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Pakistan Journal of Scientific and Industrial ResearchSeries A: Physical Sciences

Vol. 61, No. 2, May-August, 2018

Contents

Green Synthesis and Structural Characterisation of CuO Nanoparticles

Prepared by Using Fig Leaves Extract

Karim Henikish Hassan, Areej Ali Jarullah, Sally Kamil Saadi and Peter Harris 59

Synthesis, Characterisation and Antimicrobial Evaluation of

Some New Heterocyclic Compounds Using Citric Acid as a Synthon

Moayed Salim Al-Gwady, Salim Jasim Mohammed and Attalla Mohammed Sheat 66

Uric Acid Biosensor Using Immobilised Lactobacillus plantarum Mar8

on Zeolite/k-Carrageenan Membrane

Wahyuning Lestari, Dyah Iswantini, Novik Nurhidayat and Zaenal Abidin 74

Preparation of Rechargeable Battery from Poultry Waste

Abrar Ul Hassan, Ayesha Mohyuddin and Sakhawat Ali 80

Vibration Analysis of Cracked Composite Laminated Plate

Muhammad Imran, Rafiullah Khan and Saeed Badshah 84

GIS and RS Based Approach for Monitoring the Snow Cover Change in Gilgit Baltistan

Umair Bin Zamir and Hina Masood 91

Characterisation of Patala Formation Coal Reserves of Salt Range and its Application

Hafiz Muhammad Zulfiqar Ali, Aun Zahoor, Hafiz Muhammad Zaheer Afzal

and Muhammad Yasin 96

Effect of Dyeing Temperature on the Shrinkage and Fastness Properties

of Polyester/Acrylic Fabric

Musaddaq Azeem, Ahmed Fraz and Asif Javed 100

A Study of Ambient Air Quality Status in Karachi by Applying Air Quality Index (AQI)

Durdana Rais Hashmi, Akhtar Shareef and Razia Begum 106

Review

Economic Analysis of the Production of Electricity Generation and Fuel Oil

from Different Renewable Resources in Pakistan

Atif Khan, Hassan Javed Naqvi, Shabana Afzal, Zohaib Ashraf and Sana Zahid 115

Introduction

Metal oxide nanoparticles is a highly valuable material

with various applications in optical, electrical and

mechanical devices, catalysts, gas sensors, sunscreens

and cosmetics (Rajendran and Sengodan, 2017). Several

chemical and physical methods have been used for their

synthesis such as sol-gel, precipitation, sonochemical,

electro thermal synthesis, vapour deposition, electro-

chemical methods, combustion, colloid-thermal synthesis

process and microwave irradiation and pulsed wire

explosion methods (Hariprasad et al., 2016; Ahamed

et al., 2014). Most of these methods are complicated

and have drawbacks like use of hazardous organic

solvents, expensive reagent, toxic by-products, drastic

reaction condition, difficult to isolate nanoparticles and

longer time required etc. (Devi and Singh, 2014), there-

fore there is an essential need to develop environment

friendly methods for synthesis of metal oxides nano-

particles (Geraldes et al., 2016).

Nowadays, varieties of nanoparticles with well-defined

chemical composition, size and morphology have been

synthesised by different methods and their applications

in many innovative technological areas have been

explored (Yu et al., 2016; Khademi-Azandehi and

Moghaddam, 2015). The renewable nature of plant

extracts, eco-friendly aqueous medium and mild reaction

conditions make the method advantageous over other

hazardous methods (Saif et al., 2016). In the last years,

different kinds of plant extracts and their products have

received attention due to their low cost, energy-efficient

and nontoxic behaviour in approach for synthesis of

metal nanoparticles (Prasad et al., 2017). Green synthesis

of nanoparticles using plant extracts is an emerging

area of research and is potentially advantageous over

chemical or microbial synthesis as it eliminates the

elaborate process and can also meet large-scale pro-

duction with green synthesis being low cost (Nagajyothi

et al., 2017) where the role of the extract is reduction

and conversion of the salts to its corresponding oxide

nanoparticles. Regarding biological synthesis different

nanoparticles have been prepared using plants such

as neem, alfalfa, lemon grass, tamarind bark extract,

leaf extract, fruit, tea and coffee powder, peel extract

and flower extract ect. (Awwad et al., 2015). In addi-

tion to biological synthesis methods of nanoparticles

reported using Escherichia coli (Ajay et al., 2010) and

Pseudomonas fluorescens (Shantkriti and Rani, 2014)

and by Ixora coccinea leaf extract (Yedurkar et al.,

2017).

Copper oxide is an important metal oxide which has

attracted recent researchers because of its low cost,

abundant availability as well as its particular properties

(Nithya et al., 2014). It is a semiconductor material and

gains considerable attention due to its excellent optical,

electrical, physical, and magnetic properties. Its crystal

structures possess a narrowband gap, giving useful

photocatalytic and photovoltaic properties (Ijaz et al.,

2017). Different nano-structures of CuO are synthesised

in form of nano-wire, nano-rod, nano-needle, nano-

flower and nano-particle (Phiwdang et al., 2013).

Green Synthesis and Structural Characterisation of CuO

Nanoparticles Prepared by Using Fig Leaves Extract

Karim Henikish Hassana*, Areej Ali Jarullaha, Sally Kamil Saadia and Peter Harrisb

aDepartment of Chemistry, College of Science, University of Diyala, Diyala, IraqbElectron Microscopy Laboratory, Chemical Analysis Facility, University of Reading,

Whiteknights, Reading, RG6 6AF, UK

(received October 18, 2017; revised January 10, 2018; accepted March 20, 2018)

Pak. j. sci. ind. res. Ser. A: phys. sci. 2018 61A(2) 59-65

Abstract. In this study, copper oxide nanoparticles (CuO) were prepared by a simple method from the

corresponding salt using Fig (Ficus carica) leaves extracts. The particles were characterised using

XRD, SEM, TEM, and AFM techniques. XRD spectra revealed that the particle size obtained was around

(7.31 nm), which agreed fairly well with those estimated from SEM and TEM. Surface morphology of the

nanoparticles was studied by SEM, TEM and AFM.

Keywords: copper oxide, nanoparticles, fig leaves, characterisation, green synthesis

*Author for correspondence;

E-mail: [email protected]

59

Nanoparticles application for removal of pollutants has

come up an interesting area of research. The unique

properties of nanosorbents are providing unprecedented

opportunities for the removal of metals in highly efficient

and cost-effective approaches (Hassan and Mahdi,

2017).

The aim of the present work is to synthesise CuO

nanoparticles using environmentally friendly green

method from copper salt and fig (Ficus carica) leaves

extract and characterise their structure.

Materials and Methods

Material. Analytical grade materials were used without

any further purification in addition to deionised water,

fig leaves, copper (II) chloride dihydrate (CuCl2.2H2O),

sodium hydroxide (NaOH) and absolute ethanol

(C2H2OH).

Preparation of fig leaves extract. Fig leaves were

collected from a tree in a house garden, cleaned from

the suspended dirt and washed with distilled water

several times and dried in shade. They were then ground

with an electric grinder and stored away from wet,

(5 g) of this powder was added to (400 mL) of deionised

water and boiled for (30 min) until the colour of solution

change to brown�yellow. The obtained solution cooled

to room temperature and filtered, centrifuged the filtrate

at 1200 rpm for 2 min to remove biomaterials and stored

the extract at room temperature until use.

CuO nanoparticles preparation. Copper chloride

dihydrate (CuCl2.2H2O) (0.27 g) was dissolved in

(400 mL) of deionised water with continuous stirring

and then (10 mL) of fig leaves extract was added

gradually with continuous stirring also at room tempera-

ture where the colour changed from light blue to light

green, adjusted the pH of the mixture by adding sodium

hydroxide (1 M) where precipitate with a brown- dark

colour was formed, It was then filtered and washed

with deionised water several times and with ethanol

absolute to remove impurities and finally dried in an

oven at (60 °C) for 2 h. The steps are shown in Fig. 1

as flow diagram showing the steps for preparing copper

oxide nanoparticles using fig leaves extract.

Characterisation of copper oxide nanoparticles. The

X-ray diffraction pattern of the prepared oxide were

recorded using XRD-6000 with Cuka (l=1.5406A°)

that have an accelerating voltage of 220/50 Hz which

is produced by SHIMADZU Company. The scanning

electron microscope (SEM) used in imaging the nano-

particles was a scanning electron microscope AIS2300C.

Atomic force microscopy (AFM) used to study surface

morphology of the samples was AFM model AA 3000

SPM 220 V- angstrom Advanced INC, USA, and finally

transmission electron microscope (TEM) images were

recorded using a JEOL 2100 Plus instrument operated

at 200kV.

Results and Discussion

Preparation of copper oxide nanoparticles. The fig

leaves extract acts as a reducing agent (Rajendran

and Sengodan, 2017) by containing a high amount

of polyphenols and other organic groups which

take part in reaction mechanism involving reduction

of precursor to metal nano-particle in two steps

(Gottimukkala, 2017); first precursor forms a complex

by breaking the OH bond and forming a partial bond

with a metal ion. Secondly, there is breakage of the

partial bond and the transfer of electrons to form the

metal hydroxide which is then reacted with OH-1 of

sodium hydroxide to copper oxide nanoparticles and

liberated H2O and thus itself get oxidised to ortho-

quinone.

X-ray diffraction analysis. The XRD technique was

used to determine and confirm the crystal structure of

the prepared nanoparticles. XRD pattern of prepared

copper (II) oxide nanoparticles is shown in Fig. 2 with

the data of strongest three peaks shown in Table 1. The

Picking the

leaves

Wash the leavesand dry them

Preparation of

aqueous extract

Add 10 mL ofextract in the formof drops to the salt

solution

Filtrate Filtering

Add NaOH (1M) Precipitation Filtering

Copper oxidenanoparticles

Drying at 60 °C

in oven

Washed withdeionised water and

ethanol

Fig. 1. Flow diagram showing the steps for

preparing copper oxide nanoparticles using

fig leaves extract.

60 Karim Henikish Hassan et al.

Table 1. The peaks in XRD spectrum of prepared CuO

nanoparticles

No. 2q (deg.) d (Å) FWHM Intensity

(deg.) (counts)

1 34.2786 2.6138 0.5600 20

2 35.5665 2.5221 1.1283 186

3 38.6473 2.6473 1.2450 214

4 48.7888 1.8650 1.1283 47

5 53.4417 1.7131 0.8100 19

6 57.6651 1.5973 0.9200 21

7 61.6338 1.5036 1.1000 16

8 67.9818 1.3778 1.0600 30

9 68.8016 1.3634 0.2400 9

10 75.0099 1.2652 0.7000 15

500

400

300

200

100

0

int.

0 10 20 30 40 50 60 70 80 90

Fig. 2. XRD pattern of prepared copper oxides

nanoparticles.

2q

peak positions exhibited the monoclinic structure and

single phase of CuO nanoparticles and are in a good

agreement with those reported in JCPDS file (NO. 48-

1548), no other impurity peak was observed in the

XRD patterns. The broadening of the diffraction peaks

indicates that the crystal size is small.

Fig. 3. SEM image of prepared copper oxide nanoparticles.

61Green Synthesis of CuO Nanoparticles

Particle size calculation of copper oxide nanoparticles.

The particle sizes were calculated from formula given

by Ghidan et al. (2016):

0.9 lD = _______ ...................................................... 1

b cos q

where:

D = the crystallite size, l = the wave length of radiation,

q = the Bragg�s angle, b = the full width at half maximum

(FWHM).

The calculated particle size is (7.31 nm) which represents

the smallest particle size; the presence of sharp peaks

in XRD and particle size being less than 100 nm refers

to the nano-crystalline nature.

Scanning electron microscope. The surface morphology

of the prepared copper oxide nanoparticles (CuO) were

revealed through the SEM image shown in Fig. 3. It

shows a homogeneous distribution of spheroidal

nanoparticles with irregular distribution. From the SEM

images it is confirmed that the particles having size in

Fig. 4. Transmission Electron Microscope (TEM) images of prepared copper oxide nanoparticles.


Fig. 6. Granularity cumulating distribution of

prepared copper oxide nanoparticles.

8.00

6.00

4.00

2.00

0.00

(%)

0.00 40.00 80.00 120.00 160.00

Diameter (nm)

Granularity cumulation distribution chart

Table. 2. Granularity cumulating distribution and average

diameter of prepared copper oxide nanoparticles

Avg.Diameter :71.28 nm

Diameter (nm)< Volume (%) Cumulation (%)

15.00 0.47 0.47

20.00 0.93 1.40

25.00 1.63 3.03

30.00 4.43 7.46

35.00 2.80 10.26

40.00 3.26 13.52

45.00 5.13 18.65

50.00 5.13 23.78

55.00 8.62 32.40

60.00 6.76 39.16

65.00 8.39 47.55

70.00 6.53 54.08

75.00 6.76 60.84

80.00 5.83 66.67

85.00 4.20 70.86

90.00 4.43 75.29

95.00 4.20 79.49

100.00 3.26 82.75

105.00 2.80 85.55

110.00 3.03 88.58

115.00 1.40 89.98

120.00 1.86 91.84

125.00 2.56 94.41

130.00 1.17 95.57

135.00 1.63 97.20

140.00 0.23 97.44

145.00 0.70 98.14

150.00 0.93 99.07

155.00 0.70 99.77

160.00 0.23 100.00

between 34.57 nanometers as calculated by Image-J

programme which again confirmed the nanostructure

nature of the oxide (Maruthupandy et al., 2017).

Transmission electron microscope. TEM (Transmis-

sion Electron Microscope) of copper oxide nano-particles

are shown in Fig. 4. The estimated particle size is found

to be 7.5 nm for the smallest and 35 nm for the largest

one which is similar to those calculated from XRD and

calculated from SEM (Naika et al., 2015; Kumar et al.,

2015).

Atomic force microscope. The surface morphology

average grain size of prepared copper oxide nanoparticles

was studied utilizing atomic force microscope (Hassan

and Mahdi, 2016). Figure 5 is typical AFM image of

the CuO nanoparticles, it shows images measured with

size = 2032 ´ 2027 nm, and ability analytical pixel =

392, 39. Figure 5a is AFM image in three dimensions

(3D), it explains structure shape for grain and Fig. 5b

is AFM image in two dimensions (2D), it is found that

average roughness is (0.311 nm). The root mean square

(RMS) is (0.3581 nm), and average diameter being

(71.28) nm. Table 2 and Fig. 6 show the granularity

cumulating distribution and average diameter data.

Fig. 5. AFM images of prepared copper oxide

nanoparticles.

2.51nm

2.01nm

1.51nm

1.01nm

1.51nm

1.01nm

2.59nm

.../937.csmCSPM TitleTopographyPixels=(392.391)Size=(2032nm.2027nm)

2000nm

1500nm

1000nm

500nm

0nm0nm 500nm 1000nm 1500nm 2000nm

(A)

0.01nm

1524.07nm

1016.05nm

508.02nm

0.00nm 0.00nm

1520.18nm

1013.46nm

506.73nm

(B)


Conclusion

In this study copper oxide nanoparticles were prepared

well by using fig leaf extract method. X-ray diffraction

results explain that the calculated particle size is (7.31)

nm. The SEM results indicated that the average particle

size of CuO nanoparticles was found to be (34.57) nm

while those calculated from TEM seems to be (7.5-35)

nm. From AFM the average particle size observed in

the nano scale (71.28) nm, so SEM, TEM and AFM

analysis of the CuO showed that the diameters of the

particles are in a nanometer range.

Acknowledgement. The authors would like to express

special thanks to College of Science, Diyala University,

Iraq for the scientific support and to electron micro-

scopy unit in University of Reading, UK, for their

cooperation in the analysis of TEM of our samples.

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Introduction

Substituted chromens were synthesised owing to their

biological activities as antibacterial, anticoagulant,

vasodilatory and hypothermal (Khodairy et al., 2001;

El-saghier et al., 1983; Okumur et al., 1962). Also

substituted 1, 3, 4-oxadiazoles, 1, 2, 4-triazoles and 1,

3, 4-thaiadiazoles are well known to possess biological

activities, and have important uses in the agricultural,

medical and industrial applications. Some substituted

1, 3, 4-oxadiazoles possess various biological activities

as antibacterial agent(Arvind et al., 2011), antifungal

and anti-inflammatory agents (Nargunf et al., 1994;

Dutta et al.,1986), while substituted 1,3,4-thiadiazoles

show wide range of biological activities such as anti-

fungal and antiviral (Vashi et al., 1996), antibacterial

and antimicrobial (Mohan et al., 2005; 2000; Srivastava

et al., 2000). The substituted 1,2,4-triazoles and their

derivatives have attracted global interest because of

their pharmacological and therapeutic properties such

as have moderate antimicrobial activity (Mani et al.,

2015), antifungal (Reginaldo et al., 2012), antitubercular

activity (Dinesh et al., 2015), and some of triazoles

exhibited potent inhibition against AChE and BChE

(Gaochan et al., 2018).

It was found that the 1, 3, 4-oxadiazoles, 1, 2, 4-triazoles

and 1, 3, 4-thaiadiazoles are typically formed by forming

suitable esters which were converted to the corres-

ponding acid hydrazides by their reaction with hydrazine

hydrate in ethanol. Acid hydrazide is served as key

intermediate for the synthesis of the target heterocyclic

compounds where the interest of many researchers is

in organic chemistry. Several procedures were reported

for the synthesis of substituted 1,3,4-oxadiazoles,

1,2,4-triazoles and 1,3,4-thaiadiazoles and review of

some chemical research by Kuldipsinh et al. (2017);

Almasirad et al. (2011); Jitendra et al. (2010) and

Mihaela et al. (2009).


Melting point were determined in open capillary type

on Stuart melting point SMP30. The FTIR spectra were

recorded on FTIR-600 Bio Tec. Engineering Manage-

ment Co. Ltd. (UK) using KBr disk. Nuclear Magnetic

Resonance (13C & 1H-NMR) spectra were recorded on

Bruker DMX-500 NMR Spectrophotometer (300MHz);

with TMS as internal standard, and DMSO-d6 as

solvents. UV spectra were recorded on Shimadzu UV/Vis

using chloroform as a solvent.

2-(3-Oxo-3H-benzo[f]chromen-1-yl) acetic acid 1.

(Manvar et al., 2008). A mixture of citric acid (l mol)

and concentrated sulphuric acid (30 mL) was stirred

for half an hour. Then the temperature was slowly raised

during an interval of 15 min, soon the evolution of gas

was reduced. Removed the flask from the bath, leave

it aside until the reaction mixture became clear and free

from carbon monoxide bubbles. Then cooled to (10 °C)

in crushed ice. Then, a-naphthol (1 mol) was added

drop wise and the reaction mixture was stirred at room

temperature for about 48 h. The reaction mixture was

then poured onto crushed ice, the solid precipitate was

filtered off and dissolved in saturated sodium bicarbonate

solution which on acidication and then recrystallization

Synthesis, Characterisation and Antimicrobial Evaluation of

Some New Heterocyclic Compounds Using Citric Acid as a Synthon

Moayed Salim Al-Gwady, Salim Jasim Mohammed* and Attalla Mohammed SheatDepartment of Chemistry, College of Science, University of Mosul, Iraq

(received October 19, 2017; revised April 16, 2018; accepted April 23, 2018)


Abstract. In this paper several substituted 1,3,4-oxadiazoles, 1,2,4-traizoles and 1,3,4-thaiadiazoles were

synthesised by Pechmann condensation from citric acid via reaction of a-naphthol with citric acid that

gave an intermediate 2-(3-oxo-3H-benzo[f]chromen-1-yl) acetohydrazide. The structure of the new

compounds were established on the basis of physical and spectral data. These compounds were tested for

biological activities as antibacterial and antifungal agents and some of them showed a significance to

moderate activity.

Keywords: citric acid, chromens, triazoles, oxadiazoles, thiadiazoles, biological activity

Author for correspondence:


66

from ethanol gave the title compound as a brown powder

(Yield: 60%; m.p. 201-203 °C).

Methyl 2-(3-oxo-3H-benzo[f]chromen-1-yl) acetate

2. (Manvar et al., 2008). The 2-(3-oxo-3H-benzo[f]

chromen-1-yl) acetic acid 1 (1 mol) was dissolved in

methanol (30 mL), and a few drops of sulphuric acid

were added. The reaction mixture was refluxed for 3 h.

After completion of the reaction, the solvent was

evaporated and the resulting reaction mixture was

extracted with ethyl acetate, washed with sodium

bicarbonate and the solvent was removed in vacuum to

give the compound 2 as a brown powder (Yield: 67%;

m.p.: 112-114 °C).

2-(3-Oxo-3H-benzo[f]chromen-1yl)acetohydrazide

3. (Manvar et al., 2008). A mixture of (0.1 mol) ester

2, 86% hydrazine hydrate (10 mL) and methanol (40

mL) was refluxed with continuous stirring for about

3 h. After completion of the reaction, the reaction

mixture was poured onto crushed ice, the separated

solid product was filtered off, recrystallized from ethanol

which furnished 2-(3-oxo-3H-benzo[f]chromen-1-yl)

acetohydrazide 3 as a pale brown powder (Yield:

92%:m.p.: 119-120 °C).

1-((5-Mercapto-1,3,4-oxadiazol-2-yl)methyl)-3H-

benzo[f]chromen-3-one 4. (Selvakumar et al., 2011)

Hydrazide 3 (0.05 mol) was dissolved in potassium

hydroxide solution (0.56 g/100 mL ethanol). To this

solution carbon disulphide (6 mL, 0.1 mol) was added

with shaking. The reaction mixture was refluxed for

24 h until the liberation of hydrogen sulphide was

ceased. The solvent was evaporated under reduced

pressure and the residue was poured into crushed ice;

and acidified with dilute hydrochloride acid. The

precipitate was filtered off and recrystallized from

methanol which gave the compound 4 as a pale yellow

powder (Yield: 42%; m.p. :132-134 °C).

Potassium2-(2-(3-oxo-3H-benzo[f]chromen-1-yl)

acetyl)hydrazine-1-carbodithioate 5. (Yadav et al.,

2016). Acid hydrazide 3 (0.05 mol) was dissolved in

potassium hydroxide solution (0.56 g/100 mL ethanol).

To this solution carbon disulphide (6 mL, 0.1 mol) was

added with shaking, then continuously stirred for 24 h.

The solvent was evaporated under reduced pressure

and the residue was poured into crushed ice; and acidified

with dilute hydrochloride acid. The precipitate was

filtered off and recrystallized from methanol which

gave the compound 5 as a pale yellow powder (Yield:

42%; m.p.: 132-134 °C).

1-((4-Amino-5-mercapto-4H-1,2,4-triazol-3-

yl)methyl)-3H-benzo[f]chromen-3-one 6. Method-I.

(Almasirad et al., 2007). To a suspension of compound

4 (0.14 mol) in ethanol (5 mL), hydrazine hydrate

(0.28 mL) was added. The reaction mixture was refluxed

for 24 h. After completion of the reaction, the reaction

mixture was cooled and acidified with cold aqueous

(3N) hydrochloric acid. The mixture was extracted with

ether and the organic layer was washed with cold water

dried over anhyd. sodium sulphate, filtered off, and the

solvent was evaporated under reduced pressure. The

residue was recrystallized from ethanol which furnished

the compound 6 as a brown powder (Yield: 55%; m.p.

:240-242 °C).

Method-II. (Yusra et al., 2015). A suspension of salt

5 (0.01 mol), hydrazine hydrate (0.02 mol) and water

(50 mL) were refluxed for 6 h. The colour of the reaction

mixture changed to green. The reaction mixture was

cooled to room temperature: a brown solid was preci-

pitated out by adding cold water (50 mL) followed by

acidification with concentrated HCl. The precipitate

was filtered off: washed with cold water, recrystallized

from ethanol which furnished the desired compound 6

as a brown powder (Yield: 48%; m.p. :240-242 °C).

Preparation of 1-((5-amino-1,3,4-thiadiazol-2-yl)

methyl)-3H-benzo[f]chromen-3-one 7. (Harika and

Sudha, 2014). Thiosemicarbazide (0.025 mol) was

suspended in a 1,4-dioxane (25 mL) and stirrers with

the addition of 2-(3-oxo-3H-benzo[f]chromen-1-yl)acetic

acid 1 (0.03 mol). The poly phosphoric acid was added

at 0-5 °C. The reaction mixture was heated at 80-85 °C

for about 6 h and then, left to room temperature. The

solvent was evaporated; poured into crushed ice (50

mL) with vigorous stirring. Then, the reaction mixture

was basified to pH-9 by the addition of 40% NaOH

solution. The precipitate was filtered off: washed with

cold water to remove all coloured impurities which

gave the compound 7 as a pale yellow colour (Yield:

94%; m.p.:167-169 °C).

1-((5-((Substitutedbenzylidene)amino)-1,3,4-

thiadiazol-2-yl)methyl)-3H-benzo[f]chromen-3-

one8a-f. (Harika and Sudha, 2014): To (0.1 mol) of

compound 7 in ethanol (25 mL), added benzaldehyde

or substituted benzaldehyde (0.5 mol) and acetic

anhydride (0.5 mL). The reaction mixture was refluxed

for 10 h. The reaction mixture was cooled and poured

with stirring onto crushed ice contained in a 500 mL

beaker. The solid product was filtered off and dried,

67New Heterocyclic Compounds from Citric Acid

recrystallized from suitable solvent to give the

compounds 8a-f. The physical and spectral data are

listed in Tables 1 and 4, respectively.

2-((5-((3-Oxo-3H-benzo[f]chromen-1-yl)methyl)-

1,3,4-thiadiazol-2-yl)imino)indolin-3-one 8 g. To a

solution of compound 7 (0.1 mol) in ethanol (25 mL),

added isatine (0.5 mol) and acetic anhydride (0.5 mL).

The reaction mixture was refluxed for 12 h. After

completion of the reaction, the reaction was cooled,

poured with stirring onto crushed ice contained in a

(500 mL) beaker. The solid product was filtered, dried

and recrystallized from ethanol to give the compound

8g as a pale yellow (Yield: 72%); m.p.: 160-162 °C).


The synthesis of many heterocyclic system containing

substituted 1,3,4-oxadiazoles,1,2,4-triazoles, 1,3,4-

thaiadiazoles and 1,2,4-triazoles ring were achieved

from reaction of citric acid with a-naphthol to give 2-

(3-oxo-3H-benzo[f]chromen-1-yl) acetic acid 1 which

on treatment with methanol, in the presence of few

drops of sulphuric acid give ester 2 which were converted

to the corresponding acid hydrazides 3 by their reaction

with hydrazine hydrate in ethanol. The synthetic

procedures adopted are illustrated in Scheme 1.

The IR spectra for compounds 1-3 showed characteristic

absorption peak in the range of (1645-1692 cm-1)

stretching for (C=O), at (1714-1726 cm-1) stretching

group due to (C=O) group of lactones' ring. The 1H-

NMR spectrum for compounds (1-3) showed significant

peaks as the following singlet in the range (2.79-2.95

ppm) for (CH2) group, (6.32-6.45 ppm) due to (CH)

group in the ring, also the aromatic part showed multiplet

peaks in the range (7.18-8.22ppm). While 13C-NMR

spectra showed peaks for the carbon signal appeared at

d values as shown in Table 2. The UV spectra showed

absorption peaks at lmax in the range (309-398 nm),

(242-276 nm) due to (n ® p*) and (p > p*) electronic

transitions, respectively.

Oxadiazole 4 was obtained by the reaction of acid

hydrazide (Almasirad et al., 2011) with carbon disulphide

in alkaline medium under reflux conditions. The mecha-

nism of the reaction was accomplished by nucleophilic

attack of nitrogen of hydrazide at the carbon atom of

carbon disulphide to form the salts which undergoes

intra nucleophilic attack of the oxygen of the carbonyl

group on the carbon of C=S group followed by elimina-

tion of hydrogen sulphide to afford 1-((5-mercapto-

1,3,4-oxadiazol-2-yl)methyl)-3H-benzo[f]chromen-

3-one 4 (Ajllo et al., 1972). While the same reaction

under the stirring at room temperature gave different

potassium 2-(2-(3-oxo-3H-benzo[f]chromen-yl)acetyl)

hydrazine-1-carbodithioate 5, which were converted to

triazole 6 by reacting with hydrazine hydrate. Traizole

6 was obtained. Also, given by reaction of oxadiazole

4 with hydrazine hydrate as shown in Scheme 2.

Table 1. Physical data for compounds 8a-f

Comp. R M.P. Yield Colour Cryst.

no. (°C) (%) solvent

a H 185-187 39 Yellow Ethanol

b 2-OH 153-155 42 Brown Methanol

c 4-CH3 186-188 49 Brown Ethanol

d 4-OCH3 197-199 60 Pale yellow Acetone

e 2-CO2H 181-183 55 Brown Methanol

f CH=CH 184-186 35 Yellow Ethanol

OO

O O

OO

O

OO

O

OO

C

C

C

C-OH

OCH

NHNH2

NH NH2 2

H SO2 4

HO

OHOH

OH

OH

C H OH2 5

+

(2)

CH OH3

H SO2 4

(1)

(3)

3

Scheme 1

68 Salim Jasim Mohammed et al.

The IR spectra for compounds 4-6 showed characteristic

absorption peak in the range of (1646-1658 cm-1)

stretching for (C=N), at (2332-2336 cm-1) due to (SH)

group and at (1709-1718 cm-1) stretching group for

(C=O) group of lactones' ring. The 1H-NMR spectrum

for compounds 4-6 showed significant peaks as the

following singlet in the range (2.68-3.24 ppm) due to

(CH2) group,(6,25-6.39 ppm) to (CH) group in the ring,

while the aromatic part showed multiplet in the range

(7.14-8.29 ppm), also the protons of (SH) group were

appeared in the range (13.35-12.93 ppm). 13C-NMR

spectra showed peaks for the carbon signal appeared at

d values as shown in Table 2-3. The UV spectra showed

absorption peaks at lmax (374-386 nm), (228-248 nm)

for (n ® p*) and (p ® p*) electronic transitions,

respectively.

Newly synthesised compounds 8a-f were characterised

by the physical properties shown in Table 1. The

synthetic strategy for the synthesis of imines 8a-g has

been described in the Scheme 3, involves reaction of

acid hydrazide 1 with thiosemicarbazide to give first

on a product it is 1-((5-amino-1,3,4-thiadiazol-2-

yl)methyl)-3H-benzo[f]chromen-3-one 7, which is

considered as starting material for the synthesis of

imines 8a-f and 8g by its reaction with substituted

aldehydes or isatin as shown in Scheme 3. Thus treatment

of thaidiazole 7 with substituted benzaldehyde and isatin

gave the compounds 8a-f and 8g, respectively.

Table 2. Spectral data for compounds (1-3)

Comp. U.V. CHCl3 FTIR (KBr) gcm-1 1H-NMR d (ppm) 13C-NMR (d, ppm)

no. lmax nm C=O C=O Other DMSO-d6 DMSO-d6

(p ® p*) lactone

n ® p* ring

1. (266) 377 1724 1692 3345 OH- 2.95(bs,2H,CH2), 37.2,112.6,115.8,116.8,122.612,6.4,

6.42(s,1H, HC), 126.9,128.5,128.8,130.2,13,1.9155.7,

7.24-8.22(m,6H,ArH), 160.9,171.3

12.31(s,1H,OH)

2. (276) 398 1726 1685 - 3.65(s,3H,CH3), 34.9,51.8,115.7,116,6,122.4,12,3.5,

2.85(bs,2H,CH2 ), 126.9,128.4,128.8,130.2,13,2.1,

6.35(s,1H, HC), 150.6,161.1,168.3

7.18-8.17(m,6H,ArH),

3. (242) 309 1714 1645 3228, NH 2.79 (bs,2H,CH2), 45.7,112.7,115.6,116.4,122.5,126.7,

3365,NH2 6.32(s,1H, HC),7.36-8.18 128.3,128.8,130.2,131.9,151.2,144.1,

(m,6H,ArH),9.14(s,1H,NH), 161.1,170,4

4.28(d,2H,NH2)

2CS KOH

2CS KOH

2C H OH(Refluxe)

5

O O

OO

O

O O

OO

NHNH2C C

OO

S

N N

NH2

N

NHNH-C-SK

NH NH22

NH NH22

Scheme 2

(3)

(4)

(5) (6)

Stirrer

N N

+

SH


The IR spectra for compound 7 showed the following

frequencies: 3100-3300 cm-1 and 1560-1590 cm-1 due

to NH stretching and bending respectively, 1595-1600

cm-1 for C=N stretching and 1723 cm-1 due to (C=O)

group of lactones' ring, also 1H-NMR spectrum for

this compound distinguish the appearance characteristic

absorption peak in as the following singlet in 3.24

ppm due to (CH2) group,at 6.37 ppm for (CH) and

doublet at 6.91 ppm due to (NH2) group, while the

aromatic part showed multiplet in the range (7.34-

8.19 ppm). The 13C-NMR spectrum showed peaks for

the carbon signal appeared at d values as shown in the

following signal: 45.19, 115.8, 116, 4, 122.2, 123.8,

126.3, 128.1, 128.7, 130.4, 131.4, 150.4, 155.3, 161.21,

168.3, 169.8.

The IR spectra for imine compounds 8a-g showed

characteristic absorption peak in the range of (1588-

1638 cm-1) stretching for (C=N), at (1695-1722 cm-1)

stretching group for (C=O) group of lactones' ring.

The 1H-NMR spectra for compounds 8a-g showed

signi-ficant peaks as the following singlet in the range

(2.71-3.25 ppm) for (CH2) group, (6,22-6.39 ppm)

due to (CH) group in the ring, also at the range (8.71-

9.1 ppm) as singlet peak due to (CH=N) group. Which

are characterised by the compounds 8a-f, while

aromatic parts showed two types where multiple peaks

were found at range (7.49-7.83 ppm). Return to the

aromatic part which represents substituted aldehydes

while the other aromatic part showed multiplet in the

range (7.12-8.21 ppm) due to protons of chromens

Table 3. Spectral data for compounds (4-6)


no. lmax nm C=O SH C=N DMSO-d6 DMSO-d6

(p ® p*) lactone

n ® p* ring

4. (228) 374 1718 2336 1646 3.24(bs,2H,CH2), 37.2,112.6,115.8,116.8,122.612,6.4,

6.25(s,1H, HC),7.34-8.09 126.9,128.5,128.8,130.2,13,1.9155.7,

(m,6H,ArH),13.35(s,1H,SH) 160.9,171.3

5. (248) 379 1709 - - 2.68(bs,2H,CH2), 45.9,115.6,116,4,122.2,123.8,126.4,

6.39(s,1H, HC),7.14-8.21 128.1,128.7,130.4,131.8,150.4,

11.05(s,1H,NH) (m,6H,ArH),7.71(s,1H,NH),

155.4,161.1,169.8,203.5.

6. (236) 386 1712 2332 1658 3.19(bs,2H,CH2),6.26 34.2,112.5,115.4,116.1,122.4,126.3,

(s,1H, HC),7.33-8.14 128.6,128.8,130.3,131.7,150.2,

(m,6H,ArH).4.8(d,2H,NH2), 154.1,160.1

12.93(s,1H,SH).

NH NHC-NH22

O

O OOO

O

O O O O

S

SS

S

N NN N

N=CNHN

OHCNH2

N

Isatine Substitutedbenzaldehyde

(8g) (8a-f)

R

Scheme 3

(1)(7)

N N


ring. 13C-NMR spectra showed good peaks for the

carbon signal appeared at d values as shown in

Table 4.

Biological activity. All the synthesised compounds

were screened for in vitro antibacterial and antifungal

activity by adopting the disc diffusion method. For

antibacterial studies the microorganisms employed were

Esherichia coli, Staphylococcus aureus, Micrococcus,

Pseudomonas, Bacillus 11 and Bacillus 12. While for

antifungal, Microsporum gypseum, Microsporum

destortum and Trichophyton rubrum were used as

microorganisms. Both antimicrobial studies were

Table 4. Spectral data for compounds (8a-g)


no. lmax nm C=O C=N ArCH DMSO-d6 DMSO-d6

(p ® p*)

n ® p*

a (297) 359 1703 1611 3058 3.15(bs,2H,CH2),6.32 36.8,112.4,115.8,116.8,122.7,126.2,

(s,1H,HC),7.65-7.78 126.9,128.5,128.4,130.5,131.9,155.7,

(m,4H,ArH),7.26-8.12 160.9,160.5,161.3,167.9,168.5

(m,6H,ArH),9.07

(s,1H,CH=N)

b (301) 369 1711 1633 3054 2.85(bs,2H,CH2),6.35 39.7,112.4,117,6,120.4,121.7,126.2,

(s,1H,HC),7.62-7.73 128.1,128.8,131.3,132.2,150.3,

(m,4H,ArH),7.12-8.20 168.2,161.1,168.3

(m,6H,ArH),9.1

(s,1H,CH=N),11.2(s,1H,OH)

c (287) 388 1695 1597 3062 2.45(s,3H,CH3),2.75 45..4,112.7,115.6,116.4,122.5,126.7,

(bs,2H,CH2),6.37 128.3,128.8,130.2,131.9,151.1,

(s,1H,HC),7.49-7.71 160.3,160.7,161.4,168.2

(m,4H,ArH),7.36-8.18

(m,6H,ArH),8,86(s,1H,CH=N)

d (276) 391 1722 1608 3065 3.82(s,3H,OCH3),2.71 39.5,55.7,112.1,114.5,115.6,116.7,

(bs,2H,CH2),6.31 122.4,123.9,126.7,128.5128.7,130.2,

(s,1H,HC),7.54-7.68 130.5,131.3,132.4,150.3,150.4,

(m,4H,ArH),7.32-8.16 160.5,160.9,162.4,168.4.

(m,6H,ArH),8,96(s,1H,CH=N)

e (304) 412 1705 1594 2073 3.23(bs,2H,CH2),6.39 39.2,112.8,115,6,116.2,120.6,121.7,

(s,1H,HC),7.61-7.77 126.8,128.1,128.8,131.3,132.2,150.3,

(m,4H,ArH),7.23-8.19 155.8,168.2,161.1,167.3,168.2

(m,6H,ArH),8.99(s,1H,CH=N),

13.15(s,1H,OH)

f (298) 365 1721 1638 3053 2.88(bs,2H,CH2),6.25 41.1,113.4,117.1,118.9,122.3,126.8,

(s,1H,HC),6.85(s,1H,=CH)6.93 128.1,128.8,131.3,132.3,150.3,155.5,

(s1H,CH-triazole),7.24 68.2,160.7,167.6,168.2.,170.6

(s,IH,-CH=)7.52-7.83

(m,4H,ArH),7.14-8.21

(m,6H,ArH),8.71(s,1H,CH=N)

g (258) 366 1698 1588 3059 3.25(bs,2H,CH2),6.22 39.9,112.2.112.6,114.1,115.2,116.7,

(s,1H, HC),6.92-7.74 122.4,123.6,124.2,126.3,128.4,128.8,

(m,4H,ArH of isatin ring) 130.2,131.4,135.5,150.5,151.7,155.5,

7.29-8.17(m,6H,ArH),10.75 156.4,160.7,168.3,187.4

(s1H,NH)


assessed by a minimum inhibitory concentration. From

the obtained data, it is evident that compounds 8a and

8d possess a very good activity against bacteria strains

like E. coli and Staphylococcus and the compounds 8e,

8f and 8g possess almost a significant activity against

all fungi tested at 1 mg/mL and 2 mg/mL. The remaining

compounds showed a moderate activity against other

bacteria and fungi tested.

Conclusion

From the experiment it was concluded that the synthesis

of 1,3,4-oxadiazoles, 1,2,4-triazoles and 1,3,4-

thaiadiazoles were prepared on safe and simplicity with

a good product yields, and some of them showed a good

significance to moderate activity as antibacterial and

antifungal agents.

Acknowledgement

We are grateful to Department of Chemistry, College

of Science, Mosul University, for the facilities given to

perform this work. Thanks are also due to Dr. Maha A.

Al-Rejaboo, Department of Biology, College of Science,

University of Mosul for the biological assays.

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�� 72

Introduction

During the last two decades, there is an increasing

demand for the rechargeable batteries due to their

increased demand for consumption in homes, industries,

and automobiles (Armand and Tarascon, 2008). In the

United States, the demand for different batteries has

been doubled since last 10 years (Jeong et al., 2011).

Transformation and storage of energy is a very important

phenomenon in science and several researches are

underway for the storage (Walawalkar et al., 2007),

conversion (Li et al., 2012) and transformation (Tsai

et al., 1973) of different forms of energy such as heat,

light and electrical energy. Among various batteries,

lithium-ion batteries and lead batteries are very common

(Lu et al., 2013). Although rechargeable batteries are

used for so many functions, one of the principal function

of these is the storage of charge (Kang et al., 2006).

Rechargeable batteries are actually electrical batteries

which may be charged/discharged through a load in so

many times. Shapes and sizes of rechargeable batteries

range from smaller systems such as button cells (Padhi

et al., 1997) to systems with capacity in megawatts

(Manohar et al., 2012). Different combinations of

electrodes such as lead-acid, nickel-metal hydride

(NiMH), nickel -cadmium (Ni-Cd), Lithium-ion polymer

(Li-ion polymer) and lithium-ion (Li-ion) are employed

in these batteries. These batteries find their applications

in automobiles as starter, portable devices for consumers,

in power stations as power storage devices and in homes

to be used as uninterrupted power source (UPS). Protein

as the channel for the transport of selective ions has

been reported recently (Gouaux and MacKinnon, 2005).

Transport of ions through the selective channels of

proteins enable them to conduct electricity. Proteins

due to their selective channels for the conduction of

selective ions have been used in the batteries (Good-

enough and Park, 2013). Several protein resources from

the waste materials of biological origin have been

employed in the manufacture of batteries in order to

investigate the charge storage potentials (Sun et al.,

2016). Although such attempts have not been proved

yet as an alternative source for materials to be used in

conventional batteries, such materials have a large

potential to prove themselves as a charge storing site.

During the present study collagen from the poultry

waste (feather and feet) as an oxidising agent and

oxytocin as the reducing agent have been utilized during

assembly of the rechargeable battery.


A novel protein-oxytocin battery was prepared in a

cane of 12V lead battery which was discarded after its

usage in some 800cc automobiles. Each of the six

boxes having 3.2 cm2 area was converted into two boxes

with cardboard (Fig. 1). Cardboard also served as the

salt bridge. Before operation of the battery, the water

was filled for one day in order to wet the cardboard.

Graphite electrodes from the dry cells were employed

into the half-cells with the wiring as per the requirements

of the circuit. Poultry water mainly comprises of the

Preparation of Rechargeable Battery from Poultry Waste

Abrar Ul Hassana*, Ayesha Mohyuddinb and Sakhawat Alic

aDepartment of Chemistry, University of Gujrat, Gujrat, PakistanbDepartment of Chemistry, University of Management and Technology, Lahore, Pakistan

cPCSIR Laboratories Complex, Ferozpur Road, Lahore, Pakistan

(received March 6, 2017; revised February 8, 2018; accepted February 12, 2018)


Abstract. Present research involves an investigation of utilisation of poultry waste to prepare a rechargeable

battery. The alkaline solution of poultry waste was employed as the cathodic material with the pharmaceutical

grade oxytocin purchased from a local medical store as an anodic material. Power of rechargeable battery

was investigated by using a change in several parameters such as hydration and dehydration of salt bridge,

the concentration of oxidising and reducing agents, charging voltage and time of charging. Obtained results

have confirmed that concentration of oxidising and reducing agents is the key factor for battery. Optimised

conditions provided the voltage of the battery up to 8300 millivolts.

Keywords: poultry waste, oxytocin, salt bridge, voltage

*Author for correspondence:


80

skin, feather, legs and intestines of chicken after its

slaughter.

Preparation of half cells. Poultry waste (feathers and

feet) was washed with tap water in order to remove

blood and debris first by tap and then distilled water

followed by drying in a hood at ambient temperature.

Dry and clean poultry waste was grounded into smaller

pieces and then heated with the adequate amount of 5%

aqueous NaOH solution in order to get a stock solution

having the final volume of 1 liter. For anodic half-cell,

pharmaceutical grade oxytocin was diluted with different

concentrations in ppm. Each of the cathodic half-cells

was filled with 250 mL of the alkaline solution of poultry

waste and each of the anodic half cells was placed with

oxytocin solution followed by applying of graphite

electrodes of 0.5 inch length (Fig. 1).

chamber in the discarded battery cans was separated

into two half-cells with the cardboard which also served

as the salt bridge and was employed in the highly

hydrated form of 24 h wetting and in its less hydrated

form (Table 1). Both the chambers were sealed with

some gluing material. Conductive nature of salt bridge

was evaluated by charging the cell using a 12 volts

charger. Results showed that the cardboard had more

stability and voltage in its hydrated form (Table 1).

In general, an increase in power for charging may lead

to an increase of oxidising and reducing potentials of

the species (Palacin, 2009). Obtained results revealed

that increase in power of charger had led to the increase

in voltage of the battery which may be attributed with

the increase of the concentration of species responsible

for oxidation and reduction; other possible reason may

be the formation of charge storage species within the

half cells (Table 2).

Nature of electrodes is reported to be effective in the

assemblies of batteries due to their catalytic impact on

the generation of voltage by increasing or decreasing

the oxidising or reducing potential of species (Armand

and Tarascon, 2008). During the present investigation,

only single type of electrode i.e., graphite electrode in

both the half cells is employed because the primary

purpose of the research remained to evaluate the charging

potential of poultry waste.

Power and stability of batteries are directly related to

the concentrations of electroactive species within the

half cells (Divya and Ostergaard, 2009). Peptides are

found to be efficient due to their antioxidant potentials

during the oxidation-reduction reactions in batteries

Table 1. Potential of cardboard as salt bridge

Salt bridge Voltage (millivolt)

Highly hydrated 170.0

Less hydrated 105.0

Table 2. Capacity for charge storage of battery

Max voltage charger Charging Voltage

(volt) time (millivolt)

12 30 6300

24 30 7100

36 30 8300


During the present investigation, a protein source mainly

collagen and keratin as cathodic material derived from

the poultry waste and oxytocin as anodic half-cell battery

material were used in order to compute its potential as

charge storage battery. A salt bridge in a battery was

used to connect the half cells having reduction and

oxidation in them with the primary function to prevent

the accumulation of charges and thus gaining electrical

neutrality during the redox reactions (Hosseini et al.,

2012). The battery was assembled in a discarded chamber

of the 12-volt battery from an automobile. Each of the

Fig. 1. Schematic diagram of battery for protein-

oxytocin battery.

Graphite electrodes

protein-SS Oxytocin-SH

HALF CELL(OX) HALF CELL(RED)

81Rechargeable Battery from Poultry Waste

(Ai et al., 2013). Previously phenols, oxytocin, and

other related compounds have been employed in charge

storage batteries due to their anti-oxidant potentials of

hydroxyl groups present in them (Soobrattee et al.,

2005). During the whole investigation, the concentration

of protein in the cathodic half-cell remained same,

however, the concentration of oxytocin was changed

in order to optimise the cell reaction conditions. The

concentration of oxytocin ranging from 0.01 ppm to

0.2 ppm was employed. Although the trend was not

regular for adjacent values, however, a linear behaviour

of charging capacity was observed (Fig. 2). A maximum

charging voltage of 311 millivolts was observed with

the 0.18 ppm concentration of oxytocin but the maximum

difference in charge storage after and before charging

was seen with 0.01 ppm concentration rendering it to

be an optimum concentration (Table 3).

Power or capacity generally expressed in watt-hours

(Wh) of a battery is generally considered as how much

charge that battery can store. During the present study,

the power of battery was calculated by using the light

emitting diodes (LEDs) of 80 mW. Time of dissipation

of power by LEDs was recorded by subsequently

increasing the number of diodes (Table 4).

Table 3. Effect of concentration of oxytocin on storage

capacity

Concentration Before After Difference

of oxytocin(ppm) charging charging

0.01 101 203 102

0.02 106 200 94

0.03 102 128 26

0.04 97 132 35

0.05 99 190 91

0.06 120 230 110

0.07 118 232 114

0.08 203 281 78

0.09 250 290 40

0.1 281 291 10

0.15 291 310 19

0.18 262 311 49

0.2 241 297 56

Table 4. Power calculation of battery

LEDs Power dissipation

time

01 21 min

02 16 min

03 11 min 35 sec

04 7 min 18 sec

Conclusion

Increasing use of batteries demand for newer, cheaper,

simple and environmentally benign materials for the

manufacture of batteries. Present research shows

employment of no cost poultry waste as material for a

cathodic half-cell of a rechargeable battery while it

consumed a nominal amount of oxytocin in anodic half-

cell. Although its power is not comparable with market

batteries, it gave the stable source of voltage which is

encouraging to expand the circumference of this deve-

lopment. Such development needs no laborious set up

for its assembly and may be used on smaller scales.

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2568.

83Rechargeable Battery from Poultry Waste

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Introduction

Snow cover is considered an important component for

understanding the regional climate change. The change

in snow cover impacts the socioeconomic and environ-

mental domains like agriculture, water supplies, land

management etc. Currently, worldwide climatic change

draws growing interest from researchers as well as

governments (Man et al., 2014). The use of remote

sensing data is useful due to the inaccessibility of high

mountainous area. Remote sensing performs the notable

as well as continuing part in global climatic change

monitoring (Khorram et al., 2012). Considering the

actual vastness, distant nature as well as brutal climatic

conditions from the snow-covered places, remote sensing

is probably the best instrument with regard to extensive

as well as repeated research of those places within a

relatively inexpensive way (Arora et al., 2011).

Information, which can be found in various scales as

well as an improvement within electronic data infor-

mation, allow common widespread change detection

for every environment (Khorram et al., 2012; Kerr and

Ostrovsky, 2003). GIS together with remote sensing

technologies assists in quick as well as effective methods

to evaluate, imagine as well as report the periodic

variation in snow-cover (Kaur et al., 2009). Snow cover

performs an essential part of the environment programme

through altering the power as well as mass transfer

between environment and the surface area (Khosla

et al., 2011). Snow is the most important land cover in

Gilgit Baltistan (GB), Pakistan which provides the

water for rivers. Snow cover spatial monitoring is a

crucial element of investigation since it offers under-

standing regarding the quantity of water to become

anticipated through snowmelt readily available for

runoff as well as hydrant (Salomonsona and Appel,

2004). In numerous research and developing actions,

up-to-date and reliable information on the dynamic and

spatial extent of snow could be useful. Therefore, this

information may be used as a better input in climate

modeling, hydropower programme, strategic planning,

drinking water administration and much more developing

actions in the area.

A number of methods have been used for snow cover

mapping using multispectral dataset like manual

delineation, band ratio, NDSI (Normalize Difference

Snow Index) (Salomonsona and Appel, 2006) as well

as Visual interpretation, visual and supervised classi-

fication (hybrid). Manual delineation techniques such

as on-screen digitization has been broadly utilised for

mapping and estimation of the snow extent and glacial

ice, and specifically, for deglaciation and retreating

over different parts of the world (Kulkarni et al., 2007;

Khromova et al., 2006; Williams et al.,1997; Hall

et al., 1995). Paul (2000) used on screen digitization

methods for margins of glaciers through Landsat

Images within the Weissmies Area, Switzerland.

Shangguan et al. (2006) utilized Landsat data to digitize

the outline of a glacier in Muztag Ata and Konggur

mountain region.

GIS and RS Based Approach for Monitoring the Snow Cover

Change in Gilgit Baltistan

Umair Bin Zamir* and Hina MasoodDepartment of Geography, University of Karachi, Karachi-75270, Pakistan

(received July 20, 2017; revised March 7, 2018; accepted March 8, 2018)


Abstract. Snow cover mapping, monitoring, and estimation are a time consuming and complicated process

if monitored by traditional means. However, the periodical and precise mapping of snow cover can be

done by using optical satellite imagery. Satellite data archive from Landsat (1980-2014) is used with Shuttle

Radar Topographic Mission (SRTM) DEM data. The results showed that the total area of snow cover was

27987.21 km2 in 1980 and 26318.05 km2 in 2014. The variation in snow cover was 1669.16 km2 during

1980 to 2014. The combination of GIS and Remote sensing techniques help in delineating the snow cover

pockets that are retreating at the high, moderate and low rate. Furthermore, the district-wise share of snow

cover is also calculated.

Keywords: remote sensing, snow cover, SRTM, change analysis

*Author for correspondence: E-mail: [email protected]

91

The present study attempts to measure the trend of

snow cover for the years from 1980 to 2014 in entire

Gilgit-Baltistan using multi-temporal satellite data and

GIS techniques. The study also calculated the district

wise area of snow cover in the study area.


Study area. The northern administrative region, the

former Northern area of Pakistan is now known as

Gilgit-Baltistan (Hinman, 2012; Weightman, 2005). It

lies between 35°21�0� North to 75°54' 0'' East. It borders

with Xinjiang of China to the northeast, Jammu, and

Kashmir to the southeast, Afghanistan to the north,

Khyber Pakhtunkhwa province to the west, and Azad

Kashmir to the south (UNPO, 2017). Administratively,

it is divided into three divisions (The Express Tribune,

2012), now having ten districts, six in Gilgit division

(Gilgit, Ghizer, Diamir, Astore, Hunza and Nagar) and

four in Baltistan (Skardu, Shigar, Kharmang and

Ghanche) division (The Express Tribune, 2015). It

covers approximately 72,971 km² area. The area is

highly mountainous and had 1,800,000 estimated

population in 2015 (Burki, 2015). Outside the Polar

regions, world�s three longest glaciers (Biafo Glacier,

the Baltoro Glacier and the Batura Glacier) are found

in GB (Gilgit-Baltistan).

For monitoring and mapping purpose of earth surface,

one of the most valuable satellite datasets archive above

45 year available from Landsat data (Kennedy et al.,

2014; Coppin and Bauer, 1994). Several authors recom-

mended the combination of Landsat bands for snow

cover area as red, near infrared and middle infrared

(Paul and Hendriks, 2010; Paul et al., 2004). The NDSI

is recognized for their own capability to enrich the

snow/ice feature (Du et al., 2014; Silverio and Jaquet,

2009). NDSI as following equation (Du et al., 2014):

rB2 - wB5NDSI = __________

rB2 - wB5

where:

B2 = Band 2; B5 = Band 5.

The present study utilised Landsat MSS (Multispectral

Scanner System) and OLI (Operational Land Imager)

datasets of 1980 and 2014 (Table 1). All Landsat scenes

were acquired from the Earth Explorer. Four SRTM

tiles were obtained from CGIAR (Consultative Group

on International Agricultural Research). All processing

was done in ArcGIS 10. Snow covered area was

manually delineated using on-screen digitization method

in a GIS environment. By combining satellite data and

SRTM DEM (Digital Elevation Model) with digitized

snow cover area was used for accuracy. After digitization,

the area of the snow cover was obtained for the year

1980 and 2014.


The present analysis of snow cover for the period of

1980 and 2014 for the entire GB districts is illustrated

in Fig. 1. The result demonstrates that the area of snow

cover was 27987.21 km2 in 1980 whereas 26318.05

km2 area of snow was found in 2014. Figure 1 also

depicts the variation in snow cover between 34 years

in the study area calculated as 1669.16 km2. Trend

analysis of snow cover pockets that are retreating at

very high, high, moderate and low rate are given in

Fig. 2 and Table 2. In Fig. 2 where green colour repre-

sents the highly decreased area, turquoise represents

high, light blue represents moderate and dark blue

Table 1. Satellite image being used in research

Satellite Sensor name Acquisition date

Landsat MSS 6-Sep-79

MSS 14-Sep-79

MSS 6-Sep-80

MSS 7-Sep-80

MSS 26-Sep-80

MSS 22-Sep-81

MSS 14-Sep-81

OLI 17-Sep-14

OLI 17-Sep-14

OLI 24-Sep-14

OLI 28-Sep-14

Table 2. Districtwise snow cover change

Name Snow cover Snow cover Status

1980 (km2) 2014 (km2)

Ghizer/Yasin, Gupis, 6274.93 1477.67 Very high

Ishkomen, Punial

Hunza-Nager 8640.42 8473.59 High

Diamir 912.49 514.82 High

Gilgit 1341.44 623.12 High

Ghanche 4693.14 5153.90 Moderate

Astore 700.93 908.53 Moderate

Skardu/Shigar, Rondu, 5626.85 9391.75 Low

Gultari, Kharmang

92 Umair Bin Zamir and Hina Masood

93Snown Cover Change Monitoring in Gilgit

Fig. 2.District wise share and change in snow cover

GB.

Gilgit Baltistan

Snowcover Districts

1980-2014

Pakistan

Legend

Difference

V.HighHighModcratoLow

DivisionArea Snowcover 2014

Gilgit BaltistanSnowcover Districts 2014

0 55 110 220Km

N

W E

SPakistan

LowModcratoHigh

Gilgit BaltistanSnowcover Districts 1880

0 55 110 220Km

N

W E

SPakistan

DivisionArea Snowcover 2014

LowModcratoHigh

Fig. 1.Snow cover and difference map (1980-2014).

Gilgit BaltistanDifference

Legend

adm DivisionSnowcover_1980Snowcover_2014

0 55 110 220Km

N

W E

SPakistan

Gilgit BaltistanSnow Cover Map 1880

Legend

adm DivisionSnow Cover 1980

0 55 110 220Km

N

W E

SPakistan

Gilgit BaltistanSnow Cover Map 2014

Legend

adm DivisionSnow Cover 2014

0 55 110 220Km

N

W E

SPakistan

represents low changes in the snow cover area. The

trends of snow cover pockets retreating are apparent

in the past 30 years. Furthermore, the district-wise

share of snow cover is also calculated and presented in

Table 2. It can be seen that during the past three decades,

the snow cover pockets very highly retreated in Ghizer

district with 6274.93 km2 to 1477.67 km2, whereas it

shrinkage with high rate in Hunza, Gilgit, and Diamir,

moderately in Astore and Ghanche districts. The area

of snow cover in Hunza-Nager has 8640.42 km2 snow

cover in 1980 and decreased in 2014 with 8473.59 km2.

The area of snow cover in Diamir district was shrinkage

from 912.49 km2 in 1980 to 514.82 km2 in 2014 with

8473.59 km2. In Gilgit, the snow area highly retreated

with 1341.44 km2 to 623.12 km2 in 1980 and 2014. The

covered area of snow in Ghanche and Astore districts

were 4693.14 km2 to 5153.9 km2 and 700.93 km2 to

908.53 km2 in 1980 and 2014, respectively. The Skardu/

Shigar, Rondu, Gultari and Kharmang show the low

retreating trend of snow cover pockets (Table 2).

However, it is evident that the snow-covered area is

reducing continuously within the Gilgit-Baltistan and

it might be because of climate-related aspects on the

regional scale as well as around the world. The regular

monitoring associated with snow cover via satellite

images of various times might perform an important

role within environmental planning as well as hydro-

logical modeling.

Conclusion

This research offers valuable understanding into the

extent as well as nature of snow cover changes, which

has happened within the entire Gilgit Baltistan (GB),

Pakistan through 1980 to 2014. Satellite data archive

from Landsat of 1980-2014 was used and processed in

remote sensing and GIS environment to monitor the

snow cover of Gilgit-Baltistan area. The present study

shows the effectiveness of GIS and remote sensing

methods for analysing the extent of snow cover area

and their change. The result shows the combination of

GIS and remote sensing techniques helps in delineating

the snow cover pockets that are retreating at the high,

moderate and low rate.

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image information extraction techniques for snow

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clopedia of Snow, Ice and Glaciers, pp. 213-232,

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Coppin, P.R., Bauer, M.E. 1994. Processing of multi-

temporal landsat TM imagery to optimize extraction

of forest cover change features. IEEE Transactions

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in the glaciers of the eastern Tienshan Mountains

during 1977-2013 using multitemporal remote

sensing. Journal of Applied Remote Sensing, 8:

084683-084683.

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Development of methods for mapping global snow

cover using moderate resolution imaging spectro-

radiometer data. Remote Sensing of Environment,

54: 127-140.

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95Snown Cover Change Monitoring in Gilgit

Introduction

The coal deposits, available within the territorial

jurisdiction of the Punjab province of Pakistan, belong

to Permian and Paleocene age. The Permian coal-rather

sparsely available compared to that of Paleocene age

(Tertiary era) is mined out in suburbs of district Mianwali

of western salt range whereas the Patala formation of

Late Paleocene in central and eastern salt range and

Hangu formation of early Paleocene age in Makerwal

region and Surghar range contain abundant occurrence

of the Tertiary coal which is being mined out from

different localities within these areas.

This research work aims at the Tertiary coal of Patala

formation being mined out in the areas of Wahula (S-I)

district Chakwal, Dandot (S-II) and Padhrar (S-III)

district Khushab in central salt range by a Provincial

Government Agency namely Punjab Mineral Develop-

ment Corporation (PMDC) that, for operational needs,

has divided each site into several subunits consisting

of group of mines (Fig. 1-2).

Geological settings. Lithologically, the Late Paleocene

Patala formation in Upper Indus Basin contains

Calcareous Shale with alternative coal seams whereas,

in study area it comprises of Greenish Grey Carbon-

aceous Shale with occasional Pyritic nodules; marl and

white to grey nodular limestone while coal is present

in abundance in middle part of the rock unit.

The town of Balkasar has the type-locality of the Patala

formation where it is 27 to 109 meters thick and make

topographic depressions and gentle inclines. Its lower

contact with early Permian Warch Sandstone is Uncon-

formable and is marked by a Muscovite bearing

Lateritic band while it has conformably transitional

upper contact with Middle Eocene Nammal formation.

The Foraminifera fossils are found in abundance in

Patala formation with Assilina nautilus, Montlivaittia

and Rhotalia are the common species that make the

premise for the age attributed to it i.e., Late Paleocene.

Fatmi (1973) describes the Patala formation to have

deposited in Marine to lagoonal setting. While, more

recently a detailed work by Kazmi and Abbasi (2008)

suggested an off-shore back barrier depositional

set-up for it.

Characterisation of Patala Formation Coal Reserves

of Salt Range and its Application

Hafiz Muhammad Zulfiqar Alia*, Aun Zahoora, Hafiz Muhammad Zaheer Afzala

and Muhammad Yasinb

aGeological Survey of Pakistan, Sariab Road, Quetta, PakistanbSpace and Upper Atmosphere Research Commission, Quetta Cantt, Pakistan

(received May 23, 2017; revised November 17, 2017; accepted March 5, 2018)


Abstract. Early Paleocene Patala Formation in Central Salt-Range of Punjab, Pakistan is known for hosting

vast reserves of lignite coal. The coal seams located at the depth of about 145 m, mined out through under-

ground mining method. As many as 17 samples have been taken from Wahula (Site-I), Dandot (Site-II)

and Padhrar (Site-III) areas, with active mining of Salt Range, and on the basis of the results of the two

laboratory techniques viz. Proximate Lab Analysis and Ultimate Lab Analysis, the coal has been attributed

to be of Lignite class. The Proximate analysis of the samples put the percentage of fix carbon ranges at

21.39 to 28.26% for S-I, 15.54 to 25.32% for S-II and 18.52 to 28.37% for S-III, whereas, the gross calorific

value (GCV) found out to be in ranges: 3078 to 4443, 2285 to 4963 and 3429 to 3665 Kcal/kg, respectively.

Likewise, the total carbon percentage (TCP)- worked out with the help of the Ultimate Analysis - are

54.36%, 50.05% and 47.4% for these three sites accordingly. Sulphur contact ranges from 3.3 to 10.35%

is, generally, associated with coal deposits present in salt range, and due to this high sulphur content its

utility is restricted to cement industries, brick plants, coal boiler and briquetting. This study, however,

suggests that the blending of this lignite coal with limestone and high-grade coal can enable it to be used

in coal-fired power generation plants, steel mills as well as liquid fuel.

Keywords: coal characterisation, Patala formation, salt range, industrial application

*Author for correspondence;


96

Methodology. The laboratory analyses were performed

on all coal samples in strict compliance to the pertinent

ASTM codes viz. ASTM D 4749 for sieve analysis,

ASTM D 3173 for percentage moisture contents (MC)

(%), ASTM D 3175 volatile matter (VM) (%) and

ASTM D 3174 for ash contents (AC) (%). Fix carbon

percentage was calculated using simple arithmetic (sum

of MC, VM and AC subtracted from 100). The ultimate

analysis on the samples was conducted following the

instructions as laid down under ASTM D 5373-08.


Under proximate-analysis (Table 1) all of the (17)

specimens were tested for moisture contents (MC),

volatile matter (VM), fixed carbon (FC) and ash contents

(AC), while, under elemental analysis (Table 2)

percentages of hydrogen, nitrogen, sulphur and oxygen

present in the samples were evaluated so as to determine

the suitability of this coal for various industrial and

applied purposes.

Fig. 1. Showing Site-III with attached areas.

Fig. 2. Displaying Site I and II with adjacent place.

Table 1. Proximate analysis of Patala formation coal

reserves salt range

Study Moisture Ash Volatile Fix GCV

area contents contents matter carbon kcal/kg

(site) (%)

Site-III 5.07 42.33 27.64 25.06 3884

Site-II 6.26 49.44 24.25 20.12 3298

Site-I 5.14 43.20 22.75 22.75 3959

Average 5.49 44.99 24.88 22.64 3713

value

Table 2. Ultimate analysis of Patala formation coal

reserves salt range

Project Carbon Hydrogen Nitrogen Sulphur Oxygen

Name (%)

Site-III 54.36 4.5 1.06 9.31 14.45

Site-II 50.05 5.3 0.97 5.22 18.3

Site-I 47.4 4.9 0.83 4.20 16.3

Average 50.60 4.9 0.95 6.24 16.35

value

Table 3. Coal classification reference standards based

on C, H & O % after Perry (1963)

Parameters Peat Lignite Bituminous Anthracite

C 50 65 88 94

H 5.9 5.2 4.6 3.4

O 34 28 7 2.5

Table 4. Apparent density of Patala formation coal salt

range (g/mL)

Sample Site-III Site-II Site-I

No. (Padhrar) (Dandot) (Wahula)

1 1.351 1.333 1.325

2 1.365 1.351 1.341

3 1.357 1.357 1.317

Average 1.357 1.347 1.327

value

Apparent density value of the samples from three sites (S-III,

S-II, S-I) varies from 1.327 to 1.357 g/mL, as S-III>S-II > S-I.

97Characterisation of Salt Range Coal

On average the percentage of carbon in the samples,

as found out by elemental analysis is 50.60% which

is dismally low. A comparison of three sites indicate

that percentage of carbon is maximum i.e., 54.36% in

samples from site-III (Padhrar area) and minimum i.e.,

47.4% in samples collected from site-I (Wahula areas).

The sulphur content an undesired element as far as coal

quality is concerned, however, also follows the same

pattern with site-III bears the highest value i.e., 9.31%

and site-I bears lowest i.e., 4.20%. The average sulphur

value for all the samples combined stands as high as

6.24% which speaks volumes of the unsuitability of

this coal for any advance industrial use unless treated

appropriately.

Coal categorized in anthracite, bituminous and lignite

ranks depending on the value of C, H and O contents

after Perry�s reference coal analysis table as given in

Table 3 (Ismat, 2013).

The results of the elemental analysis, when compared

to the reference values as given in Table 3 made it

evidently clear that the coal present in Patala Formation

in central salt range qualifies hardly to be Lignite or in

stricter sense actually stands between Peat and Lignite

categories of Perry�s classification.

Conclusion and recommendations

· The coal quality of Patala formation (Late

Paleocene) of eastern and central salt range,

Punjab province is categorized as Lignite (Low

quality).

· Average value of GCV of eastern and central

salt range is 3656 Kcal/kg, but it changes from

2853 to 4973 Kcal/kg.

· Ultimate analysis of salt range coal deposits

provides the average percentage of C, H, N and

O as 50.60, 4.9, 0.95 and 16.35, respectively.

· General the coal reserves of salt range comprises

high proportion of volatile matter, ash, and sulphur

varies from 23.56 to 34.74%, 40.32 to 63.21%

and 3.91 to 10.4%, correspondingly.

· Coal deposits of Patala formation contains

appropriate percentage of moisture which

fluctuates from 4.32 to 9.28.

· Salt range coal reserves of Punjab province could

be precisely applicable in all varieties of coal

boiler, brick plant, briquetting, cement factories,

paper mills and chemical industries.

· Patala formation coal of salt range contains high

percentage of sulphur, so it might be utilized

in power generation and steel industries after

blending with high quality coal and desulphuri-

zation.

· It is endorsed that homegrown coal deposits of

Patala formation can be consumed in coal fired

power plants by combination with high rank

coal, to overwhelmed the energy adversities.

References

Ahmed, W., Gauher, S.H., Siddiqi, R.A. 1986. Coal

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American Society for Testing and Materials, PA,

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Bhatti, N.A. 1967. Occurrence of Permian coal near

Burikhel, Western Salt Rnge. Geological Survey

of Pakistan, Unpublished Report. pp. 21-32.

Fatmi, A.N. 1973. Depositional environment of Paleocene

rocks, Pakistan.

Table 5. Application of low quality coal in industrial sectors

Utilization Type of coal Present research remarks

Power generation Bituminous and sub bituminous Coal of Site-I can be applicable by blending with high rank coal and

limestone.

Steel production Low sulfur coal The coal of all 3 sites may be used only after desulphurization.

Liquid fuel Low sulfur and nitrogen Suitable after the calculation of N values and desulphurization

Coal boiler Lignite and bituminous mixture Valid for all kinds of coal boilers by mixing with CaCo3

Briquetting Lignite Adequate for coal briquetting

Brick plant Lignite and sub bituminous Appropriate for brick factory

Domestic Bituminous and anthracite May create serious health issues due to high % of sulphur

Cement factory Lignite and sub bituminous Acceptable for cement industries

98 Hafiz Muhammad Zulfiqar Ali et al.

Fazeelat, T., Asif, M. 2004. Organic geochemical study

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99Characterisation of Salt Range Coal

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Introduction

Air pollution is a global hazards and has immense

effects on human health, metrology, climatic changes

and ecosystem. In developing countries modernization

and industrialization increases the use of fossil fuel in

many ways and producing environmental damages

especially in rapidly growing megacities. These days

air pollution is well-known to be significantly aggravated

by infectious atmospheric trace gases, liquid droplets

and suspended solid particles (Kaldellis et al., 2012).

In Pakistan ambient air quality has increasingly deterio-

rated due to anthropogenic sources like industrialization,

unplanned urbanization, rapid growth of population,

open burning of waste and vehicular emission due to

poor transportation system. Many decade scientist and

researchers have provided undeniable data that the

emission and deposition of air pollutants damage the

life and quality of plants and animals, quality of water,

degraded the soil, productivity of forest and hazards

for human health. It becomes an important environmental

risk factor for cardiopulmonary and cardiovascular

diseases. High particulate matter pollution is one of the

most important issue in urban cities, not only affects

the status of cultural heritages but produce severe health

hazards particularly pulmonary disorders because it can

A Study of Ambient Air Quality Status in Karachi,

By Applying Air Quality Index (AQI)

Durdana Rais Hashmi*, Akhtar Shareef and Razia BegumCentre for Environmental Studies, PCSIR Laboratories Complex, Karachi-75280, Pakistan

(received October 10, 2017; revised February 23, 2018; accepted March 8, 2018)


Abstract. Present study was carried out to determine the concentration of ambient air quality in terms of

atmospheric trace gases and air born particulate matter (PM10) at 20 different locations on the busy roads

in the commercial, residential and industrial areas of Karachi city. Concentrations of trace gases and

particulate matter were used to calculate the results in terms of air quality index (AQI). At each selected

location the assessment was carried out to estimate the concentrations of trace gases and particulate matter

for a period of 8 h during January - November, 2015. Samples were collected at twenty selected locations

i.e., Jail Road (R-1), Gulberg chowrangi (R-2), Gulshan-e-Iqbal (R-3), PECHS Society (R-4) and Model

Colony (R-5) in residential areas, paramount ground, Landhi (I-1W), Abbott, Landhi (I-2W), Lucky Textile,

Landhi (I-3W), Naurus G belt, SITE (I-4E), Siemens G. belt, SITE (I-5E), Manghopir, SITE (I-6E), Singer

chowrangi, KIA (I-7W), Chamra chowrangi, KIA (I-8W) and Korangi #2 (I-9W) Port Qasim (1-10) in

industrial areas, Hasan Square (C-1), Liaquatabad (C-2), Garden (C-3), Gulistan-e-Johar (C-4) and NIPA

chowrangi (C-5) in commercial areas of the city. Results were used to analyse the concentrations of the

pollutants for air quality index (AQI). Air quality index is a single number to measure the quality of air

with respect to its effects on the human being. Results received from different air quality categories were

calculated according to national ambient air quality standard at selected locations, as residential areas

Gulshan-e-Iqbal (R-3) and PECHS Society (R-4) found the AQI under good category with respect to the

trace gases and moderate for the PM10 pollution, having low traffic density, Gulberg chowrangi (R-2) and

Model Colony (R-5) presents moderate AQI category for trace gases and PM10 with moderate traffic

density, whereas Jail Road (R-1) found under moderate pollution category for trace gases and unhealthy

level for PM10 due to high traffic flow. In industrial areas Singer chowrangi (I-7W), Chamrah chowrangi

(I-8W) and Korangi #2 (I-9W) found under moderate pollution AQI values with moderate traffic density,

Paramount ground (I-1W), Abbott (I-2W) and Lucky Textile (I-3W) found unhealthy AQI category pollution

due to high traffic congestion whereas, Naurus G. belt (I-4E), Siemens G. belt (I-5E) and Manghopir

(I-6E) locations are represented by moderate pollution AQI values for trace gases and found under poor

pollution level for PM10 pollution, may be due to industrial emissions and heavy vehicular emission. In

commercial areas as Hasan Square (C-1), Gulistan-e-Johar (C-4) and NIPA (C-5) having moderate AQI

pollution level for trace gases and unhealthy PM10 level of pollution, may be due to high traffic density,

whereas Liaquatabad (C-2) and Garden (C-3) locations found under poor and unhealthy pollution AQI

category. These locations are situated in extremely overcrowded commercial areas having very high traffic

density and commercial activities.

Keywords: ambient air quality, trace gases, particulate matter, air quality index

*Author for correspondence: E-mail: [email protected]

106

penetrate deep into the lungs and cause pulmonary

disorder (Pal et al., 2014). Besides particulate matter,

literature also suggests that there is a strong relationship

between higher concentrations of SO2, NO2 and CO

that may exaggerate several health effects (Faustini

et al., 2014).

The most common air pollutants in the urban environ-

ment are gaseous pollutants as sulphur dioxide (SO2),

nitrogen oxides (NO and NO2 collectively represented

as NOx), carbon monoxide (CO), Ozone (O3), suspended

particulate matter (SPM), methane and non methane

hydrocarbons.

Gaseous pollutants mainly effects on human health.

These pollutants are responsible for changing the

atmospheric chemistry and cause environmental damage.

SO2 and NO2 produce acids by diverse type of chemical

reactions in the environment and deposited on the

surface of sea and earth. Increasing concentration of

SO2, NO2 and CO in the atmosphere are also responsible

for global climate change. Several researches pay

attention on particulate matter (PM) pollution due to

their perilous health hazards, particularly fine particulate

matter. A number of epidemiological studies found

strong association of inhalable particulate (PM10) and

increased risk in mortality and morbidity (Sicard et al.,

2011; Brook et al., 2010).

In the atmospheric air particulate matter pollution it

mainly depends on the size of particle as micron and

sub-micron particles emitted by anthropogenic activities

(industrialization, unplanned urbanization, rapid growth

of population, open burning of waste and vehicular

emission) and natural sources (plants� photosynthesis,

forest fires, volcanic eruptions etc.) (Park and Kim,

2005). Increasing concentration of fine particulate

pollution in the atmosphere has become one of the most

important issues in urban cities paying attention to the

researchers due to its health hazards and cultural heritage

(IPCC, 2001). Severe health hazards of particulate

pollution include cardiopulmonary diseases.

As air pollution is one of the major problems of modern

day societies, especially in urban areas. In order to control

the intensity of air pollution and to avoid hazardous

effects on human being and environment, scientist use

mathematical models in order to define the overall status

of the air quality in the area under investigation. Air

quality index (AQI), a scale to show or characterize the

degree of ambient air pollution at a particular monitoring

location during a certain moni-toring period (e.g., 1, 8

or 24 h) due to the concentration of human activities

that occur in cities. The main aim of AQI calculation

is to aware the public about the risk of pollution level

day to day and to prepare for precautionary measurement

and to regulate the safety measures for health hazards.

Generally it is related with the pollutants range and

category described as good, moderate, poor or hazardous

in order to understand the meaning of AQI easily. In a

simple way AQI shows that ambient air is how much

polluted and what are the health hazards for the citizens

(Kanchan et al., 2015). Air quality Index is the number

used by the agencies to communicate to the public that

how polluted the air is or how polluted it will become

((USEPA, 2014), for an effective ambient air quality

monitoring, meteorological data of an area should also

be recorded. Some of the similar studies in the field of

ambient air quality monitoring and AQI study are

reported by Sahoo et al. (2017) and Dash and Dash

(2015a; 2015b).

United State Environmental Protection Agency (US-

EPA) concerning the calculation of AQI for five �criteria

pollutants� (CO, SO2, NO2, MP and O3) and set National

Ambient Air Quality Standards (NAAQS) in writer for

these pollutants against the risk of pollution on human

health and environment (USEPA, 2012).

The aim of this study was to determine the level of

atmospheric trace gases such as sulphur dioxide (SO2),

carbon monoxide (CO), nitrogen dioxide (NO2) and

particulate matter (PM) in the environment of Karachi

city with reference to air quality index (AQI) for the

year of 2015. This AQI study explained the range of

air quality and its relation to health hazards to provide

awareness in the nation.


Study area. Karachi lies between 24°45' N in longitude

and 66°37' E in latitude covered 3,640 km² area along

the coast of the Arabian Sea. Estimated population of

the largest metropolitan city of Pakistan, Karachi was

counted over 23.5 million people, reported in 2013 and

stand as the 2nd largest city in the world. The climate

of Karachi is moderately temperate with a high relative

humidity 58% in December (the driest month) to 85%

in August (the wettest month). Whereas, the average

temperature is about 21 °C in winter and reaches up to

35 °C in summer. The average rain fall amounts to

about 256 mm in Karachi (Sajjad et al., 2010).

107Air Quality Index Study in Karachi

Karachi is a sea shore and a busy port encountering

both the sea and land breeze periodically. It is congested

with a large number of motor vehicles, including both

public and private transportation. It has also a well

defined industrial base, such as Sindh Industrial Trading

Estate (SITE), Korangi industrial area (KIA), Landhi

Industrial Trading Estate, Northern by-pass industrial

area, Karachi Export Processing Zone, Bin Qasim and

North Karachi industrial estate, located in the boundary

of the city (Sajjad et al., 2010), there are about 20,000

small and large industrial units working in these

industrial areas of Karachi city. Main industries are

textiles, pharmaceuticals, steel, and auto-mobiles.

People migrate from the outlying region due to the

abundant employment and business opportunities in

the city. Vehicular emission, biomass, burning for

cooking and brick kilns and industrial emissions around

the Karachi city are the main contributors of atmos-

pheric pollution in Karachi.

Ambient air monitoring. Sampling. Sampling was

carried out at twenty different locations consisting of

main roads, side roads, round abouts, and open places

along the busy roads of Karachi from January to

November 2015 for gaseous pollutants and PM10.

Selected locations were categorized as residential,

commercial and industrial areas of the Karachi�s

environment.

Monitoring of gaseous pollutants were carried out by

UV fluorescent SO2 analyzer model AF22 M, NO-NOx

analyzer model, AC 32M and Snifit CO analyzer

(Model 50). These analyzers are considered as reliable

for monitoring the pollution level.

PM10 samples were collected on glass fibre filters

(203×254 mm) by using high volume air sampler with

an average flow rate of 1.0 m3/min. Eight hour average

sampling was done in duplicate at each location during

the year 2015. This instrument is reliable to measure

108 Durdana Rais Hashmi et al.

Location Map for study area

the mass concentration of particulate matter in the

atmospheric air (USEPA�Method 40 CFR).

The sampling locations were chosen to reflect the

influences from residential, commercial, industrial areas

regarding the low, moderate and heavy traffic sources.

Eight hour average sampling was done in duplicate at

each location during the year 2015. Features of air

quality stations are presented in Table 1.

Monitoring of trace gases. CO Gas analyzer (Model

50). Snifit CO analyzer (Model 50) was used to measure

the concentration of carbon monoxide. This is an ideal

analyzer for measuring the carbon monoxide in ambient

air and the results are shown in ppm. For measuring

the CO in surrounding air, meter was kept at about

1.2 m height above the ground level. At each selected

locations, CO in the ambient air was collected at an

interval of 02 min and a set of various readings was

noted to analyze the results.

UV fluorescent SO2 analyzer model AF22 M. AF22M,

sulphur dioxide analyzer capable of measuring sulphur

dioxide at ppb level. Applied to SO2 measurement, the

universally known UV fluorescent principle consists

in detecting the characteristic fluorescence radiation

emitted by SO2 molecules. In the presence of a specific

wavelength of UV light (214 nm) the SO2 molecules

reach temporary excited electronic state. The subsequent

relaxation produces a florescence radiation which is

measured by a non-cooled photomultiplier tube (PM).

NO-NOx analyzer model AC 32M. The Chemilumi-

nescent NO-NO2-NOX analyzer, model AC32M, capable

of measuring nitrogen oxides at ppb levels was applied

for nitrogen oxides measurement. Chemiluminescence

corresponds to an oxidation of NO molecules by O3

molecules. The return to a fundamental electronic state

of the excited NO2 molecules is made by luminous

radiation, detected by the PM tube. The model AC32M

is a state-of-the-art single chamber � single photomulti-

plier tube design which automatically cycles between

the NO and NOX modes.

PM10 mass concentration. In addition to the determi-

nation of elemental concentrations, airborne particle

masses of PM10 samples were calculated by using

Table 1. Descriptive features of the sampling locations during the study period in Karachi

Locations Code # Status of the sites

Jail Road R-1 Residential area with high traffic

Gulberg chowrangi R-2 Residential area with moderate traffic

Gulshan-e-Iqbal R-3 Residential area with low traffic

PECHS Society R-4 Residential area with low traffic

Model Colony R-5 Residential area with moderate traffic

Paramount ground, Landhi I-1W Industrial / residential area with high traffic

Abbott Laboratories, Landhi I-2W Industrial / residential area with high traffic

Lucky Textile, Landhi I-3W Industrial / residential area with high traffic

Naurus G. belt, SITE I-4E Industrial / commercial area with high traffic

Siemens G. belt, SITE I-5E Industrial / residential area with high traffic

Manghopir Road, SITE I-6E Industrial area with high traffic

Singer chowrangi, KIA I-7W Industrial area with moderate traffic

Chamra chowrangi , KIA I-8W Industrial area with moderate traffic

Korangi # 2 I-9W Industrial area with moderate traffic

Port Qasim I-10 Industrial area with low traffic

Hasan Square C-1 Commercial / residential area with moderate traffic

Liaquatabad C-2 Commercial / residential area with high traffic

Garden C-3 Commercial / residential area with high traffic

Gulistan-e-Johar C-4 Commercial / residential area with moderate traffic

NIPA chowrangi C-5 Commercial / residential area with moderate traffic


analytical balance (KERN, ALS 220-4). The filter papers

were weighed under controlled conditions of meteorolo-

gical parameters (humidity and temperature) before and

after collection of particulate matter. Weights for the

blank filters were also recorded. Before weighing, all

filter papers (glass fibre filter paper) were left for

24 h in desiccators to equilibrate their humidity and

temperature conditions. The collected particulate mass

was calculated by weighing the pre and post�weight

difference of the filters.

Air quality index (AQI). In this study AQI has been

calculated with reference to the concentration of

particulate pollution proposed by USEPA (2012). These

AQI values predict, evaluate and explained the air

quality status and health concerns at the selected sites.

As the air pollution increases, adverse health effect also

increases.

Following equation was used to calculate the AQI values

by using the pollutant concentration data.

IHi � ILoIp = ____________ (Cp - BPLo) + ILo BPHi BPLo

where:

Ip = Index for pollutant p; Cp = Rounded concentration

of pollutant p; BPHi = Breakpoint that is greater than or

equal to Cp; BPLo = Breakpoint that is less than or equal

to Cp; IHi = AQI value corresponding to BPHi; ILo = AQI

value corresponding to BPLo.

After compiling the data, the concentrations of SO2,

NO2, CO and PM10 pollutant were converted into an

AQI value for each location, higher the AQI value,

higher the level of air pollution that describe the

associated health hazards to the citizens.

Table 2 shows the air quality index with the category

of health risk. The air quality index zero to fifty is good

for human health and indicate clean air, 50 to 100

indicate moderate air quality, 101 to 150 point toward

unhealthy for sensitive group, 151 to 200 express

unhealthy for all people, 201 to 300 very unhealthy,

301 to 500 hazardous and > 500 indicates severe

hazardous and very critical (Table 2) (USEPA, 2012;

Gurjar et al., 2008).


Evaluation of particulate matter and trace gases

concentrations, were carried out on the basis of PM10

size fractions at the selected twenty locations in

Karachi, from January to November 2015. The sites

were Jail Road (R-1), Gulberg chowrangi (R-2),

Gulshan-e-Iqbal (R-3), PECHS Society (R-4) and

Model Colony (R-5) in residential areas, Paramount

ground (I-1W), Abbott (I-2W), Lucky Textile (I-3W),

Naurus G. belt (I-4E), Siemens G. belt (I-5E),

Manghopir (I-6E), Singer chowrangi (I-7W), Chamra

chowrangi (I-8W) and Korangi #2 (I-9W) Port Qasim

(1-10) in industrial areas, Hasan Square (C-1), Liaquat-

abad (C-2), Garden (C-3), Gulistan-e-Johar (C-4) and

NIPA (C-5) in commercial areas of Karachi.

Table 1 shows the descriptions of the sampling sites.

The recorded results varied between residential, industrial

and commercial areas of Karachi.

Table 3 depicted the statistics (mean, median, st.dev,

maximum and minimum values) of measured trace

gases and PM10 concentration in different air monitoring

areas during the study period. The highest mean concen-

trations of particulate matter and trace infectious gases

were recorded in commercial and industrial areas and

graphically represented in Fig. 1-4, respectively.

Table 4 shows the ambient AQI values that has been

calculated with the recorded pollutant concentration

data of the selected sampling locations, showing the

degree/intensity of ambient air pollution category at

monitoring locations during a certain monitoring

period (e.g., 1, 8 or 24 h) due to its surrounding metro-

logy and human activities and its relation to health

hazards.

Table 2. AQI criteria and quality category

AQI AQI category Colour show

the category

0 - 50 Good

51 - 100 Moderate

101 - 150 Unhealthy for sensitive

151 - 200 Poor/Unhealthy

201 - 300 Very poor/very unhealthy

301 - 400 Hazardous

401 - 500 Very hazardous

>500 Very critical

USEPA 150

standard

Source: USEPA 2012; Gurjar et al. (2008).


Trace gases. Atmospheric trace gases (SO2, NO2 and

CO) were measured at twenty selected locations in

Karachi during the period of January to November

2015. Samples were collected twice in a month at each

location. The sampling time was 8 h for SO2, NO2 and

1 h for CO. The samples were collected by analyzers

designed and fabricated by environmental S.A.,

France.

The total average concentrations of SO2 at twenty

selected locations in Karachi was found 46.0 mg/m3 and

under the limit of annual World Health Organization

Table 3. Statistical values of the pollutants during the

study period in Karachi

Pollutants PM10 SO2 CO NO2

mg/m3

Residential areas

Mean 141.4 32.0 2.7 73.6Median 130.0 30.0 3.0 68.0St. Dev 5.9 1.3 0.3 0.8Max 192.0 40.0 0.5 106.0Min 117.0 25.0 0.1 54.0

Industrial areasMean 161.4 39.4 3.2 79.8Median 210.0 46.0 3.6 89.0St. Dev 4.7 2.0 0.3 1.1Max 298.0 76.0 5.1 141.0Min 81.0 29.0 2.3 59.0

Commercial areasMean 256.8 56.8 4.6 106.0Median 278.0 58.0 4.3 100St. Dev 4.1 2.2 0.4 1.3Max 319.0 72.0 4.1 136.0Min 151.0 50.0 3.7 82.0

80.0

70.0

60.0

50.0

40.0

30.0

20.0

10.0

0.0

SO2

Locations

0 5 10 15 20 25

Conc. of S

O2 in m

g/m

3

Fig. 1. Concentration of SO2 at selected locations

in Karachi.

Table 4. Air quality index (AQI) and air quality category at selected locations in Karachi city

Locations Code # Values Category Values Category Values Category Values Category

PM10 SO2 CO NO2

Jail Road R-1 119.0 Unhealthy 56.0 Moderate 43.0 Good 102.0 Unhealthy

Gulberg chowrangi R-2 98.0 Moderate 54.0 Moderate 40.0 Good 78.0 Moderate

Gulshan-e-Iqbal R-3 78.0 Moderate 43.0 Good 25.0 Good 66.0 Moderate

PECHS Society R-4 88.0 Moderate 36.0 Good 17.0 Good 58.0 Moderate

Model Colony R-5 82.0 Moderate 41.0 Good 34.0 Good 51.0 Moderate

Paramount ground, Landhi I-1W 126.0 Unhealthy 59.0 Moderate 51.0 Moderate 81.0 Moderate

Abbott Laboratoy, Landhi I-2W 130.0 Unhealthy 72.0 Moderate 39.0 Good 101.0 Unhealthy

Lucky Textile, Landhi I-3W 148.0 Unhealthy 69.0 Moderate 41.0 Good 102.0 Unhealthy

Naurus G. belt, SITE I-4E 169.0 Poor 101.0 Unhealthy 53.0 Moderate 103.0 Unhealthy

Siemens G. belt, SITE I-5E 172.0 Poor 76.0 Moderate 57.0 Moderate 109.0 Unhealthy

Manghopir, SITE I-6E 167.0 Poor 65.0 Moderate 43.0 Good 90.0 Moderate

Singer chowrangi, KIA I-7W 100.0 Moderate 59.0 Moderate 39.0 Good 81.0 Moderate

Chamra chowrangi, KIA I-8W 98.0 Moderate 62.0 Moderate 41.0 Good 86.0 Moderate

Korangi #2, KIA I-9W 91.0 Moderate 49.0 Good 34.0 Good 79.0 Moderate

Port Qasim I-10 64.0 Moderate 41.0 Good 26.0 Good 56.0 Moderate

Hasan Square C-1 162.0 Poor 79.0 Moderate 49.0 Good 100.0 Moderate

Liaquatabad C-2 168.0 Poor 82.0 Moderate 59.0 Moderate 105.0 Unhealthy

Garden C-3 183.0 Poor 96.0 Moderate 64.0 Moderate 108.0 Unhealthy

Gulistan-e-Johar C-4 147.0 Unhealthy 60.0 Moderate 47.0 Good 88.0 Moderate

NIPA C-5 98.2 Moderate 69.0 Moderate 42.0 Good 81.0 Moderate


(WHO) guideline values for the European Union (WHO

2000: 50 mg/m3). Total duration of sampling in this

study was 11 months (twice a month, 8 h for SO2 and

NO2, 1 h for CO). The highest concentration (76.0 and

72.0 mg/m3) of SO2 found in the industrial and

commercial areas at location I-4E and C-3, whereas the

lowest concentration (25.0 mg/m3) in residential area at

location R-4, respectively (Fig. 1). The main source of

SO2 emission in the city center is the combustion of

fossil fuel in automobile and industrial sectors.

The total average concentration of NO2 at the selected

locations in Karachi was found 92.0 mg/m3, which is

more than double of the annual guideline value of

WHO, 2005(40 mg/m3). The NO2 concentration in the

atmospheric environment enters from both natural

and anthropogenic sources. The major anthropogenic

source of NO2 emission is fossil fuel combustion in

vehicles and industries. The highest concentration of

NO2 (141.0 mg/m3) was found in industrial area, at

location I-5E with high traffic density and industrial

emission, whereas, the lowest concentration (54.0 mg/m3)

found at location R-5 in purely residential area

(Fig. 2).

The measured CO values varied between 1.5 to 5.8

mg/m3 in residential, industrial and commercial areas.

The maximum concentration (5.8, 5.3 and 5.1 mg/m3)

of CO was measured at the commercial and industrial

locations C-2, C-3 and I-5, whereas the lowest concen-

tration (1.5 mg/m3) was found at location R-4 in

residential area. The high concentration of CO in

commercial and industrial areas probably due to the

incomplete combustion of fossil fuel in faulty vehicles

and due to different mechanical and industrial

combustion. However, the total average value of CO

(11 months at these twenty sampling locations) in

Karachi was 3.7 mg/m3 (1-h sampling time) (Fig. 3)

which is under the WHO guidelins.

PM10 concentrations. The distribution parameters for

PM10 for residential, industrial and commercial areas

varied from 117.0 to 319.0 mg/m3, for residential areas

117.0 to 192.0 mg/m3, for industrial areas 136.0 to 298.0

mg/m3 and for commercial areas 151.0 to 319.0 mg/m3,

6.0

5.0

4.0

3.0

2.0

1.0

0.0

CO

Locations

0 5 10 15 20 25

Conc. of C

O in m

g/m

3

Fig. 3. Concentration of CO at selected locations

in Karachi.

160.0

140.0

120.0

100.0

80.0

60.0

40.0

20.0

0.00 5 10 15 20 25

Locations

Conc. of N

O2 in m

g/m

3

NO2

Fig. 2. Concentration of NO2 at selected locations

in Karachi.

350.0

300.0

250.0

200.0

150.0

100.0

50.0

0.0

PM10

0 5 10 15 20 25

Locations

Conc. of P

M10 in m

g/m

3

Fig. 4. Concentration of PM10 at selected locations

in Karachi.


respectively. In residential areas PM10 concentrations

were higher at locations R-1 (192.0 mg/m3) having high

traffic density and producing emission due to vehicular

emission and different commercial activities, In Industrial

areas PM10 concentrations were higher at locations I-

5E (298.0 mg/m3) and receiving higher emissions due

to industrial and vehicular emission, whereas in

commercial areas PM10 concentrations were higher at

location C-3(319.0 mg/m3). This location was surrounded

by roundabouts having automobile repairing shops,

unplanned rickshaws stand, and traffic jams due to

narrow and congested roads and they are receiving

higher emissions due to vehicles and commercial

activities. Overall mean concentration of PM10 at various

locations of residential, industrial and commercial areas

was 202.4 mg/m3 for Karachi region (Fig. 4). The PM10

in Karachi mostly emitted from vehicular and industrial

combustion producing fine fraction, which produces

severe health hazards particularly pulmonary disorder.

It can penetrate deep into the lungs and cause pulmonary

disorder.

In general, the average trace gases and PM10 concen-

trations were higher in commercial and industrial areas

with high traffic density than the residential areas. Most

of the commercial and industrial areas having trace

gases and PM10 concentrations exceeded the specified

permissible limits by USEPA (2012).

The ambient AQI values have been calculated with the

recorded pollutant concentration data of the selected

sampling locations presented in Table 4.

The calculated AQI values of PM10 at the selected

locations vary between a maximum of 183.0 and a

minimum of 64, respectively. Results of the calculation

of AQI values for PM10 at the selected locations show

moderate pollution in residential areas and poor or

unhealthy pollution in commercial and industrial areas.

Whereas, calculated AQI values for SO2 vary between

a maximum of 101.0 and a minimum of 36, for CO

vary between a maximum of 64.0 and a minimum of

17.0, for NO2 vary between a maximum of 109.0 and

a minimum of 51.0, respectively.

The results of air quality monitoring show that the

pollution concentrations were highly variable at different

locations. This is expected as the extent of air pollutants

depend on the active mobile and stationary pollutant

emitting sources and is influenced by meteorological

factors. It can also be seen that the concentration of

particulate PM10 pollutants exceeded the allowable

standard limit at all the locations with un-controlled

emission from transport vehicles. The concentration of

gaseous pollutants was observed to be within permissible

limits at all the selected locations. Results of the

calculation of AQI values for trace gases (SO2, CO and

NO2) at the sampling locations show good and moderate

pollution in residential areas whereas moderate or

unhealthy pollution found at commercial and industrial

locations.

Conclusion

Atmospheric pollution at twenty selected locations in

Karachi, Pakistan, was characterized in terms of trace

gases and PM. The average concentration of SO2 and

NO2 at the selected sampling locations in Karachi are

higher than the annual average of WHO guidelines,

may be due to the high content of sulphur in fossil fuel

and heavy traffic density whereas concentration of CO

is lower than WHO guideline values. Overall mean

concentration of PM10 at various locations of residential,

industrial and commercial areas was 202.4 mg/m3 for

Karachi region. Elevated concentrations of PM were

observed in Karachi city, but these were still lower than

most of the southeast Asian cities.

It can be concluded from this study that the concentration

of atmospheric pollutant in the environment shows

deterioration of air quality in the city. Observed values

exceeding the permissible limits in commercial and

industrial areas and in that residential areas having both

commercial and residential status of the city. The main

source of the pollution appears to be transportation due

to congestion and fossil fuel emission.

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Pakistan Journal of Scientific and Industrial Research,

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Papers of Journals

In �Text�

Park (2005), Aksu and Kabasakal (2004) and Evans

et al. (2000) (Park, 2005; Aksu and Kabasakal, 2004;

Evans et al., 2000)

In �References�

Evans, W.J., Johnson, M.A., Fujimoto, Cy. H., Greaves,

J. 2000. Utility of electrospray mass spectrometry

for the characterization of air-sensitive organolan-

thanides and related species. Organometallics, 19: 4258-

4265.

BooksCinar, A., Parulekar, S.J., Undey, C., Birol, G. 2003.Batch Fermentation:Modeling, Monitoring, and Control,250 pp. Marcel Dekker Inc., New York, USA.

Chapters in Edited BooksNewby, P.J., Johnson, B. 2003. Overview of alternativerapid microbiological techniques. In: RapidMicrobiological Methods in the Pharmaceutical Industry,M.C. Easter (ed.), vol. 1, pp. 41-59, 1st

edition,Interpharm/CRC, Boca Raton, Florida, USA.

Papers in ProceedingsMarceau, J. 2000. Innovation systems in building andconstruction and the housing industry in Australia.In:Proceedings of Asia-Pacific Science and TechnologyManagement Seminar on National Innovation Systemspp. 129-156, Japan Int. Sci. Technol. Exchange Centre,Saitama, Japan.

ReportsSIC-PCSIR. 2002. Biannual Report, 2000-2001; 2001-2002,Scientific Information Centre, Pakistan Councilof Scientific and Industrial Research, PCSIRLaboratories Campus, Shahrah-e-Dr. SalimuzzamanSiddiqui, Karachi, Pakistan.

ThesisSaeed, A. 2005. Comparative Studies on the Biosorptionof Heavy Metals by Immobilized Microalgal Cultures,Suspended Biomass and Agrowastes.Ph.D. Thesis, 248 pp., University of the Punjab,Lahore, Pakistan.

PatentsYoung, D.M. 2000. Thermostable Proteolytic Enzymesand Uses Thereof in Peptide and Protein Synthesis,US Patent No. 6,143,517, 7th November, 2000.

Data Set from a Database (information should beretrievable through the input)

Deming, D.; Dynarski, S. 2008. The lengthening ofchildhood (NBER Paper 14124) Cambridge, MA:National Bureau of Economic Research. Retrieved July21, 2008 from http:// www.nber.org/papers/w14124)DOI No...........

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