTICLES USING

EUCALYPTUS CORYMBIA LEAVES EXTRACT AND ANTIMICROBIAL

APPLICATIONS

J.M. Sila1*

, I. Kiio4, F.B. Mwaura

2, I. Michira

1, D. Abongo

1, E. Iwuoha

3 and G.N. Kamau

1*

1Department of Chemistry, University of Nairobi, P.O Box 30197-00100, Nairobi, Kenya 2School of Biological Sciences, University of Nairobi, P.O Box 30197-00100, Nairobi, Kenya 3Sensor research laboratory Department of Chemistry, University of Western Cape, private bag Bellville, South Africa. 4School of medicine,college of health sciences,department of biochemistry,University of Nairobi p.o box 30197-00100 Nairobi,Kenya.

ABSTRACT

In this study biosynthesis of silver nanoparticles (AgNPs) using Eucalyptus corymbia and their antimicrobial

activities have been reported. This work reveals that Eucalyptus corymbia leaf extract contains a variety of

bio-molecules responsible for reduction of metal ions and stabilization of nanoparticles. These bio-molecules

are believed to contain polyphenols and water soluble heterocyclic compounds. Optimized experimental

conditions included using extraction temperature of 90˚C; plant extract pH 5.7 and silver nitrate to plant

extract ratio of 4:1. These conditions favoured the formation of higher number of nanoparticles, which were

stable within the study period. The synthesized nanoparticles were polydispersed with average mean size of

18-20 nm and were spherical in shape without significant agglomeration, as revealed from the TEM analysis.

FT-IR spectra of the plant extract revealed that functional groups OH and –C=C– are responsible for

reduction and stabilization of the nanoparticles. Anti-Microbial activity of the synthesized silver

nanoparticles were studied against gram negative bacteria Escherichia coli (E.coli) and gram positive

bacteria staphylococcus aureus. In the medium treated with silver nanoparticles, E.coli and Staphylococcus

aureus growth was inhibited, as these particles have an excellent biocidal effects and hence effective in

inhibiting bacterial growth. These nontoxic nanomaterials, which can be prepared in a simple and cost-

effective manner may be suitable for the formulation of new types of bactericidal materials.

Key words: Silver nanoparticles, Eucalyptus corymbia, Green synthesis, Escherichia coli, Staphylococcus

aureus.

INTRODUCTION

Metal nanoparticles have received significant

attention in recent years owing to their unique

properties and practical applications. They exhibit

properties that differ significantly from those of bulk

materials as a result of small particle dimension, high

surface area, quantum confinement and other effects

[1]. Metal nanoparticles size and shape dependent

properties are of interest due to wide applications as

catalyst, optical sensors, in data storage and

antibacterial properties [2]. Nanoparticles can be

synthesised through different methods; chemical,

physical and biological methods. Conventionally,

chemical synthesis has been the method of choice

because it offers faster synthetic route. However,

chemical synthesis has raised environmental concerns

because of the nature of chemicals used, such as

reducing agents (sodium borohydride), organic

solvents and non – biodegradable stabilizing agents

(sodium citrate dehydrate). These chemicals are

potentially hazardous to the environment and

biological systems [3]. Majority of the conventional

methods makes use of organic solvents because of

the hydrophobicity of the capping agents. Capping

and stabilizing agents are used to prevent aggregation

which may hinder production of small sized silver

nanoparticles [4] Due to the increasing interest in

nanoparticles synthesis and applications; there is a

need for eco-friendly approaches based on green

chemistry principles [5].


22

Green method employs principles of green chemistry

which involves exploitation of natural resources for

metal nanoparticle synthesis, which is a competent

and environmentally benign approach [6].This

involves three main steps, which must be evaluated

based on green chemistry perspectives, including

selection of solvent medium, environmentally benign

reducing agent, and non-toxic stabilisizing agents [7].

These bio–inspired methods utilize plant extracts and

micro-organisms for synthesis of nanoparticles

intracellularly or extracellularly [8]. The use of plant

in nanoparticles synthesis is more advantageous over

environmentally benign biological processes because

it eliminates elaborate process of maintaining cell

cultures.

In addition, green synthesis using plants offers a

better synthetic protocol because of the vast reserves

of plants that are easily accessible, widely distributed,

safe to handle with wide range of metabolites. Unlike

conventional methods bio-inspired methods are

economical and restrict the use of toxic chemicals

and do not require high pressure, energy and

temperatures.

The bioreduction of metal ions is done by

combinations of biomolecules found in plant extracts

(e.g. enzymes/proteins, amino acids, polysaccharides,

and vitamins) in an environmentally benign, yet

chemically complex process [9].

Depending on the origin there are three types of NPs:

natural, incidental and engineered. Natural NPs have

existed since the earth’s beginnings and still occur in

the environment, for example volcanic dusts and

mineral composites. Incidental NPs are typically

represented by engine exhaust particles, coal

combustion, or other fractions or airborne

combustion by-products [10]. Engineered

nanomaterials are defined as those nanomaterials that

are designed with specific properties and

intentionally produced via chemical or physical

processes. They are further divided into four types

[10], namely:

• Carbon-based materials, usually including

fullerenes, single walled carbon nanotubes

(SWCNT) and multi-walled carbon

nanotubes (MWCNT). Fullerenes are made

of pure carbon and represent a new carbon

allotrope discovered in 1985 (Kroto et al.,

1993).

• Metal-based materials such as quantum dots,

nanogold, nanozinc, nanoaluminum, and

nanoscale metal oxides like TiO2, ZnO and

Al2O3. Quantum dot is a closely packed

semiconductor crystal comprised of

hundreds or thousands of atoms, whose size

is in the order of a few nanometers to a few

hundred nanometers.

• Dendrimers, which are nanosized polymers

built from branched units capable of being

tailored to perform specific chemical

functions. The surface of a dendrimer has

numerous chain ends, which can be tailored

to perform specific chemical functions.

• Composites, which combine nanoparticles

with other nanoparticles or with larger, bulk-

type materials.

Silver nanoparticles (AgNps) have been proven to

have diverse importance and thus have been

extensively studied. In the recent years, there has

been an upsurge in studying AgNPs on account of

their inherent antimicrobial efficacy. Many bacteria

develop resistance to antibiotics hence the need to

develop a substitute. So far no literature has reported

any bacteria able to develop immunity against silver.

Generally the nanoparticles are designed with surface

modifications tailored to meet the needs of specific

applications they are going to be used for [9].

The exact mechanism which silver nanoparticles

employ to cause antimicrobial effect is not clearly

known. However, it has been hypothesized that silver

nanoparticles can act on microbes to cause the

microbicidal effect through various ways. In one of

the ways, silver nanoparticles are said to anchor on

the bacterial cell wall and subsequently penetrate it,

thereby causing structural changes in the cell

membrane like the permeability of the cell

membrane. This leads to formation of ‘pits’ on the

cell surface, and consequently accumulation of the

nanoparticles on the cell surface [11]. It has also been

proposed that silver nanoparticles can release silver

ions (Feng et al., 2008) and these ions can interact

with the thiol groups of many vital enzymes and

inactivate them [12] i.e., Ag+ works through

suppression of respiratory enzymes and electron

transport components which interfere with DNA

functions [13]. Silver ions are powerful

antimicrobials but are easily sequested by chloride,

phosphate and other cellular components [14]. Silver


23

nanoparticles are less susceptible to being intercepted

and therefore offer a more effective delivery

mechanism [15]. Silver ions are released from the

nanoparticles in presence of oxygen [14].

EXPERIMENTAL SECTION

Materials and reagents

100g Silver nitrate (AgNO3) crystals and 2.5 Litres of

HPLC grade Methanol, Ethanol and Diethyl Ether

were purchased from Fischer Scientific Chemicals

(United Kingdom). 50 g of oven dried AgNO3 (Sigma

Aldrich USA) was used as received for the study.

Distilled de-ionized water and Nutrient broth (Sigma-

Aldrich, USA) was obtained from the Biochemistry

laboratory at the University of Nairobi. Folin-

ciocalteus’s phenol reagent (2N), NaOH, FeCl3, and

Gallic Acid were purchased from Sigma-Aldrich

(Germany).

Extraction of polyphenols from Eucalyptus

corymbia

A leaf extract of Eucalyptus corymbia was prepared

by weighing 5g of green leaves. The leaves were

properly washed with distilled water, cut into fine

pieces and transferred to 250ml Erlenmeyer flask

containing 100ml of distilled water. The mixture was

boiled for 5 minutes before filtering using a filter

paper. The filtrate obtained was centrifuged at 15000

revolutions per minute for 10 minutes and stored at

4oC in a refrigerator for subsequent use within 7 days

after extraction.

Confirmatory test for phenolic compound in the

leaf extract

An aliquot of Folin-ciocalteus’s phenol reagent (2N)

was added to 5mLs of the leaf extract and colour

change recorded [16].

Synthesis of silver nanoparticles

1.7g of silver nitrate was dissolved in 10mL of de-

ionised water. Aqueous solution of 1mM AgNO3 was

prepared by diluting 1 ml of 1M AgNO3 in a litre of

distilled water. Different volumes of the leaf extract

were added slowly to varying amounts of aqueous

silver nitrate solution with stirring [17]. This was

repeated with 0.8mM, 0.6mM, 0.4mM and 0.2mM of

silver nitrate solution. Analysis was done on the

resulting solution.

Procedure for calculating Percent yield of silver

nanoparticles

The efficiency of the synthetic procedure in this work

was determined by calculating the percent yield of

the synthesized silver nanoparticles. 10 ml aliquot of

the mixture of plant extract and silver nitrate were

centrifuged at 15000rpm and washed with distilled

water, then dried in an oven at 60oC for 24 hours. The

nanoparticles were weighed and the mass recorded in

grams. The weight was divided by the mass of Ag+

ions in 10 ml of 1mM AgNO3. The answer above was

multiplied by 100 to get percentage yield;

Mass of Ag0

Percent yield = ----------------- x 100

Mass of Ag+

Uv-vis Spectroscopy procedure

The solution for UV-Vis analysis was prepared by

taking 1ml of silver nitrate –plant extract mixture and

diluting it ten times. UV-VIS spectra analysis was

performed using UV-VIS double beam

spectrophotometer [UV-1700 pharmaspec UV-Vis

spectrophotometer (shimadzu)] at university of

Nairobi. Scanning of the spectra was done between

200-700nm at a resolution of 1 nm using quartz

cuvette. Baseline correction was done using de-

ionized water as the blank.

FT-IR Spectroscopy Procedure

Dry powder of the sample was crushed with KBr and

the mixture pressed in a mechanical press to form a

thin and transparent pellet. The collar and the pellet

were put onto the sample holder. FTIR of plant

extract was obtained by dropping a sample between

two plates of sodium chloride (salt) and analyzed in a

liquid cell. Finally, the dried nanoparticles were

analyzed by FTIR-JAS-CO 4100 spectrophotometer

in the range 4000–400 cm-1.

Transmission Electron Microscopy Procedure

Samples for transmission electron microscopy (TEM)

analysis were prepared by drop coating biologically

synthesized silver nanoparticles solution on to

carbon-coated copper TEM grids [18].

The films on the TEM grid were allowed to stand for

2 minutes. The excess solution was removed using a

blotting paper and the grid allowed to dry under a

lamp prior to measurement. TEM images were


24

acquired with Philips Technai-FE 12 TEM

instrument, operated at an accelerating voltage of 120

kV, equipped with an Energy dispersive X-ray

(EDAX) detector (Oxford LINK-ISIS 300) for

elemental composition analysis and the EDAX

spectra was measured at an accelerating voltage of 10

Kv.

Determination of Antimicrobial Activity

Nutrient broth (Sigma, St. Louis, USA) was prepared

by adding distilled water to 3.25 gm of the powder to

make 250 ml as recommended by the manufacturer.

The medium was sterilized by autoclaving at 121o C

for 15 minutes (All American, Hillsville, USA).

Escherichia coli and Staphylococcus aureus cells

were separately inoculated and cultured overnight at

37o C. Incubation was done in a thermo-shaker

(Gallenkamp, London, England). A disk diffusion

test was carried out according to the Kirby- Bauer

disk diffusion susceptibility test protocol [19]. An

inoculum of the bacteria culture was applied

uniformly on the surface of Muller Hinton agar

(MHA) plates.

Sterile paper discs of 6mm diameter were

impregnated with 20µl nanoparticles of three

different concentrations (0.6mM, 0.8mM and

1.0mM) of nanoparticles suspended in distilled water

and placed on the plate with inoculums. A positive

control was prepared by impregnating a sterile disc of

6mm diameter with an antibiotic (Kanamycin

10mg/ml)

The plates were incubated for 15 hours at 37o C in a

research CO2 incubator ( LEEC limited, Nottingham,

United Kingdom). The plates were observed at the

end of the incubation period.

Composition of Eucalyptus corymbia

Eucalyptus corymbia leaf extract contains a variety of

bio-molecules responsible for reduction of metal ions

and stabilization of nanoparticles; among these bio-

molecules are polyphenols and water soluble

heterocyclic compounds [20], as shown in figure 1.

These compounds have been used as reducing,

capping and stabilizing agent in the synthesis of

nanoparticles such as silver, gold among others [21].

Figure 1: structure of Gallic acid and catechin.

Test for reducing capacity using Folin-ciocalteus’s

phenol reagent (2N)

When an aliquot of Folin-ciocalteus’s phenol reagent

(2N) was added to 5mLs of the leaf extract the colour

of phenol reagent changed from yellow to black.

Folin-ciocalteus’s phenol reagent (2N) also called

Gallic acid equipment method (GAE) does not only

measure phenols, but also reacts with any reducing

substance [22]. It therefore measures the total

reducing capacity of a sample. Change of its color

from yellow to black confirms the presence of

GALLIC ACID CATECHIN


25

reducing compounds in Eucalyptus corymbia leaf

extract.

RESULTS & DISCUSSION

The percentage yield of silver nanoparticles was

81.64%. The percent yield was calculated by dividing

the mass of AgNPs by the mass of Ag+ ions in 10ml

aqueous solution. The above calculated value

demonstrated that 81.6 ± 0.3 % of the silver ions

were converted to atomic state hence forming silver

nanoparticles.

Uv-vis analysis

Formation of silver nanoparticles from the plant

extract and AgNO3 was noted by visual observation,

a gradual colour change, which took less than ten

minutes from colorless solution to yellow then deep

red/brown on addition of the leaf extract of

Eucalyptus corymbia, indicating formation of AgNPs

which was further confirmed by Uv-Vis analysis

(figure 2). The observed results are in accordance

with what was reported earlier by Chandan Tamuly,

et al. [23].

The biosynthesized silver nanoparticles were found

to have absorbance peak at around 425nm as shown

in figure 1. Typically AgNPs have surface plasmons

resonance peaks with λmax values in the visible range

of 400–500 nm [24].

Figure 2: The absorbance spectra of silver nanoparticles synthesized with varying silver nitrate concentrations from

0.2 mM to 1mM at a wavelength range of 200nm to 700nm.

The appearance of the deep red/brown color was due

to collective oscillation of the conduction electrons in

resonance with the wavelength of irradiated light

[25].

Transmission Electron Microscopy and energy

dispersive spectroscopy results

The grid for the TEM analysis of Ag-nanoparticles

was prepared by placing a drop of the nanoparticles

suspension on the carbon-coated copper grid and

allowing the water to evaporate inside a vacuum

dryer. Scanning under TEM (Philips CM-10)

revealed that the average mean size of silver

nanoparticles was 18-20 nm and the particles were

spherical in shape without significant agglomeration

(figure 3a).


26

Figure 3: ( a )TEM image showing spherical silver nanoparticles and (b)An EDS spectrum showing two peaks of

elemental silver in the silver region.

Energy Dispersive X-ray Spectroscopy was used to

verify the presence of silver in the sample. Figure 3b

showed two peaks at 3.0 keV and 3.15 keV, which

are due to the elemental silver. The typical optical

absorption band peaked nearly at 3 KeV confirms

formation of metallic silver nanoparticles [26].

Fourier Transform Infra-Red (FT-IR)

spectroscopy Analysis

The FT-IR spectra of Eucalyptus corymbia leaf

extract and synthesized nanoparticles were done to

identify the possible biomolecules responsible for the

reduction of the Ag+ ions and capping of the bio-

reduced Ag-NPs. Figure 4 shows the FT-IR spectrum

of pure Eucalyptus corymbia leaf extract and bio-

synthesized AgNPs.

Figure 4: FT-IR spectra of plant extract and silver nanoparticles.

a b


27

The major absorbance bands present in the spectrum

of Eucalyptus corymbia were at 3270.82, 1634.24,

428.15 and 422.09 cm-1. The extract containing

AgNPs showed transmission peaks at 3260.7,

1634.62, 1376.62, and 1243.76 and at 425.25 cm-1.

The broad and strong bands at 3260 and 3270 cm-1

were due to bonded hydroxyl (–OH) stretch from

phenol group or alcohol group. The medium peak

centered at 1634 corresponds to –C=C– stretch from

alkenes. The peak at 1376 cm-1 and 1243cm-1 is

attributed to –C–H rocking and C–O from alkoxy

group, respectively. The functional groups mainly

OH and –C=C– are derived from heterocyclic

compounds or alkanols e.g. alkaloid, flavones and

tannins present in Eucalyptus corymbia leaf extract

and are the capping ligands of the nanoparticles [27].

The peaks at 425cm−1 suggests the presence of van

der Waals forces of interaction between oxygen

groups in alkanol structures in eucalyptus leaf extract

on the surface of Ag-NPs [28].

Therefore, the FT-IR results imply that the (–C=C)

and hydroxyl (–OH) groups of Eucalyptus corymbia

leaf extracts are mainly involved in fabrication of

AgNPs. On the other hand, additional research work

is needed to pin down the specific phenolic

compound responsible for the reduction of silver

ions.

Effect of Synthesized AgNPS on E.coli and

Staphylococus aureus

Silver has been employed most extensively since

ancient times to fight infections and control spoilage

[29]. The antibacterial activity of green synthesized

silver nanoparticles was tested on E.coli and multi-

resistant strains, specifically methicilin-resistant

Staphylococus aureus (MRSA). Clear halos were

observed for all nanoparticle concentrations used, i.e.

0.6mM, 0.8mM, 1.0mM and kanamycin 10 (mg/ml).

This is a clear indication that the growth of the two

microorganisms was inhibited by the synthesised

AgNPs. However, more tests are required to establish

the effective amount of nanoparticles and the

expected kinetics.

Figure 5: A Muller Hinton Agar (MHA) plate with Escherichia coli growth. Growth inhibition zones are indicated

by the clear halos for the three AgNps concentration and a positive control (Kanamycin 10mg/ml).


28

Figure 6: A Muller Hinton Agar plate with Staphylococus aureus growth Growth inhibition zones are indicated by

the clear halos for the three AgNps concentration and a positive control (Kanamycin 10mg/ml).

The results showed that in MHA medium treated

with silver nanoparticles, Escherichia coli and

Staphylococcus aureus growth was inhibited (figures

5 and 6). The diameters of zones of inhibition of

nanoparticles, especially those of 0.8mM and 1.0mM

concentration, compared relatively well with that of

antibiotic kanamycin, an indication of their excellent

biocidal effect.

This observation is in accordance with what was

reported earlier that silver nanoparticles can release

silver ions [30] and these ions can interact with the

thiol groups of many vital enzymes and inactivate

them [12], i.e., Ag+ works through suppression of

respiratory enzymes and electron transport

components which interfere with DNA functions

[13]. In the present study silver nanoparticles were

found to exhibit an excellent biocidal impact and

effectiveness in inhibiting bacterial growth.

CONCLUSIONS

The use of Eucalyptus corymbia leaf extract offers a

simple synthetic protocol devoid of chemicals either

as reducing, stabilizing or capping agents which is in

line with green chemistry principles. Ferric chloride

and Folin-ciocalteus’s phenol reagent tests tested

positive for presence of reducing compounds. FT-IR

spectra of the plant extract revealed that functional

groups OH and –C=C– could be the responsible

candidates for reduction and stabilization of the

nanoparticles. The particles were polydispersed with

average mean size of 18-20 nm and were spherical in

shape without significant agglomeration as revealed

from the TEM analysis. EDX spectrum revealed the

strong signal in the silver region, hence confirming

the formation of silver nanoparticles. Moreover, the

results showed that E.coli and Staphylococcus aureus

growth was inhibited on MHA plates impregnated

with known concentrations of nanoparticles. A

similar observation was made when Kanamycin

(10mg/ml) was used as a positive control. These non-

toxic nanomaterials, which can be prepared in a

simple and cost-effective manner, may be suitable for

the formulation of new types of bactericidal

materials.

ACKNOWLEDGMENTS

The authors wishes to acknowledge the National

commission for science, technology and

Innovation (NACOSTI) for funding this research

work and Department of SensorLab, university of

Western Cape (South Africa), for providing


29

laboratory facilities and key instruments needed for

the research.

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31

ADSORPTION OF ATRAZINE PESTICIDE BY SEDIMENT AND SOIL

SAMPLES: EFFECT OF EQUILIBRATION TIME ON THE FREUNDLICH

PARAMETER (n)

James K. Mbugua1*

, Antipas Kemboi1, Immaculate N. Michira

1, Vincent Madadi

1, Mark F.

Zaranyika2*

and Geoffrey N. Kamau1*

1Department of Chemistry, School of Physical Sciences, College of Biological and Physical Sciences, University of Nairobi, P.O. Box 30197,

Nairobi, Kenya, 2Department of Chemistry, University of Zimbabwe, P.O. Box MP 167, Mount Pleasant, Harare, Zimbabwe

ABSTRACT The effect of equilibration time on the Freundlich parameter n for the adsorption\desorption of atrazine

herbicide by suspended Nairobi river sediment, Kwale red soil and Limuru clay particles in an aqueous

solution was studied in terms of the Freundlich isotherm at 15, 30, 45 and 60 minutes equilibration time. Data

presented showed that for Nairobi river sediment; 1/n started low at 1.24 at 15 minutes equilibration time,

and then increased exponentially up to 1.32 at 60 minute equilibration time. For Kwale red soil, the opposite

trend was observed, with 1/n starting high at 1.31 at 15 minutes equilibration time, then dropping

exponentially down to 1.08 at 60 minute equilibration time. Kwale red soil exhibited the highest conductivity,

whereas clay had the highest amount of carbon. The amount of organic carbon and the nitrogen content of

the samples do not seem to influence the adsorption results. Possible reasons for the observed increase or

decrease in the Freundlich parameter n and effect of conductivity and organic carbon are discussed.

Key words: Adsorption, pesticide, atrazine, adsorption equilibrium constant, Freundlich isotherm.

INTRODUCTION

Atrazine (6-chloro-N-ethyl-N’-isopropyl-

1,3,5-triazine-2,4-diamine, is a selective broad

spectrum herbicide. Atrazine (Figure 1) is used to

control pre- and post-emergence broadleaf and grassy

weeds in major crops such as maize, wheat, sorghum,

and sugar cane, as well as a range of grasses, for

example, golf courses and residential loans [1].

Atrazine is widely used in conservation tillage,

designed to control soil erosion. The compound can

be found in formulations with many other pesticide

compounds. Like other herbicides, atrazine functions

by binding to the plastoquinone-binding protein,

which animals lack [2]. Plant death results from

starvation and oxidative damage, caused by

breakdown in electron transport process [3].

Figure 1: Structure of atrazine.

Atrazine has low acute oral, dermal and inhalation

toxicity, LD50-rat >1869 mg/kg, > 2000 mg/kg and >

5.8mg/L, respectively. It is non-irritating to the skin,

minimally irritating to the eyes, and is not a skin

sensitizer. It is classified under Category III for acute

oral toxicity (500 – 5000 mg/kg) and dermal toxicity

(2000 -5000 mg/kg) [1]. Related toxicity has been

given elsewhere [1, 4].

In aerobic soils, the half-life of atrazine is 13 to 261

days [5].The half life of atrazine varies greatly from

45 days [5] to 3-5 years [6] depending on the

environmental conditions. Degradation of atrazine

occurs by two pathways; the first pathway involves


32

hydrolysis of the C-Cl bond, followed by the ethyl

and isopropyl groups, catalyzed by hydrolase

enzymes. The end product of this process is cyanuria

acid. The best characterized organisms that use this

pathway are of Pseudomonas sp. strain AD [7]. The

second pathway involves de-alkylation of the amino

groups to give 2-chloro-4-hydroxy-6-amino-1, 3, 5-

triazine, the degradation of which is unknown [8].

This path also occurs in Pseudomonas species as well

as a number of bacteria [9]. Atrazine is not degraded

by sunlight on the soil surface [10]. In studies

conducted in water over ten weeks’ time, atrazine, at

low levels, was generally stable [11, 12]. In very

basic water (pH 9.0) about 65% of the atrazine was

degraded into two major metabolites after ten weeks.

The main decomposition products of atrazine are de-

ethylated atrazine (DEA), deisopropylated atrazine

(DIA), diaminochlorotriazine (DACT) and hydroxy-

atrazine (HA) [13, 14].

Atrazine has been detected in ambient air, surface

water, sediments [15] and soils [16, 17, 14].

Atrazine's residues may remain on above-ground

crops at harvest, but will dissipate over time [18].

Atrazine is a fairly persistent fungicide on plants,

depending on the rate of application. Small amounts

of one metabolite have been detected in harvested

crop [19].

Atrazine is mobile and persistent in the environment

and therefore expected to be present in surface and

ground water. This is confirmed by widespread

detection in surface and ground water. Its main route

of dissipation is microbial degradation [1]. However,

atrazine has been reported to have high binding and

low mobility in silty loam and silty clay loam soils,

and has low binding and moderate mobility in sand

[20]. As adsorption affects the rate at which

pesticides degrade in soil and sediment environments,

there is need to understand the mechanisms involved

in the adsorption of pesticides by soil and sediment

particles. In this paper we report the results of a study

of the adsorption kinetics of atrazine by Nairobi river

sediments and Kwale red soil in Kenya.

THEORETICAL

The theory behind the adsorption process has been

reported earlier by Zaranyika [21]. The characteristic

adsorption of pesticide by soils or sediments can be

described by the Freundlich empirical isotherm [22]:

Cads=k FC e

n

(1)

where KF the Freundlich constant, Cads is

concentration (mg/ml) of the pesticide adsorbed by

the soil/sediment in a colloidal solution and Ce is the

concentration of the pesticide in the solution (mg/ml)

at equilibrium [22,23]. By taking batches of known

mass of sediments (adsorbent), and mixing with

solutions of known initial concentration of pesticides,

followed by shaking and equilibration, the

concentration of the adsorbed pesticide (Cads) and that

at equilibrium (Ce) can be estimated. The Freundlich

factor KF is a constant for a given system and

therefore may be used to compare the degree of

adsorption of different solutes onto various

sediments. On the other hand, n is regarded as a

measure of adsorption non-linearity between solution

solute concentration and adsorption.

The adsorption process of pesticides on soils was

reviewed by Burchill [23]. Several factors need to be

considered in conducting adsorption studies. For

example, what is the kinetics involved, particularly

the magnitude of the adsorption and desorption rate

constants and also the energies involved. Do the latter

depict weak or strong nature of interaction between

the solute and the adsorbents? In addition, what are

the initial and equilibrium conditions and how do the

chemical composition and/or structure of both the

adsorbent and the pesticide affect the results?

In order to obtain the adsorption/desorption,

equilibrium, thermodynamic and kinetic data, there is

need to come up with a functional

adsorption/desorption equilibrium model, from which

the apparent equilibrium constant and kinetic

information can be calculated. Assuming that the

adsorption of pesticide solute by the

colloidal/sediment or both particles occurs during the

shaking period, implying when the sediment is in

suspension, then the adsorption/desorption

equilibrium can be described as follows [21, 24]:

nSXS+nX ⇔

(2)

K=[ SX n ]/[ X ]n[ S ]

(3)


33

Where X is the pesticide molecule of interest; S is

the adsorbent/substrate or adsorption site on the

sediment or colloidal particle in solution and K is

the adsorption/desorption equilibrium

constant, SXn is the particle-pesticide adsorption

complex. Since [ S ] is normally in large excess,

assumed to be unity, then equation 3 reduces to

equation 4:

[ SXn ]=K [ X ]n

(4)

Or

log [ SXn]= log K+n log [ X ]

(5).

The value of K , the equilibrium constant,

and n is the number of pesticide molecules adsorbed,

which can be obtained from the slope and intercept of

the log [ SXn] versus log [ X ] plot.

Separation of X and SXn is achieved by allowing the

mixture to settle down, then centrifuging or filtering

and collecting the supernatant aqueous suspension

consisting of the dissolved free pesticide, and any

colloidal particle adsorbed pesticide [21].

Zaranyika and Mandizha [21] suggested that

equations 4 and 5 should be modified to equations 6

and 7, respectively in order to take into account the

existence of any colloidal particle adsorbed pesticide:

[ X ]ads=nK' ( [ X ]e+[ SXn ]w )n

(6)

ln [ X ]ads

= ln (nK' )+n ln ([ X ]e+[SX

n]w)

(7)

where K' is the apparent adsorption equilibrium

constant and [ SXn]w is the concentration of the

colloidal bound fraction in suspension at settling

equilibrium. Equation 7 shows that a plot of

ln [ X ]ads versus ln ([ X ]

e+[ SX

n]w)

will not

affect the value of n, but will affect the value of

.

The aim of the present experiments was to determine

the concentrations of atrazine in dissolved and

adsorbed forms with a view to studying the behavior

of the parameter n (number of pesticide molecules

adsorbed) in the Freundilich and modified Freundlich

equations as a function of atrazine concentration and

equilibration time.

EXPERIMENTAL

Equipment, Materials and Reagents

The following materials, instruments and reagents

were used: UV-Visible spectrophotometer (Shimadzu

UV-Visible 1650 PC Shimadzu Scientific

Instruments, 7102 River wood Drive

Columbia, MD 21046 U.S.A), Analytical balance

(Fischer scientific A-160). Atomic absorption

spectrophotometer AA6300 (Shimadzu Scientific

Instruments, 7102 River wood Drive, Columbia, MD

21046 U.S.A), flame photometer and oven. Other

materials used in these experiments included

Atrazine (analytical standard 97.5% pure), Orbital

shaker, Glass bottles, Distilled water, Stop watch and

85% Acetone, sediment was collected from Nairobi

river which is about 200m from the Department of

Chemistry; University of Nairobi, Kwale Red soil

sample was obtained from Kwale, Coast County and

Clay soil sample was from Limuru, Kiambu County.

Procedure

Soil Analysis

1. Available nutrients included the following

elements P, K, Na, Ca, Mg and Mn: The oven - dried samples were extracted in a 1:5 ratio

(w/v) with a mixture of 0.1 N HCl and 0.025 N

H2SO4 [25].

Sodium (Na), calcium (Ca) and potassium (K)

elements were determined with a flame photometer,

while phosphorus (P), magnesium (Mg) and

manganese (Mn) were measured using calorimetric

methods [26].

2. Total organic carbon: Calorimetric method [27]

All organic C in the sediment and soil samples were

oxidized by acidified dichromate at 1500C for

30minutes to ensure complete oxidation. Barium

chloride was added to the cool digests. After mixing

thoroughly the digestswere allowed to stand

overnight. The concentrations of the samples were

read on the spectrophotometer at 600 nm.


34

3. Total nitrogen: Kjeldahl method [28]

Sediment and soil samples were digested with

concentrated sulphuric acid containing potassium

sulphate, selenium and copper sulphate hydrated at

approximately 3500C. Total N was determined by

distillation followed by titration with H2SO4.

4. Soil pH (1:1 soil-water)

Sediment and Soil pH was determined in a 1:1 (w/v)

sample-water suspension using a pH meter.

5. Available trace elements (Fe, Zn & Cu) were

extracted with 0.1 M HCl [27, 28].

The oven - dried samples were extracted in a 1:10

ratio (w/v) with 0.1 M HCl/water. The different

elements were determined using atomic absorption

spectrophotometer (AAS).

6. Cation Exchange Capacity (CEC) pH 7.0 and

Exchangeable Ca, Mg, K, Na. The sediment and

soil samples were leached with 1N ammonium

acetate buffered at pH 7. The leachate was analyzed

for exchangeable Ca, Mg, K and Na. The sample was

further leached with 1N KCl, and the leachate used

for the determination of the CEC. Na and K were

determined with a flame photometer, whereas Ca and

Mg were measured using (atomic absorption

spectrophotometer (AAS) CEC was determined by

distillation followed by titration with 0.01M HCl [27,

29]. Sample analysis results obtained are shown in

Table 1.

Adsorption procedure

To demonstrate the existence of the

adsorption/desorption equilibrium, 0.1g, 0.5g, 1.0g,

1.5g and 2.0g of the dried sediment were shaken

with 10ml of 2mg of atrazine aqueous solution for 60

minutes. The sediment was then allowed to settle

for 72 hours. The aqueous phase was decanted, and

then filtered through a whatman A40 filter paper, in

order to obtain concentration of atrazine in the clear

aqueous solution. [X]e + [SXn]w was determined by

UV-Visible spectrophotometer at 219 nm. The data

obtained were recorded as shown in Table 2, which

were then plotted as a function of the mass of the

sediment used (figure 1). Xads was obtained by

subtracting [X]e + [SXn]w from the initial

concentration.

To determine the values of n and nK, 0.5g of the

dried sediment was shaken with 10ml distilled water,

and then spiked at 10,20,30,40 and 50 µg/ml level of

atrazine. The samples in quadruplicate were shaken

for 15, 30, 45 and 60 minutes using an orbital shaker.

The concentration of the atrazine in the clear solution

was determined as described above. The results

obtained are shown in Table 2. Figures 3 and 4 show

the plots obtained when the natural logarithm of the

total concentration of atrazine in water, [X]e +

[SXn]w, is plotted against the concentration of atrazine

adsorbed to suspended colloidal and/or soil sample

particles, [X]ads. In figures 5 and 6 the inverse of the

slopes, n, of the regression curves in figures 3 and 4

are plotted as a function of equilibration time. An

assumption made in arriving at Figures 3 and 4, and

data in Table 3 is that the addition of sediment to the

solution does not alter the volume of the solution

appreciably.


35

Table1: Properties of the sediment used in adsorption experiment.

Profile Clay Kwale red soil Nairobi river sediment

Soil depth cm top Top Top

Soil pH-H2O (1:2.5) 5.6 5.5 7.2

Elect. Cond. mS/cm 0.17 0.52 0.18

* Carbon % 2.5 0.5 0.3

Sand % 20 78 80

Silt %

36 12 14

Clay % 44 10 6

Texture Class sl Sl Ls

Cation Exchange Capacity

me%

25.0 5.2 6.8

Calcium me% 13.1 3.1 8.9

Magnesium me% 1.7 0.9 3.1

Potassium me% 0.8 0.8 0.6

Sodium me% 0.8 1.1 0.8

Sum me% 16.4 5.8 13.4

Base % 66 100+ 100+

ESP 3.3 21.5 12.1


36

Table 2: Aqueous phase concentration of atrazine following equilibration of 0.5g of different soil samples for

different periods with water spiked with different concentrations of atrazine.

Sediment clay kwale

shaking time

(min)

spike level

(µm/ml)

[X]e

+

[SXn]w [X]ads

[X]e

+

[SXn]w

[X]ads

[X]e +

[SXn]w [X]ads

15 100 19.49 79.51 62.14 37.86 5.85 94.14

200 21.71 178.29 69.57 130.43 6.62 193.38

300 23.99 276.01 75.29 224.71 6.77 293.23

400 24.78 375.22 83.57 316.43 7.85 392.15

500 27.91 472.09 83 417 8.77 491.23

30 100 19.71 80.29 72.42 27.58 7.08 92.92

200 21.71 178.29 74.57 125.43 8.31 191.69

300 21.85 278.15 82.86 217.14 8.62 291.38

400 22.57 377.43 89.29 310.71 8.77 392.23

500 22.85 477.15 91 409 9.08 490.92

45 100 19.29 80.71 86.29 13.71 2.63 97.37

200 22.43 177.57 76.39 123.61 8.77 191.23

300 25.71 274.29 84.7 215.3 9.12 290.88

400 25.41 374.59 97.86 302.14 12.92 387.08

500 22.43 477.57 94.43 405.57 18.62 481.38

60 100 19.57 80.43 94.14 5.86 9.08 90.92

200 21.43 178.57 83.43 116.57 17.85 182.15

300 26 274 90.14 209.86 26.31 273.69

400 26.86 373.14 99.71 300.29 55.85 344.15

500 27.86 472.14 103.57 396.43 58.46 441.54


37

54321

2 0 0

1 5 0

1 0 0

5 0

0

M a s s ( g )

Se

dim

en

t [X

]e +

[S

Xn

]w (

µg

/m

l) /

[X]a

ds

s e d im e n t[X ]a d s

c la y [X ]a d s_ 1

k w a le re d [X ]a d s_ 2

S e d im e n t [X ]e + [S X n ]w (µ g /m l)

C la y [X ]e + [S X n ]w (µ g /m l)

K w a le re d [X ]e + [S Xn ]w (µ g /m l)

V a ria b le

A P l o t o f s e d im e n t[ X ] a , c l a y [ X ] a d s _ 1 , k w a le r e d [ X ] , . . .

Figure 2: Combined graph of [X]e + [SXn]w) and [X]ads versus mass of sample (sediment, Kwale red soil and clay).

4.03.53.02.52.0

6.0

5.5

5.0

4.5

ln [X]e + [SXn]w

ln [

x]a

ds

plot of ln [x]ads vs ln [X]e + [SXn]w

4.03.53.02.52.0

6.0

5.5

5.0

4.5

4.0

ln [X]e + [SXn]w

ln [

x]a

ds

Plot of ln [x]ads vs ln [X]e + [SXn]w

15min 30min

4.03.53.02.52.0

6.25

6.00

5.75

5.50

5.25

5.00

4.75

4.50

ln [X]e + [SXn]w

ln [

x]a

ds

Plot of ln [x]ads vs ln [X]e + [SXn]w

4.003.753.503.253.002.752.50

6.25

6.00

5.75

5.50

5.25

5.00

4.75

4.50

ln [X]e + [SXn]w

ln [

x]a

ds

plot of ln [x]ads vs ln [X]e + [SXn]w

45 min 60 min

Figure 3: Plots of ln [ X ]ads versus ln ([ X ]

e+[ SX

n]w)

: Adsorption of atrazine by Nairobi river sediment at

different equilibration (or shaking) times.


38

4.03.53.02.52.0

6.25

6.00

5.75

5.50

5.25

5.00

4.75

4.50

In[X]e + [SXn]w

In[X

]ad

s

S 0.162835

R-Sq 94.8%

R-Sq(adj) 93.1%

Fitted Line PlotIn[X]ads = 2.938 + 0.7642 In[X]e + [SXn]w

3.02.52.01.51.0

6.25

6.00

5.75

5.50

5.25

5.00

4.75

4.50

ln[X]e + [SXn]w)

ln[X

]ad

s

S 0.173670

R-Sq 94.6%

R-Sq(adj) 92.9%

Fitted Line Plotln[X]ads = 3.639 + 0.8638 ln[X]e + [SXn]w)

15min 30min

2.22.01.81.61.41.21.0

6.25

6.00

5.75

5.50

5.25

5.00

4.75

4.50

ln[X]e + [SXn]w)

ln[X

]ad

s

S 0.303528

R-Sq 84.0%

R-Sq(adj) 78.7%


2.252.001.751.501.251.000.750.50

6.25

6.00

5.75

5.50

5.25

5.00

4.75

4.50

ln[X]e + [SXn]w)

ln[X

]ad

s

S 0.303041

R-Sq 83.8%

R-Sq(adj) 78.4%


45min 60min

Figure 4: Plots of ln [ X ]ads versus ln ([ X ]

e+[ SX

n]w)

: Adsorption of atrazine by Kwale red soil

at different equilibration (or shaking) time.

Figure 5: Adsorption of atrazine by Nairobi river sediment (NRS): Graphs of 1/n against time.


39

Figure 6: Adsorption of atrazine by Kwale red soil (KRS): Graphs of 1/n against time.

RESULTS AND DISCUSSION When different concentrations of atrazine were

prepared in acetone, a plot of absorbance versus

concentration gave a linear calibration curve (R2 =

0.993) over the concentration range of 1 to 100 ppm.

Give this calibration curve. Figure 2 shows the results

when a 200 µg/ml atrazine solution was equilibrated

with varying amounts (0.1-2g) of sediment and

Kwale red soil. Figure 2 shows that (a) the amount of

the atrazine remaining in solution and/or suspension

decreases exponentially as the amount of sediment

increases, and (b) the amount of atrazine adsorbed by

the soil increases exponentially as the amount of

sediment increases. Check the data again and confirm

the results. This confirms the existence of an

adsorption/desorption equilibrium in the system.

It is apparent from Figure 5 that for Nairobi river

sediment, 1/n starts off low at about 1.24, then

increases logarithmically up to about 1.32. For Kwale

red soil, 1/n starts high at about 1.30, and then drops

logarithmically to about 1.088 at 60 minutes

equilibration time. Both graphs suggest that the

curves level off to a constant value with time. Similar

results were reported by Zaranyika and mandizha

[21], see figure 7, for the adsorption of amitraz by

Pote river sediment in Zimbabwe.


40

Figure 7: Adsorption of amitraz by Pote river sediment in Zimbabwe: Graphs of 1/n against time. (Data from

Zaranyika and mandizha, 1998).

According to equation 3 above, n is the number of

pesticide molecules associated with one adsorbent

site or colloidal particle. Hence the reciprocal of n

represents the number of adsorption sites or colloidal

particles associated with one atrazine molecule. In

recent articles Zaranyika and co-workers have

demonstrated that pesticides exist in four major

speciation forms in the aquatic environment [30, 31,

32]. In the water phase, pesticides exist as the free

dissolved form and colloidal-particle adsorbed form,

designated Xf and XCy, respectively, where X and C

denote pesticide molecule and colloidal particle

respectively, and y is the number of colloidal

particles in the pesticide-colloidal-particle adsorption

complex. In the sediment phase pesticides exist as the

free dissolved form (Xf) in the sediment pore water,

colloidal-particle adsorbed form (XCm), and sediment

particle adsorbed form (XSz), where m and z are the

numbers of colloidal particles and sediment particles

in the pesticide-colloidal-particle adsorption complex

and pesticide-sediment-particle adsorption complex,

respectively. The use of m for the number of

colloidal-particle adsorption complex in the sediment

phase takes cognizance of the fact that the number of

colloidal particles involved in the pesticide-colloidal-

particle adsorption complex in the water phase may

differ from that in the sediment phase, depending on

concentration and nature of colloidal particles

present.

The modified Freundlich equation as proposed

previous by Zaranyika and Mandizha [21], and as

represented by equations 6 and 7 above, does not

differentiate between colloidal and sediment

particles. It is however apparent that (SXn)w in

equations 6 and 7 can be identified with XCy, and

that Xads corresponds to the sum of XCm and XSz. If

one makes these substitutions, then equations 6 and 7

become:

([ XCm ]+[ XSz ])=nK' ([ X ]e+[ XC y ]w )n

(8)

and

ln ( [ XCm

]+[ XSz] )= ln (nK')+n ln([ X ]

e+[ XC

y]w)

(9)

Comparison of equations 7 and 9 suggests that the

value of 1/n obtained in the present experiments is in

effect the weighted mean of m and z. In terms of

equation 9, two basic equilibria are at work in the

sediment, thus:

X + mC ? XCm

(10)

X + zS ? XSz

(11)

The initial value of 1/n depends on the relative

concentrations of XCm and XSz. Depending on the


41

strength of the X-C and X-S bonds, the concentration

of the adsorption complex with the stronger bond will

increase at the expense of that with the weaker bond.

If the bond strengths differ appreciably, then the

concentration of the adsorption complex with the

strongest bonds will dominate. On the other hand, if

the bond strengths are approximately equal, then both

adsorption complexes will co-exist. In either case a

constant value of 1/n will be attained when a balance

between the two equilibria is reached. The increase or

decrease in the value of 1/n exhibited by Nairobi

river sediment and Kwale red soil respectively can be

interpreted to mean that the balance between the two

equilibria had not been reached in the equilibration

time of 60 minutes that was allowed. Several workers

have studied the adsorption of pesticides by

sediments and soils [33, 34, 12 and 34]. The

minimum equilibration time of 2 hours was reported

by [12].

The fact that n is always less than unity ( --), suggests

that the modified Freundlich equation is better

formulated in terms XCy, XCm and XSz, according to

equations 10, 11 and 12.

X + yC ? XCy

(12)

Since [C] and [S] are normally in large excess, the

respective equilibrium constants are given by

equations 13 to 15, respectively:

Kads(C )=

[ XCm

]

[ X ][C ]m=

[ XCm

]

[ X ]

(13)

Kads( S )=

[ XSz]

[ X ][ S ]z=

[ XSz]

[ X ]

(14)

Kads(C )=

[ XCy]

[ X ][C ]y=

[ XCy]

[ X ]

(15)

underscore missing in the three equations. Please

correct accordingly.Equations 8 and 9 show that the

apparent equilibrium constant K’ determined

according to equation 7 has thermodynamic

significance only in the limiting cases (a) and (b)

shown below:

(a) [ X ]e>> [ XC

y]; [ XC

m]>>[ XS

z]

(16)

(b) [ X ]e>> [ XC

y]; [ XC

m]<<[ XS

z]

(17)

Table 3: Value of [X]e, [XCy], [XCm] and [XSz] (g/mL) obtained for chlorpyrifos, pirimiphos-methyl and

fenamiphos.

Speciation form Concentration (g/mL)

Chlorpyrifos Pirimiphos-methyl Fenamiphos

[X]e 2.65 x 10-6 4.618 x 10-5 6.187 x 10-5

[XCy] 1.98 x 10-6 1.638 x 10-5 8.82 x 10-6

[X]e/[XCy] 1.34 2.82 7.01

[XSz] 9.684 x 10-4 5.694 x 10-4 5.751 x 10-5

XCm 1.969 x 10-5 1,093 x 10-4 1.917 x 10-5

[XSz]/ XCm 49.18 5.21 3

The values of [X]e, [XCy], [XCm] and [XSz] have

been estimated for a number of systems by Zaranyika

[30] as shown in Table 3. It is apparent from Table 3

that in general [X]e > [XCy] and [XSz] > XCm,

although limiting cases (a) and (b) are not completely

attained. Thus in the case of chlorpyrifos, pirimiphos-

methyl and fenamiphos, the adsorption equilibrium

constant cannot be determined on the basis of

equation 7. Thus equation 7 can only yield the

apparent equilibrium constant as long as limiting

cases (a) and (b) are not attained. As the

concentration and nature of colloidal and sediment

particles differs from sediment to sediment, the

apparent equilibrium constant may be used to

compare the degree of adsorption of different solutes

onto a specific sediment. The use of the Freundlich

adsorption constant has the advantage of being

simple. that it is simple and is not time consuming.


42

CONCLUSIONS

In the aquatic environment atrazine exists both in

solution and as colloidal-particle-pesticide and

sediment-particle-pesticide adsorption complexes.

From the foregoing discussion we conclude that the

reciprocal of the Freundlich parameter n can be

interpreted as the weighted mean of the number of

colloidal particles and number of sediment particles

associated with a single atrazine molecule in the

respective adsorption complexes. The initial value of

n (or 1/n) upon introduction of the pesticide to the

system, is determined by the concentration of

colloidal particles, as well as the concentration of the

pesticide, but will increase or decrease depending on

the adsorption bond strengths between the pesticide

and sediment particle, and between pesticide and

colloidal particle, until an equilibrium is reached

when n becomes constant, giving the expected

average value.

ACKNOWLEDGEMENTS:

The authors wish to express their sincere gratitude to

VicRes and the Inter-University Council of East

Africa for funding this research work. Moreover, the

writers wish to acknowledge the Kenya Bureau of

Standards (KEBS) for donating the atrazine

pesticide and Ministry of Roads and Transport,

Kenya Government, for availing UV-Vis instrument

facilities.

REFERENCES 1. US EPA Interim Re-registration

Eligibility Decision for Atrazine, Case

No.0062, in Pesticides Re-registration

Status/Pesticides/US EPA, US EPA,

Washington DC, 20460.

(http//www.epa.gov/oppsrrd1/REDs/atr

azine_combined_docs.pdf Accessed on

30th August 2013) (2003).

2. Appleby, Arnold P.; Müller, Franz;

Carpy, Serge "Weed Control".

Ullmann's Encyclopedia of Industrial

Chemistry.2001:235-301 (2001).

3. X. Zhang, Y. Shen, X. Yu, and X. Liu,

Ecotoxicology and Environmental

Safety 78: 276-280. (2012).

4. WHO/FAO (1996), WHO/FAO Data

Sheets on Pesticides, No. 82: Atrazine.

WHO/IPCS/DS/96.82, (1996).

5. R.C. Turner and J.S. Clark , Trans.

Comm. II & IV Int. Soc. Soil Science,

pp. 208-215 (1966).

6. D.E. Armstrong C. Chester and J.H.

Harris, “Atrazine hydrolysis in soil”

Soil Science Society of American Proc.,

31: 61-66. (1967).

7. J.L. ACERO, K. Stemmler and U, Von

Gunter: A predictive tool for drinking

water treatment, environ. Sci. technol.,

34, 591-597 (2000).

8. Y. Zeng C.L. Sweeney, S. Stephens,

and P. Kotharu, Atrazine Pathway

Map. Wackett LP. Biodegredation

Database 2004 (2004).

9. D. Warncke, and J.R. Brown, Potassium

and other basic cations. pp. 31-33

(1982).

10. L.J. Krutz, D.L. Shaner, C. Accinelli,

R.M. Zablotowicz and W.B. Henry,

Journal of Environmental Quality 37

(3): 848–857 (2008).

11. A.K. Salama, A.A. Al-Mihannaand, and

M.Y. Abdalla, . Journal of the King

Saud University of Agricultural Science

11(1): 25-32 (1999).

12. B.K. Singh, A. Walker and D.J. Wright,

Soil Biology and Biochemistry 38(9):

2682-2693 (2006).

13. B.K. Singh, A. Walker, J.A.W. Morgan,

and D.J. Wright, Applied Environmental

Micobiology 69(12): 7035-7043;

Applied Environmental Microbiology

69(9): 5198-5206 (2003).

14. W.E. Pereira, and C.E Rostad,

Environ.sci technol.,24,1400-1406

(1990).

15. Ackerman and Frank ,International

Journal of Occupational and

Environmental Health 13: (4): 437–445

(2007).

16. D.W. Koplin, S.J. Kalkhoff, D.A.

Goolsby, D.A. Sneck-Fahrer, and E.M.


43

Thurman,., Ground Water, 35, .679-

688. (1995).

17. S.M.C.W. Miller J.V. Sweet, Depinto,

and K.C. Hornbuckle,

Environ.sci.technol.34 55-61 (2002).

18. A. Mehlich, Determination of P, Ca,

Mg, K, Na, and NH4. North Carolina

Soil Test Division (Mimeo 1953); 23-89

(1953).

19. L.P. Wackett, M.J. Sadowsky, B.

Martinez, N. Shapir, Applied

Microbiology and Biotechnology 58

(1), 39–45 (2002).

20. J. Koprivnikar, M.R. Forbes, R.L.

Baker, Environmental Toxicology and

Chemistry: 26 (10), 2166–70 (2007).

21. M.F. Zaranyika, and N.T. Mandizha,

Journal of Environmental Science and

Health B33 (3), 235-251 (1998).

22. R.J. Hance, Weed Res. 5, 108-114,

(1965)

23. S, Burchill D.J. Greenland, and M.H.B.

Hayes, Adsorption of organic

molecules, in the chemistry of soil

processes, Greenland D.J. ND Hayes

M.H.B., EDS., Wiley and sons, NY,

(1981).

24. J. Graham-Bryce, Behavior of

pesticides in soils; the chemistry of soil

processes, Greenland and Hayes, NY

(1981).

25. T.W. Jones, W.M. Kemp, J.C.

Stevenson and J.C Means, J. Environ.,

Qual.,11,632-638 (1982).

26. In J.R. Brown (ed.), Recommended

Chemical Soil Test Procedures for the

North Central Region. (Revised.)

Missouri Agr. Exp. Sta. SB1001.

Columbia, 25-96 (2007)

27. E.A. Gislason, N.C. Craig, J. Chem.

Thermodynamics 37, 954-966 (2005).

28. Jan-Åke Persson, Mårten Wennerholm,

Stephen O’Halloran, Handbook for

Kjeldahl Digestion:11- 42 (2008).

29. Carroll andDorothy, Geological Society

of America Bulletin 70 (6): 749-780

(1959).

30. M.F. Zaranyika, M. Jovani, and J. Jiri,

South African Journal of Chemistry 63,

227-232 (2010).

31. M.F. Zaranyika and M.G. Nyandoro,

Journal of Agriculture and Food

Chemistry 41(5), 838-842 (1993).

32. M. F. Zaranyika and J. Mlilo, South

African Journal of Chemistry 14(1),1-9

(2012).

33. M.F. Zaranyika and S. Nyoni, Int. J.

Res. Chem. Environ. 3, 26-35, (2013).

34. B.T. Bowman, W.W. Sans Soil Sci.

Soc. Am. J., 41, 574-579 (1977).


44


45

THE BRACHISTOCHRONE PROBLEM AND STELLAR COLLAPSE

N. M. Monyonko Physics Department, University of Nairobi, P.O.BOX 30197-00100, NAIROBI, Kenya.

ABSTRACT

A model of a fully collapsing star to a black hole is discussed. The properties of the static completely

collapsed star especially in the direct neighborhood of its surface area considered reveal thermodynamic

and quantum theoretic features. Furthermore, the brachistochrone classical gravitation theory and the

quantum mechanical decay (weak) interaction theory show interesting parallels. The interior metric

solution of a collapsing star is found to be transformable to the exterior metric solution which implies that

a collapsing star could be interpreted as the counterpart of the large-scale expanding universe model.

INTRODUCTION

The shortest time variational problem under the

influence of gravity is related to stellar collapse.It

is well known that stellar demise results in

contraction of the carbon core to some highly

compressed state,the gravitational force dominating

the hydrostatic pressure, separating the star’s

enevelope from the core. In the case of very

massive stars,this gravitational force is so great and

rapid that that the collapse is complete and the

density of compressed mass tends to infinity

resulting in a black hole[1]Examples may include

Cygnus X-1,a strong source of X-rays in the

constellation Cygnus, a compact body of about ten

solar masses, of size less than 300km across. Any

particle approaching closer than this boundary of

the region of no escape that surrounds the black

hole usually termed the one way membrane or

horizon will be trapped .Matter falling into a black

hole is crushed to a dense point at the centre.

According to quantum theory, an empty space

consists of particle-antiparticle pairs correlated to

each other .Stephen Hawking at the University of

Cambridge had shown that quantum effects cause

black holes to runatemperature.Correlations

between the emitted particles contain information

about everything that falls into the black hole the

hole evaporates.This information is never

destroyed.It is recoverable and it is

random,accordingtoJuanMaldacena(1998).Any

three-dimensional region of the universe can be

described by information encorded on its two-

dimennsional boundary.The universe is a

projection of information on aboundary.An

information Paradox develops here.Black holes

swallow mass and grow according to the principle

of equivalence in general relativity.The Hawking

quantum theory stipulates that black holes lose

mass and evaporate. AhmedAmheiri, Donald

Marolf, Joseph Polchinnski and James

Sully(2013)reveal that this sharp conflict between

quantum theory and general relativity is an

important clue to their unification. Donald Marolf

(2009) showed that every model of quantum

gravity will obey the same rules, whether or not it

is built from string theory. Gauge-Gravity duality

continues to provide insights and strong evidence

that all information is carried away by the

Hawking radiation[ 2].

We will consider the dynamics of the collapse and

the properties of a static completely collapsed star

in the neighbourhood of the horizon. The Einstein

free field equations are nonlinear and therefore

difficult to solve. By imposing symmetry

conditions as constraints dictated by physical

arguments on the line element of the metric, the

equations simplify. In the comoving coordinate

system a natural separation of space and time is

realized. Spherical symmetry requires the proper

time interval to depend only on the rational

invariants[3].

In 1963,Roy Patrick Kerr discovered a two-

parameter family of solutions which describe the

space-time around the black hole horizon. The two

parameters are mass and angular momentum of

black hole [4]. Karl Schwarzchild in 1915 found a

static solution with zero angular momentum.[5]

In section one, we derive the geodesics in the

Schwarzchild space-time.In section two, we

compare the collapse with brachistochrone problem

and conclude the analysis in section three before

the references.’

1. The Geodesics In The Schwarzschild Space-

Time


46

Consider the geodesics in the Schwarzschild space-

time with aid of the Hamilton formalism.

It is possible to derive the geodesics equation of a

metric with the line element 2ds given by: .

ji

ji dxdxgds =2 (1.1)

Where ijg is the metric tensor.

With aid of the Euler-Lagrange formalism where

we take as our Lagrangian L

ττ d

dx

d

dxgL

ji

ji2

1= (1.2)

τd is the affine parameter along the geodesic.

Choosing the value of the Hamiltonian H in the

form

LH

LLL

Lrr

r

m

rt

r

m

Lpprptp

tqqLpqtpqH

rt

f

k

kkkkkk

=⇔

=−=

−−−−

−−=

−++−=

−=∑=

2

])sin(2

1)

21[(

)(

),,(),,(

222222

2

1

φθθ

φθ φθ

&&&

&

&&&&

&&

From equations (1.1)and (1.2) the Lagrangian L has

the property

dsd

ce

constd

ds

d

dx

d

dxgL

ji

ij

∝

=

==

τ

τττsin

.2

1

2

12

And dsd ∝τ is a parameter which also could be

identified as the proper time.

The Langrangian for the Schwarzschild solution

can be written as

])sin(

/21)

21[(

2

1

22222

22

φθθ &&

&&

rr

rm

rt

r

mL

−−

+−

−−= (1.3)

Letting πθ2

1= when 0=θ& with 0=θ&& and θ

remaining constant in our Lagrangian (1.3) for a

choice of parameter τd giving us

1

0

22 == dsL

giving a value of +1 or zero.Hence

2

2

222

/21/212 ds

r

l

rm

r

rm

EL =−

−−

−=

&

(1.4)

where

ds2> 0 (time – like geodesics)

ds2 = 0 (null geodesics)

In the following discussion we will deal with time-

like and null geodesies separately. Furthermore we

are going to restrict us to radial geodesics.

Especially we would like to see , what will happen

for r → 2m, which imply that we assume that, the

"radius" r of our mass body will be smaller than 2m

otherwise our discussion would not be valid,

because we would have to use the interior solution

for r → 2m).

Time-Like Geodesics[10,11,12]

We solve equation (1.4) for the time-like

geodesics (ds2>0).

+

−−=

2

22

2

12

1r

l

r

mE

d

dr

τ) (1.5)

If we write Hamilton’s equations for a value of

πθ2

1= in the following way

lconstd

drp ===− .2

τφ

φ

So that

2r

l

d

d=

τφ

then we can express equation (1.4) with aid of the

chain rule in terms of φ

4

4

2

22

22

)]1)(21([l

r

r

l

rmE

d

d

d

dr

d

dr+−−=

=

φτ

τφ

= mrrrl

m

l

rE 22)1( 23

22

42 +−+− (1.6)


47

For any particular geodesics we can rotate the axes

of reference in a way so that πθ2

1= is possible

because our problem is completely spherically

systematic.

If we are introducing the coordinate transformation

drudrrduru 221 −=−=⇔= −− (1.7)

Then equation (1. 7) can be replaced by

]224

)1[( 2

322

24

22

mrrrl

m

l

rEu

d

dr

dr

du

d

du

+−+−=

=

φφ

2

2

2

23 122

l

Eu

l

mumu

−−+−= (1.8)

Once we have determined the solution for this

differential equation we can also express u as a

function of r and t.

we restrict ourself only to radial geodesics

( ).0=⇒=⇒ lconstφ

Substituting (l= 0) in (1.5) yields

)1(2 2

2

Er

m

d

dr−−=

τ

rm

E

ddt

/21−=

τ ( 1.9)

For an observer at infinity,the coordinate time

equals the proper time.

We investigate a particle which is at a distance r, at

rest and which will be attracted by the gravitational

force and fall towards the center. It’s first

derivative 0==τd

drr& ,for irr = and we can

write with (1.9)

21

2

E

mri −= (1.10)

The particle will move towards the central body

and is at irr = at rest, hence ir must be the

maximal distance from the origin ( maxrri = ), so

we can introduce the following convenient variable

substitution for r .

)cos1(2

1

2

1cos2 ηη +== ii rrr

with πη ≤≤0 (1.11)

We like to calculate the value for η when the

particle reaches )( Hrr =η the coordinate

mrr H 2== (we set).

r= Hr = ⇒−

=== HHE

mmrr η

2

1cos

1

22 2

2

HH

EE ηη 2

1cos1

2

1cos

1

11 22

2−⇔

−=

EE

E

HH

H

arcsin22

1sin

2

1sin11 22

=⇒=

⇔

−=−⇔

ηη

η

So we can summarize with the obvious values

within r = ri and r = 0

0=η irrfor =→ i

m2=η Erfor arcsin2=→

πη = 0=→ rfor

(1.12)

With (1.11) and (1.10) we can write equation (1.9)

as follows

)1(

2

1cos1/2

2

)1(2

2

22

2

2

E

Em

m

Er

m

d

dr

−−−

=

−−=

η

τ

ηη

η2

1tan)1(

2

1cos

cos1)1( 22

2

212

2EE −=

−−=

(1.13)

and


48

and

)1(2

1cos

2

1cos

2

1cos

1

22

12

1

22

2

2

2

E

E

E

m

mE

r

m

E

ddt

−−=

−

−=

−=

η

η

η

τ

with

HH

H

E

E

ηη

η

222 cos2

1sin11

2

1sin

=−=−

⇒=

⇒

HHE ηη2

1cos

2

1sin11 222 =−=−

we finally write

H

E

d

dt

ηη

η

τ2

1cos

2

1cos

2

1cos

22

2

−= (1.14)

According to (1.11) we have for the derivative of r

withrespect

toη

)2

1cos()

2

1sin()

2

1cos( 2 ηηη

ηηii rr

d

d

ddr −==

(1.15)

and taking the square root of (1.13) leads to

η

ηη

2

1tan

2

2

1tan)1( 2

r

m

Ed

dr

−=

−−=

(1.16)

Where we have chosen the negative prefix for the

square root, because the particle is falling freely

towards the origin.

With equation (1.16), (1.15) and with aid of the

chain rule we are able now to express the

derivation of the parameter r (which is proportional

to the proper time) as a function of our new

coordinate η .

( )ηη

ηηη

η

ητ

ητ

cos122

1cos

2

2

1cos

2

1sin(

2

1sin

2

1cos

2

32

3

+==

−=

==

m

r

m

r

rm

r

d

dr

drd

d

d

ii

ii

(1.17

Latter equation can easily be integrated to yield

( )ηη

ηητ

sin2

)cos1(2

3

23

+=

+= ∫

m

r

dm

r

i

i

(1.18)

To evaluate τ for the values for mrr H 2==

and r = 0 we substitute the corresponding η values

(see 1.12) in above equation which gives

)sin(2

3

HHi

Hm

rηητ +=

and

m

ri

2

3

0 πτ = ( 1.19)

We can see with equation (1.19) that, our particle

will reach the singularity at Hrr = and at r=0

according to his own clock in a finite time,

furthermore it can be seen that an observer

travelling with the particle wouldn't observe

something special when he would pass Hrr =

We investigate now how a resting observer at r

→ ∞ (according to (1.15) his proper time τd dr

would be equal to the coordinate time dt ) would

see the free falling particle towards the origin of the

spherically symmetric body. Therefore we make

use of the chain rule and equation (1.14/1.1again


49

H

i

m

rE

d

d

d

dt

d

dt

η

η

ητ

τη2

1cos

2

1cos

2 2

43

== (1.20)

ηηη

ηd

rEt

H

i

2

1cos

2

1cos

2

1cos

2 22

43

−∫=

To solve above integral we make use of an integral

table and obtain

finally

ηη

ηη

ηηηη

2

1tan

2

1tan

2

1tan

2

1tan

log2

])1()sin(2

1[

2)( 2

3

−

++

+−++=

H

H

i

m

Er

t

1.21)

We see that the second term of our solution for t

has a. singularity at Hηη = so that

H

t

ηηη

→

∞→)(lim

So for our observer at inifinity, it seemed to be that

the free falling particle would reach the coordinate

r = 2m in an infinite time in sharp contrast to

(1.19). which says that the particle takes a finite

proper time to reach the coordinate r = 2m.

We have found out that it is impossible for an

observer who is beyond the coordinate r = rH to

observe anything what is behind this border.

Therefore we call the surrounding area at Hrr =

the event, horizon.[9]

It shall be emphasized here that the value r = 2m

for the event horizon is valid for every kind of

external observer.

1.2 Null Geodesies[14]

In case of a null geodesics (ds = 0) we can write for

equation (1.5)

( ) 02

12

222

1

=−−

−−

r

lrE

r

m&

2

2

22

)2

1( Er

m

r

l

d

dr=−+

⇔τ

(1.22)

From Hamilton’s equations, we have

2r

l

d

d=

τφ

r

md

dt

21

1

−=

τ

(1.23)

Analogous to the previous section we introduce the

coordinate substitution u = r-1and write for equation

(1.33) with aid of (1.34) and the chain

rule.

2

23

21

2D

umud

du+−=

φ

where E

lD = (1.24)

In the following we will restrict us to radial

geodesies ( 0=⇒ l ). In this case the equations

(1.22) and (1.23) reduces to the following relevant

equations.

Ed

dr±=

τand

r

m

E

dr

dt

21−

= (1.25)

The term Ed

dr±=

τ can easily be integrated

which yields the solution

±+±= .constEr τ (1.25a)

For an infalling particle we have to choose the

negative sign for E and thus it can be seen that as

was in the case for time-like geodesics that the null

geodesics crosses the event horizon in a. finite

proper time and will also reach the origin in a finite

proper time.


50

Again we are going to see how it would look like

for an observer at rest placed at infinity. Therefore

we use the chain rule and equation (1.25) and get

−±==r

m

dt

d

d

dr

dt

dr 21

ττ

(1.26)

This ordinary differential equation can be solved by

separation of the variables

±+

−+±=−

∫±= constm

rmr

r

m

drt ]1

2log2[

21

(1.27)

We have found an analogous solution to the time-

like geodesic motion. Our null geodesies will take,

an infinite2 coordinate time3 to reach the event

horizon at Hrr =

We have seen in the last two sections that a particle

or a light-ray which falls radially to a spherically

symmetric body with a radius smaller than its

Schwarzchild radius (i.e. mr 2< ) cannot be seen

at the event horizon or beyond it! It follows that

such a spherical body would be just black for r <

2m.We call such a body a Black Hole.

1.3 Black Holes and Thermodynamics

Within the framework of general relativity we

found as a solution f0r a spherically symmetric

body-- the Schwarzschild metric.

Furthermore we derived the radially geodesies due

to such a Schwarzschild body, where we have

considered in particular a spherical body with

radius smaller than its so called Schwarzschild

radius (r <2mG/c2), which was called a black hole,

because it is not possible for any external observer

to look beyond the Schwarzschild radius, where the

red-shift becomes infinite.

In this section we try to connect some aspects of

thermodynamics with the relativistic object of a

black hole. Therefore we start with some properties

of a black hole.

In our discussion about the radial geodesies of a

Schwarzschild hole, we saw, that their properties

are completely determined by the value of their

mass. Indeed it was shown by

Hawking,S.W&Ellis,G.F.R(1994)[15],Norman

Gurlebeck(2015)[16],Wei xu, Jia Wang&Xin he

Meng(2015)[17] and Don N.Page(2005)[18]. that

the most general Black Hole is completely

determined by its mass, its angular momentum and

its electric charge, only',that is. the hole could have

been composed of matter or antimatter, there is also

the possibility that it could consist of gravitational

waves, only (which is indeed possible according to

Einstein's relation concerning energy and mass –(

E= mc2).

Furthermore, once a particle has fallen into a black

hole, then nearly all its information is lost (except

of its mass m, angular momentum L and electric

charge Q. which affects the property of the black

hole).

That a black hole is completely determined by the

values Lm, and Q is usually referred as No-Hair

theorem, which was paraphrased by Wheeler and

proved among others by Stephen Hawking.

Now, let us discuss some consequences of the "No-

Hair" theorem.

According to the second law of thermodynamics

,the entropy of the universe is always increasing.

Now, let us assume that, a package with an

"amount of entropy" is dropped into a black hole.

An external observer would not be sure if the

amount of entropy in the universe would have

increased or decreased, because he would never be

able to tell what is happening inside the black hole

(see discussion about geodesies and also about the

gravitational collapse).

Indeed, if quantum effects are neglected, the

number of configurations would be infinite, since

the black hole could have been formed by the

collapse of a cloud of indefinitely large number of

particles of indefinitely low mass.The field –

theoretic creation and annihilation contradicts the

principle of equivalence.

According to the statistical interpretation of the

entropy, given by Boltzmann, we have the relation

Ω= logkS (1.28)

Where S is the entropy, k : is the so called

Boltzmann constant and Ω the number of possible

configurations in the system.


51

From our discussion above and equation (1.28), the

black hole would have an infinite entropy, because

an infinite amount of particle would imply an

infinite value of configurations of the system.

We show now, that the entropy of a black hole

must be finite, if we make some rough quantum

mechanical estimations.

According to Heisenberg's Uncertainty Principle

we have

hpq ≥∆∆ (1.29)

We know that one’s a particle was captured by a

black hole, it can never escape from it, hem e its

radial position is located with an uncertainty of the

radius Hr of the black hole, hence

2

2

c

mGrq H==∆ (1.30)

where m is the mass of the black hole, c is the

speed of light and G the gravitational constant.

Substitution of (1.30) in (1.29) yields

mG

hcp

2

2

≥∆

So, the following relation must hold for the

momentum

mG

hcp

2

2

≥∆ (1.31)

Furthermore, we know from quantum mechanics

that every particle can be described as wave with

the wavelength.

p

h=λ (1.32)

and the energy

pchc

hEparticle ===λ

ν (1.33)

We get finally with (1.33) and (1.31)

mG

hcpcE particle

2

3

≥= (1.34)

So that we. get as a restriction of the whole

amount; of particles N(m) in a black hole.

mG

hc

mc

pc

mc

E

EmN

Particle

BlackHole

2

)(3

22

≤==

(1.35)

PW

hb

L

r

cG

cGmmN =≤⇔

2

2

/

/2)(

h

where2/2 cGmrbh = is the radius of the black

hole and 2/ cGhLPW = the so called Planck-

Wheeler length, which represents according to

Wheeler the smallest scale at which space time can

be regarded as a smooth manifold.

Because we do not know anything about the

consistence of the black hole, we consider always

the maximal possible number of particles in the

system, which is

PW

bh

pw LL

cmGNmN

τ===

22

max

)/2()( (1.

36)

According to (1.36) the maximum number of

particles is proportional the surface area A of the

black hole.

Now, if we assume that every particle (or photon,

graviton, etc.) has a finite number of intrinsic

quantum states s, then the number of possible

configuration, would be )(mNs Hence, we get with

the Boltzmann interpretation of entropy (1.28)

AsmkNskS mN ∝== log)(log )( (1.37)

Hence, we get as a solution that the entropy of a

black hole must be proportional to its surface area,

so we can write

Sbh = αkA (1.38)

Where α is a constant and A the surface area of the

black hole.


52

Now, let us assume that two Schwarzschild black

holes with mass M1 and M2 would collide with

each other, so for the surface A12 of the combined

black hole we get

21

2

2

2

12

21214

2

2214

2

12

)(16

)2(16

)(16

AAMMG

MMMMc

G

MMc

GA

+=+≥

++=

+=

((

2112 AAA +≥

⇔ (1.39)

With (1.38) we can equivalently write

⇔

bhbhbh SSS 2112 +≥

which is the second law of thermodynamics.

At this juncture, we shall mention without proof

that relation (1.39) for the surface of black hole

also holds for the general type of black holes, the

Kerr holes, and is usually referred as Hawking’s

area theorem[12-17].

To remove our paradox about loss of entropy in the

universe, which was stated in the beginning, we

introduce the

Generalized Second Law of Thermodynamics:

that

The sum of the black hole entropy

(PROPORTIONAL surface area) and the

ordinary thermal entropy outside black holes

cannot decrease.

With (1.37) and (1.36)we can write

hc

GkmmkNSbh 2

2

)( ==

⇒ )(2 2

4mcd

hc

kGdSbh =

dEdST bhbh =⇒ with

kGm

hcTbh

2

4

=

(1.40)

For the general Kerr hole we state that (1.40) turns

to

dLdQdEdST bhbh Ω++== φ (1.41)

Where φ is conventionally defined electric

potential, dQ is the change of the electric charge,

Ω is the rotational angular frequency and dL is

the change of the angular momentum.

Hence dQφ is the work done on the hole by

adding the charge dQ , dLΩ is the work done by

addition of angular momentum dL and

)( 2mcddE = is the corresponding change in the

hole’s energy.

If we compare (1.41) with the classical thermo

dynamical relation

PdVTdSdE −= (1.42)

Where T T = temperature, S = entropy, P =

pressure and V = volume of the system, we could

identify bhT in (1.40) and (1.41) as temperature of

a black hole.

Suppose, a black hole would have a finite, non-zero

temperature in a classical sense, which is

proportional to the inverse of the mass of a black

hole. It would behave like a Planck black radiator.

We have found out that it is impossible for any

particle (or photon) to escape from the sin face of

the black hole, then it seems to be that a thermo

dynamical interpretation of the differentials (1.

40/1.41) will not be consistent with general

relativity.

Surprisingly it was discovered by the English

physicist Stephen Hawking, that black holes indeed

radiate' like a black body radiator and that they

have a temperature other than zero, therefore

Quantum Field Theory has to be considered, which


53

leads to the assumption that the theory of general

relativity also has to extended, So as to consider the

quantum field properties of both particles and

fields.

2.0 Gravitational Collapse

We now discuss a model of a collapsing star. We

just consider the simplest case in which a

spherically symmetric "dust" cloud does not

interact with itself and where the pressure is

negligibly small.

We introduce the Gaussian-/Comoving coordinates

for a free falling dust cloud whose metric can be

written as[25]

)sin)(,(),( 222222 φθθ ddtrVdrtrUdtds +−−= (2.1)

For a perfect fluid we have the choice for the

energy-momentum tensor

ki

ik UUT ρ= (

2.2)

),( trρ is here the proper energy density and Ui

the velocity four vector. In the comoving

coordinate system Ui is given by

U0 = 1 U1= U2 = U3 = 0 (2.3)

According to (2.2) we have the conservation law

0; =i

ijT (2.4)

Equations (2.2) and (2.4) are automatically

satisfied (momentum conservation) for j=1,2,3.

For the energy conservation we have

)2

(0 0;0V

V

U

U

ttT

i

i

i

i

&&

++∂∂

=Γ+∂∂

== ρρ

ρρ

which also can be written as

( ) 0=∂∂

UVtρ

(2.5)

For Einstein's equation we can write with (2.2)

)2

1(8

)2

1(8

ikki

j

jikikik

gUUG

TgTGR

−−=

−−=

ρπ

π

(2.6)

With (2.1) and (2.3) we get

We simplify the problem of solving the above

differential equations. Out of this we assume that

the proper mass/energy density is independent of

its position ( )(),( ttr ρρ = ). Therefore we search

for a separable solution .

)()(),( 2 rftRtrU = )(),(),( rgtrStrV = (2.7)

.

Substitution of (2.12) in (2.11) yields

02

'

2

'

2

=−−′

UV

VU

V

VV

V

V &&&

(2.8)

We finaly

obtain

)]sin(1

)[( 2222

2

2222 φθθ ddr

kr

drtRdtds ++

−−=

(2.20)

We see that the derived metric (2.9) is of the same

form as the Robertson-Walker metric which is

spatially homogenous and isotropic[26].

According, to the conservation of energy (see 2.5)

we have

0)),(),()(( =∂∂

trUtrVttρ

mconsttRt ==)()( 3ρ (2.9)

Where m can be intepreted as a mass equivalent.

This will suddenly be clear if we consider that all

the dust particles are in free fall (hence no particle

will travel away), furthermore we know from

Birkhoff’s theorem that the metric of a. spherically

Symmetric body can be transformed in such a

way,that the metric becomes the static


54

Schwarzschild metric[27,-34], hence there is no

way that energy (mass) can be radiated away in

form of gravitational waves. The energy which is

radiated away in form of electro-magnet waves can

be neglected.

According to (2.9) we have

)0()0()()( 33 RmtRmt −− =⇔= ρρ (2.10)

With the transformation )0(

~

R

rr = and setting

)0(/)()(~

RtRtR =

we get by dropping the tilde.

1)0( =R (2.11)

So we can write for (2.10) with(2.11)

mmR == − )0()0( 3ρ (2.12)

⇒ )()0()()( 33 tRtmRt −− == ρρ (2.13)

With (2.7) we get for (2.8)

mconsttRt ==)()( 3ρ

+++=−22

22

22

2 2

2

2

2

2)(4

rR

rR

fR

fRR

fR

fRtG

&&&&

ρπ

+ 44

422

24

22

22

2

2

4

4

242

rR

rRR

fR

fRR

rR

RR &&&&

−−

RRtRtG &&3)()(4 2 =− ρπ (2.14)

By using (2.13) then above equation can be written

as follows

RRtRG

&&=− − )()0(3

4 1ρπ

(2.15)

By substitutions we can write

)()0(3

8)( 12 tR

GktR −+−= ρ

π& (2.16)

Let us assume now that our spherically symmetric

body is at rest at t=0 (in standard coordinates), so

we get beside R(0) = 1 as an additional condition

0)0( =R& (2.17)

By substituting t = 0 in (2.29) we obtain

)0(3

8ρ

πGk = (2.18)

Hence we can write for (2.16)

]1)([)( 12 −= − tRktR (2.19)

To determine R(t) in the abover equation we

separate variables

variables

dRR

Rdtk

R

dRdtk

−=⇔

−=

−

1

11

(2.20)

Upper integral can be solved parametrically. The

solution is given as follows

kt

2

sinηη += where )cos1(

2

1η+=R ) (2.21)

For πη = we have 0)( == πηR = with the

corresponding proper time

)0(8

3

222

sin

ρπππππ

GkktT ==

+== (

2.22)

Hence our fluid sphere with pressure is at rest and

has a finite radius R(0),compared to a "sphere"

without radius at a finite time T (RT) = 0).

Note:

Because we have calculated in the comoving

coordinate system, t is automatically proportional

to the proper time.

We've shown so far that our sphere will collapse

for a. commoving observatory in a finite time T to

a. "pointlike sphere" with radius zero. The question

is now how an external observer will experience

the collapse of the sphere.

We try to answer this question with aid of the

Birkhoff's theorem, which is a powerful tool for

describing an external gravitational field of a

spherically symmetric body.

We have shown above that, it is always possible to

find a coordinate transformation, such that, the

metric outside a spherically symmetric body takes

the form of the Schwarzschild solution.


55

)sin(~

~)~2

1(~)2

1(

2222

2122

φθθ ddr

rdr

mGtd

r

mGds

+−

+−−−= −

(2.23)

As a reminder we write again the interior solution

(2.19) for the collapsing star

)sin)((1

)( 22222

2

2222 φθθ ddtRr

kr

drtRdtds +−

−−=

(2.24)

With (2.23) and 2.24) we have derived the exterior

and the interior solution of a collapsing star.

Unfortunately the coordinate systems used in (2.23)

and (2.24) are not the same, so that we are forced to

match them together.

We assume that the metric in space is continuously

determined, thus we expect the interior- and

exterior solution to become equal on the surface (r

= rs = const) of the collapsing star.

Fortunately we did not transform during the whole

derivation of the interior solution, the angular part

of the metric, so that we have

θθ~

= φφ~

= (2.25)

Substituting (2.38) in (2.23) and in (2.24), setting

r,t = const ⇒ ŕ,ť = const ⇒ dr, dr,dt = 0 and

considering that ds is an invariant, we get the

following metric form of (2.23) and (2.24) on the

star surface at r = rs

)sin)(( 222222 φθθ ddtRrds s +=

rtRrs~)( =⇒ at srr =

)sin(~ 22222 φθθ ddrds += (2.26)

By the discussion of the geodesic line section

(2.1/2.2) we found out that

constEr

Gm

ds

td==− )~

21(

~ (2.27)

Furthermore, we have for our commoving

coordinates that.

1=ds

dt (2.28)

Multiplying the inverse of (2.28) with (2.27) and

application of the chain rule, yields

constEr

Gm

dt

td==

− ~2

1~

(2.29)

Differentiating (2.23) with respect to t yields

212 )~

()~2

1(2

1~

)(dt

rd

r

Gm

r

Gm

dt

td

dt

ds −−−

−=

(2.30)

Substituting (2.28) and (2.29) in (2.30) yields

12 = 211

22~

~2

1~2

11

−−

−=−−

dt

rd

r

Gm

r

GmE

−−=

⇔r

GmE

dt

rd~

21

~2

2

(2.31)

With the matching condition rsR(t)= ŕ at the star

surface with r = rs equation(2.31) can be written as

−−=

=

=r

GmE

dt

tdRr

dt

rds

21

)(~2

22

2

)(

2132

22

tRr

Gm

r

E

dt

dR

ss

+−

=

(2.32)

According to (2.19) we have

)1)(( 1

2

−=

− tRkdt

dR (2.33)

Setting (2.32) and (2.33) gives us


56

ktR

k

r

E

tRr

Gm

ss

−=−

+)(

1

)(

2

2

2

3 (2.34)

Because (2.34) is valid for all t and R(t) is the only

occurring function depended on t, then by

comparison of the coefficients we get.

kr

E

s

−=−2

2 1⇔

22 1 skrE −= ( 2.35)

and krGmkr

Gms

s

3

32

2=⇔= (2.36)

Substitutions (2.35) and making m the subject of

the formula leads us to familiar relation.

)0(3

4 3ρπ

srm = (2.36)

With (2.22) we have determined the required factor

for connecting td~

and dt on the surface area.

According to (2.29) we can write

2

2

22 21~

dtr

GmEtd

−

−= (2.37)

Now, we check if with aid of the matching

conditions refered in (2.44) and (2.31), the exterior

solution (2.23) transforms to the metric of the

interior solution 2.24) for

srr =

The interior solution (2.24) gives us for the surface

area (r = rs, ,dr = 0) the following metric

)sin)(( 2222222 φθθ ddtRrdtds s +−= (

(2.38)

With y = rsR(t), θ = θ and φ = φ (see 2.26. the

angular part of the exterior solution (2.33) does

obviously match to (2.38), so that we only have to

consider the case where ,θ ,φ = const ⇒ dθ =

dφ = 0. Hence, it has to be shown that

2

1

22 ~~

21~2

1 rdr

Gmtd

r

Gmdt

−

−−

−= (2.3

9)

According to equation (2.32) we can write for the

differential 2222 2

1~ dtr

GmdtErd

−−=

(2.40)

Substituting (2.37) and (2.40) in the right hand side

of (2.39) gives us

221

222

212

~)~2

1)(~2

1(

)~2

1)(~2

1(

~)~2

1(~)~2

1(

dttdr

Gm

r

Gm

dtEr

Gm

r

Gm

rdr

Gmtd

r

Gm

=−−+

+−−=

=−−−

−

−

−

2122 ~)~2

1(~)2

1( rdr

Gmtd

r

Gmdt −−−−=⇔

Hence, our matching conditions fit.

We finally investigate how an external observer

experiences the collapse of the star. Consider radial

signals emitted from the star surface. For our

external observer we have to use the exterior

solution (2.23) of the collapsing star.

Suppose, the signal leaves the star surface at a time

)(~~11 tttt == . At this time the radial coordinate

of the surface area is given by ).( 11 tRrr s= The

signal shall reach the external observer, who is

placed at the radial coordinate 2~~ rr = , at the time

2~~tt = .

If consider only radial signals (dθ = dφ = 0),

which travel on null geodesies (⇒ ds = 0) then we

have with (2.23)

] 2

1

2

1

2

1

)]14

~log(4~[

/21

~1~~~

~

~12

~

~

r

r

r

r

t

t

Gm

rGmr

rGm

rdtttd

−+=

−=−= ∫∫

2

1

~~12 )]1

4

~log(4~~~ r

rGm

rGmrtt −+=−

(2.41)


57

Hence, for ∞→−⇔→ 121~~2~ ttGmr i.e. for

an external observer it seems to be that collapsing

will never reach a state where it has a radius equals

the Schwarzschild-radius (it reaches this status for

.∞→t )

Furthermore, the red-shift of the emitted signal,

become as bigger as the radius of the star tends to

the Schwarzschild radius. For Gmr 2~1 → the red-

shift becomes infinity, so that an external observer

is not able anymore, to observe anything, which is

emitted from the stars surface, hence, the star has

become a so called Black Bole.

It shall be emphasized, that according to the own

watch of the star, it will pass the event horizon at r

= 2Gm in a finite time (see equation 2.21). So, it is

possible to travel inside of a. black hole, but once

one is inside he will not have a chance to escape

out of the black hole.

2.1 The Brachistochrone Problem and Collapse

We discuss the following problem

Let A and B be two points, say A = (0,0) and B =

(x1,y1), connected by a smooth wire.

We shall now consider a ring without, friction and

without initial velocity which slides down the wire.

The question is now: What must the form of wire

be if the ring takes the shortest possible time to

reach B?

The corresponding integral to above problem can

be written in the, general form

dtI ∫= (2.42)

The time element dt can be expressed by the arc

length ds divided by the particle velocity v

v

dsdt = (2.43)

The arc length ds has according to Pythagoras the

form 222 dydxds += ⇒ 22 dydxds += ,

whereas the particle velocity can be computed with

aid of energy conservation.

E = Epot + Ekin = const = 0 (say) ⇔ Epot = - Ekin

⇔

2

2

1~ mvymg =⇔

⇒ gyygv 2~2 =−=

yy ~−= (2.44)

Substitution in (2.44) yields

gy

dydx

v

dsdt

2

22 +== (2.45)

Consider y to be a parametrized function of x ,

then we can write (2.45) as

dxgy

ydt

2

1 ′+= ( 2.46)

With (2.46) the integral (2.42) can be written as

follows

∫∫ =′+

=∫=11

002

1xx

Ldxdxgy

ydtI (2.47)

To get the an extremal value of (2.47), we take its

variation

LdxI ∫= δδ (2.48)

We see that L is not explicitly dependent on t,

thus by virtue of Euler-Lagrange equation, we have

gAconstL

y

Ly

2

1==−

′∂∂′ (2.49)

gAgy

y

gy

y

yy

2

1

2

1

2

1=

′+−

′+′∂

∂′⇔ ’

dyyA

ydx

y

yAy

−=⇔

−=′ (2.50)

Latter integral can be solved parametrically The

corresponding solution is

)sin(2

1ηη +−= Ax where

2cos2 η

Ay =

(2.51)

If we compare the solution (2.51) of the

Brachistochrone problem with the solution (2.34)

of the earlier discussed collapsing star, then we see,

that both of the solutions are mathematically

identical.


58

If we now consider that in both cases the

gravitational force plays a governing role, then it is

interesting to investigate more about the

similarities between the classical Brachistochrone

problem and the relativistic collapse of a

star.Heavy massive particle elements are subject to

weak(decay) interaction force .

3.CONCLUSIONS

By the treatment of the thermodynamic properties

of a black hole, we have recognized, that the

general theory of relativity in it’s classical form is

not sufficient to describe the properties of a black

hole, so that it has to be extended to it’s quantum

theory.

Secondly, a radiating black hole would show us the

deep connection between thermodynamics,

quantum mechanics and general relativity, which

leads us to the conclusion that a great unifying

theory can indeed exist, so that it is worthy

searching for.

Thirdly,we have found out that the solution to the

equation for a collapsing star and the solution of

the Brachistochrone problem are mathematically

identical.Under consideration that the gravitational

collapse and the Brachistochrone problem are

issues that are directly related to weak nuclear

decay and gravitation, respectively, then we come

to the conclusion that a further treatment of this

problem would show us other interesting parallels.

Lastly, we saw that, the interior solution for the

interior metric of a collapsing star is identical with

the "exterior" metric due to a large-scale model of

an universe, so that an expanding universe could be

interpreted as the counterpart of a collapsing star.

ACKNOWLEDGEMENT

We thank members of Physics Department,

University of Nairobi for useful discussions.

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y,J.:Journ.High Energy Physics

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9. Marolf,D.:Phys.Rev.D79,044010(2009)

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59

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1975)

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442(1981)

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Quantum Mechanics-(Lectures given at

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60


61

ADSORPTION CHARACTERISTICS OF CAPTAFOL PESTICIDE BY

SEDIMENT AND SOIL SAMPLES: APPARENT THERMODYNAMIC

PROPERTIES USING SPECTROSCOPIC METHODS

Antipas K. Kemboi, James K. Mbugua, Vincent O. Madadi, Peterson M. Guto and Geoffrey

N. Kamau

Department of chemistry, university of Nairobi, P.O Box 30197-00100 Nairobi

ABSTRACT

This study was aimed at adsorption of captafol by red soils and the sediments, by varying the initial

concentration of the adsorbate, shaking time and weight of adsorbent. The sediment and the red soil used

were analyzed for pH, texture, cation exchange capacity and organic carbon content. The adsorption was

determined by measuring concentrations of the pesticide using UV-Vis-NIR spectrophotometer before

and after the attainment of equilibrium. Freundlich and Langmuir adsorption isotherms were used to

establish adsorption behaviour of the pesticide at equilibrium conditions. The relationship between

sediments and soil characteristics and thermodynamic properties was explored following Gibbs free

energy expressions. Captafol was found to absorb radiation at 442 nm. A calibration for captafol

exhibited a linear relationship for concentration range from 0.2 to 40 ppm, and slight deviation as the

concentration increased to 100 ppm. This was in accordance with the Beer’s law. Freundlich isotherm

fitted well for most of the data. Adsorption rate for captafol by red soil and sediment was found to be

0.035 mg/min and 0.0245 mg/min, respectively. Thermodynamics parameters demonstrated that

adsorption process was exothermic and spontaneous. Gibbs energy (ΔG), apparent equilibrium constant

(K’) and number of adsorption sites (n) were some of the thermodynamic properties investigated. The

calculated values for K’ were 57.34±4.6 and 58.16±4.7, ΔG: -9.98±0.19 (kj/mol) and -10.05±0.21 (kj/mol),

n: 1.08±0.03 and 1.10±0.01 for the sediment and red soil, respectively.

Key words: Captafol, adsorption, equilibrium constant, pesticide

INTRODUCTION

The use of pesticides is increasing all over the world on

daily basis as food demands increase due to ever

increasing population. It is worth noting that when

pesticides are applied to the field, it is only a small

portion which reaches its target while the remaining

major part is released into the environment. There is

risk of the pesticides finding their way into human food

chain. This may lead to problems, such as leaching,

toxicity to non-target organisms and accumulation.

Pollution of the soil, ground and surface waters involve

risk to the environment as well as to human health due

to the possibility of direct or indirect exposures [1].

The behaviour and the fate of these pesticides in the

soil environment are governed by various factors,

which include retention, transportation and

transformation processes. Although retention includes

all the processes that limit movement of pesticides in

soils, the primary means of retention is adsorption of

pesticides in soil constituents.

Captafol is a broad-spectrum protective contact

fungicide [2]. It is very effective in control of almost all

fungicidal diseases of plants except powdery mildews.

It is widely used outside the U.S.A to control foliage

and fruit disease on citrus, apples, cranberry, tomato,

coffee, potato, pineapple, onion, peanut, stone fruit,

blueberry, cucumber, prune, watermelon, wheat, sweet

corn, barley, oilseed rape, strawberry and leek. It is a

general use sulfanimide pesticide of the isoindole

family of pesticides (figure 1). The overall aim of the

current study is to establish the adsorption

characteristics of captafol in selected soil and sediment.


62

Figure 1: Structure of Captafol: 3a,4,7,7a-

tetrahydoisoindole-1,3-dione;1,1,2,2-tetrachloro-1-

methylsulfanyl-ethane.

MATERIALS AND METHOD

Soil sampling

The red soil used in this study was collected from Kwale

County while the sediment was collected from Ngong

River in Nairobi. The collected soil samples were stored

in plastic bags during the road transport. Soil pH was

determined by using a direct reading type pH meter with

glass electrode and calomel reference electrode. The soils

were sieved through IS (International Standard) sieve

No.10 (2 mm aperture as per IS 2720 (part 4), 1987). The

fraction passing through the sieve was collected and

preserved in air tight plastic containers for further studies.

Captafol standard

A stock of 100 ppm solution of captafol was prepared by

transferring exactly 0.2875 mL of (0.350 g/mL) solution

of captafol into a 100ml volumetric flask. The solution

was diluted to the volumetric mark with Acetonitrile:

water solution (70: 30 % v/v).

Kinetic study

The adsorption kinetic study was carried out in batch

mode using 10 ml viols with 0.5 g of appropriate

soil/sediment with a solid: solution mass ratio of (1:20)

and 10 ml of 100 ppm of technical captafol solution.

Sorbent masses were accurate to ± 0.001g and solution

volumes to ± 0.5 ml. The studies were conducted in

triplicate for all samples on an orbital shaker (Fischer

scientific A-160) at 150 revolutions per minute (rpm) for

a period of 24 h at room temperature (25 ± 2 °C). From

the triplicate flasks, 5 ml of sample was collected at time

intervals of 0.5, 1, 2, 3, 8 and 24 h. The collected samples

were further filtered and analysed by the UV-Visible-NIR

spectrophotometer.

Equilibrium study

Adsorption equilibrium studies were conducted for all

soils with an adsorbent quantity of 5 g with captafol

concentrations of 50, 60, 70, 80, 90 and 100 ppm in

identical viols containing 10 ml of distilled water. A

blank was maintained to determine the effect of captafol

adsorption on the viols. After the addition of soil samples,

the mixtures were agitated in an orbital shaker at 150 rpm

for 3 h (estimated equilibrium time) at 25 ± 2 oC. After 3

h, 5 mL of sample was collected from each viol, the

collected samples were filtered and analyzed using UV-

Visible-NIR Spectrophotometer.

Data analysis

The data obtained was analyzed by Freundlich and

Langmuir adsorption models [3]. The Langmuir model is

presented as x/m = qmaxbqe / 1+bqe where, x is the amount

of solute adsorbed (mg or moles), m is weight of

adsorbent (mg, g), qe is equilibrium concentration of the

solute, qmax is amount of solute adsorbed per unit weight

of adsorbent required for monolayer coverage of the

surface (maximum capacity) and b is a constant related to

the heat of adsorption.

Freundlich expression is given as follows: Cads=KfCe1/n

where Kf is the Freundlich constant, Cads is

concentration(mg/ml) of the pesticide adsorbed by the

sediment/soils in a colloidal solution and Ce is the

concentration of the pesticide in the solution (mg/ml) at

equilibrium [3]

In order to obtain the adsorption/desorption, equilibrium,

thermodynamic and kinetic data, there is the need to

come up with a functional adsorption/desorption

equilibrium model from which the apparent equilibrium

constant and kinetic information can be calculated.

Zaranyika and Mandizha [4] modified the above equation

and came up with the following expression: [X]ads= nK’

([X]e + [SXn]w)n, where X is the pesticide molecule of

interest, S is adsorbent/substrate, K’ is the apparent

adsorption equilibrium constant and [SXn]w is the

concentration of the colloidal bound fraction in

suspension at settling equilibrium. On taking the natural

logarithm the equation above yields a linear expression

given as:

ln[X]ads=ln (nK’)+n ln([X]e +[SXn]w)n.


Calibration curve


63

Standard solutions of captafol: 1, 2, 4, 6, 8, 10, 20, 40,

60, 80 and 100 ppm were prepared by serial dilutions

from the 100 ppm standard stock solution of captafol

into 5 ml volumetric flasks and completing the volumes

to the mark with ethanol: water solution (70:30% v/v).

The absorbance was measured at 420 nm [5] against a

blank solution.

A linear relationship was obtained by plotting the

absorbance against the concentration of captafol, within

the range of 0-100 ppm. From the calibration curve

below, the detection limit was found to be 0.001 ppm.

The calculated molar absorptivity for captafol was

0.006709 L mol-1cm-1.

Figure 2: Calibration curve for absorbance versus concentration of captafol.

Extent of equilibration time

Equilibrium study was carried out for different

concentrations of captafol (50, 60, 70, 80, 90

and 100mg/l) in 5 grams of Kwale red soil. It

was clear from the experimental result that as

the concentration of the captafol solution

increased, the amount adsorbed also increased.

Equilibrium was attained within 3 hours

(figure 3). Hence this shaking time was found

to be appropriate for optimum adsorption and

was used in all subsequent experiments. The

experimental results of adsorption of captafol

on both the sediment and red soil at various

initial concentrations as a function of contact

shaking time tend to level off after some time

(figure 3). Moreover, the data revealed that the

percent adsorption increases with the increase

in initial pesticide concentration as the actual

amount of pesticide adsorbed per unit mass of

adsorbent increased with increases in captafol

concentration. This implies that the adsorption

is dependent on the initial concentration of the

pesticide. This is because at lower

concentration the ratio of the initial number of

captafol molecules to the available surface

area is low. However, at high concentration

the available sites of adsorption becomes


64

fewer, and hence the decrease in the rate of adsorption.

Figure 3: Initial amount of captafol (50, 60, 70, 80, 90, and 100 mg/l) versus equilibration time.

Table 1: Measured values of the selected parameters of the red soil and sediments samples.

Profile Red soil Ngong river sediment

Soil depth cm Top Top

Soil pH-H2O (1:2.5) 5.5 7.2

Elect. Cond. mS/cm 0.52 0.18

* Carbon % 5 3

Sand % 78 80

Silt % 12 14

Clay % 10 6

Texture Class Sl Ls

Cat. Exch. Cap. me% 5.2 6.8

Calcium me% 3.1 8.9

Magnesium me% 0.9 3.1

Potassium me% 0.8 0.6

Sodium me% 1.1 0.8

Sum me% 5.8 13.4

Base % 100+ 100+

ESP (Exchangeable Sodium Percentage) 21.5 12.1


65

Effect of organic matter

Sediment and red soil exhibited different values for the

measured parameters (table 1). According to

Abdelhafid et al., and Cox et al., organic matter content

in the soils play very important roles in determination

of the extent to which adsorption/desorption takes

place, as well as the biodegradation by the

microorganism [6, 7]. From the results obtained in the

current research work, both the sediment and the red

soil contained some organic matter (table 1). The

organic matter (OM) content in the red soil which was

slightly higher than the sediment probably influenced

the migration of captafol to it, as reported earlier by

Berglofet al., and Yu et al.,[8, 9]. Generally, the affinity

between pesticide molecules and soil particles is

dependent on soil properties like organic matter and

properties of the pesticide. Although a great proportion

of pesticide molecules are adsorbed by soils high in

organic matter content and/or high clay content [10],

the differences in OM for the two types of samples was

not much (table 1).

Kinetic study

In this study, adsorption kinetics exhibited an immediate

adsorption and attained pseudo adsorption equilibrium

within a period of three hours for both the red soil and the

sediment. After pseudo equilibrium, there was minimal

difference of captafol concentration in the adsorbate even

after 24 hours observation (figure 4).

Figure 4: Percentage adsorption of captafol versus equilibration time.

These results compares favorably with what was reported

previously by Beck and Jones [11]. They found out in

their study that the sorption of atrazine and isoproturon

herbicides were adsorbed from the solution in the first

hour of the 24 h sorption experiments. A rapid initial

adsorption of captafol is a surface phenomenon. The

hydrophobic nature of captafol resulted to the rapid filling

of the empty adsorption sites during the initial steps

which followed a linear variation. This was followed by a

slow migration and diffusion of the compound. This led

to a drastic decrease in adsorption rate into the organic

matter matrix and mineral structure, similar to what was

reported there earlier by Gao et al., [12]. Similarly,

Parkpian et al. and Mathava et al. [13, 14] observed this

trend in the study of endosulfan on lowland and upland

soils.

It is evident from the results that the adsorption of

captafol is fast during the initial stages and the portion of

pesticide taking part in the long term behavior is

insignificant as compared to those participating in the

preliminary phase of rapid adsorption. The kinetic

rate estimated by Lagergren pseudo first order model

1898 [15] is given by the equation:,

Log (qe-qt) = log qe - k.t/2.303,

While the second order equation is given by

Ho`s pseudo second order model [16]

t/qt = 1/k2qe2 + t/ qe

Where qe is the amount of adsorbate adsorbed at

equilibrium; qt is the amount of adsorbate adsorbed on

the surface of the sorbent at any time; k is the rate

constant of sorption and t is the time. Table 2 below

shows the data for pseudo second order rate constants.

The adsorption rate was found to follow pseudo second

order rate with the sediment adsorbing at 0.0245 mg/min

and red soil at 0.035 mg/min. The slightly high values for

the red soil may be attributed to the higher organic matter

in red soil than in sediment samples.


66

Table 2: Data for pseudo second order rate constants.

Time (h) Qe (mg/g) for red soil Qe (mg/g) for sediment

0 0 0

0.5 0.5 0.5

1 0.85 0.7

1.5 1.2 1

2 1.4 1.2

2.5 1.5 1.3

3 1.6 1.4

Figure 5: Concentration of captafol in the adsorbate.

Equilibration Study

The behavior of captafol adsorbed was studied at room

temperature with equilibration time ranging from 30

minutes to 3 hours. The Freundlich isotherms were used.

Freundlich coefficients were calculated as shown in Table

3 below. The calculated coefficients exhibit variation

with increasing equilibration time.


67

Table 3: Calculated Freundlich coefficients for sediments.

Sediment Equilibration

time (min)

n K’ G r2

30 1.04 49.56 -9.67 0.956

60 1.09 58.18 -10.07 0.969

120 1.1 60.39 -10.16 0.971

180 1.1 61.22 -10.03 0.971

Average 1.08±0.03 57.34±4.6 -9.98±0.19

The calculated values of Freundlich coefficients for red

soil are shown in Table 4. The calculated number of

adsorption sites (n) remained relatively constant with

variation of equilibration time, as expected, while the

Gibbs free energy (G) and the apparent equilibrium

constant (K’) increased slightly with the increasing

equilibration time. The above trend for sediments was

also observed in the case of red soil as adsorbent (table

4).

Table 4: Calculated Freundlich coefficients for the Kwale red soil.

Red soil Equilibration

time (min)

n K’ G r2

30 1.08 50.2 -9.7 0.978

60 1.11 60.13 -10.15 0.969

120 1.104 62.25 -10.24 0.974

180 1.11 60.06 -10.12 0.961

average 1.10±0.01 58.16±4.7 -10.05±0.21


68

Tables 3 and 4 demonstrate that the adsorption data for

the red soil was higher than that of the sediments,

which is attributed to higher organic matter and clay

observed in red soil, compared to sediments. The

negative value of Gibbs free energy in all cases

suggests that the adsorption process is

thermodynamically favorable.

The trend observed in this research work is in line with

what was reported earlier by Torrents et al., [17], who

conducted the sorption study of non-ionic pesticides

and found that the intensity of sorption was a function

of herbicide and clay content.

CONCLUSION

Organic matter content of soil has significant influence

on the adsorption of captafol. Soil with high organic

matter content has better pesticide’s adsorption ability.

Red soil had higher organic matter content and

exhibited enhanced captafol adsorption capacity than

the sediment. The increase in initial concentration also

led to increased adsorption capacity. The results from

the present study would help in designing of effective

fungicide management strategies, aimed at protecting

non target materials. The calculated n had a value close

to one, as expected, but the slightly higher value than

one suggested extent of deviation from ideal situation,

brought about by random experimental errors.

ACKNOWLEDGEMENT

The authors highly appreciate the funding support from

Vicres-Inter University Council of East Africa.

REFERENCES

1. Bajeer, M.A., Nizamani, S.M., Sherazi, H.,

and Bhanger, M.I., American Journal of

Analytical Chemistry, 3: 604-611 (2012).

2. Captafol: US patent 3,178,447 (1965).

3. B.T. Bowman and W. W. Sans, Soil Sci. Soc.,

Am. J. 41:514-519 (1977).

4. M.F. Zaranyika and T.N. Mandizha,.J.

Environ. Sci health B-pestic 01, 33(3):235-251

(1998).

5. Balbir C. Verma, Devender K. Sharma, Hari

K. Thakur, Bh. Gopal Rao and Narendra K.

Sharma, Analyst 116, 867-870 (1991).

6. R. Abdelhafid, S. Houot and E. Barriuso, Soil

Biology and Biochemistry 32, 389-401 (2000).

7. L. Cox, A. Cecchi, R. Celis, M. C. Hermosín,

W. C. Koskinen and J. Cornejo, Soil Sci. Soc.

Am.J. 65, 1688-1695 (2001).

8. T. Berglof, T.V. Dung, H. Kylin and I.

Nilsson, I. Chemosphere, 48, 267–273

(2002).

9. Zhou Yu, Y., Q.-X. , Chemosphere 58 (6),

811–816 (2005).

10. F. Hugpienberger, J. Letey, Jr. and W. J.

Farmer. Adsorption and mobility of pesticides

in soil. Calif. Agric. 27:8- 10 (1973).

11. A.J. Beck, A.E.J. Johnston and K.C. Jones,

Critical Rev. Environ. Sci. Technol. 23: 219-

248 (1996).

12. J.P. Gao, J Maguhn, P. Spitzauer and A.

Kettrup, Water Res. 32, 1662–1672 (1998a).

13. P. Parkpian, P. Anurakpongsatorn, P. Pakkong

and W.H. Patrick, J. Environ. Sci.Health B33

(3), 211–233 (1998).

14. K. Mathava and P. Ligy, Chemosphere,

Vol.62, Issue 7, pp.1064-1077 (2005).

15. S. Lagergren, S. Zur theorie der sogenannten

adsorption gelöster stoffe. Kungliga Svenska

Vetenskapsakademiens. Handlingar, Band 24,

No. 4, p. 1-39 (1898).

16. Yuh-Shan Ho, Review of second-order models

for adsorption systems, Journal of Hazardous

Materials B136, 681–689 (2006).

17. A. Torrents, and S. Jayasundera,

Chemosphere, 35 (7), 1549–1565 (1997).


69

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www.e-salama.com 14

th AFRICALMA/E-SALAMA WORKSHOP/CONFERENCE

DECEMBER 14-18, 2015, Kampala, Uganda 1. THEME: COMPETENT PERSONNEL IN A LABORATORY: A MUST FOR ALL

2. WORKSHOP PROGRAM

The workshop will cover areas of Quality Assurance under following subheadings:

2.1 Laboratory Management, including -Accreditation Process

-Leadership and cost cutting avenues - Laboratory design, construction and equipment-instrumentation - Laboratory personnel training, hiring and management - Laboratory safety and risk management - Laboratory information management - Equipment and chemicals procurement - Equipment repair and maintenance - Laboratory Budget preparation and financial control. 2.2 Operational Assurance - Preparation of product specifications - Use of standard testing procedures (STP) - Use of Standard Operating procedures (SOP) - Validation of analytical measurements - Documentation of Analytical measurements - Handling of Quality complaints - Sampling for laboratory analysis - Statistical analysis of analytical data - Shelf-life and stability testing - Analytical method development and evaluation - Process Quality control 2.3 Laboratory Accreditation - Internal and external certification - Certification by the National Bureau of Standards and Private Organizations - Accreditation by the International Standards Organization. 3. LANGUAGE OF THE WORKSHOP

The Workshop/Conference will be conducted in English.


73

4. VENUE The workshop venue will be held at … Hotel, Kampala: Organizers are E-SALAMA Local Secretariat and Nairobi Secretariat. 5. ACCOMMODATION: There are several hotels in Mombasa, prices ranging from USD 25 to 200. Details can be provided at a request. 6. ORGANIZING INSTITUTIONS (i) East and Southern Africa Laboratory Manages Association (E-SALAMA): E-SALAMA Secretariat:

Email: [email protected], [email protected], [email protected] (iv) E-SALAMA: Uganda Secretariat: Contact Person: Dr. J. Wasswa (v) E-SALAMA: Sudan Secretariat: Contact Person: Prof. N. Bashir (vi) E-SALAMA: Nairobi Secretariat: Contact Person: David Koech

7. LOCAL ORGANIZATION COMMITTEE Dr. John Wasswa, Department of Chemistry, Makerere University, E-SALAMA Chairman Mr, Michael Wesuta, Mbarara University, Uganda, E-SALAMA Member ….

8. INTERNATIONAL COMMITTEE

Dr S.A. Mbogo, University of Dar-es-Salaam: Chairman, Tanzania E-SALAMA Secretariat Prof. Claude Lucchesi, ALMA Founder Member, USA Prof. Willem de Beer, South Africa, E-SALAMA Trainer Prof. N. Bashir, University of Gezira, Chairman, E-SALAMA Sudan Secretariat

David Koech, Kenya Bureau of Standards, Executive Secretary, E-SALAMA Prof. M.F. Zaranyika , University of Zimbabwe: Chairman, Zimbabwe E-SALAMA Secretariat Prof. G.N. Kamau, University of Nairobi, Executive Director, E-SALAMA

Ms Jane Mumbi, Nairobi Water Company Kenya, Treasurer E-SALAMA Ms Florence Kisulu, Kenya Bureau of Standards, Secretary and Publicity, E-SALAMA Dr. Joseph Mwaniki, University of Nairobi, Trainer and Webmaster, E-SALAMA

Mr. Kariuki Waweru, Government Chemist Department, Kenya, E-SALAMA Committee Member Prof. A. Gachanja, J.K. University of Agric & Technology: E-SALAMA Instrumentation Specialist

9. WORKSHOP FEES & REGISTRATION Confirm your intention to participate via e-mail or Tel/fax. See contact information below. DECEMBER 15-19, 2014

Registration Form: Please include the following information in your registration:

• Title • Surname • First Name(s) • Position • Company/Institution name • Address • Code/City • Country • Phone • Fax • E-mail • Plan to make presentation(yes/no): Put the title:


74

Workshop Fees Participants: US$300 Timing Completed forms should reach the Workshop Organizers by 5th September, 2015. Payment: Participants are requested to remit their fees in US dollars or the equivalent in Kenya shillings. Make cheques and bank drafts payable to: Later If you have any questions about this Conference, please contact either: Dr. John Wasswa Prof. G.N. Kamau David Koech Department of Chemistry Department of Chemistry Kenya Bureau of Standards Makerere University University of Nairobi P.O. Box 54974 – 00200 Kampala, Uganda P.O. Box 30197 Nairobi, Kenya

Nairobi, Kenya Tel: 256 772504657, 254 724642944, 254 722486412, 254 722320607 Tel: 254 4440164, 254 722822196

Email: [email protected], ][email protected], Email: [email protected], Email: [email protected]

For further details, visit the conference website at http://www.e-salama.com

FIRST ANOUNCEMENT AND CALL FOR ABSTRACTS: TCCA-ESAECC:

EAST AND SOUTHERN AFRICA ENVIRONMENTAL CHEMISTRY

CONFERENCE (ESAECC) AND

THE 11TH THEORETICAL CHEMISTRY CONFERENCE IN AFRICA (TCCA)


75

VENUE: University of Nairobi, Mombasa, Kenya

DATES: June 15 to June 17, 2016

THEME

CHEMISTRY FOR DEVELOPMENT AND INDUSTRIALIZATION IN AFRICA

B A C K G R O U N D

TCCA is reaching the 11th conference, a milestone to celebrate and reckon with. ESAECC

has been conducted jointly with TCCA for a number of years. The joint conferences have

attracted researchers from Africa and beyond and provided ideal ground for exchanges of

ideas and experiences in Sciences and Technology.

The major objectives of the joint conferences are the following:

• To bring together African scientists to exchange ideas and research results in the fields of theoretical/computational chemistry and of environmental chemistry.

• To promote research capacity building for theoretical/computational chemistry, as a

scarce skill area in the continent.

• To foster collaboration among African scientists and between African scientists and

scientists from other continents.

CALL FOR ABSTRACTS We are inviting you to be part of the organizing committee by submitting an oral or poster paper for presentation at the conference. We also encourage you to invite your colleagues who are interested in these fields to submit papers for presentation. This is an opportunity for everyone to come to a gathering of international speakers on wide ranging issues related to Environmental Chemistry and Theoretical Chemistry. Abstracts should not exceed 300 words and should be submitted to the Conference Secretariat by e-mail. The name of the presenting author, if submitting with co-authors, should be underlined. The institution of author(s), postal address, e-mail, and telephone numbers should be included. The deadline for abstract submission is March 30, 2016.


76

TOPICS

Environmental Chemistry Theoretical Chemistry

• Environmental management and analysis,

• Atmospheric chemistry, • Soil Chemistry, • Mining and the environment • Surface and ground water

quality, • Impact of Industry and

Agriculture on the environment, • Fate and speciation of metals

in biological and environmental samples,

• Fate and persistence of agricultural chemicals in the environment,

• Industrial wastes, • Plastic waste management • Pesticide analysis

• Computational chemistry of molecules

• Computer-aided design of industrially-relevant substances

• Drug design • Nanoscience • Study of molecules in solution • Interfaces of

theoretical/computational chemistry with other areas of chemistry

• Teaching of theoretical chemistry in African universities

• Theory versus experimental results

• Atomistic theories • Molecular structure-activity

design • Solvent free reaction

environment

.

LOCAL ORGANISING COMMITTEE

Prof. G.N. Kamau, Conference Chairperson, Prof. A.O. Yusuf, COD, Department of Chemistry Dr. Vincent Madadi, Secretary Mr. Charles Mirikau, Organizing Secretary Dr. Peterson M. Guto Dr. Immaculate Michira Dr. Albert Ndakala Prof. J.P. Kithinji Dr. J.M. Wanjohi Mr. James K. Mbugua Dr. Joseph Mwaniki

INTERNATIONAL ADVISORY BOARD

Prof. Liliana Mammino, University of Venda, South Africa


77

Prof. Nabil Bashir, University of Gezira, Sudan Prof. Geoffrey Kamau, University of Nairobi, Kenya Prof. Enos Kiremire, University of Namibia, Namibia Prof. Amos Mugweru, Rowan University, U.S.A. Prof. Egid Mubofu, University of Dar es Salaam, Tanzania Prof. Maurizio Persico, Univerity of Pisa, Italy Prof. Mirco Ragni, University of San Salvador, Brazil Prof. S. Jonnalanda, Kwa-Zulu Natal, South Africa Prof. Mark Zaranyika, University of Zimbabwe Prof. Saaban Mbogo, Open University of Tanzania Dr. John Wasswa, Makerere Univesrity Dr. Fredrick Oduor, University of Nairobi, Kenya Prof. Rufus Sha’Ato, University of Agriculture, Makurdi, NIGERIA

CONFERENCE PROGRAM This part of the website is still under preparation:

REGISTRATION The deadline for registration is March 30, 2016. Registration fees are as follows:

Participants:

a for scientific participants: US$ 200.00

b Students : US$100.00

c Local participants : US$ 150.00

Registration fees will cover the book of abstracts, morning and afternoon teas/coffee/snacks, lunch and conference facilities during the days of the conference. Details about how to process the payment will be available on the Conference website shortly.

EXCURSION Thursday June , 2014, there will be the possibility of an excursion to view the biggest Baobab tree in Southern Africa. Details about the excursion will be available on the Conference website shortly.

is this a good idea for the excursion? OK

ACCOMMODATION

The area offers possibility of accommodation for different budgets. A list of suggested hotels and guesthouses will be available on the Conference website shortly.


78

TRAVELLING TO MOMBASA International flights arrive in Mombasa directly or via Nairobi. Transport will be organized for pick up of participants from the airport to the hotel. Details of transport arrangements will be provided later.

CONFERENCE PROCEEDINGS Peer-reviewed conference proceedings will be prepared after the conference. Details for the submission of the complete papers, including the deadline, will be announced later.

EXHIBITORS Companies interested in exhibiting their equipment/apparatus, instruments, or in holding vendor workshops, demonstrations or seminars, are invited to send their inquiries to the Conference Secretariat.

For further details, visit the conference website at http://www. e-salama.com

or Contact the Conference Secretariat, e-mail address:

Dr. Vincent Madadi: [email protected]

Copies to: [email protected] [email protected]


79

INTERNATIONAL UNION OF PURE AND APPLIED CHEMISTRY

Dear Colleagues,

The second African Conference on Research in Chemical Education will be held at the

University of Venda (South Africa), 22-27 November 2015.

The conference wishes to emphasise the roles of chemical education for development and,

in particular, for sustainable development in Africa and worldwide. It also wishes to

stimulate attention to all the challenges of chemical education – those already identified

througha number of years and those that are appearing recently as the results of deep

ongoing changes. Do your best to find a space in your agenda, to come and share your

experiences, reflections and insights with all the participants.

The University of Venda is located in an area rich of natural beauties and cultural heritage,

offering excellent opportunities for combining an exciting high-quality scientific experience

with a delightful immersion in the warmth of Africa.

Looking forward to meeting you in November!

Liliana Mammino

(conference chairperson)

Conference website https://sites.google.com/site/acrice2015

Contact us [email protected]


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