International Journal of Energy, Sustainability and Environmental...

International Journal of Energy, Sustainability and Environmental Engineering Vol. 1 No. 1 (September – October, 2014)

ISSN: 2394-3165

Editorial Advisory Board

Prof. Madhab Ranjan Panigrahi Orissa Engineering College Bhubaneswar 751 007 Dr Swaminathan Sivaram National Chemical Laboratory Dr Homi Bhabha Road Pune 411 008

Dr. Shashi Ahuja Department of Science & Technology New Delhi Dr. Sabbu Thomas Mahatma Gandhi University Priyadarshini Hills, Kottayam-686560 Kerala, India

Editorial Board

Dr. Amulya Kumar Panda National Institute of Immunology JNU Complex New Delhi – 110 067 Dr. Swachchha Majumdar Central Glass and Ceramic Research Institute Kolkata Dr. Mantu Bhuyan CSIR-North Eastern Institute of Science and Technology Jorhat, Assam Dr. T. K. Lohani Orissa Engineering College Bhubaneswar

Dr. Maya Nayak Orissa Engineering College Bhubaneswar

Dr. J. K. Meher Department of Computer Science and Engg Vikash College of Engg for Women Bargarh, Odisha, India Dr. Raghunath Mandal Institute of Media Studies Bhubaneswar

Editor: Dr. Biranchinarayan Tosh

E.mail: [email protected] Fax: 0091-06758-239723 Phone: 239737; 9437560248 Website: www.oec.ac.on

Published by Dr. Biranchinarayan Tosh on behalf of Hiranya Kumar Centre for Research & Development, Orissa Engineering College, Bhubaneswar 751 007 International Journal of Energy, Sustainability and Environmental Engineering is issued bimonthly by HKCR&D – OEC and assumes no responsibility for the statements and opinions advanced by the contributors. The editorial staff in the work of examining papers received for publication is assisted, in an honorary capacity, by a large number of distinguished scientists and engineers. Communications regarding contributions for publication in the journal should be addressed to the Editor, International Journal of Energy, Sustainability and Environmental Engineering, Hiranya Kumar Centre for Research and Development, Orissa Engineering College, Bhubaneswar 751 007 Correspondence regarding subscriptions and advertisements should be addressed to the Sales & Distribution Officer, Hiranya Kumar Centre for Research and Development, Orissa Engineering College, Bhubaneswar 751 007 Annual Subscription: Rs 1600.00 $ 300.00* Single Copy: Rs 320.00 $ 60.00* (*Inclusive of first class mail) For inland outstation cheques, please add Rs 50.00 and for foreign cheques, please add $ 10.00. Payments in respect of subscriptions and advertisements may be sent by cheque/bank draft, payable to Hiranya Kumar Centre for Research and Development, Orissa Engineering College, Bhubaneswar 751 007. Bank charges shall be borne by subscriber. Claims for missing numbers of the journal will be allowed only if received within 3 months of the date of issue of the journal plus the time normally required for postal delivery of the journals and the claim. © 2014 Hiranya Kumar Centre for Research and Development, Orissa Engineering College, Bhubaneswar 751 007

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International Journal of Energy, Sustainability and Environmental Engineering Vol. 1 Issue 1 (September – October, 2014)

CONTENTS

Editorial 2

Papers

Trace Metals in water from different sources of Bhubaneswar Town 3

Nibedita Pattnayak

Determination of Major and Trace Elements in Bittern for Possible Value Addition 8

Niva Nayak & Chitta R Panda

Sediment quality assessment through Geo-accumulation index of

Brahmani river-estuarine system, Odisha, India. 13

Subas Chandra Asa, Prasanta Rath

An Economic and Eco-Friendly Soil Conditioner: Fly Ash 16

Bismita Rout

Prediction of Nickel Binding Sites in Proteins from Amino acid Sequences by 19

Radial Basis Function Neural Network Classifier

G C Dash, M R Panigrahi, J K Meher, M K Raval

Sustainable Development in the conflicting scenario of Environment and Development 24

Chitta Ranjan Panda

Present practice of Municipality Solid Waste Management in Bhubaneswar, Odisha, India 28

Rabindra Panda, Amarendra Harichandan, Himansu Sekhar Patra, Kajal Parashar

Guidelines for Authors 35

Keyword Index 37

Author Index 38

2


Editorial……. Energy and Environment: The Key Factors in Sustainable Development

The increasing demand of affluent middle-class consumers has encouraged expansion of manufacturing

activities. Obviously, the demand-supply gap for energy and water gets widened and increase in their supply

means further climate change. The inevitable side effect is increased waste generation, and shortage of waste

handling and management capacities further increase the threat to environment. The impact of climate change

and environmental degradation may be witnessed everywhere from agriculture, health to natural resources. The

unequal distribution of these resources is only aggravating the problem further, especially in developing

countries. On the other side, societal demand for a cleaner environment and a better quality of life is increasing.

Therefore, sustainable solutions to these problems are the need of the hour to ensure that our future generations

live in a better environment.

Every economic, environmental and developmental issue of today centers on ‘Energy’. Energy is

directly linked with the key global challenges that the world faces -- poverty alleviation, climate change, and

global, environmental and food security. The world needs clean, efficient and reliable energy services to meet its

long-term needs for economic growth and development. But, as happening now, emissions from the burning of

conventional and non-renewable fossil fuels are major contributors to urban air pollution, acidification of land

and water, and the unpredictable effects of climate change. Energy-related greenhouse gas emissions are

projected to increase by 57 per by 2030. The undeniable fact is that current patterns of energy production and

consumption are unsustainable and threatening the environment on both local and global scales. Obviously,

reducing CO2 and other greenhouse gas emissions from the burning of fossil fuels is at the heart of current

efforts to address climate challenge.

An accepted fact is that the accelerated use of renewable and more energy efficient technologies can

provide ‘win-win’ options to tackle global and local development challenges. In the current context of rising and

volatile energy prices, many developing countries are looking for alternatives to imported energy sources.

Switching to low- or zero-carbon fuels can contribute to significant emission reductions. The International

Energy Authority estimates that a 50 per cent reduction in CO2 emissions by 2050 would require an increase to

46 per cent share of renewable energy in global power generation. The five most used sources of renewable

energy – hydropower, solar, wind, geothermal and biomass -- are already contributing and achieving higher

levels of penetration in energy generation and consumption.

Local energy renewable resources and improved energy efficiency help create local jobs and save

foreign exchange. They also contribute to increased energy security through increased energy supply and

climate security through reduced greenhouse gas emissions. Pursuing energy and climate security in tandem

will create greater scope for diversifying energy sources, increasing local energy production, improving access

to energy by the world’s poor and reducing dependence on oil and gas imports.

Sustainable development is nothing but development that meets the needs of the present generation

without compromising the ability of future generations to meet their needs. Sustainability thus emerges as a

crucial component of any successful paradigm to guide development in the new Millennium. It requires a new

emphasis on the nature and size of inputs to development, especially energy, resource, chemical and other

material input. Related terms and concepts that are emerging include Eco-efficiency, Eco-sustainability, Eco-

design, Product Life – Cycle, and Green Productivity.

Dr. M.R. Panigrahi

M.Tech (IIT Chennai); Ph.D (IIT Kharagpur)

Raman Awardee (CSIR)

(For Advanced Research on Renewable Energy)

DIRECTOR ACADEMIC / PRINCIPAL,

Orissa Engineering College, Bhubaneswar

[email protected]

International Journal of Energy, Sustainability and Environmental Engineering

Vol. 1 (1), September 2014, pp. 3-7

Trace Metals in water from different sources of Bhubaneswar Town

Nibedita Pattnayak

Department of Chemistry, Orissa Engineering College, Bhubaneswar – 751 007

Received 25 August 2014; accepted 02 Septembert 2014

Abstract In industrial zone different types of industries emits highly cocentrated polluted water. The concentrated of

pollution depends upon the situation of point with respect to the industries that emits the polluted water. A study was

conducted to detect some trace metals like iron, manganese, copper, zinc, nickel, chromium in the five different sources of

drinking water in Bhubaneswar, a rapidly growing town of Odisha. The study was extended over a period of one year

collecting in every month. The study reveals that the parameters are within the specified limits of WHO standards except

some are above the limit.

Key words Pollutants, Trace metals, Iron, Manganese, Copper, Zinc, Nickel, Chromium

Humans ingest water as plain drinking water, water in

other beverages, and water in food (inherent, and/or

added during preparation) and they also obtain some

water from metabolism of food. Approximately one

third of the daily average fluid intake is thought to be

derived from food. Drinking water, regardless of its

source, may be subjected to one or more of a variety

of treatment processes aimed at improving its safety

and/or aesthetic quality. Water is one of the

abundantly available substances in nature. Pollution

of land, water and air as a result of increasing in

population is a challenge of serious dimensions. The

main purpose of water analysis is to evaluate methods

of treatments of ground water with to reuse or

dispose, ascertain quality of water.

Material and Method

Five water samples are collected in every month from

different sites in polythene bottles which are

thoroughly cleaned with 1:1 HNO3, rinsed several

times with distilled water and dried1. The collected

water samples were grouped under following

categories.

S1 – Raw water from river Kuakhai

S2 – Tap water

S3 – Tube well water

S4 – Open well water

S5 – Kedargouri spring well

Monitoring Period

Monitoring was done during August 2011 to July

2012 in every month covering a total hydrological

cycle i.e. pre-monsoon, monsoon and post-monsoon

periods.

Analytical Procedure

The analytical grade chemicals were made metal free

by complexing the metal with ammonium pyrrolidine

dithiocarbamate (APDC) and extracting the metal

complex in methyl isobutyl ketone (MIBK). Iron was

removed by extraction with acetyl acetone.

Flame atomic absorption spectrophotometric

methods were used for all trace metals. Prior to

analysis samples were concentrated ten folds by

controlled evaporation. During evaporation, samples

were acidified to avoid losses due to adsorption on the

walls of the container. The samples were then cooled

and metals were complexed with ammonium

pyrrolidine dithiocarbamate (APDC). The metallic

complexes were extracted in methyl iso-butyl ketone

(MIBK). After concentration, iron, manganese,

copper, zinc, nickel, chromium were determined by

Corresponding Author:

Nibedita Pattnayak

e-mail: [email protected]

4 Int J Ener Sustain Env Engg, September 2014

atomizing in Perkin-Elmer analyst 700 (Model MHS-

15) atomic absorption spectrophotometer. Resonance

lines and hollow cathode lamps of respective metals

were used and the instrument was optimized for

maximum response2.

Result and Discussion

The range and mean values of trace metals of

different water samples collected from sources like

river, pond, open well, tube well, tap water were

given in the Table 1-6 and the month wise

fluctuations of trace metal content in these sources of

water were shown in fig.1 to 6.

Iron

Table 1 Concentration of Iron in water sample, in mg/L

Month S1 S2 S3 S4 S5

Aug,2011 1.31 0.25 0.29 1.55 1.46

Sep,2011 1.08 0.09 0.57 0.04 0.05

Oct,2011 0.15 0.3 0.1 0.12 0.12

Nov,2011 0.09 0.04 0.69 0.01 0.02

Dec,2011 0.49 0.58 1.58 0.08 0.08

Jan,2012 0.25 0.09 2.5 0.04 0.04

Feb,2012 0.08 0.09 1.05 0.07 0.07

Mar,2012 0.05 0.05 0.37 0.04 0.04

Apr,2012 0.72 0.06 0.25 0.07 0.07

May,2012 0.57 0.16 0.39 0.06 0.06

June,2012 0.35 0.15 0.28 0.49 0.49

July,2012 0.98 0.03 0.25 0.04 0.03

Mean 0.51 0.157 0.693 0.217 0.211

S1 – Raw water from river Kuakhai S2 – Tap water S3 –

Tube well water S4 – Open well water S5 – Kedargouri

spring well

The maximum allowable concentration of iron in

drinking water is 0.1 mg/l according to WHO report,

1971. But according to Ministry of Works and

Housing Report, 1975, the maximum allowable

concentration and the permissible concentration of

iron drinking water is 1.0 mg/l and 0.3 mg/l

respectively3. Out of twelve samples collected from

kuakhai river raw water only two samples (Aug, 2011

and Sep, 2011) were found to contain iron content

above the maximum allowable concentration.

Similarly three samples (Dec, 2011 and Jan, 2012

and Feb, 2012) of tube well water, one sample (Aug,

2011) of open well and Kedargouri spring water were

found to contain iron content above the maximum

allowable concentration which is given in Table 1.

However, the average values of all the categories

of samples never exceeded the maximum allowable

concentration.

Manganese

The maximum allowable concentration and the

permissible concentration of manganese in drinking

water is 0.5 mg/l and 0.1 mg/l, respectively according

to Ministry of Works and Housing Report, 1975. The

average values of all the categories of samples never

exceeded the maximum allowable concentration

which is given in Table 2.

Table 2 Concentration of Manganese in water sample,

in mg/L


Aug,2011 0.4 0.1 0.6 0.1 0.1

Sep,2011 0.6 0.1 0.7 0.09 0.1

Oct,2011 0.2 0.3 0.4 0.2 0.4

Nov,2011 0.3 0.1 0.6 0.5 0.2

Dec,2011 0.1 0.1 0.3 0.1 0.1

Jan,2012 0.3 0.2 0.8 0.2 0.1

Feb,2012 0.2 0.1 0.3 0.2 0.2

Mar,2012 0.1 0.1 0.6 0.1 0.1

Apr,2012 0.3 0.2 0.1 0.2 0.2

May,2012 0.2 0.2 0.4 0.1 0.1

June,2012 0.2 0.05 0.25 0.05 0.2

July,2012 0.1 0.1 0.3 0.1 0.1

Mean 0.25 0.1375 0.446 0.162 0.158



spring well

Copper


permissible concentration of copper in drinking water

is 3.0 mg/l and 1.0 mg/l respectively according to

ICMR report. But according to WHO report the

values are 1.5 mg/l and 1.0 mg/l respectively4. It was

found that all the categories of water examined were

free from copper pollution, Table 3.

Zinc

The maximum allowable concentration and

permissible concentration of zinc in drinking water

are 15.0 mg/l and 5.0 mg/l respectively according to

ICMR report. But according to ISI the values are 10.0

mg/l and 5.0 mg/l respectively. It was found that all

the categories of water contained zinc much below

the permissible limit (Table 4).

5 Pattnayak N: Trace Metals in Water

Table 3 Concentration of Copper in water sample, in

mg/L


Aug,2011 0.026 0.04 0.03 0.027 0.02

Sep,2011 0.014 0.018 0.023 0.011 0.017

Oct,2011 0.026 0.017 0.034 0.03 0.02

Nov,2011 0.017 0.012 0.035 0.023 0.013

Dec,2011 0.04 0.014 0.037 0.009 0.009

Jan,2012 0.05 0.018 0.01 0.007 0.008

Feb,2012 0.041 0.025 0.012 0.009 0.007

Mar,2012 0.045 0.05 0.021 0.12 0.006

Apr,2012 0.35 0.03 0.04 0.14 0.007

May,2012 0.03 0.032 0.009 0.15 0.1

June,2012 0.04 0.035 0.007 0.16 0.12

July,2012 0.05 0.013 0.005 0.006 0.009

Mean 0.061 0.025 0.022 0.058 0.028



spring well

Table 4 Concentration of Zinc in water sample, in mg/L


Aug,2011 0.04 0.74 0.7 0.096 0.74

Sep,2011 0.243 0.47 0.58 0.034 0.33

Oct,2011 0.043 0.78 0.6 0.09 0.34

Nov,2011 0.05 0.79 0.63 0.14 0.38

Dec,2011 0.069 0.69 0.71 0.13 0.23

Jan,2012 0.094 0.67 0.67 0.125 0.39

Feb,2012 0.087 0.68 0.73 0.25 0.44

Mar,2012 0.065 0.82 0.79 0.24 0.63

Apr,2012 0.07 0.84 0.82 0.19 0.7

May,2012 0.023 0.91 0.65 0.18 0.62

June,2012 0.095 0.82 0.67 0.142 0.64

July,2012 0.087 0.67 0.65 0.142 0.42

Mean 0.081 0.74 0.683 0.147 0.488



spring well

Nickel


permissible concentration of nickel in drinking water

are not fixed either by WHO, 1971 or by Ministry of

Works and Housing, Government of India, 1975. But

the recommended maximum concentration of nickel

in irrigation water (Ayers and Westcott, 1976) is fixed

to be 0.20 mg/l5. It was found that all the categories of

water contained nickel much below the permissible

limit, Table- 5. Table 5 Concentration of Nickel in water sample, in

mg/L


Aug,2011 0.025 0.025 0.014 0.017 0.026

Sep,2011 0.015 0.015 0.02 0.03 0.007

Oct,2011 0.025 0.025 0.018 0.018 0.027

Nov,2011 0.025 0.03 0.019 0.019 0.01

Dec,2011 0.026 0.02 0.04 0.019 0.02

Jan,2012 0.03 0.015 0.05 0.016 0.23

Feb,2012 0.035 0.02 0.034 0.022 0.03

Mar,2012 0.035 0.025 0.032 0.023 0.029

Apr,2012 0.03 0.025 0.031 0.022 0.02

May,2012 0.025 0.029 0.03 0.018 0.023

June,2012 0.025 0.022 0.03 0.019 0.024

July,2012 0.03 0.018 0.032 0.018 0.026

Mean 0.027 0.022 0.029 0.020 0.039



spring well

Chromium Table 6 Concentration of Chromium in water sample,

in mg/L.


Aug,2011 0.03 0.02 0.02 0.02 0.017

Sep,2011 0.02 0.008 0.01 0.008 0.02

Oct,2011 0.03 0.04 0.04 0.04 0.012

Nov,2011 0.04 0.05 0.03 0.05 0.03

Dec,2011 0.05 0.06 0.032 0.043 0.05

Jan,2012 0.087 0.065 0.047 0.046 0.055

Feb,2012 0.06 0.06 0.06 0.047 0.045

Mar,2012 0.05 0.05 0.045 0.06 0.047

Apr,2012 0.04 0.06 0.04 0.043 0.049

May,2012 0.07 0.03 0.05 0.042 0.05

June,2012 0.081 0.05 0.052 0.044 0.052

July,2012 0.085 0.08 0.049 0.046 0.056

Mean 0.054 0.048 0.040 0.040 0.040



spring well

The maximum permissible level of chromium,

according to WHO report and ICMR in drinking

water is 0.05 mg/l. It was found that five samples

(Jan, Feb, May, June, July, 2012) from Kuakhai river

water, five samples (Dec, 2011, Jan, Feb, Apr, July,


2012) from tap water and one sample (Mar, 2011)

from open well contained chromium above the

maximum allowable concentration which is given in

Table 6.

However, the average values of all the categories

of samples never exceeded the maximum allowable

concentration.

Fig. 1 – Fluctuation of Iron contents in different categories

of water samples

Fig. 2 – Fluctuation of Manganese contents in different

categories of water samples

Fig. 3 – Fluctuation of Copper contents in different


Fig. 4 – Fluctuation of Zinc contents in different categories

of water samples

Fig. 5 – Fluctuation of Nickel contents in different


Fig. 6 – Fluctuation of Chromium contents in different


00.51

1.52

2.53

Iro

n (

mg/

l)

SAMPLING MONTHS

S1

S2

S3

S4

S5

00.20.40.60.8

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,mg/

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SAMPLING MONTHS

S1

S2

S3

S4

S5

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0.20.25

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SAMPLING MONTHS

S1

S2

S3

S4

S5

0

0.2

0.4

0.6

0.8

1

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01

1

Sep

,20

11

Oct

,20

11

No

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01

1

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1

Jan

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12

Feb

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12

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2

May

,20

12

Jun

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SAMPLING MONTHS

S1

S2

S3

S4

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0.15

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SAMPLING MONTHS

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SAMPLING MONTHS

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7 Pattnayak N: Trace Metals in Water

Conclusion Along with the treatment processes, the drainage

system of Bhubaneswar city should be improved. In

some cases the values are above the permissible limit.

The parameters related to such pollution are well

studied and interpreted to its maximum extent and

utmost care. The entire parameters are plotted to the

graphs in excel sheet. Wherever the maximum

permissible limit according to WHO standard is

available they are plotted. As a whole the present

investigation reveals that the water gets contaminated

from various sources of natural as well as

anthropogenic origin, which badly needs purification

for safe use of dependent inhabitants6.

References

1. APHA, Standard methods for examination of water

and waste water (Am Pub Heal Assoc, New York),

1998, 522.

2. Pande S P & Hasan M Z, Indian J Env Health, 20

(1978) 121.

3. Kannan K, Fundamentals of Environmental Pollution

(S. Chand and Company Ltd., New Delhi), 1991.

4. Sahu B K, Das H K, Behera S K & Singh, B C, J

Teach Res Chem, 1 (1994) 47.

5. Samantray P, Mishra B K, Panda C R & Rout S P,

Indian J Human Ecol, 26 (2009) 153.

6. Das H K, Das A, Mishra B, Das S K & Bhuyan N K, J

Geol Assoc Res Centre, 21 (2013) 213.


Vol. 1 (1), September 2014, pp. 8-12

Determination of Major and Trace Elements in Bittern for Possible Value

Addition

Niva Nayaka & Chitta R. Panda

b

aOrissa Engineering College, Bhubaneswar, Odisha

bCSIR-Institute of Minerals and Materials Technology, Bhubaneswar, Odisha

Received 30 August 2014; accepted 05 September 2014

Abstract Sea is considered as a storehouse of chemicals when land based resources become depleted. The waste

seawater bittern rejected at solar salt fields could be utilised for the recovery of valuable marine chemicals. A study

was carried out for the determination of major and trace elements present in brine and bittern to exploit the possibility

of producing various economically important marine chemicals. From the study it is found that every naturally

occurring element is found in sea water and moreover, six major ions constitute more than 98 % of dissolved solids.

They are sodium ion (Na+), chloride (Cl

-), sulphate (SO4

2-), magnesium ion (Mg

2+), calcium ion (Ca

2+), and potassium

ion (K+). Present attempt of bittern characterisation could provide possible utilisation of waste sea bittern, which is a

rich source of potassium and magnesium.

Keywords Bittern, Brine, Salt, Major elements

The Oceans of earth are aqueous, electrolytic

solutions, covering about 71 % of the earth’s

surface1. Sea water is a multiphase system

consisting of a solution of high ionic strength and

suspended particles which include living organisms,

their remains, terrestrially derived minerals, and

material derived from in situ inorganic processes.

The dissolved materials in sea water may be broadly

classified into (i) major constituents, (ii) trace

elements, (iii) nutrients and (iv) organic materials.

It contains an average of 3.5% of various elements

in solution and hence each cubic mile of seawater

holds 166 million tons of solids. Of the 60 elements

reported from seawater nine most abundant

elements constitute over 99% of the total dissolved

solids out of which sodium and chlorine constitute

85.2% of dissolved solids in seawater2. The

elements which are in constant proportion to one

another are chloride 54.8% of total salt, sodium ion

30.44%, sulfate ion 7.5%, magnesium ion 3.7%,

calcium ion 1.2%, potassium ion 1.1%, carbonate

ion 0.3 %, bromide ion 0.2 % and the borate ion

0.07%3. As the demand for land based resources are

increasing and due to rapid depletion, the emphasis

is being shifted to alternate sources that are

abundant and unexploited. Seawater that covers

71% of the earth’s surface holds about 330 million

cubic miles of water and is an important terrestrial

renewable resource1. The history of extraction

processes goes back to the Chinese who started

extraction of common salt prior to 2200 BC, after

which seawater became the principal source of salt

production 4.

With the development of science newer

processing techniques for recovery of minerals from

seawater have come into play. However, more

emphasis has been given to the complete utilization

of the seawater and bittern. Seawater bittern is the

waste by-product rejected at the common salt

manufacturing plants. After the separation of salt

between 24-290Be' density, the left over viscous

solution of 29-300 Be' is called ‘bittern’ and the

major constituents of which are sodium chloride,

magnesium sulfate, magnesium chloride and

potassium sulfate along with a small quantity of

sodium sulfate, bromide, borax and some other

minor constituents5. It could be easily imagined the

production of huge tonnage (10.8 MT) of bittern

from different salt industries of our country are

being wasted. Considering it as a cheap source, the

strategic metals can be recovered by further

evaporation under controlled conditions to get the


Niva Nayak


9 Nayak N & Panda C R: Determination of Major and Trace Elements

crude salt and mixed salt. Hence, bittern can be

directly processed to recover magnesium,

potassium, bromide, boron and other economically

important chemicals.

In India, the salt production industries are

located at the coastlines of India: the Arabian Sea

and the Bay of Bengal. The western coast salt

industries are situated in Maharastra and Gujarat,

while the eastern coast salt industries are situated in

Orissa, West Bengal, Tamilnadu and Andhra

Pradesh. Recently the salt and marine chemical

industries are passing through a crucial period,

arising out of massive shrimp cultivation. For a ton

of shrimp produced nearly 1.8 tons of debris is

discharged as a result of which the entire seawater

gets contaminated and adversely affect the salt

farming. If this trend continues one has to think of

alternative method of making salt and other

chemicals from seawater bittern. With such a rising

number of salt manufacturing plants, where the

generation of bittern is huge tonnage, the extraction

of valuable chemicals or metals will be worthwhile

with the help of innovative advance technology.

Hence, attempt has been taken in this study to

initially make speciation of the available metal

values present in brine/bittern before adopting the

recovery processes for extraction.

Materials and method

Sample collection The state of Orissa has a long coastline and one

would expect large and small salt works dotting the

coast producing substantial quantities of salt for

industrial and for human consumption. In the

beginning of the season the density of seawater is

between 1.50 Be' (Baume) to 2

0 Be' and rises to 4

0

Be' by the end of March. The rise in density which

is affected by low wind velocity and high humidity

reaches at 250 / 26

0 Be' crystallising the salt. The

bottom is left over at the end of manufacturing

season (at the end of monsoon season) and collected

in deep ponds. The bittern samples were collected

from these ponds along with brine in a

polypropylene container. The samples under study

were collected from Huma, Solar salt field, Ganjam,

Orissa.

Reagents

The reagents used for analysis of brine and bittern,

viz. EDTA, KOH, NH4Cl, BaCl2, AgNO3, KSCN,

KCl, NaCl, Ferric Ammonium Sulfate, Eriochrome

black-T and Pattern Reed indicators are of AnalaR

grade. Similarly, HCl, HNO3, ethyl alcohol, nitro

benzene and liquid NH3 used as solvents are of

commercial grade.

Chemical analysis of brine and bittern

Firstly, the brine and bittern 26.50 Be' are filtered to

remove suspended particles and are used as such

without any further pre-concentration. Bittern of

26.50 Be' is then subjected to artificial desalination

resulting 290 Be' which along with the brine was

subjected to analysis. The pH and Electrical

conductivity are measured. Suitable aliquot of

sample were diluted with distilled water and were

analysed for the major elements like Mg, Ca, Na, K,

SO42-

, Cl-

and trace elements like Fe, Cr, Mn, Si,

Ni, Co, Sb, Al and Boron.

Measurement of pH and EC

The pH of the seawater and bittern were measured

by using pH meter (ORION MODEL 1260) with

glass electrode. It was first standardized against

freshly prepared buffer solutions of known pH

values of required range (pH = 4.0, 7.0, 9.2) and

then pH of the samples were measured. The

electrical conductances of samples were measured

by ORION MODEL 1260 with Conductivity Bridge

using the standard procedure.

Estimation of Ca & Mg

The calcium and magnesium content of seawater

and bittern were determined by complexometric

titration with EDTA. The diluted sample maintained

at pH 10 by adding suitable buffer like NH4Cl /

NH4OH was titrated against EDTA using

Eriochrome black-T indicator for total Ca & Mg.

For estimation of calcium 8M KOH was used as

buffer for maintaining pH-12 along with Pattern

Reed Indicator. In both the cases colour changes

from wine red to blue. The Mg concentration was

determined by subtracting the volume obtained for

Ca from the total Ca + Mg volume.

Estimation of Sulfate (SO42-

) (Gravimetric) The diluted samples were precipitated near its

boiling point as barium sulfate (BaSO4) in an acidic

medium (HCl) by the addition of barium chloride

solution. The resulted precipitate was then boiled,

filtered, washed with hot water until free of

chloride. Then the precipitate was dried, ignited and

weighed as BaSO4.

Estimation of Chloride

Chloride was estimated by Volhard’s titration

method. The sample solution was treated with an

excess of standard silver nitrate and the residual

silver nitrate was determined by titration with

standard thiocyanate using ferric alum (40% Ferric

Ammonium Sulfate with water) indicator. As the

AgCl is more soluble than AgSCN, nitrobenzene

was added for the coagulation of AgCl. The sample

10

Int J Ener Sustain Env Engg, September 2014

solution was titrated until a permanent faint reddish-

brown colouration appears.

Atomic Absorption Spectrometry (AAS)

The elements namely Fe, Mn, Ni, Cr, Co and Sb

were analysed by Atomic Absorption Spectrometer

(Shimadzu model AA6300) where suitable hollow

cathode lamps were used for the absorption of

characteristic lines by the analyte and the

concentration vs. absorbance plot obeying the

Beers - Lamberts law counts the concentrations of

the corresponding elements.

Inductively Coupled Plasma Spectrometry

(ICP-OES) The quantitative evaluation of elements like Al, Ti,

Si, and B was done by ICP (PERKIN ELMER,

PLASMA-400) spectrophotometer. A high

temperature (10,000K) Argon Plasma source is used

for the excitation of the element and the

concentrations are measured as a function of the

emission intensity of the emission spectra generated

by the particular element.

Estimation of Na & K

The concentration of Na & K was determined by

Flame Photometer (ELICO - MODEL CL 22D)

using specific filter for the wavelength of particular

element. Calibration curves were made with

suitable standard solutions made from AR grade

KCl and NaCl and the concentrations of the

unknown samples were calculated.

Results and Discussion As solar evaporation is the cheapest and most

economic means for the pre-concentration of sea-

bittern, in salt industries, sea water is subjected to

solar evaporation for recovery of salts. The sea

water and the bittern of 26.50 Be' collected after salt

removal were subjected directly for analysis of pH,

EC major and trace element. 1500 ml of 26.50

Be'

bittern is further subjected to artificial desalination

resulting 910 ml of 290

Be' bittern, causing an

appreciable volume reduction to 60.66 %. This

desalinated bittern was also analysed for pH, EC,

major and trace elements.

Table 1 pH and EC of brine and bittern

Parameter Brine

20 Be'

Bittern

26.50 Be'

Bittern

290 Be'

pH 8.15 6.949 6.71

EC (μS/cm) 26200 515000 505000

The pH is one of the most important factors,

which controls the aquatic environment. All the

chemical and biological reactions are directly

dependent upon the pH of the system. It is typically

limited to a range between 7.5 and 8.4 in

seawater

6.

The pH of collected sea water is 8.15 whereas the

26.50 Be' bittern is ~ 6.949. Similarly, for 29

0 Be'

bittern pH is found to be ~ 6.71 as shown in Table

1. Seawater is generally alkaline in nature. This

alkalinity is due to the presence of the bicarbonates

(HCO3-), carbonates (CO3

2-) and the (H2BO3

-)

7.

During solar evaporation as the bicarbonates and

carbonates are removed as CaCO3, the pH of the

bittern does not remain alkaline. After removal of

salt the 26.50 Be' bittern changes to 29

0 Be' where a

slight decrease in pH is observed.

Table 2 Major elements (gms/lit) in brine and bittern

Major

Elements

Brine

20 Be'

Bittern

26.50 Be'

Bittern

290 Be'

Mg 1.223 30.633 49.607

Ca 0.28 0.130 0.100

SO42-

1.983 42.82 64.70

Cl- 18.73 185.389 191.979

Na 4.5 73.75 53.75

K 0.1 7.313 10.875

Table 3 Trace elements (mgs/lit) in brine and bittern

Trace

Elements

Brine

20 Be'

Bittern

26.50 Be'

Bittern

290 Be'

Al 0.01 nd nd

B 4.3 37.30 48.49

Co 0.11 4.67 2.65

Cr 0.20 2.01 1.74

Fe 0.20 7.9 7.0

Mn 0.21 0.99 0.68

Ni 0.16 0.03 0.1

Sb 0.0004 7.0 6.0

Si 2.9 nd nd

Similarly, the sea water has a very high

conductivity due to the amount of total dissolved

salts. During artificial desalination or volume

reduction the water level decreases with increase of

dissolved solids, thus contributing to higher

conductivity values8. The electrical conductivity of

sea water is measured to be 26200 μS/cm whereas it

is 515000 μS/cm for 26.50 Be' bittern due to the

volume reduction during solar evaporation. It is

dependent upon the ionic concentration9 and ionic

mobility of the mineral content in solution. These

conductive ions come from dissolved salts and

inorganic materials such as alkalis, sulphides and

carbonate compounds10

. However, the electrical

conductivity of 290

Be' Bittern is found to be

505000 μS/cm showing a lesser value than 26.50 Be'

bittern. This may be due to the removal of NaCl

during artificial desalination from 26.5 to 290 Be'.

11 Nayak N & Panda C R: Determination of Major and Trace Elements

The most abundant dissolved ions in seawater

are sodium, chloride, magnesium, sulphate and

calcium11

. The concentrations of these ions are high

due to the arrival of more salts by rivers with time.

The analysis data for various important elements in

brine and bittern are given in Table 2 and 3. It

shows that with progressive evaporation of sea

brine the concentration of some major elements

increases while some decreases. The concentration

of major elements like Mg, K and SO42-

anion

increases appreciably with the increase in density.

This is because Mg and K salt does not precipitate

out below 290

Be'. The concentration of Ca falls

with rise in density and remains almost constant

from 26.50 Be' to 29

0 Be' Bittern. In this study of

artificial desalination the 290

Be' bittern shows the

negligible concentration of calcium. This is due to

the fact that solid fractions of calcium carbonate and

calcium sulphate separated between 10-170 Be' and

17-240 Be' density, respectively and common salt

within the density range of 24-290

Be' during solar

evaporation or artificial desalination. This is due to

very long residence times of sodium and chlorine in

sea water, while calcium (vital for carbonate

formation) tends to precipitate much more quickly 12

. This is further supported by Anthoni J.F. that sea

salt can be made by evaporating sea water, may be

artificially or naturally13

. Major amount of sodium

chloride is removed within density of 290

Be' and

some percentage of sodium chloride is carried away

with the waste liquor bittern showing higher

concentration than 26.50 Be'. This may be due to the

presence of MgCl2, KCl and other chloride bearing

cations present in the bittern. Similarly, SO4 2-

anion

although is removed as calcium sulphate in the

process of evaporation, the SO42-

content is also

enriched. This may be attributed due to the presence

of magnesium and potassium as magnesium and

potassium sulphate in the system. Several reports

have been appeared on this aspect of utilisation and

extraction of valued chemicals from sea water 14

.

The presence of trace elements in seawater is

generally due to the riverine inputs of weathering

product of the exposed continent and inputs

resulting from the interaction of seawater with

oceanic crust. It is observed from the table that the

concentration of Co, Cr, Fe, Mn and Sb increases

from sea water to 26.50 Be' bittern but the

concentration is found to be less in 290 Be' bittern.

Generally, Aluminium occurs as Al3+

(aq) under

acidic conditions, and as Al (OH)4- (aq) under

neutral to alkali conditions. Table 3 shows a less

concentration of Aluminium in seawater whereas

the concentration of Al is not detected in 26.50 Be'

and 290 Be' bittern. Similarly, Silicon which

remains as silicic acid in water is found to be 2.9

mgs/l in the seawater and remains undetected in

bittern. This may be due to co-precipitation with Na

and Ca salts. The Boron content in sea brine, bittern

and marine by-product was also studied by

Dhandhulika & Seshadri14

. Boron occurs as B(OH)3

(aq) or B(OH)4- (aq)in seawater. Its concentration

varies with a large proportion as compared to the

other trace elements. Also the boron concentration

is found to be higher than the other mentioned

elements in bittern.

Conclusion Indian Salt industry produced around 15.0 million

tonnes of salt every year. Bittern generated in Salt

industry contains enriched Potassium and

magnesium salts in addition to other important

chemicals. Potential recovery of chemicals from

bittern in India has not been fully exploited.

Considering significance of developing indigenous

source of supply for Potash and Magnesia which are

important both for the Agricultural and strategic

reasons, sea bittern could be utilized to recover

potassium and magnesium. There are no viable land

based Potash reserves in India but it has seawater,

which is a possible source of Potassium salts

although in low concentration. With no significant

land based source of potash, India imports it’s entire

requirement of potash. Besides potassium and

magnesium, it is also possible to recover sodium

chloride, sodium carbonate, bromine, and other

strategic metals and chemicals out of this. But the

processing routes have the further disadvantage that

large quantities of seawater must be handled. So it

is better to extract these salts from the bittern for

which analysis of bittern plays the major role. In

other way this can also simultaneously solve the

disposal of such a huge quantity of waste generated

at salt field.

References

1 Sverdrup H U, Jhonson M W & Fleming R H, The

oceans, Their Physics, Chemistry and General

Biology (Prentice-Hall, Englewood Cliffs, N. J.),

1942, 1087.

2 Harvey H W, The Chemistry and Fertility of Sea

Waters (Cambridge Univ. Press London), 1960, 240.

3 Mero J L, The Mineral Resources of the Sea, In:

Elsevier Oceanography Series (Elsevier Publishing

Company,Amsterdam-London- New York), 1965, 25.

4 Armstrong E F & Miall L M, Raw Materials from the

Sea (Chemical Publishing Co.,Brooklyn, N.Y.), 1946,

196.

5 Estefan S F, Hydrometallurgy, 10 (1983) 39.

6 Chester J & Roy T, Marine Geochemistry. (Blackwell

Publishing, ISBN 978-1-118-34907-6) 2012.

7 James D B, Chemistry and Industry, 1977, 550.

12

Int J Ener Sustain Env Engg, September 2014

8 LCRA, Water Quality Indicators. In Colorado River

Watch Network, 2014.

9 EPA, 5.9 Conductivity. In Water: Monitoring and

Assessment, 2012.

10 Miller R L, Bradford W L & Peters N E, Specific

Conductance: Theoretical Considerations and

Application to Analytical Quality Control. In U.S.

Geological Survey Water-Supply, 1998.

11 Hogan C M, Calcium. ed. Jorgensen A & Cleveland

C, Encyclopedia of Earth. National Council for

Science and the Environment, 2010.

12 Pinet P R, Invitation to Oceanography. (St. Paul:

West Publishing Company). 1996, 126.

13 Anthoni J F, Report of the Royal Society, 2005

14 Dhandhukia M M & Seshadri K, Salt Res & Ind, 7

(1970) 87.


Vol. 1 (1), September 2014, pp. 13-15

Sediment quality assessment through Geo-accumulation index of Brahmani

river-estuarine system, Odisha, India.

Subas Chandra Asa1*

, Prasanta Rath2

1*

Dept. of Chemistry, Mohan Subudhi College, Baramba, Cuttack, Odisha 2Dept. of Chemistry, School of Applied Sciences, KIIT University, Bhubaneswar


Abstract Geo-accumulation index (Igeo) is a technique of rating sediment quality and an effective tool to assess the

sediment quality with respect to heavy metals. Twenty five sediment samples were collected from the whole stretch of

river Brahmani and near shore. Concentrations of some selective heavy metals such as Fe, Mn, Co, Ni, Cu, Zn, Cr, Pb

and Cd were determined by using atomic absorption spectrophotometer. The values of Igeo of the samples were found in

the range of 0 – 4 with respect to different metals indicating alarming conditions for Cd followed by Co.

Keywords Sediment quality, Heavy metal, Geo-accumulation index (Igeo)

River estuarine sediments provide a major sink for

heavy metals in the aquatic environment by

different physico-chemical processes such as

precipitation, adsorption and chelation. However,

some of the sediment-bound metals may remobilize

and be released back to water with a change of

environmental conditions and impose adverse

effects on living organisms. Sediments have proved

as the excellent indicators of environmental

pollution, as they accumulate pollutants to the levels

that can be measured reliably by a variety of

analytical techniques. The concentration of heavy

metals in sediment depends on variety of factors

such as basin geology, physiography, chemical

reactivity, lithology, mineralogy, hydrology,

vegetation, land use pattern and biological

productivity. Level of heavy metals in sediments

derived from the natural process is known as

lithogenic background1. Besides the natural

processes, additional influx may be from the

industrial activities, mining practices and

municipality/urban waste in its basin which causes

their enrichment. The magnitude of influx in to the

river system varies depending upon the intensity of

these activities. The river Brahmani not only obtains

sediments from natural sources but also receives

enormous amount of solid waste from industrial

activities at Rourkela, Angul-Talcher, and Jajpur

area; mining activities at Angul- Talcher and

Sukinda in addition to municipality/urban waste

from Rourkela, Angul-Talcher and Jajpur urban

setups. Brahmani River carries substantial amount

of coal fly ash from thermal power plants in the

basin2. This is a major environmental problem faced

by India today which is the disposal of about 110

million tons of fly ash generated from coal based

thermal power plants3. Coal fly ash is a mixture of

metallic oxides, silicates and other inorganic

particulate matter along with un-burnt carbon. Apart

from this, it also contains many trace metals.

Therefore in this study an attempt has been made to

assess the concentration level of some selective

heavy metals in the sediments of Brahmani river-

estuarine system in addition to quantify their

enrichment through the use of Geo-accumulation

index (Igeo) .

Material and methods In order to study the concentration of some selective

heavy metals such as Fe, Mn, Co, Ni, Cu, Zn, Cr,

Pb and Cd in the sediments of Brahmani River,

Estuary and near-shore environment, 25 sampling

locations (Fig:1) were chosen on the basis of

location of major industries, mines, municipal

discharge points and accessibility of sampling sites.

Sediment samples were collected from different


Subas Chandra Asa



stations in and around the said industrial areas of

Rourkela, Angul-Talcher, Jajpur-Sukinda, Dhamara

estuary and near-shore. Powdered samples were

digested in triplicate, in 100ml Teflon beakers

followed by addition of 2ml HClO4, 12ml HF and

8ml HNO3. The concentration of metals Fe, Mn,

Cu, Cr, Ni, Co, Pb, Zn & Cd were estimated by

AAS (Varian, Model Spectra 20+) in flame mode.

All the samples were analyzed in triplicate with

blanks similarly treated for metal analysis.

Geo-accumulation index (Igeo) was first

introduced by Muller4 to compare the present-day

heavy metal concentration with the pre-civilized

background values. This index has been used by

various workers for their studies5-7

.

Igeo = log2

Where, Concentration of element ‘n’,

Geochemical background values.

Results Discussion

The average concentration of different metals Fe,

Mn, Co, Ni, Cu, Zn, Cr, Pb and Cd of sediments of

the river, estuary and coast are presented in

Table.1. The concentration of Fe, Mn and Cr

was found to be higher in the three zones.

Table 1 Average metal concentrations of sediments of

Brahmani river, estuary and coast.

Metals Unit River Estuary Coast

Fe % 2.88 3.21 2.02

Mn µg/g 515.46 652.17 436.77

Co µg/g 30.65 67.06 26.95

Ni µg/g 33.69 64.68 35.77

Cu µg/g 21.66 29.38 11.52

Zn µg/g 52.86 71.35 29.33

Cr µg/g 216.90 347.04 157.77

Pb µg/g 21.47 31.91 22.20

Cd µg/g 2.06 1.63 0.74

The world surface rock average8 has been used

as the geochemical background. The factor 1.5 was

used to account for possible variation in background

data due to lithogenic effect. Igeo < 0 (class 0) means

pollution free, 0 ≤ Igeo < 1 (class 1) refers to

pollution free to moderately polluted, 1 ≤ Igeo < 2

(class 2) refers to moderately polluted, 2≤ Igeo <

3(class 3) moderate to strongly polluted, 3 ≤ Igeo < 4

(class 4) strongly polluted, 4 ≤ Igeo < 5 (class 5)

strong to very strongly polluted and Igeo ≥ 5 (class 6)

refers to very strongly polluted. Based on world

surface rock average, the Igeo values are calculated.

The Igeo values of Fe, Mn, Cu, Ni and Zn remain in

class ‘0’ in all segments including rivers, estuary

Fig. 1 – Map showing sampling stations

15 Asa S C & Rath P: Sediment Quality Assessment

and coast. Also in river Pb remains in class ‘0’

which changes into ‘1’ in estuary and then to ‘0’ in

coast. In both the rivers and estuary, Cd remains in

class ‘4’ which changes to class ‘3’ in coast. For the

rivers Co remains in class ‘1’ while in estuary it

remains in class ‘2’ indicating its accumulation due

to flocculation/ coagulation which again comes to

class ‘1’ in coast. In Brahmani River Cr remains in

class ‘1’ indicating its inputs from upstream mining

activities particularly in D/S of Sukinda. Due to

accumulation in estuary, Igeo for Cr changes to class

‘2’ in estuary. Towards coast it again changes to

class ‘1’.

Acknowledgement The authors are grateful to Late U. C. Panda for his

dedicated contribution during the study.

References 1. Wedpohl K H, in Metals and their compounds in

environment, edited by E Merian (VCH Publication)

1991, 3.

2. Rath P, Panda U C, Bhatta D & Sahu K C, J Hazard

Mater, 163 (2009) 632.

3. Sarkar A, Rano R, Mishra K K & Sinha I N, Fuel

Process Technol, 86 (2005) 1221.

4. Muller G U, Umschau, 79 (1997) 566.

5. Rath P, Panda U C, Bhatta D & Sahoo B N, J Geol

Soc India, 65 (2005) 487.

6. Krupadam R J, Smita P & Wate S R, Geochem J, 40

(2006) 513.

7. Asa S C, Rath P, Panda U C, Parhi P K & Bramha S,

Environ Monit Assess, 185(2013) 6719; DOI

10.1007/s10661-013-3060-3.

8. Martin J M & Meybeck M, Mar Chem, 7 (1979) 173.


Vol. 1 (1), September 2014, pp. 16-18

An Economic and Eco-Friendly Soil Conditioner: Fly Ash

Bismita Rout

Department of Chemistry, Orissa Engg. College, Bhubaneswar


Abstract Repeated cultivation on the same soil and indiscriminate use of fertilizer gradually decrease the soil fertility.

Whereas fly ash, which has good compatibility with soil is an industrial waste, consuming large amount of water, energy

and land area for its disposal. So here an attempt has been made to use fly ash as an economic soil conditioner. To achieve

this object raw fly ash was collected from CPP (captive power plant) Nalco, Odisha. It is then activated by acid to

concentrate the micro and macro nutrients. Soil sample was collected from Khurda district which was analyzed and found to

be laterite in nature. Then the activated ash was added to 20 kg of laterite soil at the amount of 0, 100, 200, 300, 400, 500,

and 600gm in different pot. Mechanical shaker was used for proper mixing. Activated ash, soil sample and mixtures were

analyzed and was found that the activated ash improving both the physical and chemical properties of soil.

Keywords Activated fly ash, Laterite soil, Physio-chemical properties, Soil conditioner

Fly ash is an amorphous mixture of ferro-alumino

silicate generated from combustion of coal at a

temperature of 500 to 15000 C and belongs to coal

combustion by product. The physical, chemical and

mineralogical properties of fly ash depend on the

nature of parent coal1, 2

. In India 38% of this waste is

utilized in different ways like building construction

material, bricks, blocks and roads etc; [source

www.tifac.org.in]. Estimation tells that the production

of fly ash will exceed to 140 million tons by 20203.

The fly ash particle can easily escape from emission

control devices due to their small size and get

suspended in the air. Repeated exposure to such

polluted air can cause irritation in nose, eyes,

respiratory tract and severe arsenic poisoning2, 4

. On

the other hand it has good compatibility with soil,

both being in-organic stable and silicon forming the

major matrix1. Thus here an attempt has been made to

enhance the nutrient contained of soil by using

activated fly ash.

Materials and Methods A bulk of soil sample from 0-25 cm depth was

collected from Khurda district, which was analyzed to

be laterite in nature. Boiler ash was collected from

CPP NALCO, Angul. Both the soil sample and fly

ash were air dried, and then the air dried fly ash was

activated chemically by 1 N Sulphuric acid. 20kg of

the air dried soil sample was taken in seven different

pots. To each pot activated fly ash was added at the

amount of 0, 100, 200, 300, 400, 500 and 600g

respectively. For proper mixing the mixtures were

shaken for 15 min by the help of mechanical shaker.

The soil sample, raw fly ash and the mixtures all

are analyzed for various physic-chemical

characteristics. Particle size in soil sample was

analyzed by hydro-meter method5. Ca

2+ + Mg

2+ were

determined by EDITA titration method, where

eriochrome black T was used as indicator in an

alkaline medium6. Organic matter contained in the

soil, fly ash and mixtures were determined by the

calculation in loss of weight by ignition. Total

Nitrogen was determined by the Kjeldahl procedure7.

Available K amount was calculated by ammonium

acetate method8. P was estimated by formation of

phosphomolybdate complex, where ascorbic acid was

used as reducing agent to produce a blue colour9. Mn,


Bismita Rout


http://www.tifac.org.in/

17

Rout B: An Economic and Eco-Friendly Soil Conditioner: Fly Ash

Fe, Zn and Cu amount determination was made by

0.005M DTPA extract by atomic absorption

spectroscopy, whereas Al3+

amount was done by

aquaregia method.

After the analysis the value obtained for various

physic-chemical characteristics of soil, fly ash and the

mixtures are shown in Table 1, Table 2 and Table 3

respectively.

Results Discussion Table 1Physico-chemical properties of laterite soil sample

Sl. No. Characteristics Value Units

1 dry bulk density 1.37 g/cc

2 total porosity 48 %

3 pH 6.7 ----

4 electrical conductivity 0.29 dSm-1

5 Ca++

+ Mg++

41 mg/kg

6 Al+++

389.6 mg/kg

7 available K 162.7 mg/kg

8 total N 273.3 mg/kg

9 available P 52.5 mg/kg

10 Fe 347 mg/kg

11 Mn 13 mg/kg

12 Zn 6.2 mg/kg

13 Cu 5.7 mg/kg

14 organic matter 765 mg/kg

Table 2 Physico-chemical properties of activated fly ash

Sl. No. Characteristics Value Units

1 dry bulk density 1.17 g/cc

2 total porosity 52 %

3 pH 8.2 ----

4 electrical conductivity 2.4 dSm-1

5 Ca++

+ Mg++

739 mg/kg

6 Al+++

300 mg/kg

7 available K 190 mg/kg

8 total N Nil mg/kg

9 available P 352 mg/kg

10 Fe 155 mg/kg

11 Mn 136 mg/kg

12 Zn 36 mg/kg

13 Cu 42 mg/kg

14 organic matter Nil mg/kg

The experimental data represented in table- 3 revels

that the activated fly ash is affecting the physical

properties of soil in a positive manner. The dry bulk

density of soil mixture is decreasing; total porosity is

increasing which will increase the water holding

capacity. Increase in electrical conductivity was also

recorded which implies that, there is increase in

soluble salt concentration in the soil-activated fly ash

mixture. Not only the physical properties, but the

amount of micro-nutrients like Fe, Mn, Zn, Cu are

also increased, which is generally can’t supply by any

chemical fertilizers.

Table 3 Impact of fly ash on soil

Sl.

No. Characteristics

20kg soil

+ 0g

activated

FA

20kg

soil +

100g

activated

FA

20kg

soil

+200 g

activated

FA

20kg

soil

+300g

activated

FA

20kg

soil

+400g

activated

FA

20kg soil

+500g

activate

FA

20kg soil +

600g

activated FA

Units

1 dry bulk density 1.37 1.35 1.32 1.29 1.25 1.24 1.21 g/cc

2 total porosity 48 48.3 49 49.9 50.3 51.2 51.8 %

3 pH 6.7 6.7 6.9 6.9 7.1 7.2 7.3 ----

4 electrical

conductivity 0.29 0.51 1.12 1.30 1.37 1.40 1.41 dSm

-1

5 Ca++

+ Mg++

41 73 94 117 132 158 172 mg/kg

6 Al+++

389.6 380.2 375 369 352 348 342 mg/kg

7 available K 162.7 169.3 172 176 178 181 184.5 mg/kg

8 total N 273.3 273.1 273.2 273.3 273.3 273.3 273.3 mg/kg

9 available P 52.5 94.3 100.1 103.2 110 115 119 mg/kg

10 Fe 347 329 311 297 284 277 269 mg/kg

11 Mn 13 27 32 37 44 51 63 mg/kg

12 Zn 6.2 9.5 11.3 12.9 14.2 17 23 mg/kg

13 Cu 5.7 6.2 7.9 8.2 9.9 11.1 12.3 mg/kg

14 organic matter 765 769 769 770 770 771 771 mg/kg


Conclusion From the above study we concluded, a good soil

conditioner from fly ash can be prepared when it is

acid activated and best result will be found when 1kg

of soil will mixed with nearly 30g of activated fly ash.

References: 1. Adriano D C, Page A L, Elseewi A A, Chang A C &

Satraughan I, J Env Qlty, 9(3) (1980) 333.

2. Carlson C L & Adriano D C, J Env Qlty, 22(2) (1993)

227.

3. Kalra N, Joshi H C, Chaudhary A, Chaudhary R &

Sharma S K, Bioresour Technol, 61 (1997) 39.

4. Finkelman R B, Belkin H E, Zhang B S & Centeno J A,

Arsenic poisoning caused by residential coal

combustion, in Guizhou Province, Chaina, Proceedings

of 31st international geological Congress, (Rio de

Janeiro, Brazil) pp. 41 – 42.

5. Day P R, in Particle fractionation and particle size

analysis in methods of soil analysis, Agronomy no 9,

part 1, edited by C. A. Black, (Am Soc Agron Madison,

Wisconsin, USA) 1965.

6. Rechard L A, Diagnosis and improvement of saline and

alkali soils, (U. S. Deptt. Agri. Hand book) pp. 6 – 160,

1954.

7. Jackson, M.L. 1964. Análisis químico de los suelos.

Ediciones Omega S.A., Barcelona.

8. Black, C. A., 1965, “Methods of soil analysis Part 2,”

ASA, 677 Segoe Rd S, Madison, WI 53711.

9. Lindsay W L & Norvell W A, Soil Sci Amer J, 42

(1978) 421.


Vol. 1 (1), September 2014, pp. 19-23

Prediction of Nickel Binding Sites in Proteins from Amino acid Sequences by Radial

Basis Function Neural Network Classifier

G C Dash1, M R Panigrahi

2, J K Meher

3, M K Raval

4

1Department of Chemistry, APS College, Roth, Balangir, Odisha, India.

2Department of Chemical Engineering, Orissa Engineering College, Bhubaneswar, India

3Department of Computer Science and Engg, Vikash College of Engg for Women, Bargarh, Odisha, India

4Department of Chemistry, Gangadhar Meher College, Sambalpur, Odisha, India


Abstract Prediction of Ni-binding proteins has not received intensive and specific attention. There is also a need for

a sequence based predictive method for metal binding site with high accuracy so that it can be applied at proteomic

scale. A radial basis function neural network classifier is developed to predict nickel binding sites in proteins from

sequence alone data. Two physicochemical parameters namely, polarizability and partial charge of the ligand atom of

amino acid side chains are used as features for the classifiers. The accuracy of the classifier is 94%.

Keywords Ni-binding, neural network, physicochemical parameters, ligand, polarizability

The crucial test of knowledge of coordination

chemistry lies in our ability to predict metal binding

to ligands or proteins along with their

thermodynamic and kinetic stabilities. Because of

the functional and sequence diversity of

metalloproteins, it is necessary to design algorithms,

which include different aspects of metal-ligand

complex formation for predicting metal-binding

proteins. The problem has been approached from

different direction to develop algorithms with

greater accuracy.

An approach to begin with is to classify as metal

binding and non-metal binding proteins. Obvious

choice in this situation is Support Vector Machine

(SVM) method1. The method predicts 67% of the

87 metal-binding proteins non-homologous to any

protein in the Swissprot database and 85.3% of the

333 proteins of known metal-binding domains as

metal-binding. These suggest the usefulness of

SVM for facilitating the prediction of metal-binding

proteins1.

Structural information also has been used for

predicting metal-binding sites based on the

detection of principal liganding residues and metal-

ligand complex architectures2, the use of common

local structural parameters2, combination of

sequence and structural profiles3, analysis of bond

strength contributions4, and the computation of

force fields5. However, metal specificity in proteins

with loosely or temporarily bound metals, such as

enzymes that use metal ions as cofactors, are often

poorly characterized6. Therefore, sequence-based

computational methods appear to be useful for these

types of proteins and whose 3D structures are not

determined experimentally7. Besides, sequence

similarity methods, the sequence-based methods

include metal-binding sites sequence motifs8,

multiple sequence alignments against known metal-

binding proteins, and neural networks of sequence

segments of amino acids of higher metal-binding

propensity9,10

. Combinatorial application of multiple

structural, sequence alignments and annotation

methods has been found to be highly useful for

improving prediction accuracy of metal-binding

proteins1.

Empirical force field method – The empirical

force field Fold-X is developed to predict the


G C Dash

e-mai: [email protected]

M R Panigrahi


J K Meher


M K Raval



position of single atom ligands (structural water

molecules and metal ions). Fold-X predicts 76% of

water molecules interacting with two or more polar

atoms of proteins in high-resolution crystal

structures and within 0.8 Å standard deviation in

position on average. The prediction of metal ion-

binding sites have accuracy between 90% and 97%

depending on the nature of metal ion, with an

average standard deviation of 0.3 – 0.6 Å on the

position of binding. The force field includes Mg2+

,

Ca2+

, Zn2+

, Mn2+

, and Cu2+

. The accuracy of the

energy prediction using the force field is sufficient

to efficiently discriminate between Mg2+

, Ca2+

, and

Zn2+

binding5.

Sequence based prediction method – Algorithms

to predict of metal binding sites in proteins from

sequence are helpful in identifying the

metalloproteins and annotation of uncharacterized

proteins on a genomic scale. Development of such

algorithms are highly challenging due to the

enormous amount of alternative candidate

configurations7. Passerini et al. (2012) develop new

algorithm based on structured output learning for

determining transition-metal-binding sites

coordinated by cysteines and histidines. The

inference step (retrieving the best scoring output) is

intractable for general output types (general

graphs). Metal binding has been proved to be the

algebraic structure of a matroid assuming that no

residue can coordinate more than one metal ion.

This allows to employ greedy algorithm7. Test of

predictor in a highly stringent setting where the

training set consists of protein chains belonging to

SCOP folds achieves 56% precision and 60% recall

in the identification of ligand-ion bonds7.

Another sequence based predictor- MetalloPred,

is developed, which consists of three levels of

hierarchical classification using cascade of neural

networks from sequence derived features9. The 1

st

layer of the prediction engine is for identifying

whether a protein is a metalloprotein or not. The 2nd

layer is for determining the main functional class.

The 3rd

layer is for identifying the sub-functional

class. The overall success rates for all the three

layers are ~ 60% that were obtained through cross-

validation tests on the datasets of non-homologous

proteins with cut off of 30% sequence identity in

the same class or subclass9.

We have made an attempt to use hard and soft

acid-base (HSAB) concept in metal complex

formation considering the concerned two

physicochemical parameters: partial charge and

polarizability of binding ligand atoms of amino acid

residues, to predict nature of metal binding to

proteins. Metal ion Ni is selected for the study as

prediction of Ni binding to the protein has been not

been intensively and specifically studied so far. A

neural network classifier has been applied yielding

an accuracy of ~95%.

Materials and Datasheet

Ni-Binding Protein Data Set

Co-ordinate files of metalloproteins are obtained

from the protein data bank (PDB)11

(www.pdb.org/pdb). For the study in this work we

have chosen a non-redundant set of PDB files of Ni-

binding proteins determined by the X-Ray

diffraction experimental method and reported up to

September 2010. The available PDB files are

manually scrutinized by removing PDB entries with

proteins with single ligand to Ni ion and proteins

surface binding Ni. These proteins may be

contaminated with Ni ions. However, some single

ligand binding Ni, those which are interfacially

bound to multiple chains in multimeric proteins has

been considered.

Ni-Binding Sequence Data Set

A set of Ni-binding segments of 15 amino acid

residues are prepared by selecting sequences Si-7 to

Si+7, where ith residue binds to Ni. The set contains

200 Ni-binding sequences, which are used as Ni-

binding data set. Similar procedure is followed for

Ca and Cu-binding data sets. Randomly 15 residue

long segments are selected from no-metal binding

protein sequences to prepare no-metal binding data

set. No-metal binding, Ca-binding and Cu-binding

data sets together constitute no-Ni-binding data set.

Ca ion and Cu ion represent the hard and soft metal

ions respectively. Ni lies in the borderline of hard

and soft classification. Hence the present classifier

which is based on HSAB properties may classify

Ni-binding sites in the background of no-metal

binding and other metal binding sites in proteins.

Calculation of Feature Parameters

Polarizability and partial charge of the ligand

binding atoms namely, OD1(Asp), OD2 (Asp/Asn),

OE1(Glu), OE2 (Glu/Gln), OZ (Tyr), ND1(His),

NE2 (His), SG (Cys/Met), are calculated in energy

optimized amino acids (X) protected by acetyl

(Ace) and N-methyl amide (NMe) group on N-

terminus and C-terminus respectively ( AceXNMe),

using QSAR module of molecular modeling

software HyperChem Pro 8.0. Energy optimization

is done by semi-empirical method (PM3).

The parameters are assigned to those amino

acids only whose side chains are associated with

metal binding. Rest all are assigned zero values.

Polarizability and partial charge are the two

parameters of the ligand, which are considered to be

21 Das et al.: Prediction of Nickel Binding Sites

crucial in explaining the metal-ligand bond

formation in terms of the hard-soft acid-base

(HSAB) principle12

. Of course, the HSAB principle

has been criticized regarding its tenability recently

in case of ambident reactivity13

.

Table 1 Physicochemical parameters of amino acid

residues used in algorithm for prediction of Ni-binding

sites in proteins

Amino acid Polarizability Partial charge

A 0 0

R 0 0

N 0.57 -0.5679

D 0.57 -0.8014

C 3.00 -0.3119

Q 0.57 -0.5679

E 0.57 0.8014

G 0 0

H 1.03 -0.5727

L 0 0

I 0 0

K 0 0

M 3.00 -0.3119

F 0 0

P 0 0

S 0.64 -0.6546

T 0.64 -0.6546

W 0 0

Y 0.64 -0.55791

V 0 0

Radial basis function neural network

classifier (RBFNNC) In this paper we have introduced a low complexity

radial basis function neural network (RBFNN)

classifier to efficiently predict the sample class14-16

.

The potential of the proposed approach is evaluated

through an exhaustive study by many benchmark

datasets. The experimental results showed that the

proposed method can be a useful approach for

classification. A radial basis function network is an

artificial neural network that uses radial basis

functions as activation functions. It is a linear

combination of radial basis functions. The radial

basis function network (RBFNN) is suitable for

function approximation and pattern classification

problems because of their simple topological

structure and their ability to learn in an explicit

manner. In the classical RBF network, there is an

input layer, a hidden layer consisting of nonlinear

node function, an output layer and a set of weights

to connect the hidden layer and output layer. Due to

its simple structure it reduces the computational

task as compared to conventional multi layer

perception (MLP) network. The structure of a RBF

network is shown in Fig. 1.

Fig. 1 Architecture of a radial basis function network

In the RBFNN based classifier, an input vector x is

used as input to all radial basis functions, each with

different parameters. The output of the network is a

linear combination of the outputs from radial basis

functions.

For an input feature vector x, the output y of the

jth output node is given as.

k

2k

x(n) CN N

2

j kj k kj

k 1 k 1

y w w e

(1)

The error occurs in the learning process is

reduced by updating the three parameters, the

positions of centers (Ck), the width of the Gaussian

function (σk) and the connecting weights (w) of

RBFNN by a stochastic gradient approach as

defined below:

ww(n 1) w(n) J(n)w

(2)

k k c

k

C (n 1) C (n) J(n)C

(3)

k k

k

(n 1) (n) J(n)

(4)

Where, 21J(n) e(n)

2

, e (n)=d(n) - y(n)

is the error, d(n) is the target output and y(n) is the

predicted output. w C and are the learning

parameters of the RBF network.

Simulation Studies and Discussions In order to compare the efficiency of the proposed

method in predicting the class of the Nickel binding

data we have used standard datasets. All the

datasets categorized into two groups: binary class to

assess the performance of the proposed method. The

dataset consists of amino acid sequences of 15

characters. 200 sequences from Ni-binding protein

dataset and 200 sequences from non-Ni-binding

X

1

X

2

X

N

Y

1

Y

2

Y

3

Y

N

W

0

W

kj

Input

s

Output

Input

Layer

Output

Layer

Hidden

Layer

φ

φ

φ

φ


dataset are taken as training set. The feature

selection process proposed in this paper includes

polarizability and partial charge as shown in the

Table 1. To implement the RBFNN classifier, we

first read in the file of protein sequence which are

represented with numerical values. The

performance of the proposed feature extraction

method is analyzed with the neural network

classifiers: RBFNN. The leave one out cross

validation (LOOCV) test is conducted by

combining all the training and test samples for the

classifiers with datasets17

. LOOCV is a technique

where the classifier is successively learned on n-1

samples and tested on the remaining one. i.e., it

removes one sample at a time for testing and takes

other as training set. It involves leaving out all

possible subsets so the entire process is run as many

times as there are samples. This is repeated n times

so that every sample was left out once. Repeating

these procedure n times gives us n classifiers in the

end. Our error score is the number of

mispredictions18

. Out of 200 sequences from Ni-

binding protein dataset, 192 samples are detected as

true positive whereas out of 250 sequences from

non-Ni-binding protein dataset 17 samples are

detected as false positive.

The prediction accuracy has been analyzed in

terms of two measuring parameters such as

accuracy (A), precision (P) and recall (R). These are

are defined in terms of four parameters true positive

(tp), false positive (fp), true negative (tn) and false

negative (fn). tp denotes the number of Nickel

bindings and are also predicted as Nickel binding, fp

denotes the number of actually Non nickel bindings

but are predicted to be Nickel bindings, tn is the

number of actually Non nickel bindings and also

predicted to be Non nickel bindings, and fn is the

number of actually Nickel bindings and predicted to

be Non nickel bindings.

Accuracy

The accuracy of prediction of Ni-binding in amino

acid sequence is defined as the percentage of Ni-

binding correctly predicted of the total binding

sequences present. It is computed as follows:

(5)

Precision

Precision is defined as the percentage of Ni-binding

correctly predicted to be one class of the total Ni-

binding predicted to be of that class. It is computed

as:

(6)

Recall

Recall is defined as the percentage of the Ni-

binding that belong to a class that are predicted to

be that class. Recall is computed as:

(7)

Table 2 Measuring parameters for prediction accuracy

Actual

Predicted

Nickel

Binding

(NB)

Non Nickel

Binding

(NNB)

NB 192 (tp) 17 (fp)

NNB 8 (fn) 233 (tn)

The accuracy, precision and recall are 0.94, 0.91,

and 0.96 respectively. The accuracy of sequence

based classifiers reported so far is about 65%.

Hence the present classifier appears to have high

accuracy compared to existing sequence based

classifiers It needs to be extended for all the metal

ions found in biosystems before it can be used at

proteomic level. However, it fulfills the need of a

classifier for Ni-binding proteins keeping in view

the growing database of Ni-binding proteins along

with the escalating interest of scientific community

in the field during last decade.

Conclusion The classifier in the present work is performs with

high accuracy, to the tune of 94%. The method

would be extended to data sets with all other metal-

binding sequences and success with similarly high

accuracy is expected. A sequence of 15 residues

long is chosen arbitrarily in the present work.

Further investigation is necessary to find out

whether the accuracy is dependent on length of

sequence.

Acknowledgement The authors wish to thank management members

and the principal of the college for all kinds of

supports to complete this work. References 1. Lin H H, Han L Y, Zhang H L, Zheng C J, Xie B,

Cao Z W & Chen Y Z, Bioinformatics, 7(Suppl

5):S13, 2006 doi:10.1186/1471-2105-7-S5-S13

2. Gregory D S, Martin A C, Cheetham J C & Rees A

R, Protein Eng, 6 (1993) 29.

nnpp

np

ftft

ttA

pp

p

ft

tP

np

p

ft

tR

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Wernisch L & Jones D T, J Mol Biol, 342 (2004) 307.

4. Nayal M & Di Cera E, Predicting Ca2+

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in proteins, Proceeding of Natural Academy of

Science, USA, 91 (1994) 817.

5. Schymkowitz J W, Rousseau F, Martins I C,

Ferkinghoff-Borg J, Stricher F & Serrano L,

Prediction of water and metal binding sites and their

affinities by using the Fold-X force field, Proceeding

of Natural Academy of Science, USA, 102 (2005)

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6. Jensen M R, Petersen G, Lauritzen C, Pedersen J &

Led J J, Biochem, 44 (2005) 11014.

7. Passerini A, Lippi M & Frasconi P, IEEE/ACM Tran

Comput Biol Bioinform, 9 (2012) 203.

8. Rigden D J & Galperin M Y, J Mol Biol, 343 (2004)

971.

9. Naik P K, Ranjan P, Kesari P & Jain S, J Biophys

Chem, 2 (2011) 111.

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& Yang Y S, Int J Neural Syst, 15 (2005) 71.

11. Berman H M, Westbrook J, Feng Z, Gilliland G, Bhat

T N, Weissig H, Shindyalov I N & Bourne P E,

Nucleic Acids Research, 28 (2000) 235.

12. Glusker J P, Katz A K & Bock C W, Metal ions in

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Ed, 50 (2011) 6470.

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formultivariable interpolation: A review, paper

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Approximationof Functions and Data, RMCS,

Shrivenham, England, 1985.

15. Broomhead D S & Lowe D, Complex Systems, 2

(1988) 321.

16. Chen S, Cowan C F N & Grant P M, IEEE Trans

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http://nar.oxfordjournals.org/cgi/content/abstract/28/1/235


Vol. 1 (1), September 2014, pp. 24-27

Sustainable Development in the conflicting scenario of Environment and

Development

Chitta Ranjan Panda

Department of civil engineering, Institute of Technical Education and Research, Bhubaneswar, India


Abstract With the continuous growth of population and subsequent ever growing demand for the consumer goods, there

has been principal thrust upon the development processes for the production of goods to meet the requirements. As a result,

there have been serious efforts in the areas of industrial and technological development. Our economy has essentially

focused on the growth and development oriented plans and programmes. All these development processes particularly

industrial development consumed huge amount of natural resources like ores, minerals, fossil fuel and forest resources etc

resulting in mindless exploitation of these resources and resulted in degradation in environment. Even the most precious

divine gift like air and water has become impure & scarce because of our own activities. In this conflicting scenario of

environment and development, sustainable development emerges as solution to these problems.

Key words resources, environment, development, sustainable, waste

The large-scale development processes and the

resultant mindless exploitation of natural resources

have exceeded the carrying capacity of the source

environment thereby leading to depletion of natural

resources. We are likely to face resource depletion

even for hitherto inexhaustible resources. At the same

time, enormous amount of waste from these

development processes are being dumped into the

sink environment thereby surpassing the assimilating

ability of the sink environment resulting in the

degradation in different components of the

environment thereby causing environmental pollution

problems.

Economic development activities have also

brought about problems with potentially dramatic

consequences. Climate change is the most visible,

most talked about at the moment; especially after the

recent (2007) Intergovernmental Panel on Climate

Change report1 confirmed that the climate is almost

certainly undergoing significant change as a result of

human activity. The loss of key elements of an

ecosystem can alter the balance between its

components and lead to long-term or permanent

changes2. For example, the problem of water is not

one of scarcity, but mismanagement. Emil Salim3

pointed out unsustainable development has degraded

and polluted the environment in such a way that it

acts now as the major constraint followed by social

inequity that limits the implementation of perpetual

growth.

The present paper analyses the conflict of interest

between the environment and the development and

then analyses and discusses the concept of

Sustainable Development for a solution to this

problem. This paper delves in to the environment

management with an emphasis on waste management

as the most important component in Sustainable

Development.

Conflicting scenario of Environment vs

Development

The proponents of development primarily focus on

production, productivity, product marketability and

finally profit for the organization. They chart out

growth strategies and action plans which further


Chitta Ranjan Panda

e-mail: [email protected], Tel No: 09438148473

25 Panda C R: Sustainable Development

accelerate the development processes. They have

scant regard for the environmental problems. At the

same time, the proponents of environment and the

environmental activists denounce the development

activities as the destroyer of environment. They

oppose setting of industries, opening up of mines,

opening highways etc. Thus there has been tug of war

between them and both of them present clear

antagonistic views. While we cannot put a brake on

the development activities for obvious reasons of

meeting the needs of the ever increasing population,

we can no longer close our eyes on the environmental

problems. The time has come for a clear introspection

of the problem and act accordingly and swiftly.

It has been clearly evidenced, that every

development process has associated environmental

problems, those need to be addressed. The world

summits like UN Conference on Human Environment

(UNCHE) at Stockholm in 1972, UN Conference on

Environment & Development(UNCED) at Rio de

janeiro in 1992, UN Conference on Environment &

Development(UNCED) at Johannesburg in 2002 and

many other climate change summits and protocols

including the recent one at Copenhagen in 2009

clearly indicates the alarming trend, intense

deliberations and the resulting frantic efforts to find

the solutions to the environmental problems, which is

threatening our very existence on earth.

Sustainable Development

Are there any compromise solutions to the aforesaid

problems? Can there be the development activities

particularly industrial development without degrading

the environment? Finally can both development and

environment coexist together? The concept of

Sustainable Development seems to be the answer to

all these questions. World Commission of

Environment & Development in its report “Our

Common Future” first coined the idea of Sustainable

Development in 19874. Sustainable Development is a

development process that fulfills the need of the

present generation without compromising the

requirement of the future generation. Since then this

path breaking concept has been the central idea of any

modern development processes. A lot has been

deliberated upon this issue in the very important Earth

summits at Rio de janeiro in 1992 and at

Johannesburg in 2002. In the extensive discussion and

use of the concept since then, there has generally been

recognition of three aspects of sustainable

development. Reed2 outlined Economic, Environment

and Society as the three major components of

sustainable development. An economically

sustainable system must be able to produce goods and

services on a continuing basis, to maintain

manageable levels of government and external debt,

and to avoid extreme sectoral imbalances which

damage agricultural or industrial production. An

environmentally sustainable system must maintain a

stable resource base, avoiding over-exploitation of

renewable resource systems or environmental sink

functions, and depleting non-renewable resources

only to the extent that investment is made in adequate

substitutes. This includes maintenance of biodiversity,

atmospheric stability, and other ecosystem functions

not ordinarily classed as economic resources. A

socially sustainable system must achieve

distributional equity, adequate provision of social

services including health and education, gender

equity, and political accountability and participation.

UNEP Post-2015 Discussion Paper5 concludes that

one of the principal outcomes of Rio+20 were the call

to produce a set of universally applicable sustainable

development goals (SDGs) that balance the

environmental, social and economic dimensions of

sustainable development. This Paper provides advice

and guidance on how environmental sustainability

can be incorporated in the SDGs. An analysis of

current environmental goals and targets shows that

the successful ones are built on general support from

society and a scientific consensus that the problem

exists and is urgent. The ones making most progress

tend to be embedded in effective governance regimes,

and be easier to implement because solutions are

readily available. A key to success also seems to be

that goals are underpinned by specific and measurable

targets. After considering the above and other lessons

from current goals, the following framework is

proposed for embedding environment in the SDGs

A rationale and overarching vision for the SDGs,

which is a narrative describing the basis for

including environmental sustainability in the

SDGs

An integrated approach for embedding

environment in goals and targets which proposes

basic characteristics and types of goals and targets

to be selected

A set of six criteria for assessing or proposing

goals and targets, and guidance on how to use

them. The criteria are: (i) Strong linkage of

environment with socio-economic developmental

goals; (ii) Decoupling of socio-economic

development from escalating resource use and

environmental degradation; (iii) Coverage of


critical issues of environmental sustainability such

as important irreversible changes in the global

environment; (iv) Take into account current global

environmental goals and targets, (v) Scientifically

credible and verifiable; and (vi) Progress must be

trackable.

Environment management, a key component in

sustainable development

Environment management is a broad area comprising

of resource management, water conservation &

management, energy conservation & management,

waste management, ecological restoration, corporate

social responsibility etc. Waste management is the

most important aspect of Environment management.

In general Environment management in a

manufacturing organization should include the

following important aspects

Resource management that includes optimum use

of raw material, beneficiation of lo of w grade

minerals and substitution of environmentally

harmful material.

Water and wastewater management that includes

optimum use of water and recycling/reuse of

treated wastewater

Energy management that includes optimum use of

energy and use of renewable sources of energy.

Process optimization should result in more

production and less waste generation.

Preventive maintenance should achieve minimum

leakage and spillage resulting loss of material,

utility and product

Good housekeeping ensures proper waste

collection and storage

Finally waste management should focus amount

on recycling, reuse, recovery and reduction of

waste so that minimum amount of waste is

available for disposal.

Waste Management

Tammemagi6,7

suggested waste management

hierarchy as an ordered set of preferred strategies that

can be used to reduce the amount of waste being

disposed. The hierarchy has five strategies, generally

ordered in decreasing preference as follows:(i) waste

minimization, (ii) reuse, (iii) material recycling, (iv)

energy recovery and (v) waste disposal8. In this

hierarchy, the higher level preferences preserve the

embedded energy of materials and maximize

recovered resources. For example, minimizing waste

conserves more energy when compared to reuse,

while recycling conserves more energy and materials

when compared to strategies to recover energy from

materials. Disposal of waste as an end of the pipe

management option is the least preferred strategy as

the embedded energy of materials is lost. Therefore,

higher levels of the hierarchy are more

environmentally benign than the lower levels in most

cases; with burying waste in the ground as the least

desirable approach to waste management.Seadon8

proposed a sustainable waste management system

incorporates feedback loops, is focused on processes,

embodies adaptability and diverts wastes from

disposal. He defined the goals of sustainable waste

management as (i) protecting health and the

environment, (ii) minimizing the burden on future

generations and (iii) conserving resources. In 1992,

the United Nations defined sustainable waste

management in chapter 21 of Agenda 21 as the

application of the integrated life cycle management

concept in waste management9.

Waste Utilization

Large amount of unmanaged solid waste particularly

from industries, mining and building sectors has

resulted in an increased environmental concern.

Recycling/reuse of such wastes as a sustainable

construction material appears to be viable solution not

only to pollution problem but also an economical

option for design of green buildings. In recent years,

there have been conscious efforts to utilize more and

more waste and recyclable material in building and

construction sectors. There are, however, important

constraints on the use of waste materials; they must

be fulfilling the engineering requirements in terms of

physical properties and they must not contain

excessive amounts of deleterious components which

might cause problems in use. The technical evaluation

of waste materials is, therefore, the essential first

stage. Concrete is the most largely consumed

construction material worldwide. The production of

raw materials used in concrete such as aggregates,

cement etc requires a significant amount of energy

input and causes various environmental problems

including green house gas emission The concept of a

sustainable development in the field of construction

and engineering offers several possibilities for

utilization of the recycled solid waste materials.

Sustainable development implies such a developing

path, which will ensure the use of natural resources

and will create assets in a manner to ensure meeting

the needs of the present generations, without

compromising the future generations. In the

construction sector, sustainable development is in the

27 Panda C R: Sustainable Development

form of green concrete with the use of the waste as

concrete aggregate materials.

Panda et al10

presented a case study of

utilization of a problematic industrial waste.

Ferrochrome slag, a major solid waste in ferrochrome

industries faces the disposal problem because of

residual chromium content in it. This can be suitably

utilized as concrete aggregate material with

chromium immobilization in cement concrete matrix

without causing significant environmental pollution

problem. Thus waste utilization should become one of

most important consideration in green concrete

manufacturing.

Conclusion With adequate Resource conservation & Planning,

there must be optimum & judicious use of resources

to meet the need of the present generation. The waste

in its right perspective is to be considered as resources

misplaced instead of things to be disposed. Hence

Comprehensive waste management must focus on

waste minimization, waste utilization & recycling and

material & energy recovery from waste. Thus

Resource Conservation and Waste Management

should form the basic issues in Sustainable

Development.

References 1. IPCC, Climate Change, Mitigation of Climate Change.

Contribution of Working Group III to the Fourth

Assessment Report of the Intergovernmental Panel on

Climate Change. IPCC working Group I Technical

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1Structural Adjustment, the Environment and

Sustainable Development, Chapter 2, 1997.

3. Salim E, Institutionalising Sustainable Development,

ISBN-978-92-64-01887-7 © OECD 2007

4. WCED, World Commission on Environment and

Development, Brundtland Report to the United Nations,

Our Common Future (Oxford University Press, UK)

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5. UNEP Post-2015 Discussion Paper 1 Version 2,

(Macmillan, New York) 19 July 2013.

6. Tammemagi H, The Waste Crisis: Landfills,

Incinerators, and the Search for a Sustainable 2012

United Nations Conference on Sustainable

Development (Rio+20)

7. Price J L & Joseph J B, Sustain Develop, 8 (2000) 96.

8. Seadon J K, J Cleaner Product 18 (2010)

9. United Nations Conference on Environment &

Development, 1992. Agenda 21. Conches.

10. Panda C R, Mishra K K, Nayak K C, Panda B D &

Nayak B B, Construct Build Mater, 49(2013).

International Journal of Energy, Sustainability and Environmental Engineering Vol. 1 (1), September 2014, pp. 28-34

Present practice of Municipality Solid Waste Management in

Bhubaneswar, Odisha, India.

Rabindra Panda1, Amarendra Harichandan

1*, Himansu Sekhar Patra

2, Kajal Parashar

2*

1Gandhi Institute Of Technology, Bhubaneswar,Odisha, India.

1* Konark Institute of Science and Technology, Bhubaneswar, Odisha, India.

2Ph.D scholar(complted) Geography Dept.,Utkal University .

2*School of Applied science, KIIT University, Bhubaneswar, Odisha, India.


Abstract The effective management of Municipal solid waste has become a monumental challenge in the town with high

population density and experiencing the problem of rapid urbanization. The level of economic development determines the

quantity and composition of solid waste. Higher the level of economic development, greater the proportion of waste

composition and the waste generated from various human activities, both industrial and domestic, can result in health

hazards and have a negative impact on the environment. Understanding the waste generated, the availability of resources,

and the environmental conditions of Bhubaneswar (BBSR) town, this paper attempts to assess the existing state of municipal

solid waste management (MSWM) in Bhubaneswar city with the aim of identifying the main obstacles to its efficiency and

the prospects for improvisation of the solid waste management system in the city. The existing solid waste management

system in the city is found to be highly inefficient. Primary and secondary collection, transportation and open dumping are

the only activities practiced that too in a nontechnical manner. This study is based on field visit, secondary data collection,

interviews with different individuals who were directly or indirectly involved with the projects and also through the

discussions with the relevant Bhubaneswar Municipal Council (BMC) officials to get a clear idea about the present situation

of the city .This paper suggests some approaches for effective management of municipal solid waste (MSW) in BBSR city.

Keywords Source segregation, 3R technology, Aerobic composting, Sanitary landfill

Urbanization is now becoming a global

phenomenon, but its ramifications are more

pronounced in developing countries. Increase in

population, migration trends and changing life

style have significant impact on the quantity and

quality of waste generation in any urban area.

The quantity of Municipal Solid Waste (MSW)

has also increased tremendously with improved

life style and social status of the populations in

urban centers1. Further the situation of solid

waste management has been worsening due to

space constraint2, poor technical skill, limited

financial resources, lack of political will power

and civic awareness3. As a result more than 90%

of the M.S.W generated in India is directly

disposed on land in an unsatisfactory manner4

and BBSR is no exception to this. Issues related

to the disposal have become challenging as more

land is needed for the ultimate disposal of these

solid wastes.

Bhubaneswar is located in the Khurda district

of the state Orissa between 20°12’00”N to

20°23’00”N latitude and 85°44’00”E to

85°54’00”E longitude on the western fringe of

the coastal plain across the main axis of the

Eastern Ghats. It is situated on the Howrah -

Chennai main south Eastern Railway line at

435km from Howrah and 1215 km from Chennai

and the National Highway no.5 connecting

Kolkatta and Chennai passes through the city. The

city lies to the western side of the “Mahanadi Delta”

on the bank of the river Kuakhai, distributaries of

river Mahanadi and 30 kms. South west of Cuttack

city. The river Daya which has branched off from

Kuakhai flows along the south eastern part of the

city5 .

BBSR has developed as a commercial hub with a

number of educational and other institutions. As per

census of india 2011, BBSR has a population of


Amarendra Harichandan


29

Panda et al.: Present Practice of Municipality Solid Waste

837737 in 20116. BBSR city consist of 60 wards

and covers an area of 150 sq. Km and covering

approximately 1.6 lakhs number of houses7. Map of

BMC dumping site is given in Fig. 1.

Fig. 1 Map of BMC dumping site

An attempt has been made in this paper to

review the present practice of solid waste

management in BBSR.

Materials and Methods Information on generation and management of

waste in Bhubaneswar Municipality was

collected from published documents and data

available with the Municipal Council.

Preliminary survey on the physical constituents

of the wastes, socio-economic status of the

Municipal Council and conversations with the

Public were conducted to assess the solid waste

generation in BBSR. Data on the existing

facilities available for collection practice,

transportation mechanism, segregation and

disposal practice of the waste were collected

from the BMC. Household waste generation was

assessed through a questionnaire survey from the

randomly selected households in BBSR.

Results and Discussion Municipal Solid Waste includes commercial and

residential wastes generated in municipal or

notified areas, in either solid or semi-solid form

excluding industrial hazardous wastes, but

including treated bio-medical wastes. The

Government of India issued Municipal Solid

Waste (Handling and Management) Rules, 20008

for its implementation at the local level. The

mandatory requirements of the rule are,

Source segregation and storage at source

Door to door collection

Abolition of open storage

Daily sweeping of the street

Transportation of waste in covered vehicles

Waste processing by composting or energy

recovery

Disposal of inerts by sanitary land filling

Fig. 2 Municipal solid waste generation trend line

The BBSR city economy has many major

players. With the pace of urbanization, increase

in population since few years the generation of

solid waste has increased tremendously as shown

in Fig. 2. Since few year the city economy has

grown up to a greater extent which is reflected

from Gross District Domestic Product (GDDP) in

Table 1. Increase in GDDP growth rate and

population explosion accelerated the increase in

solid waste generation as there is a positive

correlation between economic growth, population

growth and MSW generation. Fig. 3 and Fig. 4

shows that there is a regular increase in GDDP

and population growth. In 2005 the GDDP

growth rate and population was Rs./- 546715

lakhs and 690635 person respectively. It was

increased to Rs./- 815937 lakhs and

811410person respectively in 2009. At the same

time it was noticed that the MSW in the year

2005 was 400 MT/day and it was increased to

450MT/day in 2009. This increase in MSW will

put extra pressure on Municipal authorities

Fig. 3 GDDP growth trend line of Khurda


Fig. 4 Population growth trend line of BBSR

Bhubaneswar city consists of 60 wards,

responsibility of the waste management in 20

wards is entrusted upon the BBSR Municipal

Council and in rest 40 wards, the responsibility is

entrusted upon private agencies. The city

generates waste to the tune of approximately 590

MT per day7.

Maximum percentage of solid waste consists

of biodegradable which is around 50.66%(Table

1) of the total waste and is made up of vegetable,

fruit remainders, leaves, spoiled food, eggshells,

cotton, etc. Next to biodegradable waste another

major percentage of solid waste consists of the

total waste is recyclable (dry waste) waste which

consists of newspapers, thermocol, plastic, wires,

iron sheets, glass, etc. Debris includes

construction waste, renovation waste, demolition

waste, etc.

Table 1 Gross District Domestic Product (GDDP) at

2004-2005 current prices (in lakhs)

District Year GDDP in lakhs

Khurda 2005 546715

2006 598556

2007 685087

2008 744196

2009 815937

Source:Economic Survey of Odisha 2011-2012[9]

Table 2 MSW in YEAR

Year MSW generated

(in MT/day)

MSW collected

(in MT/day)

2002 350 250

2005 400 250

2009 460 360

2011 590 440

Source: State Pollution Control Board, BBSR

Management of Waste Source Segregation and storage at source

It was introduced with a view of setting

aside of biodegradable and recyclable materials

from the waste stream before these are collected

with the other MSW to facilitate reuse, recycling

and composting. Proper segregation of waste

would lead to better options and opportunities for

its scientific disposal11

.Different types of

recyclable wastes such as papers, cardboards,

plastics, scrap metal and bottles are segregated

from the biological wastes at the household level

and are being sold to the kabadias. Also a major

percentage of recyclable wastes collected by rag

pickers (Fig. 5). However, few percent of such

waste are still being mixed up with the biological

wastes due to negligence at household level.

Table 3 Average solid waste composition in BBSR

town10

Component

Average % Fraction

Biodegradable organic

fraction (leaves, wood, grass

etc.)

50.66

Paper, cardboard

5.74

Plastic, polyethylene

5.70

Metal

0.79

Glass, Ceramics

0.46

Inert materials (ash, stone,

bricks, soil, silt , earth etc.)

27.15

Rubber, leather 2.10

Bone 0.00

Coconut 2.20

Rags 3.21

Fig. 5 Rag pickers activity

Collection

Primary collection

The primary waste collection of the city is

headed by a Chief Health Officer of BMC.

Twelve Sanitary Inspectors are assigned to

different zones, reporting directly to the Chief

Health Officer. Each Sanitary Inspector presides

over Zamadars. The Zamadars are assigned to a

number of wards. The sweepers and loaders

(Table 5) are assigned to report the Zamadars

31


where the sweepers are provided with four

different types of containers with varying

capacities (Table-4). The research study reveals

that there are 348 collection points available in

the city. At present, only one sweeping machine

is operating in the city.

Secondary collection

The Sanitation department of the Municipal

Corporation looks after also the task of

secondary collection and disposal of wastes.

Various types of vehicles such as trucks of 6 MT

capacity, mini trucks of 4MT capacity and

tractors with trailers of 3MT capacity are used

for secondary collection and disposal of wastes

in Bhubaneswar city.

At present, the civic body has six mechanized

vehicles (hook loader lorries) for disposal of

solid waste.

Earlier street bin system was used for disposal

of solid waste from households. However, this

method has a major disadvantage of littering the

wastes (Fig. 6) over the road and thereby reduces

public hygienic condition as well as aesthetical

view of the place[12]

. Therefore door to door

collection system have adopted by the Municipal

Council. Handcarts and tricycles with bells are

now being used for Municipal Solid Waste

(MSW) collection from doorsteps and collect the

solid waste from the households every morning

and dump it in the garbage bin placed at

specified street corners or directly transfer to

vehicles going to the disposal site. The no. of

hand carts and tricycles used are given in Table-

4. The solid waste collection efficiency of BMC

in 60 wards is approximately 60-70%.

Fig. 6 Littering of waste on road

Abolition of open storage

However, this could not be achieved in the

town due to lack of public awareness. Still there

are 51 storage bins available in the town which

are not sufficient for disposal of waste. Due to

the absence of adequate storage capacity for

generated refuse, the lack of financial resources

to engage more persons for collection from door

to door or narrow/ kutcha lanes inside the town

and poor discipline among the generators, waste

is also continually dumped on the road.

Table 4 Details of BBSR Municipality and its

Storage, Collection facility of solid waste7.

Name of City BBSR

Population

837737

Name of

Municipal

body

BBSR municipality,

BBSR (20)

Private agencies

(40 wards)

Total No of

Ward

60

Collection

Area covered

by BBSR

Municipality

150

No. of houses

covered

1.6 lakh

Details of Waste

Total quantity of Waste

collected per day(MT/day)

440

Details of Storage and Collection facility, processing etc.

Name of

storage

tank/Vehicle

used for

collection

Specification

(shape/size )

Existing

numbers

No of bin

provided

700 mmd×800 mmh 687

No of Auto

Tripper

0.5 MTs 14

No of Tractor

Trolley

1-1.5 MTs 150

No of

container

9 cub. Mt(iron) 60

No of Tri

cycles

-- 270

No of Trucks --- 8

No of dumper

placers

9 cubic Mt 6

No of

excavator

---- 4

Other Wheel barrow 600

Transportation of waste in covered vehicles

BMC is using three different types of vehicles

such as, truck, tipper truck, tractor-trailer (Table

5) for transportation of MSW. On an average,

around 440MT per day of wastes is transported

out of total around 590 MT to the dumping site


during 2011 whereas the un collected quantity of

solid waste during 2002,2005and 2009 are

230,250,360MTs respectively. During

transportation of SW, few vehicles are using nets

to avoid spillage of the waste on the road.

Transportation of SW in open trucks result in lot

of littering. Manual loading and unloading is

performed. Wastes are transported daily with the

help of vehicles carrying out 1 or 2 trips per day.

Difficulties in using the covered vehicles for

transportations are mainly due to financial

constraint and attitude of workers. Due to lack of

collection facility around 30%-40% of generated

solid waste remains on road/street/at different

palaces of city.

Table 5 Total manpower engaged for collection and

transportation of Solid Waste7

Collection by BBSR Municipality

Corporation (20) wards)

Collection by Private

Agencies ( 40 wards)

1146 2677

Treatment and processing

There is no treatment facility for treatment of

municipal solid waste in Bhubaneswar. The

corporation also currently does not involve any

waste processing. Whatever little waste

processing that takes place is for the recyclables

through a chain of informal recyclers operating

in the city. There are 60-70 small waste dealers

who collect the recyclable waste (glass, paper,

metal, plastics, and electronics) either using their

own network of people going door-door or

buying it from waste pickers paying on a per unit

basis. This acts as an incentive for the waste

generator to segregate and store the waste and for

the waste picker to scavenge the waste dumps. A

very rough estimate is 30-40 kg of recyclable

waste per dealer per day. These dealers further

sell the recyclables to big dealers.

Disposal

Management systems in developing countries are

dealing with many difficulties, including low

technical experience and low financial resources

which often cover only collection and transfer

costs, leaving no resources for safe final

disposal[4]

.That is what happening in BBSR town

also. There is no sanitary landfill in Bhubaneswar

city and no provision for leachate checking. The

city does not have even controlled dumps. The

solid waste after collection from 60 wards under

the control of BMC and private agencies are

being dumped at Bhuasuni having land area of

61acre Table-6. The dumping process involves

following steps. Direct disposal of solid waste

from vehicles at the dumping yard. Partially

distribution of collected solid waste at the

dumping yard by JCB. Partially compaction of

waste using roller to minimize the formation of

leachate. Not covering the area with a thin layer

of soil (Fig. 7 and 8).

Fig. 7 Vuasuni dumping site

Fig. 8 Vuasuni dumping site

Current solid waste management practice in BBSR

town is schematically shown in Fig. 9.

Fig. 9 MSW management procedure in BBSR

33


Table 6 Details of Disposal site7

Site information

BMC (60

wards)

Location

Bhuasuni

mauza

Area

61 Acre

Lighting facility on site

Yes

No. of Compacter(roller) used

1

Weather area is fenced

Partly

Total manpower available on

the site

-

Weather covering is done on

daily

No

Suggestion

Solid waste management system in BBSR city is

encountered with several difficulties, like low

technical experience and low financial resources.

MSW is presently disposed in an Bhuasuni dumping

site followed by open dumping process which is not a

proper method of disposal because open dumps pose

environmental hazards which cause ecological

imbalance with respect to land, water, and air

pollution[13]

and also poses a threat to human

health because it Causes environmental

pollution[14]

. So sanitary landfill treatment

method should be adopted as it has proved to be

the most economical and acceptable method for

disposal of solid waste[15]

.

Since no sanitary landfill treatment option is

provided, possibility of fly and mosquito

breeding at the disposal sites can not be ruled

out. Moreover, smoke nuisance is caused by the

unauthorized burning of waste by rag pickers

(fig-5 and fig-8) to reduce the volume of

waste[16]

. Open burning of MSW or obnoxious

gas should be prohibited at the disposal sites

otherwise it would adversely affect health of the

people of surrounding area by obnoxious gas

generation due to incomplete combustion of solid

waste.

Since no sanitary landfill treatment option is

provided, the disposal site is not properly fenced

and waste contains high levels of biodegradable

material and hence, it attracts rodents, stray

animals, cattles as shown in fig-10 thus

contributes to the spread of filth and disease. So

proper fencing of disposal area should be done.

Since no leachate collection and treatment

option is provided, possibility of groundwater

contamination in the surrounding area can not be

ruled out[17]

. Therefore, proper land filling

procedure should be adopted for dumping of

solid waste.

Keeping in view the projected population growth

(Table-7) solid waste generation(fig.2) in future

will puts more pressure on the partially existing

municipal solid waste management

infrastructure. So 3R technologies (3R-Reduce,

Reuse, And Recycle) should be adopted which is

a resource conservation activity and it may offer

a greater return for many products in energy

saving[18]

.

Fig. 10 Cattles movement

Table 7 Census of India[6]

and from Projected

population in BBSR city

Year Population

1931 9024

1941 9253

1951 16512

1961 38211

1971 105491

1981 219211

1991 411542

2001 648632

2011 837737

2021 1,430000

2031 1,900000

As the biodegradable waste fraction

generation is very high (Table 3) in BBSR city in

comparison to other type of waste fraction,

environment friendly process of aerobic

composting should be applied in management of

city MSW.

Further, keeping in view the projected

population growth and simultaneous increase in

solid waste generation, following

recommendations are made to improve the solid

waste management practice in the town.

Recommendations

Disposal of wastes in the streets, open spaces, in

vacant areas or into drains should be banned.

Levy of administrative charges for littering of

streets.

Source segregation of wastes.

Primary collection of wastes, i.e. door-to-door


should be implemented.

3R technologies should be used which helps to

minimize the problems associated with the

generation and safe disposal practices of

municipal solid waste.

Waste collection should be performed on a

regular basis, i.e. daily collection.

Street sweepers should be

equipped with individual containerized

wheelbarrows, metal plate and tray, long

handled broom and protective gear.

Mechanized containers should be used to

enhance storage capacity.

Litter bins should be provided at public

places, such as—bus stands, taxi stands,

market places.

Abolition of open waste storage sites and

manual collection.

Upgrading of existing dumpsites or disposal

sites.

Open burning of biomedical wastes should be

prohibited.

Scientific incineration facility should be

available inside or outside the premises.

The safe and environment friendly process of

aerobic composting requires less land space

and should be applied in management of

MSW.

Sitting, construction and operation of sanitary

landfills should be done systematically.

Capacity building programme for BBSR

Municipal Council should be established.

Public awareness strategies should be taken

into consideration.

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Waste Manage, 27 (4) (2007) 490.

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Trankler J, Potentialsof recycling municipal solid

waste in Asia vis-a-vis Recycling in Thailand.

SEA-UEMA Project (2006).

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[e.g. Guczi L, Pt/Nb2O5/Al2O3 system: A molecular approach

to understand metal support interaction, paper presented at

the 11th National Symposium on Catalysis, Hyderabad, 2-

4 April 1993].

Thesis – Reference to a thesis should include the name of the

author, title of the thesis, university or institution to which it

was submitted, and year of submission [e.g. Jha R K,

Synthesis of Optional Cascade Control Systems, Ph.D.

Thesis, Indian Institute of Technology, Madras, 1987].

Patent – Reference to a patent should include names of

applicant, country of origin and patent number or the

application number, and date of filing [e.g. E.I. du Pont de

Nemours & Co., U S Pat 2, 463, 219, 1 March 1949].

Specification – Reference to a specification should include the

name of the specification, specification number, organization

within parenthesis and year [e.g. Indian standards

specifications IS: 271 (Bureau of Indian Standards, New

Delhi), 1975].

Even if a reference contains more than two authors, the names

of all the authors should be given. The abbreviations et al.,

idem and ibid should not be used.

Data – Only such primary data as are essential for

understanding the discussion and the main conclusions

emerging from the study should be included. All such

secondary data as are of interest to a specific category of

readership may, if necessary, be supplied on demand. A

footnote to this effect may be inserted at a suitable place in the

paper.

Tables – Tables should be typed on separate sheets of paper

without any text matter on the page. They should be numbered

consecutively in Arabic numeral and should bear brief titles.

Column headings should be brief. Units of measurement

should be abbreviated and placed below the headings. Nil

results should be indicated and distinguished clearly from

absence of data. The same set of data should not be

represented both in tables and figures. Inclusion of structural

formulae inside the tables should be avoided as far as possible.

Tables should be referred to in the text by number in sequence

and not by terms like ‘above’, ‘below’, ‘preceding’ or

‘following’.

Illustrations – Illustrations should be numbered consecutively

in Arabic numerals. Captions and legends to the figures should

be self-explanatory, typed on a separate sheet of paper and

attached at the end of the manuscript. Line drawings should be

made by an artist using stencil on white drawing paper

(preferably Bristol board) or cellophane sheet. Computer

prints should be dark, sharp and clearly readable.

Micrographs should include bench marks. Special care

should be taken with computer listings, which are often not

suitable for reproduction. In the case of photographs, prints

must be on glossy paper and must show good contrast. If an

illustration is taken from another publication, reference to the

source should be given and prior permission secured. Figures

should be referred to in the text by numbers in sequence and

not by terms like ‘above’, ‘below’, ‘preceding’ or ‘following’.

Spectra, curves and XRD patterns should be included only if

they pertain to new compounds and are essential to the

discussion; otherwise, only significant numerical data should

be included in the text.

For satisfactory reproduction, the graphs and line drawings

should be drawn to about twice the printed size. The size of

letters, numbers, dots, lines, etc should be sufficiently large to

permit reduction to the page (175 mm) or the column (85 mm)

width, as required in the journal, without loss of details.

Lettering size should be kept in such a way that in final prints

it is 7-9 pt size in arial font. Colour figures should be made in

CMYK (photoshop; tiff or jpg files) with resolution of 250-

300 dpi. Black and white figures or half tones should be in

bitmap/grey scale with 200 dpi.

Structural Formulae – The number of structural formulae

should be restricted to the bare minimum. Wherever the

purpose is adequately served, chemical or common named

should be preferred. Structural formulae should be numbered

in sequence and referred to in the text by their numbers.

Reaction schemes should be referred to in the text as ‘Scheme

1’ or ‘Chart 1’, etc, and not by expressions like ‘below’,

‘above’, ‘preceding’, or ‘following’. Suitable caption should

be given.

Mathematical material – Equations must be clearly written,

each on its own line, well away from the text. All equations

must be numbered consecutively in Arabic numerals with the

number in parentheses near the right hand margin. Authors

must indicate wherever special characters (Greek, German,

script vector, tensor, matrix, etc.) are required. All other

variable symbols should be set in italic types. Vectors must be

underlined by a wavy line and tensors by two wavy lines. The

SI system of units and symbols is recommended.

Equation – Equations should be set using the equation editor

software.

SI units – The Journal requires the use of SI units for all

numerical data. Common metric (cgs), English Engineering,

or other frequently used units may be given in parentheses

following the SI units.

The Hiranya Kumar Centre for Research & Development

(OEC, Bhubaneswar) assumes no responsibility for the

statements and opinions advanced by the contributors

Published by Dr. B. Tosh on behalf of HKCR&D, OEC, Bhubaneswar 751 007 and printed at Devee Printers, Nuapatna, Cuttack – 754035


Author Index

Asa, S C 13

Dash, G C 19

Harichandan, A 28

Meher, J K 19

Nayak, N 8

Panda, C R 8

Panda, C R 24

Panda, R 28

Panigrahi, M R 19

Parashar, K 28

Patra, H S 28

Pattnayak, N 3

Rath, P 13

Raval M K 19

Rout, B 16


Keyword Index

3R technology 28

Activated fly ash 16

Aerobic composting 28

Bittern 8

Brine 8

Chromium 3

Copper 3

Development 24

Environment 24

Geo-accumulation index (Igeo) 13

Heavy metal 13

Iron 3

Laterite soil 16

Ligand 19

Major elements 8

Manganese 3

Neural network 19

Ni-binding 19

Nickel 3

Physicochemical parameters 19

Physio-chemical properties 16

Polarizability 19

Pollutants 3

Resources 24

Salt 8

Sanitary landfill 28

Sediment quality 13

Soil conditioner 16

Source segregation 28

Sustainable 24

Trace metals 3

Waste 24

Zinc 3

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