BMW Mgt Using GIS and RS_new_May31_2013

8/12/2019 BMW Mgt Using GIS and RS_new_May31_2013

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IDENTIFICATION OF INCINERATOR SITES FOR DISPOSAL OF

BIO-MEDICAL WASTE USING REMOTE SENSING AND

GEOGRAPHIC INFORMATION SYSTEMS

Arunava Bandyopadhyay1, Kiran Kumar Shetty2, Deepak Choksi3, Abhijat A. Abhyankar4

1. Post Graduate Student, National Institute of Construction Management and Research,Pune

2. Post Graduate Student, National Institute of Construction Management and Research,Pune

3. Project Engineer, Centre of Studies in Resources Engineering, Indian Institute ofTechnology, Bombay

4. Assistant Professor, National Institute of Construction Management and Research, [email protected]

1

Abstract

The Pune city and its adjoining areas are experiencing high population growth mainly due

to the availability of new opportunities in Education, IT, and Manufacturing sectors and

addition of other 28 villages to Pune Municipal Corporation. This urbanization has led to

an increase in the quantity of Bio-Medical Waste generation from the hospitals. The

location of a biomedical waste incinerator facility is an important problem due to its

environmental, social, and economic impacts. The improper disposal of these kinds of

waste is of great concern to human health and environment.

This paper identifies two incinerator sites for the proper disposal of Bio-Medical Waste

generated in Pune city and the adjoining areas, using Remote Sensing and GeographicalInformation Systems. The identification of two incinerator sites is based on Biomedical

Waste Management and Handling Rules, 2010. IRS P6 LISS III satellite data was utilized

for landcover classification. The classified satellite image and GIS tools and techniques

were used for the identification of incinerator sites. The selection criteria for identification

of incinerator sites were built up area, road network, and wind speed and direction. Further,

fifty six hospitals in and around Pune were attached to either incinerator site based on the

shortest route between the incinerator and the hospital.

Keywords: Bio-Medical Waste (BMW), Biomedical Incinerator, Supervised Classification

using Maximum Likelihood Classifier, Remote Sensing, GIS

1 Introduction

The biomedical waste poses challenges to human health and environment due to its

infectious characteristics. Improper disposal or treatment of this waste constitutes a grave

risk [1]. Siting a municipal incineration facility is a complex task and requires the meeting

of regulations and minimization of economic, environmental, health, and social costs. It

also involves multiple objectives and number of candidate alternatives is theoretically

possible. Such complexity requires the development of systematic, transparent and clear

procedures that reduce the uncertainties, and support the decision makers to undertake

sound decisions [2].


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Remote sensing and GIS tools have been used for identification of potential Solid Waste

Dump Sites [3; 4]. Siting of Municipal Incinerator was attempted using GIS for the city of

Austin, Texas. The methodology of multi-criterion decision analysis (MCDA) and set of

economic and environmental criteria was developed and implemented as a linear

optimization problem [5]. GIS was used for siting of a nuclear waste repository. Firstly, all

data layers were established (geology, transportation, nature conservation area and

population statistics). These layers were digitized and these data layers were then processed

so that they represented specific siting criteria. For e.g. the nature conservation layer was

processed to show protected layers where no development is permitted. Similarly other data

layers were processed with specific siting criteria. Later, all these layers were combined to

obtain nuclear waste repository site [6]. A similar approach was used in the house hunting

case study. In this case, three criteria were considered namely, proximity to schools,

property insurance and proximity to main roads. The next step was involved

standardization of criterion scores, followed by allocation of weight, and finally application

of the MCE algorithm [7].

A common treatment facility for Bio-Medical Waste exists is in the heart of the Pune cityand it needs relocation because it is causing environmental and social problems. Moreover,

as per Biomedical waste Management and Handling Rules 1998 and 2010, one biomedical

waste incinerator facility can cater to a population of 30 lakhs only [8; 9]. The present

population, future growth, and addition of another 28 villages to PMC will make PMC the

largest Municipal Corporation, in term of area in sq. kms. in Maharashtra, India. In this

paper we have attempted to identify two biomedical incinerator facilities by using remote

sensing and GIS based on the above considerations.

2. Study area

The study area considered is Pune city and its coordinates are from 73 45 00 E, 18 45

00 N to74 00 00 E, 18 15 00 N. Pune is the second largest city in Maharashtra,

eighth largest in the country, and the ninth largest metropolis in India. Figure 1 shows the

study region i.e. Pune city on state map of Maharashtra and country map of India. It is

situated 560 metres above the mean sea level. It is situated on the leeward side of the

Sahyadri mountain range, which forms a barrier from the Arabian sea. The major rivers in

Pune are, Mula, Mutha, Pavana and Indrayani. Pune has a tropical wet and dry climate.

Pune experiences three seasons annually namely, summer, monsoon, and winter. The

monsoon lasts from June to October, with moderate rainfall. Most of the annual rainfall in

the city falls between June and September, and July is the wettest month of the year. As per

the 2011 Census of India estimate, the population of the Pune urban agglomeration wasaround 5,049,968 [10].

Pune and its adjoining parts have seen skilled labour from across India due to software,

automobile and education sectors. The growth rate in the core part of the city is about 2 to

2.5% per year and the annual growth rate in the peripheral wards is about 4.4%. The

literacy rate is about 81% [11].

The Bio-Medical Waste generated in the twin cities of Pune and Pimpri Chinchwad

comprises around 20% of the total waste generated in Maharashtra. However about 37% of

the total BMW is disposed of in the open, posing a serious threat to humanity [12].


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Figure 1: India Maharashtra Pune

3 Methodology

The methodology involves relevant data collection, landcover classification using remotely

sensed data, followed by overlay analysis using GIS for identification of appropriate

incinerator sites. We have used ERDAS Imagine (version 9.1) for landcover classification

and GRAM++ GIS (Version 11.1)software for overlay analysis. Hand held GPS was used

to record the latitude and longitude of the hospitals.

3.1 Data

The Survey of India (SOI) toposheets (E43H14 and E43H15) and satellite image of IRS P6

LISS III (23 m x 23 m; Path: 95 and Row: 59) of December 14, 2011 of Pune city and

adjoining areas were obtained from Regional SOI office, Pune and NRSC, Hyderabad

respectively. The latitude and longitude of fifty six hospitals selected in the present study

were recorded using hand held GPS device and then digitized on the map.

3.2 Landcover Classification

The satellite image was geometrically corrected using Survey of India (SOI) Toposheet.

The study area includes the Pune city and five kilometers radius around it. This area was

extracted using a standard digitized vector map. For supervised classification, green, red

and near IR bands were considered i.e.Band 2, Band 3 and Band 4 of the IRS P6 LISS III

satellite and standard FCC was generated. Using Supervised Classification with theMaximum Likelihood Classifier technique, land cover classification was performed on the

IRS P6 LISS III satellite image [13]. Four distinct land cover classes namely, vegetation,


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barren land, urban built-up, and airport were identified. The area of each landcover class

covered is shown in Table 1. Figure 2 shows the landcover map of Pune and adjoining

areas.

Table 1: Landcover class and its corresponding area

Layer Area (sq.kms.)Vegetation 415.724

Barren Land 128.022

Urban Built-up 228.799

Airport 9.731

Figure 2: Landcover Map

3.3 Identification of Incinerator sites using GRAM ++

Further after landcover classification, the pixel value for urban built-up was kept as one and

the rest of the land covers as zero. The incinerator should be located at a site which will

have minimal effects on human health, flora and fauna. We have proposed a buffer of 100

m from the main road, 250 m from the built up and further the incinerator site should be

within five kilometers of the city limits.

The distance from main road, built up and city limit distance was selected based on expert

opinion approach. Applying the above buffers, 15 incinerator candidate sites were

identified. Figure 3 shows the spatial distribution of fifteen Candidate Incinerator sites in

Pune. Table 2 depicts the reasons for not considering six candidate incinerator sites namely,

B, C, E, F, H and M for further analysis. Hence only nine identified incinerator sites are

considered for further analysis


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Figure 3: Fifteen Candidate Incinerator Sites

Table 2: Incinerator sites

Incinerator Sites Latitude Longitude Accepted/Rejected Remarks for Rejection

O 7337' 25" 1845' 30" Accepted NA

A 7345' 29" 1835' 22" Accepted NA

B 7346' 57" 1831' 54" Rejected On Pashan Lake

C 7346' 22" 1827' 46" Rejected NDA Area

D 7345' 42" 1826' 56" Accepted NA

E 7345' 35" 1826' 42" Rejected Near Khadakwasla Lake

F 7348' 22" 1828' 40" Rejected Near Warje FlyoverG 7340' 00" 1828' 11" Accepted NA

H 7351' 26" 1827' 03" Rejected Near Katraj Lake

I 7357' 49" 1827' 53" Accepted NA

J 7357' 49" 1827 33" Accepted NA

K 7359' 22" 1825' 05" Accepted NA

L 7359' 28" 1835' 26" Accepted NA

M 7353' 38" 1858' 38" Rejected Military Engineering College

N 7352' 57" 1840' 35" Accepted NA

The Wind Intensity and Directionprofile of Pune city showed that the wind direction is

mostly towards the West to South West, with absolutely no wind in the South and small

percentage of wind in the North direction [14].

Further, two levels of criteria for our analyses were selected namely, Level 1: Overlay

Analysis with South West Sectors Buffers around the points and Level 2: Overlay Analysis

with Full Buffered Areas. For each criterion, three separate buffers of 500 m 1000 m and

1500 m were considered for excluding the Urban Built area around each site.

The selection of the buffers is based on determination of flue gases concentration using

Guassian Plume model. The carbon content [15] and other elemental contents, atmospheric

stability, effective stack height, wind velocity at the top of the stack and Pasquills stabilitytype were used for calculation of emission rate and ground level concentration. The flue

gas concentration of Carbon Monoxide (CO) at the chimney exceeded the national ambient


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air quality standard. We calculated the ground level concentration for CO at centre line

concentration at 500 and 1000 m. The emission rate data was procured from the presently

working biomedical incinerator in Pune.

It was found that for 1000 m buffer, the ambient concentration of CO was within the limits

of National Air Quality Standards. Further a safety factor of 1.5 was considered so as to

reduce the risk to peoples heath and to the environment. Hence a buffer of 1500 m was

considered in the intersection calculations (Annexure 1 demonstrates the calculations for

determination of CO concentration at a distance of 500 m, 1000 m and 1500).

The buffered incinerator point was overlaid with Urban Built-up Area using GRAM ++ to

find the percentage intersection. Table 3 depicts the result of the overlay analysis of SW

sector buffers with urban built up area.

Table 3: Overlay Analysis of SW Sectors Buffers with urban built up area

Sr. No Points Sector Buffer(m.)

Total Area (sq. m.) IntersectionArea (sq. m.)

%Intersection

1 ASouth

West

500 196349.54 0 0.00%

1000 785398.16 0 0.00%

1500 1767145.87 0 0.00%

2 DSouth

West

500 196349.54 0 0.00%

1000 785398.16 0 0.00%

1500 1767145.87 0 0.00%

3 GSouth

West

500 196349.54 148449.88 75.60%

1000 785398.16 496039.86 63.20%

1500 1767145.87 879837.13 49.80%

4 ISouth

West

500 196349.54 41638.38 21.20%

1000 785398.16 123104.78 15.70%

1500 1767145.87 320434.51 18.10%

5 JSouth

West

500 196349.54 0 0.00%

1000 785398.16 0 0.00%

1500 1767145.87 905.182 0.10%

6 KSouth

West

500 196349.54 0 0.00%

1000 785398.16 0 0.00%

1500 1767145.87 0 0.00%

7 LSouth

West

500 196349.54 16293.28 8.30%

1000 785398.16 244399.201 31.10%

1500 1767145.87 964019.073 54.60%

8 OSouth

West

500 196349.54 98940.073 50.40%

1000 785398.16 405906.32 51.70%

1500 1767145.87 870694.76 49.30%

9 NSouth

West

500 196349.54 0 0.00%

1000 785398.16 0 0.00%

1500 1767145.87 0 0.00%


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It was observed that the points G, L and Ohave greater than 50% intersection with Urban

Built-up Area. Hence we rejected these points, and the points were not considered for

Level 2 analysis. For the other points, an overlay analysis of full buffered areas with urban

built up area was performed and the results are depicted in Table 4.

Table 4: Overlay Analysis of Full Buffered Areas with urban built up area

Sr. No. PointsBuffer

(m.)

Total Area

(sq.m.)

Intersection

Area (sq.m.)

%

Intersection

1 A

500 785398.16 427246.03 54.40%

1000 3141592.65 1781398.71 56.70%

1500 7068583.47 4009957.46 56.70%

2 D

500 785398.16 427246.032 54.40%

1000 3141592.65 299615.33 9.50%

1500 7068583.47 1041864.8 14.70%

4 I

500 785398.16 165648.355 21.10%

1000 3141592.65 663498.61 21.10%

1500 7068583.47 1494455.94 21.10%

5 J

500 785398.16 0 0.00%

1000 3141592.65 95044.14 3.00%

1500 7068583.47 533152.358 7.50%

6 K

500 785398.16 0 0.00%

1000 3141592.65 0 0.00%

1500 7068583.47 0 0.00%

9 N

500 785398.16 0 0.00%

1000 3141592.65 0 0.00%

1500 7068583.47 0 0.00%

It can be seen from table 4 that the sites A and D have more than 50% intersection with

Urban Built Up area. Thus we have only four remaining candidate incinerator sites namely,

I, J, K and N.

The incinerator sites i.e. I, J and K are close to each other. Therefore we have selected I

as the most appropriate incinerator site as it is closer to the Central Business District (Refer

Figure 3 for the location of Incinerator site I, J and K). Finally, we identified two locations

for setting up of biomedical Incinerators in Pune. The coordinates of N and I are

735257E, 184035 N and 735749E, 185753 N respectively and are depicted in

Figure 4.


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Figure 4: Biomedical Incinerator sites N and I

As per Bio-Medical Waste Management Handling Rules, 2010, the minimum area required

for siting an Incinerator is one acre i.e.approximately 4047 sq. m, the actual area available

at the incinerator sites is validated through site visit. It was found that the area available for

incinerator at site N and I are 2.4 and 4.36 acres respectively.

Further, the researchers digitized the hospital points and road network on the base map in

GRAM++ as point and line layer respectively. Table 5 depicts the latitude and longitude ofthe selected hospitals in the study area. The spatial distribution of hospitals selected in the

present study is shown in Figure 5.

Table 5 Hospitals and corresponding latitude and longitude

Sr. No. Hospitals Coordinates

North

(D/M/S)

East

(D/M/S)

1 Ace Multi Speciality Hospital 18 30 12 73 49 45

2 Aditya Birla Memorial Hospital, Pune 18 37 44 73 46 28

3 Aundh Chest Hospital, Pune 18 34 35 73 48 22

4 Baner Multispeciality Hospital 18 33 48 73 46 59

5 Bharti Hospitals 18 27 27 73 51 22

6 Bora Hospital Pune 18 31 15 73 51 24

7 Bharati Hospital Pune 18 27 34 73 51 23

8 Chormale Accident and General Hospital 18 29 57 73 57 9

9 Chandralok Hospital 18 28 48 73 51 40

10 Chintamani Hospital 18 28 32 73 51 44

11 Chitale ENT Hospital Pune 18 30 29 73 51 10

12 Dhanvantri Hospital 18 39 21 73 46 6

13 D Y Patil Hospital & Research Centre Pune 18 38 9 73 49 414 Deenanath Mangeshkar Hospital Pune 18 30 16 73 49 57


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15 Deendayal Memorial Hospital Pune 18 31 29 73 50 28

16 Gandhi Hospital 18 30 8 18 30 8

17 Godbole Hospital Pune 18 31 23 73 50 42

18 Gupte Hospital Pune 18 31 13 73 50 24

19 Gurudwara Command Hospital 18 29 59 73 53 20

20 Hardikar Hospital Pune 18 31 52 73 50 5221 Inlaks and Budhrani Hospital Pune 18 32 10 73 53 14

22 Jagtap Hospital 18 28 41 73 49 25

23 Jehangir Hospital Pune 18 31 49 73 52 37

24 Jog Hospital Pune 18 30 33 73 49 18

25 Joshi Hospital, Pune 18 31 1 73 50 5

26 K E M Hospital Pune 18 31 12 73 52 3

27 Kamala Nehru Hospital Pune 18 31 22 73 51 43

28 Kotbagi Hospital Pune 18 33 40 73 48 18

29 Krishna Hospital Pune 18 30 34 73 48 46

30 Kidney Cure Clinic & Modern Homoeopathic Hospitals 18 27 35 73 51 27

31 Lokmanya Care Hospital Pune 18 39 22 73 46 2432 Medipoint Hospital Pvt. Ltd 18 33 54 73 48 9

33 Mohintara Hospital 18 30 3 73 55 47

34 Marathe Nursing Home 18 30 17 73 49 13

35 Medipoint Hospital Pune 18 33 54 73 48 8

36 Naidu Hospital Pune 18 31 53 73 52 7

37 Naik Hospital Pune 18 30 37 73 51 34

38 NM Wadia Hospital Pune 18 30 26 73 51 17

39 Nobel Hospital 18 30 18 73 55 39

40 Poona Hospital & Research Center Pune 18 30 40 73 50 32

41 Ranka Hospital 18 29 42 73 51 4342 Rathi Hospital Pune 18 30 1 73 56 11

43 Ruby Hall Clinic, Pune 18 32 1 73 52 38

44 SAI SNEH HOSPITAL 18 27 25 73 51 40

45 Sahyadri Hospital Pune 18 30 47 73 50 21

46 Sahyadri Hospital,Bopodi, Pune 18 34 15 73 50 16

47 Sahyadri Hospital, Hadapsar, Pune 18 30 10 73 55 40

48 Sahyadri Hospital, Kothrud, Pune 18 30 27 73 48 22

49 Shree Samarth Hospital 18 30 6 73 56 2

50 Siddhi Hospital Pune 18 27 51 73 51 34

51 Sancheti Hospital Pune 18 31 47 73 51 11

52 Sanjeevan Hospital Pune 18 30 36 73 50 14

53 Sasson General Hospital Pune 18 31 33 73 52 19

54 Shree Hospital Pune 18 33 12 73 53 56

55 Shashwat Hospital 18 29 42 73 48 48

56 Surya Hospital Pune 18 31 16 73 51 21


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Figure: 5: Spatial distribution of the Fifty Six Hospital

The distance between each hospital and the identified incinerator sites (N and I) using the

digitised road network and the shortest path was computed. Figure 6 depicts the shortest

path between Incinerator site I and hospital No. 46.

Figure: 6: Shortest Distance path between Incinerator site I and Hospital No. 46


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It was deduced that the hospitals with no. 2, 12, 13, 30, 40 and 41 should transport

biomedical wastes to Incinerator site N and the rest to Incinerator site I. It can beseen

that majority of the hospitals are routed towards incinerator I. The reason being that most

hospitals digitized in the present study are in the Central or Northern parts of Pune which

are nearer to the site I. Incinerator site N would cater to the hospitals in the southern parts

of Pune.

4 Conclusion, limitation and future work

The present study attempts to identify two incinerator sites for treatment of Biomedical

Waste at Pune and adjoining parts using Remote Sensing and GIS. The present population

is more than 30 lakhs and with addition of another 28 villages in Pune Municipal

Corporation the population will increase significantly. This will make the PMC the largest

municipal corporation in terms of geographical area in the Maharashtra state. The

developed methodology and spatial analysis performed in the present study are simple to

use and could be used for identification of Biomedical Incinerator sites in other cities.

The working biomedical incinerator located in the heart of the Pune city fulfils National

Ambient Air Quality Standards for sulphur dioxide and nitrogen dioxide and not for Carbon

monoxide. The study keeps in mind this incinerator while designing the buffers of 500 m,

1000 m and 1500 m and assumes similar issues with other biomedical incinerators.

It is expected that the vehicle containing the infectious waste will travel through the major

roads only. The water bodies in Pune and adjoining areas are not considered for supervised

classification due to the major misclassification errors. The errors are due to mainly

because of mixing of water pixels with other landcover classes. In some places the width of

the rivers is too small to get classified in this satellite image. This problem can be

overcome by using a higher spatial resolution satellite image. The water hyacinth coversthe river water. This is another reason of misclassification of water as the spectral

reflectance signature is very close to vegetation class. Also, inputs from base map are taken

regarding water bodies only during acceptance/rejection of identified candidate incinerator

sites. In the present study, the classification of satellite image is at USGS level 1.

Moreover, we have only considered fifty six hospitals. Digitization of all medical

institutions generating these kinds of wastes would increase the quantum of waste disposal

at Incinerator site I. It is assumed in the present study that the population density spatially

over the study area is the same.

The study doesnt consider vehicles required for collection of biomedical waste from all

hospitals from the study region within prescribed time limits, the quantum of biomedicalwaste generated by each hospital. Further, the study does not categorize hospitals as large

or small. The number of beds in each hospital can be a proxy for overall biomedical waste

generation. The city of Pune regularly faces traffic problems. The speed of the vehicle is

an important factor while allocating hospitals to biomedical waste collection vehicle. The

land acquisition for incinerator and surrounding buffer areas will be another challenge. The

Resettlement and Rehabilitation (R & R) of the project affected people (PAP) presently in

the buffered region will be of immediate concern to the government.


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REFERENCES

[1] Bio-Medical Waste: Ministry of Urban Development, GOI

http://urbanindia.nic.in/publicinfo/swm/chap7.pdf

(Last accessed on March 04, 2013).

[2] Erkut, E., Newman, S., 1989. Analytical models for locating undesirable facilities.

European Journal of Operational Research 40, 275291.

[3] Aruna, D, T. Byragi Reddy, Swamy A. V. V. S., 2012. Selection of Potential Waste

Dump Sites for Kakinada City using GIS and Remote Sensing Techniques,

International Journal of Engineering Sciences Research-IJESR, 3(5), September-

October.

[4] Nishanth. T., Prakash M. N., Vijith. H., 2010. Suitable Site Determination forUrban Solid Waste Disposal using GIS and Remote Sensing Techniques in

Kottayam Municipality, India, International Journal of Geomatics and Geosciences,

1(2).

[5] Jayanthi Rajamani 2002. Siting Obnoxious Facilities using an Integrated GIS-DSS

http://www.crwr.utexas.edu/gis/gishydro03/Classroom/trmproj/Rajamani/GISproject2.htm (last accessed on May 5, 2013)

[6] Openshaw, S., Carver, S. and Fernie, J., 1989. Britans Nuclear Waste: Safety and

Siting Belhaven, London

[7] Heywood, I., Cornelius, S., and Carver, S., 1998. An Introduction to Geographic

Information Systems. Addison Weseley Longman Ltd.

[8] Ministry of Environment and Forest Notification on Bio-Medical Waste

(Management and Handling) Rules, 1998

http://envfor.nic.in/legis/hsm/biomed.html (last accessed on May 5, 2013)

[9] Biomedical waste, Biomedical treatment facilities

http://cpcb.nic.in/wast/bioimedicalwast/BMWtreatmentfacilities.pdf (last accessed

on May 5, 2013)[10] Pune City Population Census 2011

http://www.census2011.co.in/census/city/375-pune.html


[11] Waste Quantification and Characterisation of Pune, 2006. Extract from the report

Strategic Action Plan for Integrated Solid Waste Management Plan, Pune (Volume

1)http://www.unep.or.jp/ietc/GPWM/data/T1/IS_2_WasteQC_Pune.pdf


[12] Status of Biomedical Waste Management in the State-Maharashtra for MPCB, 2011

http://mpcb.gov.in/images/pdf/Status_BMW_MahJune2011.pdf


[13] Lillesand T. T. and Kiefer R. W., 1994. Remote Sensing and Image Interpretation.John Wiely and Sons, Inc.

[14] General Features of Pune District,MPCB, Chapter 1

http://mpcb.gov.in/relatedtopics/CHAPTER1.pdf(Last accessed on March 04, 2013).

[15] N. E. Mastorakis, C. A. Bulucea, T. A. Oprea, C. A Bulucea and P Dondon, 2011.

Holistic Approach of Biomedical Waste Management System with Regard to Health

and Environmental Risks, International Journal of Energy and Environment, 5(3).
http://urbanindia.nic.in/publicinfo/swm/chap7.pdfhttp://www.google.co.in/url?sa=t&rct=j&q=as%20per%20provisional%20reports%20of%20census%20india%2C%20population%20of%20pune%20city%20in%202011%20is%203%2C115%2C431.%20&source=web&cd=1&cad=rja&ved=0CC4QFjAA&url=http%3A%2F%2Fwww.census2011.co.in%2Fcensus%2Fcity%2F375-pune.html&ei=mxw0Ubr6AYKJrAfDp4DICw&usg=AFQjCNHZsZX09zze9Uw9TTiMNasm7ncSJghttp://mpcb.gov.in/images/pdf/Status_BMW_MahJune2011.pdfhttps://www.google.co.in/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&ved=0CDMQFjAB&url=http%3A%2F%2Fmpcb.gov.in%2Frelatedtopics%2FCHAPTER1.pdf&ei=nR80UeX-DYTTrQfmmYG4Ag&usg=AFQjCNFT8WLIQhtHqC2TTWY1di_u0e0Kpg&bvm=bv.43148975,d.bmkhttp://mpcb.gov.in/relatedtopics/CHAPTER1.pdfhttp://mpcb.gov.in/relatedtopics/CHAPTER1.pdfhttp://mpcb.gov.in/relatedtopics/CHAPTER1.pdfhttps://www.google.co.in/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&ved=0CDMQFjAB&url=http%3A%2F%2Fmpcb.gov.in%2Frelatedtopics%2FCHAPTER1.pdf&ei=nR80UeX-DYTTrQfmmYG4Ag&usg=AFQjCNFT8WLIQhtHqC2TTWY1di_u0e0Kpg&bvm=bv.43148975,d.bmkhttp://mpcb.gov.in/images/pdf/Status_BMW_MahJune2011.pdfhttp://www.google.co.in/url?sa=t&rct=j&q=as%20per%20provisional%20reports%20of%20census%20india%2C%20population%20of%20pune%20city%20in%202011%20is%203%2C115%2C431.%20&source=web&cd=1&cad=rja&ved=0CC4QFjAA&url=http%3A%2F%2Fwww.census2011.co.in%2Fcensus%2Fcity%2F375-pune.html&ei=mxw0Ubr6AYKJrAfDp4DICw&usg=AFQjCNHZsZX09zze9Uw9TTiMNasm7ncSJghttp://urbanindia.nic.in/publicinfo/swm/chap7.pdf


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ANNEXURE I

Calculations for determining concentration of Flue gases

Assumptions:

1. 2.5 tonnes of Bio Medical Waste is being burnt in 6 hours per day.2. Carbon content in Bio-Medical Waste is 50% by mass3. Pasquills stability type C i.e.Slightly Unstable Atmospheric condition is chosen4. Effective Stack Height = (30 + 2) m = 32 m5. Wind velocity at top of stack is 6.0 m/sec.The concentration of various effluent gases at the Biomedical Waste Incinerator Chimney

are as follows:

1. Sulphur Dioxide : 15.40 g/cum2.

Nitrogen Dioxide : 8.30 g/cum3. Carbon Monoxide : 11.4 mg/cum

4. Carbon Dioxide : 0.1 mg/cumFrom National Ambient Air Quality Standards (2009),

Concentration of Pollutants in Ambient Air Standards

Pollutant Time Weighted

Average

Concentration in Ambient Air

(Industrial, Residential, Rural and Other Areas)

Sulphur Dioxide Annual 50 g/cum

Nitrogen Dioxide Annual 40 g/cumCarbon Monoxide 8 hours 2 mg/cum

Carbon Dioxide NA NA

Hence, we see that the concentration of Carbon Monoxide exceeds the prescribed limits.

Thus the site for the Biomedical Waste incinerator should be such that there is a minimum

distance between the incinerator site and the urban area.

Step-1: Determination of Emission rate (Q) for Carbon Monoxide:

Total waste burnt per hour = 0.42 tonnes

Emission Rate (Q) = 0.42 103 50 100 = 210 Kgs. of Carbon/hr.Molecular Mass of Carbon = 12

Molecular Mass of Oxygen = 16

C + O = CO

12Kgs. + 16Kgs. = 28 Kgs.

210Kgs. + 280Kgs = 490 Kgs

Q = 490 Kgs. CO/hr = 490 103 3600 = 136.11 gm/sec.


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Step-2: Determination of centre line concentration at a distance of 500 m from source

From Passquill Gifford Turner (PGT) diffusion coefficients, Vertical Diffusion Coefficient

(z) and Horizontal Diffusion Coefficient (y) are:

z = 40 m

y = 60 m

C(500, 0) = 136.11 ( 6 40 60) exp {(12) (32 40)2}

= 2.18 10-3 gm/cum = 2.18 mg/cum, which exceeds the permissible limits

Step3: Determination of centre line concentration at a distance of 1000 m from

Source:


(z) and Horizontal Diffusion Coefficient (y) are:

z =70 m

y = 125mC(1000, 0) = 136.11 ( 6 70 125) exp {(12) (32 70)2}

= 7.743 10-4gm/cum

= 0.774 mg/cum, which is within the limits.

However considering the increase in the quantity of biomedical wastes, higher capacity

incinerators will be used in future. Hence a factor of safety of 1.5 is considered for analysis.

Step4: Determination of centre line concentration at a distance of 1500 m from

Source:


(z) and Horizontal Diffusion Coefficient (y) are:z =90 m

y = 150 m

C(1500, 0) = 136.11 ( 6 90 150) exp {(12) (32 90)2}

= 5.02 10-4gm/cum

= 0.50 mg/cum, which is well within the limits.

Hence three buffers of 500 m, 1000 m and 1500 m are considered around the candidate

incinerator sites and further analysis is carried out.

BMW Mgt Using GIS and RS_new_May31_2013

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